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27 pages, 4418 KiB  
Article
Genome-Wide Identification, Characterization, and Expression Analysis of BES1 Family Genes in ‘Tieguanyin’ Tea Under Abiotic Stress
by Yanzi Zhang, Yanlin Zhang, Zhicheng Yang, Qingyan Li, Weixiang Chen, Xinyan Wen, Hao Chen and Shijiang Cao
Plants 2025, 14(3), 473; https://doi.org/10.3390/plants14030473 (registering DOI) - 5 Feb 2025
Abstract
The BRI1-EMS-SUPPRESSOR 1 (BES1) family comprises plant-specific transcription factors, which are distinguished by atypical bHLH domains. Over the past two decades, genetic and biochemical studies have established that members of the BRI1-EMS-SUPPRESSOR 1 (BES1) family are crucial for regulating [...] Read more.
The BRI1-EMS-SUPPRESSOR 1 (BES1) family comprises plant-specific transcription factors, which are distinguished by atypical bHLH domains. Over the past two decades, genetic and biochemical studies have established that members of the BRI1-EMS-SUPPRESSOR 1 (BES1) family are crucial for regulating the expression of genes involved in brassinosteroid (BR) response in rapeseed. Due to the significance of the BES1 gene family, extensive research has been conducted to investigate its functional properties. This study presents a comprehensive identification and computational analysis of BES1 genes in ‘Tieguanyin’ (TGY) tea (Camellia sinensis). A total of 10 BES1 genes were initially identified in the TGY genome. Through phylogenetic tree analysis, this study uniquely revealed that CsBES1.2 and CsBES1.5 cluster with SlBES1.8 from Solanum lycopersicum, indicating their critical roles in fruit growth and development. Synteny analysis identified 20 syntenic genes, suggesting the conservation of their evolutionary functions. Analysis of the promoter regions revealed two types of light-responsive cis-elements, with CsBES1.4 exhibiting the highest number of light-related cis-elements (13), followed by CsBES1.9 and CsBES1.10. Additional validation via qRT-PCR experiments showed that CsBES1.9 and CsBES1.10 were significantly upregulated under light exposure, with CsBES1.10 reaching approximately six times the expression level of the control after 4 h. These results suggest that CsBES1.9 and CsBES1.4 could play crucial roles in responding to abiotic stress. This study offers novel insights into the functional roles of the BES1 gene family in ‘Tieguanyin’ tea and establishes a significant foundation for future research, especially in exploring the roles of these genes in response to abiotic stresses, such as light exposure. Full article
(This article belongs to the Special Issue Responses of Crops to Abiotic Stress)
26 pages, 1186 KiB  
Article
Optimizing BFloat16 Deployment of Tiny Transformers on Ultra-Low Power Extreme Edge SoCs
by Alberto Dequino, Luca Bompani, Luca Benini and Francesco Conti
J. Low Power Electron. Appl. 2025, 15(1), 8; https://doi.org/10.3390/jlpea15010008 - 5 Feb 2025
Abstract
Transformers have emerged as the central backbone architecture for modern generative AI. However, most ML applications targeting low-power, low-cost SoCs (TinyML apps) do not employ Transformers as these models are thought to be challenging to quantize and deploy on small devices. This work [...] Read more.
Transformers have emerged as the central backbone architecture for modern generative AI. However, most ML applications targeting low-power, low-cost SoCs (TinyML apps) do not employ Transformers as these models are thought to be challenging to quantize and deploy on small devices. This work proposes a methodology to reduce Transformer dimensions with an extensive pruning search. We exploit the intrinsic redundancy of these models to fit them on resource-constrained devices with a well-controlled accuracy tradeoff. We then propose an optimized library to deploy the reduced models using BFLoat16 with no accuracy loss on Commercial Off-The-Shelf (COTS) RISC-V multi-core micro-controllers, enabling the execution of these models at the extreme edge, without the need for complex and accuracy-critical quantization schemes. Our solution achieves up to 220× speedup with respect to a naïve C port of the Multi-Head Self Attention PyTorch kernel: we reduced MobileBert and TinyViT memory footprint up to ∼94% and ∼57%, respectively, and we deployed a tinyLLAMA SLM on microcontroller, achieving a throughput of 1219 tokens/s with an average power of just 57 mW. Full article
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Figure 1

Figure 1
<p>Conceptual diagram summarizing the challenges and contributions of this work.</p>
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<p>The MHSA scheme. An arbitrary Input sequence is linearly projected in Query, Key, and Value (Q, K, V) vectors using learnable parameters. Each vector is split evenly in <span class="html-italic">n_heads</span> chunks. For each Attention head, represented with different colors, the corresponding Q and K chunks are multiplied to generate an Attention Map, which is, in turn, activated via the Softmax operator (see <a href="#jlpea-15-00008-f003" class="html-fig">Figure 3</a>) and then multiplied with the corresponding V chunk, to generate a portion of the Attention Output vector. Once every head has concluded its computation, the Attention Output is linearly projected back to the original sequence shape through another set of learnable parameters.</p>
Full article ">Figure 3
<p>The Softmax scheme normalizes each row of the Attention Map by subtracting the row-wise maximum, applying the exponential function, and dividing by the row sum, ensuring the scores of each row sum to 1, providing a “probabilistic” representation of the Head’s Attention Scores on each token.</p>
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<p>The GAP9 architecture scheme, based on the PULP platform architecture. The SoC domain on the left contains the Fabric Controller RISC-V core, L2 and L3 memory levels (SRAM and MRAM), HyperFlash, I/O interfaces, and signals. On the right is the cluster domain, composed of 9 RISC-V cores operating in parallel, with access to a shared L1 TCDM, shared FPUs, and instruction cash via an interleaved logarithmic interconnect. A non-blocking DMA unit manages data movements between different memory levels and domains, enabling multiple tiling strategies and pipelining for DNN applications.</p>
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<p>Execution loops of matrix multiplication. The naïve implementation is on top. On the left side, an example of unrolling with factor <math display="inline"><semantics> <mrow> <mn>2</mn> <mo>×</mo> <mn>4</mn> </mrow> </semantics></math>, in which the inner loop explicitly calculates eight output values, referring to two consecutive rows and four consecutive columns. Since these values are calculated using similar, consecutive inputs, data reuse in the register file is maximized. On the right side is a <math display="inline"><semantics> <mrow> <mn>1</mn> <mo>×</mo> <mn>2</mn> </mrow> </semantics></math> unrolling with SIMD instructions. Because SIMD instructions operate on packed word vectors of 2 bfloat16/half data, we are calculating eight output values in the inner loop on two consecutive rows and four consecutive columns, like in the example on the left.</p>
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<p>Pseudo-assembly code of matrix multiplication loop. On the left side is the naïve version. On the right side, the same loop uses hardware loops. The branch instructions and checks are not included in the loop by using hardware loops, improving performance. The color scheme of this image is the same as that used in <a href="#jlpea-15-00008-f005" class="html-fig">Figure 5</a> to facilitate linking each instruction to the corresponding implementation.</p>
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<p>Dataflow of the parallelized MatMul between Q and K. We follow the same nomenclature used in <a href="#sec3dot1-jlpea-15-00008" class="html-sec">Section 3.1</a>, shortening <math display="inline"><semantics> <mrow> <mi>n</mi> <mtext>_</mtext> <mi>h</mi> <mi>e</mi> <mi>a</mi> <mi>d</mi> <mi>s</mi> </mrow> </semantics></math> to <span class="html-italic">n</span> for the number of heads. Data are stored contiguously for each head on Q and K to enable access optimizations during matrix multiplication. The workload is split as evenly as possible to the cluster cores on the sequence dimension <span class="html-italic">L</span>, which is also the dimension of the square Attention maps. Only the address for the first element of the multiplication is required, as the rest of the data are accessible via post-increment instructions. Each Attention map <span class="html-italic">A</span>, one for each head, is computed sequentially, reusing data from K.</p>
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<p>The parallel tiling scheme for a linear layer. Given an input tensor of shape <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>×</mo> <mi>K</mi> </mrow> </semantics></math> and a weight tensor of shape <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>×</mo> <mi>W</mi> </mrow> </semantics></math>, the output tensor would be shape <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>×</mo> <mi>W</mi> </mrow> </semantics></math>. As the L1 memory is limited, we store the input, weight, and bias in the larger but slower L2 memory. To optimize execution, we transfer the data chunks required for computing a <math display="inline"><semantics> <mrow> <mi>h</mi> <mtext>_</mtext> <mi>t</mi> <mi>i</mi> <mi>l</mi> <mi>e</mi> <mo>×</mo> <mi>w</mi> <mtext>_</mtext> <mi>t</mi> <mi>i</mi> <mi>l</mi> <mi>e</mi> </mrow> </semantics></math> output tile from L2 to L1 using a non-blocking DMA unit, which manages transfers in both directions. The data chunks are stored sequentially in a shared memory region, and each core of the cluster has different pointers to access the correct data to calculate the output tile in a parallel fashion as described in <a href="#sec4dot2-jlpea-15-00008" class="html-sec">Section 4.2</a>.</p>
Full article ">Figure 9
<p>FP32 and FP16 MHSA Kernel performance on the sequence of 64 elements, embedding and projection size of 512, using four Attention heads. L1 versions use dynamic tiling strategies to fit a TCDM of 128KBs, whereas L2 versions are fully deployed on a larger but slower memory level and do not use any form of tiling.</p>
Full article ">Figure 10
<p>The distribution of internal operations in an MHSA kernel (on the left) and execution cycles (on the right). As the Softmax operation is more complex to optimize than the matrix multiplication due to its exponential and multiple iterations on the same data, its impact on the execution cycles grows with the sequence length.</p>
Full article ">Figure 11
<p>The single-encoder performance shown as MACs/cycle on GAP9 device on different sequence lengths and projection sizes, using four Attention head MHSA kernels. Less efficient parallelization and data movement schemes must be employed when working on smaller projection sizes, as the shape of the intermediate values may only partially fit on the L1 memory or not be evenly distributed to all computing cores. Increasing the sequence length also increases the Attention map size by a quadratic factor, increasing the less optimized Softmax’s overhead on computation cycles. Results have been color-graded, with darker green being the best.</p>
Full article ">Figure 12
<p>Comparison of parallelization of three SoA libraries. Cycles were counted when executing an MHSA kernel on GAP9, with an input sequence of 64 tokens with an embedding size of 64 projected to 8 heads, each of hidden size 64 (total hidden size 512). As both PULP-NN [<a href="#B27-jlpea-15-00008" class="html-bibr">27</a>] and TinyFormer [<a href="#B18-jlpea-15-00008" class="html-bibr">18</a>] are designed for Quantized Neural Network (QNN) inference, we compare their int8 data precision performance.</p>
Full article ">Figure 13
<p>The memory and latency tradeoff against accuracy on the GLUE benchmark. We start removing encoder layers starting from the classifier head. When pruning from MobileBert, memory and latency decrease linearly, down to fit for deployment on extreme edge devices. Accuracy does not follow the same behavior, as the error stays below 0.2 even with a single encoder layer left. Latency has been calculated on 128 tokens, setting the platform frequency to 370 MHz.</p>
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<p>The distribution of MACs/FLOPs (on the left) and runtime cycles (on the right) of a deployed MobileBert model based on the type of operating block.</p>
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<p>The distribution of internal operations in a TinyViT-5M Base model. MAC and FLOP operations are distributed on the left, and the distribution of execution cycles is on the right. Cycles have been counted on kernels executed with a tiling strategy to fit a 128 KB scratchpad memory.</p>
Full article ">Figure 16
<p>Number of learnable parameters (in millions) versus error in different model configurations. <b>FM</b>—the original TinyViT-5M. <b>A</b>—cropped embedder. <b>B</b>—cropped first encoder. <b>C1 to 5</b>—cropped second encoder, the number symbolizes how many layers were cropped from it. <b>D</b>—cropped third encoder. <b>E</b>—both embedder and second encoder cropped. <b>F</b>—all encoders cropped once. <b>G</b>—all encoders reduced to single-layer kernels.</p>
Full article ">Figure 17
<p>Execution cycles on FP16 accuracy vs. model error. The model labels represent the same models as listed in <a href="#jlpea-15-00008-f016" class="html-fig">Figure 16</a>.</p>
Full article ">Figure 18
<p>Confusion matrix, averaged over all the pruned models extracted from TinyViT, of the first 50 classes among the 1000 present in the Imagenet1k dataset. On average, the models associate the correct class for the majority of the test set. As each class has only 50 instances present in the test set, a value of 50 in the confusion matrix means that all the predictions of the models are correct for the specific class.</p>
Full article ">Figure 19
<p>Execution time and average power profiling of the tinyLLAMA model deployed on the GAP9 platform, generating a sequence of 256 tokens on three different computation frequencies. Time and power consumption for printing instructions were ignored.</p>
Full article ">
16 pages, 5968 KiB  
Article
Polyethylene Polyamine-Modified Chitosan Aerogels: Enhanced CO2 Adsorbents with Lamellar Porous Structures
by Hui Ming, Haoxin Jiang, Ruiyang Zheng, Mei Wu, Hongying Li, Zhengxin Li, Xudong Zhang, Zihao Yuan and Ziyue Wang
Polymers 2025, 17(3), 414; https://doi.org/10.3390/polym17030414 - 4 Feb 2025
Viewed by 457
Abstract
Due to the continuous growth of global carbon dioxide emissions, the development of cost-effective carbon dioxide capture technology has attracted extensive attention. Amino-modified chitosan aerogels with lamellar porous structures are good candidates as carbon dioxide adsorbents because of their degradable properties and low [...] Read more.
Due to the continuous growth of global carbon dioxide emissions, the development of cost-effective carbon dioxide capture technology has attracted extensive attention. Amino-modified chitosan aerogels with lamellar porous structures are good candidates as carbon dioxide adsorbents because of their degradable properties and low energy consumption. Polyethylene polyamine-modified chitosan aerogels (PEPA-CSs) were prepared through a process of crosslinking and freeze-drying using a chitosan solution, polyethylene polyamine (PEPA), and epichlorohydrin (ECH) as raw materials. The amino group of PEPA was proven to be successfully grafted on the chitosan surface by FITR and XPS. The SEM and TEM analysis showed a rich three-dimensional porous structure and a good rigidity and bearing capacity of the PEPA-CS. The adsorption capacity was significantly increased by PEPA grafting with a maximum value of 1.59 mmol/g at 25 °C and 1 bar through both physical and chemical interactions, which indicates a potential for broad application prospects in industrial CO2-capture applications. Full article
(This article belongs to the Section Polymer Networks)
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Figure 1

Figure 1
<p>Schematic of the preparation process and structural units of PEPA-CS.</p>
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<p>Diagram of carbon dioxide absorption unit.</p>
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<p>(<b>a</b>) FTIR spectra of a. PEPA-19, b. PEPA-15, c. PEPA-11, d. PEPA-7, e. PEPA-3. (<b>b</b>) FTIR spectra of modified aerogels with 2 g chitosan cross-linked 24 h and 1 g chitosan cross-linked 24 h. (<b>c</b>–<b>e</b>) Physical diagram of 2 g chitosan cross-linked 24 h modified aerogel. Physical diagram of 2 g chitosan cross-linked 12 h modified aerogel. Physical diagram of 1 g chitosan cross-linked 24 h modified aerogel. (<b>f</b>) Physical diagram of PEPA-3, PEPA-7, PEPA-11, PEPA-15, PEPA-19.</p>
Full article ">Figure 3 Cont.
<p>(<b>a</b>) FTIR spectra of a. PEPA-19, b. PEPA-15, c. PEPA-11, d. PEPA-7, e. PEPA-3. (<b>b</b>) FTIR spectra of modified aerogels with 2 g chitosan cross-linked 24 h and 1 g chitosan cross-linked 24 h. (<b>c</b>–<b>e</b>) Physical diagram of 2 g chitosan cross-linked 24 h modified aerogel. Physical diagram of 2 g chitosan cross-linked 12 h modified aerogel. Physical diagram of 1 g chitosan cross-linked 24 h modified aerogel. (<b>f</b>) Physical diagram of PEPA-3, PEPA-7, PEPA-11, PEPA-15, PEPA-19.</p>
Full article ">Figure 4
<p>FTIR spectra of PEPA-15 and pure CS aerogel.</p>
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<p>Thermogravimetric curves of PEPA-CS aerogel.</p>
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<p>(<b>a</b>,<b>b</b>) SEM image of PEPA-CS aerogel. (<b>c</b>) TEM image of PEPA-CS aerogel. (<b>d</b>) SEM and TEM image of pure CS aerogel.</p>
Full article ">Figure 7
<p>N<sub>2</sub> adsorption–desorption isotherm of (<b>a</b>) PEPA-15, (<b>b</b>) PEPA-19, (<b>c</b>) Cumulative Pore Volumes, (<b>d</b>) Cumulative Pore Area.</p>
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<p>XPS spectra of (<b>a</b>,<b>b</b>) N 1s and (<b>c</b>,<b>d</b>) O 1s before and after modification.</p>
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<p>CO<sub>2</sub> adoption of PEPA-3, PEPA-7, PEPA-11, PEPA-15, PEPA-19.</p>
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<p>CO<sub>2</sub> absorption capacity of PEPA-15 at different pressures.</p>
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18 pages, 3089 KiB  
Article
A Machine Learning Approach for Enhanced Glucose Prediction in Biosensors
by António Abreu, Daniela dos Santos Oliveira, Inês Vinagre, Dionisios Cavouras, Joaquim A. Alves, Ana I. Pereira, José Lima and Felismina T. C. Moreira
Chemosensors 2025, 13(2), 52; https://doi.org/10.3390/chemosensors13020052 - 4 Feb 2025
Viewed by 222
Abstract
The detection of glucose is crucial for diagnosing diseases such as diabetes and enables timely medical intervention. In this study, a disposable enzymatic screen-printed electrode electrochemical biosensor enhanced with machine learning (ML) for quantifying glucose in serum is presented. The platinum working surface [...] Read more.
The detection of glucose is crucial for diagnosing diseases such as diabetes and enables timely medical intervention. In this study, a disposable enzymatic screen-printed electrode electrochemical biosensor enhanced with machine learning (ML) for quantifying glucose in serum is presented. The platinum working surface was modified by chemical adsorption with biographene (BGr) and glucose oxidase, and the enzyme was encapsulated in polydopamine (PDP) by electropolymerisation. Electrochemical characterisation and morphological analysis (scanning and transmission electron microscopy) confirmed the modifications. Calibration curves in Cormay serum (CS) and selectivity tests with chronoamperometry were used to evaluate the biosensor’s performance. Non-linear ML regression algorithms for modelling glucose concentration and calibration parameters were tested to find the best-fit model for accurate predictions. The biosensor with BGr and enzyme encapsulation showed excellent performance with a linear range of 0.75–40 mM, a correlation of 0.988, and a detection limit of 0.078 mM. Of the algorithms tested, the decision tree accurately predicted calibration parameters and achieved a coefficient of determination above 0.9 for most metrics. Multilayer perceptron models effectively predicted glucose concentration with a coefficient of determination of 0.828, demonstrating the synergy of biosensor technology and ML for reliable glucose detection. Full article
(This article belongs to the Special Issue Electrochemical Sensing in Medical Diagnosis)
33 pages, 3262 KiB  
Review
Cigarette Smoke Contributes to the Progression of MASLD: From the Molecular Mechanisms to Therapy
by Jiatong Xu, Yifan Li, Zixuan Feng and Hongping Chen
Cells 2025, 14(3), 221; https://doi.org/10.3390/cells14030221 - 4 Feb 2025
Viewed by 335
Abstract
Cigarette smoke (CS), an intricate blend comprising over 4000 compounds, induces abnormal cellular reactions that harm multiple tissues. Non-alcoholic fatty liver disease (NAFLD) is a prevalent chronic liver disease (CLD), encompassing non-alcoholic fatty liver (NAFL), non-alcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular carcinoma (HCC). [...] Read more.
Cigarette smoke (CS), an intricate blend comprising over 4000 compounds, induces abnormal cellular reactions that harm multiple tissues. Non-alcoholic fatty liver disease (NAFLD) is a prevalent chronic liver disease (CLD), encompassing non-alcoholic fatty liver (NAFL), non-alcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular carcinoma (HCC). Recently, the term NAFLD has been changed to metabolic dysfunction-associated steatotic liver disease (MASLD), and NASH has been renamed metabolic dysfunction-associated steatohepatitis (MASH). A multitude of experiments have confirmed the association between CS and the incidence and progression of MASLD. However, the specific signaling pathways involved need to be updated with new scientific discoveries. CS exposure can disrupt lipid metabolism, induce inflammation and apoptosis, and stimulate liver fibrosis through multiple signaling pathways that promote the progression of MASLD. Currently, there is no officially approved efficacious pharmaceutical intervention in clinical practice. Therefore, lifestyle modifications have emerged as the primary therapeutic approach for managing MASLD. Smoking cessation and the application of a series of natural ingredients have been shown to ameliorate pathological changes in the liver induced by CS, potentially serving as an effective approach to decelerating MASLD development. This article aims to elucidate the specific signaling pathways through which smoking promotes MASLD, while summarizing the reversal factors identified in recent studies, thereby offering novel insights for future research on and the treatment of MASLD. Full article
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Figure 1

Figure 1
<p>In MASLD, CS affects the AMPK signaling pathway in different ways in the liver (<b>A</b>), adipose tissue (<b>B</b>), and ileum (<b>C</b>) to perturb lipid metabolism. The solid arrows represent ‘facilitation’, the dashed arrows in different colors represent ‘transport’, and the solid ‘T’ lines represent ‘inhibition’. Abbreviations: CS: cigarette smoke; MPO: myeloperoxidase; Keap1: Kelch-like ECH-associated protein 1; Nrf2: nuclear factor erythroid 2-related factor 2, ARE: antioxidant response element; CAT: catalase; SOD: superoxide dismutase; HO-1: heme oxygenase-1; ROS: reactive oxygen species; AMPK: AMP-activated protein kinase; mTOR: mammalian target of rapamycin; pS6-K: p70 ribosomal S6 kinase; pS6: phosphorylated S6 ribosomal protein; SREBP: sterol regulatory element-binding protein; NAD+: nicotinamide adenine dinucleotide; Sirt1: Sirtuin 1; PGC1-α: peroxisome proliferator-activated receptor-γ co-activator 1; NR: nicotinamide riboside; SRE: sterol response elements; Acetyl CoA: acetyl coenzyme A, Acetoacetyl CoA: acetoacetyl coenzyme A; HMG CoA: 3-hydroxy-3-methyl glutaryl coenzyme A; ACC: acetyl CoA carboxylase; Fas: fatty acid synthases; SCD1: stearoyl-CoA desaturase-1; Malonyl CoA: malonyl coenzyme A; FFA: free fatty acid; MKP1: MAP kinase phosphatase-1; P38-MAPK: p38 mitogen-activated protein kinase; JNK: c-Jun-NH 2 -terminal kinase; IRS1: insulin receptor substrate 1; AKT: protein kinase B; SMPD-3: sphingomyelin phosphodiesterase 3; B. xylanisolvens: Bacteroides xylanisolvens. (This figure was created with <a href="http://biorender.com" target="_blank">biorender.com</a>, accessed on 3 February 2025).</p>
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<p>The molecular mechanism of CS-induced hepatocellular damage. CS can trigger the injury and death of hepatocytes through oxidative stress, inflammation, and apoptosis-related signaling pathways. The black arrows represent the progression of molecular mechanism in MASLD. The red arrows represent the positive or negative effect of CS exposure on development and progression of MASH. The red cross mark represents CS exposure can inhibit the transcription of Acsl3 and Mel. Abbreviations: CISD3: CDGSH iron sulfur domain 3; Drp1-S637: dynamin-related protein 1 serine 637; MDA: malondialdehyde; CYP2E1: cytochrome P450, family 2, subfamily E, polypeptide 1; NOS2: nitric oxide synthase 2; 4-HNE: 4-hydroxynonenal; SOD: superoxide dismutase; CAT: catalase; GSH: glutathione; HO-1: heme oxygenase 1; ROS: reactive oxygen species; PARD: programmed death receptor; NAD+: nicotinamide adenine dinucleotide; Sir1: silent information regulator 1; PINK1: PTEN-induced putative kinase; NRF1/2: nuclear respiratory factor 1; NF-κB: nuclear factor-kappa B; ERK: extracellular regulated protein kinase; PI3K/Akt: phosphatidylinositol-3-kinase/protein kinase B; IR: insulin resistance; PKC: protein kinase C; PPARα: peroxisome proliferator-activated receptor α; SREBP1c: sterol regulatory element-binding protein-1c; TGs: triglycerides; KCs: Kupffer cells; SMPD3: sphingomyelin phosphodiesterase 3; AMPKα1: AMP-activated protein kinase; TNF-α: tumor necrosis factor α; IL: interleukin; GM-CSF: granulocyte–macrophage colony-stimulating factor; NLRP3/6: Nod-like receptor protein 3/6; ER stress: endoplasmic reticulum stress; PERK: protein kinase RNA-like ER kinase; eIF2α: eukaryotic initiation factor 2; CHOP: CCAAT–enhancer-binding protein homologous protein; Bcl2: B-cell lymphoma-2; Bax: Bcl-2 associated X protein; APAF1: apoptotic peptidase activating factor-1; GSDMD: gasdermin D; TRAIL: tumor necrosis factor-related apoptosis-inducing ligand; Fas-L: Fas ligand; FADD: Fas-associating protein with a novel death domain. (This figure was created with <a href="http://biorender.com" target="_blank">biorender.com</a>, accessed on 10 December 2024).</p>
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<p>Downstream signaling in regard to the promotion of liver fibrosis by CS. The solid arrows represent ‘facilitation’, the dashed arrows in different colors represent ‘transport’, and the solid ‘T’ lines represent ‘inhibition’. (<b>A</b>) Nicotine promotes cholangiocyte proliferation. CS activates macrophages, generates ROS and inflammatory molecules to transform inactive HSCs into active MFBs. Additionally, the CS/MAPK/AP-1 signaling pathway in hepatic epithelial cells can promote EMT, which is a potential source of MFB. (<b>B</b>) CS-induced signaling pathway in HSCs. CS can trigger various downstream signaling pathways to activate collagen production, promote HSC proliferation and survival, and stimulate the recruitment of MDMs to continuously induce liver fibrosis. Abbreviations: CS: cigarette smoke; KC: Kupffer cell; MDM: monocyte-derived macrophages; MCP-1: monocyte chemoattractant protein-1; HSC: hepatic satellite cell; MFB: myofibroblasts, ROS: reactive oxygen species; TGF-β: transforming growth factor-β; TNF-α: tumor necrosis factor-α; IL-1β: interleukin-1β; IL-6: interleukin-6; EMT: epithelial–mesenchymal transition; AP-1: activator protein-1; TβRI: TGF-β type I receptor; TβRII: TGF-β type II receptor; nAChR: neuronal nicotinic acetylcholine receptor; DVL-2: disheveled 2; STAT-3: signal transducer and activator of transcription 3; TIMP-1: metalloproteinase-1; MMP: matrix metalloproteinase; Fli-1: friend leukemia virus integration-1; α-SMA: α-smooth muscle actin; Col1A1: collagen type I α1 chain; Col3A1: collagen type III α1 chain; GSK-3β: glycogen synthase kinase-3β; PI3K: phosphatidylinositol-3-kinase; PKC: protein kinase C. (This figure was created with <a href="http://biorender.com" target="_blank">biorender.com</a>, accessed on 3 February 2025).</p>
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17 pages, 2887 KiB  
Article
Preparation and Properties of Glycerohydrogels Based on Silicon Tetraglycerolate, Chitosan Hydrochloride and Glucomannan
by Sergei L. Shmakov, Olga S. Ushakova, Marina A. Kalinicheva and Anna B. Shipovskaya
Gels 2025, 11(2), 103; https://doi.org/10.3390/gels11020103 - 2 Feb 2025
Viewed by 292
Abstract
Glycerohydrogels based on silicon glycerolate, chitosan (CS) and polyvinyl alcohol (PVA) are widely studied for use in biomedical applications. In line with the general trend of replacing synthetic polymers with natural ones in such compositions, it would be of interest to replace PVA [...] Read more.
Glycerohydrogels based on silicon glycerolate, chitosan (CS) and polyvinyl alcohol (PVA) are widely studied for use in biomedical applications. In line with the general trend of replacing synthetic polymers with natural ones in such compositions, it would be of interest to replace PVA with the polysaccharide glucomannan (GM), as well as to introduce functional additives to impart the desired properties, including gelation time, to the final hydrogel. In this work, a comprehensive study of the preparation conditions and properties of glycerohydrogels based on silicon tetraglycerolate, chitosan hydrochloride (CS·HCl) and GM was carried out. Viscometry was used to assess the conformational state of CS·HCl and GM macromolecules, and their associates in solution before gelation. Gelation was studied using the vessel inversion method. The mucoadhesive and the dermoadhesive properties of the glycerohydrogels obtained were assessed using the tearing off method from the model substrates simulating mucous and dermal tissues. The conformational state of the individual polymers and their mixed associates in solution before gelation was estimated; the intrinsic viscosity and the hydrodynamic radius of the macromolecular coils were calculated. The influence of various factors (addition of ε-aminocaproic and hydrochloric acids, sodium chloride, hydroxide and tetraborate to vary the acidity and ionic strength of the medium, as well as temperature) and the molecular weight of chitosan on the gelation time was studied. The gelation time achieved was less than 2 min, which is promising in practical terms, i.e., for creating liquid plasters. Our best samples are not inferior to the commercial preparation “Metrogyl Denta”® in terms of tearing force during mucoadhesion and dermoadhesion at short gelation times. Thus, the glycerohydrogels synthesized by us and based on silicon tetraglycerolate, CS·HCl and GM could find usage in new biopharmaceutical and biomedical applications. Full article
(This article belongs to the Special Issue Chemical Properties and Application of Gel Materials)
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<p>Viscometric properties of solutions of glucomannan, chitosan hydrochloride and their mixtures. (<b>a</b>,<b>b</b>) Concentration dependence of the reduced viscosity (η<sub>sp</sub>/<span class="html-italic">C</span>) of solutions of GM (<b>a</b>), CS-80·HCl and CS-200·HCl (<b>b</b>) (CS-200·HCl solutions of higher concentrations cannot be studied by capillary viscometry, since the solution flow time would be too long due to the high molecular weight of the polymer, which would lead to large errors in determining the reduced viscosity.) at 25 °C. (<b>c</b>) Diagram of the intrinsic viscosity of GM + CS-80(200)·HCl mixtures of different compositions, 25 °C; the dashed straight lines correspond to the additive values of intrinsic viscosity [η]. The insets show a schematic representation of the macromolecular coils of GM (<b>a</b>), CS-80(200)·HCl (<b>b</b>) and the associate GM + CS-80(200)·HCl (<b>c</b>).</p>
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<p>Viscometric properties of solutions of glucomannan, chitosan hydrochloride and their mixtures. (<b>a</b>,<b>b</b>) Concentration dependence of the reduced viscosity (η<sub>sp</sub>/<span class="html-italic">C</span>) of solutions of GM (<b>a</b>), CS-80·HCl and CS-200·HCl (<b>b</b>) (CS-200·HCl solutions of higher concentrations cannot be studied by capillary viscometry, since the solution flow time would be too long due to the high molecular weight of the polymer, which would lead to large errors in determining the reduced viscosity.) at 25 °C. (<b>c</b>) Diagram of the intrinsic viscosity of GM + CS-80(200)·HCl mixtures of different compositions, 25 °C; the dashed straight lines correspond to the additive values of intrinsic viscosity [η]. The insets show a schematic representation of the macromolecular coils of GM (<b>a</b>), CS-80(200)·HCl (<b>b</b>) and the associate GM + CS-80(200)·HCl (<b>c</b>).</p>
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<p>Dependence of the gelation time of the systems on the <span class="html-italic">C</span><sub>Polym</sub>/<span class="html-italic">C</span><sub>Si</sub> ratio (<span class="html-italic">C</span><sub>GM</sub>/<span class="html-italic">C</span><sub>Si</sub>) for: (<b>a</b>) GM (the lower abscissa axis), GM + CS-80·HCl of 1:1 and 1:2 wt.% composition with and without the addition of AmA (the higher abscissa axis); (<b>b</b>) GM + CS-80(200)·HCl + AmA with the addition of STB (Systems with STB and without AmA were studied but are not included in our manuscript because without the addition of AmA the pH of the formed hydrogels is highly acidic, which is not suitable for biomedical applications), 25 °C. The systems with ultra-fast gelation (<b>b</b>) were then used to evaluate the mucoadhesive and dermoadhesive properties. The <span class="html-italic">C</span><sub>Polym</sub> values correspond to the total concentration of GM + CS-80(200)·HCl in the gelation system, <span class="html-italic">C</span><sub>Si</sub> is the concentration of Si(OGly)<sub>4</sub>. The absolute concentrations of the polymers in the mixture and their values recalculated to the silicon concentration are given in <a href="#app1-gels-11-00103" class="html-app">Tables S3-1 and S3-2</a>. Here, in <a href="#gels-11-00103-f002" class="html-fig">Figure 2</a>a and further in Figure 4, the gelation time of Si(OGly)<sub>4</sub> in an aqueous medium is indicated on the ordinate axis, <span class="html-italic">C</span><sub>Si</sub> = 47.0 wt.%.</p>
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<p>Dependence of the gelation time of the GM + CS-80(200)·HCl mixture with and without the addition of AmA on the NaOH concentration in the gel-forming system, 25 °C. The pH values in the legend correspond to the acidity index of the initial system before the introduction of NaOH. The absolute concentrations of the polymers and NaOH in the mixture are given in <a href="#app1-gels-11-00103" class="html-app">Table S4</a>.</p>
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<p>Dependence of the gelation time of the systems based on CS-80·HCl + AmA (<b>a</b>,<b>b</b>) and CS-200·HCl + AmA (<b>c</b>) without and with the addition of HCl or NaCl on the <span class="html-italic">C</span><sub>CS·HCl</sub>/<span class="html-italic">C</span><sub>Si</sub> ratio, 25 °C (<b>a</b>,<b>c</b>) and 37 °C (<b>b</b>,<b>c</b>). The absolute concentrations of the polymers in the mixture are given in <a href="#app1-gels-11-00103" class="html-app">Table S5</a>.</p>
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<p>Photos of our biomedical experiments on a tensile testing machine with the obtained glycerohydrogel based on CS-80·HCl. (<b>a</b>) Fixed flap of rat skin (upper platform) and applied glycerohydrogel (lower platform). (<b>b</b>) Bringing the glycerohydrogel into contact with the dermal surface of rat skin with a force of 1.3 N. (<b>c</b>) The state of the adhesive contact at the end of the experiment to overcome adhesive forces.</p>
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20 pages, 15436 KiB  
Article
Genome-Wide Identification and Expression Pattern Analysis of Nuclear Factor Y B/C Genes in Pinus koraiensis, and Functional Identification of LEAFY COTYLEDON 1
by Xiuyue Xu, Xin He, Qun Zhang and Ling Yang
Plants 2025, 14(3), 438; https://doi.org/10.3390/plants14030438 - 2 Feb 2025
Viewed by 401
Abstract
The nuclear factor Y (NF-Y) transcription factor is widely involved in various plant biological processes, such as embryogenesis, abscisic acid signaling, and abiotic stress responses. This study presents a comprehensive genome-wide identification and expression profile of transcription factors NF-YB and NF-YC in Pinus [...] Read more.
The nuclear factor Y (NF-Y) transcription factor is widely involved in various plant biological processes, such as embryogenesis, abscisic acid signaling, and abiotic stress responses. This study presents a comprehensive genome-wide identification and expression profile of transcription factors NF-YB and NF-YC in Pinus koraiensis. Eight NF-YB and seven NF-YC transcription factors were identified through bioinformatics analysis, including sequence alignment, phylogenetic tree construction, and conserved motif analysis. We evaluate the expression patterns of NF-YB/C genes in various tissues and somatic embryo maturation processes through the transcriptomics of ABA-treated tissues from multiple nutritional tissues, reproductive tissues, and somatic embryo maturation processes. The Leafy cotyledon1 (LEC1) gene belongs to the LEC1-type gene in the NF-YB family, numbered PkNF-YB7. In this study, we characterized the function of PkLEC1 during somatic embryonic development using genetic transformation techniques. The results indicate that PkNF-YB/C transcription factors are involved in the growth and development of nutritional tissues and reproductive organs, with specific high expression in PkNF-YB7 embryogenic callus, somatic embryos, zygotic embryos, and macropores. Most PkNF YB/C genes do not respond to ABA treatment during the maturation culture process. Compared with the absence of ABA, PkNF-YB8 was up-regulated in ABA treatment for one week (4.1 times) and two weeks (11.6 times). However, PkNF-YC5 was down-regulated in both one week (0.6 times) and two weeks (0.36 times) of culture, but the down-regulation trend was weakened in tissues treated with ABA (0.72–0.83 times). In addition, the promoter of PkNF YB/Cs was rich in elements that respond to various plant hormones, indicating their critical role in hormone pathways. The overexpression of PkLEC1 stimulated the generation of early somatic embryos from callus tissue with no potential for embryogenesis, enhancing the somatic embryogenesis ability of P. koraiensis callus tissue. Full article
(This article belongs to the Special Issue Advances in Forest Tree Genetics and Breeding)
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<p>Phylogenetic analysis and multiple alignment of amino acid sequences. Multispecies phylogenetic analysis of NF-YB (<b>A</b>) and NF-YC (<b>B</b>) proteins, including <span class="html-italic">Arabidopsis thalian</span>, <span class="html-italic">Pinus koraiensis</span>, <span class="html-italic">Pinus taeda</span>, <span class="html-italic">Pinus tabuliformis</span>, <span class="html-italic">Populus trichocarpa</span>, <span class="html-italic">Picea abies</span>, <span class="html-italic">Oryza sativa</span>, and <span class="html-italic">Triticum aestivum</span>. Amino acid alignment of conserved domains of NF-YB (<b>C</b>) and NF-YC (<b>D</b>) proteins from different organisms. The sequence under the red line represents the region that interacts with NF-YA, while the sequence under the blue line represents the region that interacts with NF-YB; the sequence above the green line represents the region that interacts with NF-YC, while the sequence below the cyan line represents the region that binds to DNA. Gray lines include segments with conserved HFM regions.</p>
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<p>Structural analysis of proteins and conserved structures encoding corresponding proteins. Predicted conserved motifs and structures of PkNF-YBs (<b>A</b>) and PkNF-YCs (<b>B</b>). Different colors represent different conserved motifs. Yellow represents the protein-coding sequence (exon); green represents upstream/downstream sequences; the black line represents introns.</p>
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<p>Chromosomal location and intra species collinearity analysis of PKNF-YB/C. Thick red lines indicate duplicated gene pairs. The red font represents members of the NF-YB family, while the green font represents members of the NF-YC family. Chromosome numbers were displayed in the outer ring of each chromosome. There is no collinearity between <span class="html-italic">NF-YB</span> and <span class="html-italic">NF-YC</span> family members within this species. Scale bars marked on each chromosome indicate chromosome length (Mb).</p>
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<p>The genomes of <span class="html-italic">P. koraiensis</span>, <span class="html-italic">A. thaliana</span>, and <span class="html-italic">P. tabulaeformis</span> were subjected to collinearity analysis. The highlighted red line represents the <span class="html-italic">NF-YB/C</span> gene pairs with collinearity.</p>
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<p>Analysis of <span class="html-italic">cis</span>-elements of <span class="html-italic">PKNF-YB/C</span> promoters.</p>
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<p>GO enrichment analysis of NF-YB (<b>A</b>) and NF-YC (<b>B</b>) family members. KEGG enrichment analysis of NF-YB (<b>C</b>) and NF-YC (<b>D</b>) family members.</p>
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<p>Tissue-specific expression patterns of <span class="html-italic">PkNF-YB/C</span> genes in callus, embryo, root, stem, and leaf. EC: embryogenic callus; NEC: non-embryogenic callus; SE: somatic embryogenesis; embryo: zygotic embryo; seed: mature seed. The depth of color and the size of the circle area represent the level of expression. The transcriptome expression data underwent log<sub>2</sub><sup>(FPKM)</sup> transformation and were normalized using a 0–1 approach. The circle on the right serves as the scale bar. The larger the area, the redder the color, indicating a higher relative expression level.</p>
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<p>Expression patterns of the <span class="html-italic">PkNF YB/C</span> genes at different stages of reproductive organ development. FA–FD indicate different stages of microsporophyll: tender branches without differentiated microsporophyll, immature microsporophyll, mature microsporophyll, and dried and withered microspore leaves after pollen dispersion. MA–ME indicate different stages of megasporophylls: tender branches without differentiated megasporophyll, female flower bud (megasporophyll), closed megasporophylls before pollination, macrosporophyll unfolding during pollination, and closed megasporophylls after pollination. ZA–ZD: ovules during the female gametophyte stage, ovules during pollen tube extension, fertilized ovules, and an ovule that begins cell division and development. The color and the size of the circle area represent the level of expression. The transcriptome expression data underwent log<sub>2</sub><sup>(FPKM)</sup> transformation and were normalized using a 0–1 approach. The circle on the right serves as the scale bar. The larger the area, the redder the color, indicating a higher relative expression level.</p>
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<p>Expression patterns of PkNF YB/C genes in ABA treatment. CK: white space handling; +ABA: somatic embryos grown on mature medium supplemented with 80 μmol∙L<sup>−1</sup> ABA; −ABA: somatic embryos grown on mature medium supplemented without ABA. The transcriptome expression data were normalized using CK as the control standard, while the data from other treatment groups were normalized using log<sub>2</sub><sup>FPKM (treatment)/FPKM (CK)</sup> as values.</p>
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<p>Subcellular localization of <span class="html-italic">PkNF-YB/C</span> proteins. DAPI: a nuclear staining dye; BF: bright field; merge: The merged images of BF, eGFP, and DAPI staining. White arrow indicates the location of the cell nucleus.</p>
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<p>Analysis of the transcriptional activation activity of <span class="html-italic">PkNF-YB/C</span> proteins. pGBKT7: negative control.</p>
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<p>The protein interaction network of PkNF-YB and PkNF-YC. The red nodes represent the PkNF-YB and PkNF-YC proteins, while the green nodes represent the predicted interaction proteins. The connecting lines represent the interacting relationships.</p>
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<p>Identification and transgenic lines of PkLEC1 in <span class="html-italic">P. koraiensis</span>. qRTPCR detection of PkLEC1 transgenic lines (<b>A</b>). Pk18S was used as a control. Each error bar represents the standard deviation of three biological replicates. Asterisks indicate levels of significance (Dunnett’s test; *, <span class="html-italic">p</span> &lt; 0.05). Mature phenotype of <span class="html-italic">PkNF-YB 7</span> transgenic cell lines (<b>B</b>). WT and <span class="html-italic">PkNF-YB 7</span> transgenic lines under 8-week mature culturation (T31, T33, and T34).</p>
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21 pages, 5047 KiB  
Article
Electrospun WO3/TiO2 Core–Shell Nanowires for Triethylamine Gas Sensing
by Wenhao Li, Bo Zhang, Xiangrui Dong, Qi Lu, Hao Shen, Yi Ni, Yuechen Liu and Haitao Song
Chemosensors 2025, 13(2), 45; https://doi.org/10.3390/chemosensors13020045 - 2 Feb 2025
Viewed by 519
Abstract
In this work, WO3/TiO2 core–shell (C-S) nanowires (NWs) were successfully synthesized by the coaxial electrospinning method and subsequent high-temperature calcination treatment. After some microscopic structural characterizations, although the prepared WO3–TiO2 and TiO2–WO3 C-S NWs [...] Read more.
In this work, WO3/TiO2 core–shell (C-S) nanowires (NWs) were successfully synthesized by the coaxial electrospinning method and subsequent high-temperature calcination treatment. After some microscopic structural characterizations, although the prepared WO3–TiO2 and TiO2–WO3 C-S NWs displayed quite different surface morphologies, both of the shell coatings were uniform and their typical shell thicknesses were extremely close, with mean values of 22 and 20 nm, respectively. In gas sensing tests, WO3/TiO2 C-S NWs exhibited good selectivity towards triethylamine (TEA) without significant interfering gases. Compared with bare WO3 and TiO2 NWs, WO3/TiO2 C-S NWs showed better gas sensing performance. Specifically, the optimal operating temperature and response of TiO2–WO3 C-S NWs to 100 ppm TEA were 130 °C and 106, which were reduced by 70 °C and increased by 5.73 times compared to bare WO3, respectively. Obviously, the C-S nanostructures contributed to improving the gas sensing performance of materials towards TEA. Finally, some hypothetical sensing mechanisms were proposed, which were expected to have important reference significance for the design of target products applied to TEA sensing. Full article
(This article belongs to the Special Issue Recent Progress in Nano Material-Based Gas Sensors)
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<p>XRD patterns of TiO<sub>2</sub> NWs, WO<sub>3</sub> NWs, WO<sub>3</sub>–TiO<sub>2</sub> C-S NWs, and TiO<sub>2</sub>–WO<sub>3</sub> C-S NWs.</p>
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<p>FESEM images under different magnifications of (<b>a</b>–<b>c</b>) TiO<sub>2</sub> NWs, (<b>d</b>–<b>f</b>) WO<sub>3</sub> NWs, (<b>g</b>–<b>i</b>) WO<sub>3</sub>–TiO<sub>2</sub> C-S NWs, and (<b>j</b>–<b>l</b>) TiO<sub>2</sub>–WO<sub>3</sub> C-S NWs.</p>
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<p>TEM images under different resolutions of (<b>a</b>–<b>d</b>) WO<sub>3</sub>–TiO<sub>2</sub> C-S NWs and (<b>e</b>–<b>h</b>) TiO<sub>2</sub>–WO<sub>3</sub> C-S NWs.</p>
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<p>(<b>a</b>) XPS full spectra of four products; high-resolution Ti 2p spectra of (<b>b</b>) TiO<sub>2</sub> NWs, (<b>c</b>) WO<sub>3</sub>–TiO<sub>2</sub> C-S NWs, and (<b>d</b>) TiO<sub>2</sub>–WO<sub>3</sub> C-S NWs; high-resolution W 4f spectra of (<b>e</b>) WO<sub>3</sub> NWs, (<b>f</b>) WO<sub>3</sub>–TiO<sub>2</sub> C-S NWs, and (<b>g</b>) TiO<sub>2</sub>–WO<sub>3</sub> C-S NWs; high-resolution O 1s spectra of (<b>h</b>) TiO<sub>2</sub> NWs, (<b>i</b>) WO<sub>3</sub> NWs, (<b>j</b>) WO<sub>3</sub>–TiO<sub>2</sub> C-S NWs, and (<b>k</b>) TiO<sub>2</sub>–WO<sub>3</sub> C-S NWs.</p>
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<p>Response curves of sensors based on TiO<sub>2</sub> NWs, WO<sub>3</sub> NWs, WO<sub>3</sub>–TiO<sub>2</sub> C-S NWs, and TiO<sub>2</sub>–WO<sub>3</sub> C-S NWs to 100 ppm TEA at different temperatures.</p>
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<p>(<b>a</b>) Response–recovery curves of sensors based on (<b>a</b>) TiO<sub>2</sub> NWs, (<b>b</b>) WO<sub>3</sub> NWs, (<b>c</b>) WO<sub>3</sub>–TiO<sub>2</sub> C-S NWs, and (<b>d</b>) TiO<sub>2</sub>–WO<sub>3</sub> C-S NWs to 100 ppm TEA at their respective optimal working temperatures. Comparison of response–recovery properties of four sensors to 100 ppm TEA at (<b>e</b>) 130 °C and (<b>f</b>) 220 °C.</p>
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<p>Sensing tests of sensors based on (<b>a</b>) TiO<sub>2</sub> NWs, (<b>b</b>) WO<sub>3</sub> NWs, (<b>c</b>) WO<sub>3</sub>–TiO<sub>2</sub> C-S NWs, and (<b>d</b>) TiO<sub>2</sub>–WO<sub>3</sub> C-S NWs to TEA under the set concentration gradients at their respective optimal working temperatures. (<b>e</b>) Response–concentration correlation curves of our four sensors. Linear response–concentration fitting curves of (<b>f</b>) TiO<sub>2</sub> and WO<sub>3</sub> NWs and (<b>g</b>) WO<sub>3</sub>/TiO<sub>2</sub> C-S NWs to TEA at their respective optimal operating temperatures.</p>
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<p>Cyclic test curves of sensors based on (<b>a</b>) TiO<sub>2</sub> NWs, (<b>b</b>) WO<sub>3</sub> NWs, (<b>c</b>) WO<sub>3</sub>–TiO<sub>2</sub> C-S NWs, and (<b>d</b>) TiO<sub>2</sub>–WO<sub>3</sub> C-S NWs to 100 ppm TEA at their respective optimal working temperatures.</p>
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<p>(<b>a</b>) The responses of the four sensors to 100 ppm of different kinds of VOCs at their respective optimal operating temperatures. (<b>b</b>) A comparison of the response ratios of TEA to other interfering VOCs for the four sensors.</p>
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<p>(<b>a</b>) Energy band diagrams of TiO<sub>2</sub> and WO<sub>3</sub>. (<b>b</b>) Types and variations of energy barriers in TiO<sub>2</sub>–WO<sub>3</sub> C-S NWs.</p>
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<p>A comparison of the four prepared materials’ resistances at the same temperature.</p>
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13 pages, 724 KiB  
Article
Theoretical Analysis of Power Conversion Efficiency of Lead-Free Double-Perovskite Cs2TiBr6 Solar Cells with Different Hole Transport Layers
by Vivek Bhojak and Praveen Kumar Jain
Eng 2025, 6(2), 28; https://doi.org/10.3390/eng6020028 - 1 Feb 2025
Viewed by 423
Abstract
In recent years, there has been significant investigation into the high efficiency of perovskite solar cells. These cells have the capacity to attain efficiencies above 14%. As the perovskite materials that include lead pose a substantial environmental risk, components that are free from [...] Read more.
In recent years, there has been significant investigation into the high efficiency of perovskite solar cells. These cells have the capacity to attain efficiencies above 14%. As the perovskite materials that include lead pose a substantial environmental risk, components that are free from lead are used during the process of solar cell development. In this work, we use a lead-free double-perovskite material, namely Cs2TiBr6, as the main absorbing layer in perovskite solar cells to enhance power conversion efficiency (PCE). This work is centered on the development of solar cell structures with materials such as an ETL (electron transport layer) and an HTL (hole transport layer) to enhance the PCE. In this theoretical work, we perform simulations and analysis on double-perovskite Cs2TiBr6 to assess its efficacy as an absorber material in various HTLs like Cu2O and CuI, with a fixed ETL of C60 using SCAPS (Solar Cell Capacitance Simulator, SCAPS 3.3.10) Software. This is a one-dimensional solar cell simulation program. In this work, the thickness of the double-perovskite material is also varied between 0.2 and 2.0 µm, and its efficiency is observed. The effect of temperature variation on efficiency in the range of 300 K to 350 K is observed. The effect of defect density on efficiency is also observed in the range of 1 × 1011 to 1 × 1016. In this theoretical work, perovskite solar cells, including their absorbing layer, demonstrate outstanding ETLs and HTLs, respectively. As a result, the cells’ achieved PCE is improved. This work demonstrates the effectiveness of this lead-free double-perovskite structure that absorbs light in perovskite solar cells. Full article
15 pages, 395 KiB  
Article
A Snapshot Survey of Uterotonic Administration Practice During Cesarean Section: Is There a Difference Between the Attitudes of Obstetricians and Anesthesiologists?
by Nuray Camgoz Eryilmaz, Selin Erel and D. Berrin Gunaydin
Medicina 2025, 61(2), 253; https://doi.org/10.3390/medicina61020253 - 1 Feb 2025
Viewed by 403
Abstract
Background and Objectives: We aimed to evaluate the current uterotonic administration practices among anesthesiologists and obstetricians and gynecologists (OBGYNs) during cesarean section (CS), focusing on variations in approaches for low- and high-risk postpartum hemorrhage (PPH) cases. The objective was to identify key [...] Read more.
Background and Objectives: We aimed to evaluate the current uterotonic administration practices among anesthesiologists and obstetricians and gynecologists (OBGYNs) during cesarean section (CS), focusing on variations in approaches for low- and high-risk postpartum hemorrhage (PPH) cases. The objective was to identify key differences and provide evidence that could contribute to the development of standardized national protocols for uterotonic usage. Materials and Methods: A snapshot online survey was employed between October 2021 and January 2022 and distributed to anesthesiologists and OBGYNs from university-affiliated, government, and private hospitals across Turkey, consisting of 23 questions addressing demographic data, institutional PPH rates, first-line uterotonic choices, administration methods, and dose adjustments for low- and high-risk PPH cases. Specific questions also targeted uterotonic usage in the presence of comorbidities such as pre-eclampsia and cardiac disease. Results: There were 204 responses (54% anesthesiologists and 46% OBGYNs) out of 220, yielding a response rate of 92.7%. Oxytocin was the most common first-line uterotonic for CS with low-risk PPH (99.1% of the anesthesiologists and 96.8% of the OBGYNs). In total, 60% of the anesthesiologists favored an intravenous (IV) bolus followed by infusion, while 56.4% of the OBGYNs preferred IV infusion alone (p < 0.001). For CS with high-risk PPH, approximately half of the participants reported increases in oxytocin dose, while 26.4% of the anesthesiologists and 20.2% of the OBGYNs opted for combined oxytocin and carbetocin use. During intrapartum CS, 69.1% of anesthesiologists and 77.7% of OBGYNs reported no change in dose. However, 11.8% of the anesthesiologists indicated combining oxytocin and carbetocin (p < 0.05). In managing pre-eclampsia and cardiac disease, the anesthesiologists were likely to reduce uterotonic doses (15.5%) and avoid methylergonovine (35.5%) compared to the OBGYNs, who reduced doses less frequently (4.3%), but 79.8% of the OBGYNs avoided methylergonovine (p < 0.001). Conclusions: There was considerable variability in uterotonic administration practices between the anesthesiologists and OBGYNs. Full article
(This article belongs to the Section Intensive Care/ Anesthesiology)
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<p>Flowchart.</p>
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19 pages, 2723 KiB  
Article
miRNA Signatures in Alveolar Macrophages Related to Cigarette Smoke: Assessment and Bioinformatics Analysis
by Davida Mirra, Renata Esposito, Giuseppe Spaziano, Concetta Rafaniello, Francesca Panico, Antonio Squillante, Maddalena Falciani, Diana Marisol Abrego-Guandique, Eleonora Caiazzo, Luca Gallelli, Erika Cione and Bruno D’Agostino
Int. J. Mol. Sci. 2025, 26(3), 1277; https://doi.org/10.3390/ijms26031277 - 1 Feb 2025
Viewed by 309
Abstract
 Cigarette smoke (CS) is a driver of many respiratory diseases, including chronic obstructive pulmonary disease (COPD) and non-small cell lung cancer (NSCLC). Tobacco causes oxidative stress, impaired phagocytosis of alveolar macrophages (AMs), and alterations in gene expression in the lungs of smokers. [...] Read more.
 Cigarette smoke (CS) is a driver of many respiratory diseases, including chronic obstructive pulmonary disease (COPD) and non-small cell lung cancer (NSCLC). Tobacco causes oxidative stress, impaired phagocytosis of alveolar macrophages (AMs), and alterations in gene expression in the lungs of smokers. MicroRNAs (miRNAs) are small non-coding RNAs that influence several regulatory pathways. Previously, we monitored the expressions of hsa-miR-223-5p, 16-5p, 20a-5p, -17-5p, 34a-5p, and 106a-5p in AMs derived from the bronchoalveolar lavage (BAL) of subjects with NSCLC, COPD, and smoker and non-smoker control groups. Here, we investigated the capability of CS conditionate media to modulate the abovementioned miRNAs in primary AMs obtained in the same 43 sex-matched subjects. The expressions of has-miR-34a-5p, 17-5p, 16-5p, 106a-5p, 223-5p, and 20a-5p were assessed before and after in vitro CS exposure by RT-PCR. In addition, a comprehensive bioinformatic analysis of miRNAs KEGGS and PPI linked to inflammation was performed. Distinct and common miRNA expression profiles were identified in response to CS, suggesting their possible role in smoking-related diseases. It is worth noting that, following exposure to CS, the expression levels of hsa-miR-34a-5p and 17-5p in both smokers and non-smokers, 106a-5p in non-smokers, and 20a-5p in smokers, shifted towards those found in individuals with COPD, suggesting them as a risk factor in developing this lung condition. Moreover, CS-focused sub-analysis identified miRNA which exhibited CS-dependent pattern and modulated mRNA involved in the immune system or AMs property regulation. In conclusion, our study uncovered miRNA signatures in AMs exposed to CS, indicating that CS might modify epigenetic patterns that contribute to macrophage activation and lung disease onset and progression. Full article
(This article belongs to the Special Issue Roles and Mechanisms of Non-Coding RNAs in Human Health and Disease)
18 pages, 4964 KiB  
Article
The Numerical Simulation and Experimental Investigation of the Laser Quenching Process of GCr15 Joint Bearings
by Xiuli Yang, Hao Zhang, Dongliang Jin, Xiqiang Ma and Maolin Cheng
Coatings 2025, 15(2), 158; https://doi.org/10.3390/coatings15020158 - 1 Feb 2025
Viewed by 279
Abstract
Joint bearings are widely used in modern industry in order to improve the mechanical properties of the outer surface of its inner ring. A laser quenching experiment was carried out in this paper. First of all, an experimental investigation was conducted on GCr15 [...] Read more.
Joint bearings are widely used in modern industry in order to improve the mechanical properties of the outer surface of its inner ring. A laser quenching experiment was carried out in this paper. First of all, an experimental investigation was conducted on GCr15 ball-bearing material utilizing laser quenching, focusing on the effects of laser irradiation angles ranging from 0° to 10° and laser power levels between 600 W and 1100 W on the degree of hardening and microstructural alterations of the bearing material. Additionally, a reliable finite element analysis model was developed to assess the temperature field throughout the process. The findings indicate that an inclined laser enhances the stability of the hardened layer. Specifically, the hardening effect is minimal when the laser power is below 700 W, and optimal hardening is observed at power levels between 800 W and 900 W. During the laser quenching process when the temperature of the bearing material surpasses Ac1, the cooling rate can exceed 1700 °C/s. In regions where the peak temperature exceeds Ac1, the microstructure will undergo refinement, resulting in a reduction in the size of the martensite and a significant decrease in the number of carbides. In addition, the hardness value of these regions can be increased by 6 to 8 HRC, and the thickness of the quenching layer may exceed 0.3 mm. In the temperature range between Ac1 and Ms, the bearing material undergoes tempering, resulting in lower hardness compared to the base material, along with larger martensite and carbide particles. Furthermore, when using the overlap technique during the laser quenching, there will be a tempering zone both inside and on the surface of the bearing; meanwhile, the heat zones generated by different passes of the laser may have partly interacted, and the hardened zone generated by the previous pass may undergo tempering again. Full article
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<p>The inner ring of the GCr15 knuckle bearing used in this study.</p>
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<p>Principle of laser hardening.</p>
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<p>Sample under optical microscope.</p>
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<p>The methodological framework of this study. Analysis of experimental results.</p>
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<p>Measurement method of the sample’s hardness.</p>
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<p>Variation of sample hardness with laser power. (<b>a</b>) Relationship between hardness and laser power. (<b>b</b>) Relationship between hardening layer’s depth and laser power.</p>
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<p>Hardness distribution inside the sample. (<b>a</b>) The hardness test results along the depth direction (900 w, 0°). (<b>b</b>) The hardness test results along the edge direction (900 w, 0°). (<b>c</b>) The hardness test results along the depth direction (900 w, 10°). (<b>d</b>) The hardness test results along the edge direction (900 w, 10°).</p>
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<p>Results of the laser quenching simulation.</p>
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<p>Results of the laser quenching simulation.</p>
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<p>Hardness distribution on the surface of the sample. (<b>a</b>) The temperature distribution curves of the sample’s surface at 4.48 s. (<b>b</b>) The temperature distribution curves of the sample’s surface at 13.2 s.</p>
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<p>Prediction of the width of the strengthening and tempering area. (<b>a</b>) Prediction of the distribution of enhanced area and tempering area on the sample’s surface. (<b>b</b>) The width of the enhanced area and tempering area in actual and predicted results.</p>
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<p>The temperature distribution in the strengthening zone along the depth direction. (<b>a</b>) The Selection method of nodes A~A0.7. (<b>b</b>) The peak temperature distribution curve in the material’s strengthening zone along the depth direction.</p>
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<p>The material’s surface temperature and the cooling speed.</p>
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<p>Microstructure of each region of the sample. (<b>a</b>) The SEM scanning images of the hardened zone. (<b>b</b>) The SEM scanning images of the tempering zone. (<b>c</b>) The SEM scanning images of the matrix zone. (The areas marked with green frames indicate martensite, while those marked with red frames indicate carbides).</p>
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18 pages, 5428 KiB  
Article
Phylogenetic and Expression Analysis of SBP-Box Gene Family to Enhance Environmental Resilience and Productivity in Camellia sinensis cv. Tie-guanyin
by Yusen Gao, Yingxin Wen, Qinmin Lin, Yizhuo Feng, Xinying Shi, Siyao Xiao, Elisabeth Tumukunde, Kehui Zheng and Shijiang Cao
Plants 2025, 14(3), 422; https://doi.org/10.3390/plants14030422 - 1 Feb 2025
Viewed by 321
Abstract
Tieguanyin tea, a renowned oolong tea, is one of the ten most famous teas in China. The Squamosa Promoter Binding Protein (SBP)-box transcription factor family, widely present in plants, plays a crucial role in plant development, growth, and stress responses. In this study, [...] Read more.
Tieguanyin tea, a renowned oolong tea, is one of the ten most famous teas in China. The Squamosa Promoter Binding Protein (SBP)-box transcription factor family, widely present in plants, plays a crucial role in plant development, growth, and stress responses. In this study, we identify and analyze 22 CsSBP genes at the genome-wide level. These genes were distributed unevenly across 11 chromosomes. Using Arabidopsis thaliana and Solanum lycopersicum L. as model organisms, we constructed a phylogenetic tree to classify these genes into six distinct subfamilies. Collinearity analysis revealed 20 homologous gene pairs between AtSBP and CsSBP, 21 pairs between SiSBP and CsSBP, and 14 pairs between OsSBP and CsSBP. Cis-acting element analysis indicated that light-responsive elements were the most abundant among the CsSBP genes. Protein motif, domain, and gene architecture analyses demonstrated that members of the same subgroup shared similar exon–intron structures and motif arrangements. Furthermore, we evaluated the expression profiles of nine CsSBP genes under light, shade, and cold stress using qRT-PCR analysis. Notably, CsSBP1, CsSBP17, and CsSBP19 were significantly upregulated under all three stresses. This study provides fundamental insights into the CsSBP gene family and offers a novel perspective on the mechanisms of SBP transcription factor-mediated stress responses, as well as Tieguanyin tea’s adaptation to environmental variations. Full article
(This article belongs to the Special Issue Advances in Forest Tree Genetics and Breeding)
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<p>Distribution of <span class="html-italic">CsSBP</span> genes in <span class="html-italic">Camellia sinensis</span> cv. <span class="html-italic">Tie-guanyin</span> chromosomes. In the figure, the blue regions within the chromosomes indicate areas with low gene density, meaning that the number of genes in these regions (each stripe representing approximately 10,000 bp) is relatively low. The yellow regions indicate areas with high gene density, where the number of genes is higher. The white regions indicate the absence of genes. The chromosome sequence number is shown on the left of each chromosome, with a ratio provided on the far left to assess chromosome length and gene position.</p>
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<p>Protein motifs, domain composition and structures of CsSBP gene family in Tieguanyin. (<b>A</b>) A phylogenetic tree was constructed in MEGA using the maximum likelihood algorithm with a bootstrap value of 1000. (<b>B</b>) The colorful boxes represent distinct motifs within the protein sequences of CsSBP genes. (<b>C</b>) Analysis of functional conserved domains was performed in the Pfam database. (<b>D</b>) The gene organization of the <span class="html-italic">CsSBP</span> family is illustrated, where the coding sequence (CDS) is represented by yellow rectangles and the untranslated region (UTR) by green rectangles. Introns are denoted by black lines.</p>
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<p>The phylogenetic analysis of SBP proteins originating from Tieguanyin (CsSBP), <span class="html-italic">Arabidopsis thaliana</span> (AtSBP), and <span class="html-italic">Solanum lycopersicum</span> L. (SISBP) was executed through the utilization of the neighbor-joining approach. In addition, the maximal likelihood method was engaged and the bootstrap value was established as 1000. The six subgroups of SBP proteins (groups I–VI) are distinguished by unique colors in the outermost circle.</p>
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<p>In the analysis of synteny for the <span class="html-italic">CsSBP</span> family in Tieguanyin, gray lines denote all regions of synteny within the Tieguanyin genome, whereas brown lines signify pairs of duplicated <span class="html-italic">CsSBP</span> genes. The number corresponding to each chromosome is displayed in a rectangular box.</p>
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<p>Predicted cis-acting regulatory elements within the promoter sequences of the <span class="html-italic">CsSBP</span> genes are shown. On the left, the phylogenetic tree with branches marked by bootstrap values is illustrated. The promoter location at −2000 bp is exhibited on the right. The cis-acting regulatory elements within this promoter region are classified into 24 unique types, each denoted by a distinct color. The bottom axis indicates the abundance of each type of cis-acting element.</p>
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<p><span class="html-italic">Arabidopsis thaliana, Solanum lycopersicum</span> L., <span class="html-italic">Oryza sativa,</span> and Tieguanyin <span class="html-italic">SBP</span> gene synteny analysis. The red lines emphasize the syntenic <span class="html-italic">SBP</span> gene pairs, whereas the gray lines in the background depict the collinear blocks within the genomes of Tieguanyin in comparison to other plants.</p>
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<p>The expression patterns of the candidate CsSBP genes were examined under various stress conditions, with error bars indicating the standard deviation (SD). One-way ANOVA was used for statistical analysis to ascertain significant differences, with the number of asterisks indicating the level of significance as follows: * for <span class="html-italic">p</span> ≤ 0.05, ** for <span class="html-italic">p</span> ≤ 0.005, *** for <span class="html-italic">p</span> ≤ 0.0005, and **** for <span class="html-italic">p</span> ≤ 0.0001.</p>
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<p>Predicted mechanisms of SBPs that enable plants to withstand intense environmental stresses.</p>
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21 pages, 1745 KiB  
Article
Modeling the Nexus Between Technological Innovations and Institutional Quality for Entrepreneurial Development in Southeastern Europe
by Lobna Alsadeg Altaher Suliman and Muri Wole Adedokun
Sustainability 2025, 17(3), 1173; https://doi.org/10.3390/su17031173 - 31 Jan 2025
Viewed by 483
Abstract
Entrepreneurship has been critical in fostering economic growth. The technological innovations and quality of institutions are crucial in promoting entrepreneurship and promoting an environment conducive to entrepreneurial activities. This study investigated the effect of technological innovations and institutional quality on entrepreneurial development with [...] Read more.
Entrepreneurship has been critical in fostering economic growth. The technological innovations and quality of institutions are crucial in promoting entrepreneurship and promoting an environment conducive to entrepreneurial activities. This study investigated the effect of technological innovations and institutional quality on entrepreneurial development with annual data from 2014 to 2021 across Southeastern European countries. The cross-sectional auto-regressive regressive distributed lag model (C-S ARDL), quantile regression and Granger causality were employed to achieve the objectives of this study. A dynamic panel generalized method of moments (GMM) estimator was also applied to perform a robust analysis. The findings revealed a significant long-term relationship between technological innovations and entrepreneurial development, with a coefficient of 0.088. There also exists a significant and positive impact on institutional quality and entrepreneurial development in the long run, with a coefficient of 5.912. Furthermore, the outcome revealed that the exchange rate negatively influences entrepreneurial development in Southeast Europe. The Granger causality reports a bi-directional relationship between technological innovations and entrepreneurial development in Southeastern Europe. The study concluded that a significant relationship exists between technological innovations, institutional quality, and entrepreneurial development in Southeastern Europe. The study recommends that governments of Southeastern European countries strengthen their regulatory structures and institutions to improve the welfare of society through a reduction in political, social, and economic unpredictability while boosting trust and investment from entrepreneurs. Full article
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<p>Conceptual framework.</p>
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<p>Conceptual Model for Entrepreneurial Development.</p>
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14 pages, 249 KiB  
Article
Coccidia Vaccine Challenge and Exogenous Enzyme Supplementation in Broiler Chicken 2—Effect on Apparent Ileal Nutrient and Energy Digestibility and Intestinal Morphology 7 and 14 Days Post-Challenge
by Sunday A. Adedokun, Andrew Dunaway and Richard Adefioye
Animals 2025, 15(3), 401; https://doi.org/10.3390/ani15030401 - 31 Jan 2025
Viewed by 428
Abstract
The effect of exogenous mixed-enzyme supplementation (xylanase, β-glucanase, and pectinase) and coccidia vaccine challenge (CVC, Coccivac B-52™) on broilers fed a corn–SBM (CS) and a wheat–CS (WCS)-based diet was examined in this study. On day 14, 448 Cobb by-product breeder male broiler chickens [...] Read more.
The effect of exogenous mixed-enzyme supplementation (xylanase, β-glucanase, and pectinase) and coccidia vaccine challenge (CVC, Coccivac B-52™) on broilers fed a corn–SBM (CS) and a wheat–CS (WCS)-based diet was examined in this study. On day 14, 448 Cobb by-product breeder male broiler chickens were assigned to treatments (factorial arrangement) in a completely randomized design, with each treatment replicated seven times. Treatment effect was evaluated within each diet type as a 2 (enzyme levels) x 2 (CVC, 0 or 20X) factorial arrangement of treatments 7 and 14 days post-CVC. The 7-day (days 14–21) post-CVC, BWG, and feed efficiency (birds on the CS-based diet) were lower (p < 0.05), while birds on enzyme-supplemented diets had higher (p < 0.05) BWG compared to birds on diets without enzyme supplementation. Between days 21 and 28, an interaction between CVC and exogenous enzyme resulted in higher (p < 0.05) BWG compared with the challenged birds fed diets without enzyme supplementation. For birds fed WCS-based diets, CVC influenced (p < 0.05) BWG and feed efficiency (decreased days 14–21 and increased days 21–28), while CVC birds had higher BWG and feed efficiency 14 days post-CVC. Apparent ileal digestibility of dry matter, energy, and DE were lower (p < 0.05) in CVC broilers fed either the CS- or WCS-based diets (7 and 14 days post-CVC). Interaction between CVC and exogenous enzyme supplementation indicated that CVC, irrespective of exogenous enzyme supplementation with the WCS-based diet, decreased (p < 0.05) Ca utilization (7 days post-CVC) but increased (p < 0.05) Ca utilization compared to CVC birds without enzyme supplementation 14 days post-challenge. Seven days post-CVC, irrespective of the diet type, CVC resulted in lower (p < 0.05) duodenal VH and VH:CD and higher (p < 0.05) CD. Enzyme supplementation influenced (p < 0.05) duodenal CD (increased) and VH:CD (decreased) in birds fed the WCS-based diet. Results from this study showed that complete recovery from CVC was influenced by diet type, with CVC birds fed WCS-based diet having higher BWG and feed efficiency compared to the unchallenged birds. Full article
(This article belongs to the Section Animal Nutrition)
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