Search Results (54,098)

: Objectives: To determine whether a closed dressing protocol reduces the surgical site infections (SSI) rate compared to conventional closing techniques. Methods: Patients who underwent lumbar spine surgery at two neurosurgical centers were retrospectively included from June 2015 to December 2019. Data on patients, general risk factors, and surgical risk factors for SSI were collected. Patients were subdivided into two groups: a Closed Protocol where the Dermabond^® ± Prineo^® dressing system was used, and a Conventional Protocol, namely sutures or staples. Statistical analysis was undertaken to compare the infection rates among the different closure techniques. Results: Altogether, 672 patients were included. In the whole cohort, 157 (23.36%) underwent skin closure with staples, 122 (18.15%) with sutures, 98 (14.58%) with intracutaneous sutures, 78 (11.61%) with Dermabond^®, and 217 (32.29%) with Demabond^® + Prineo^®. The overall infection rate was 2.23% (n = 15). Skin suture had the highest infection rate (4.10%), while the lowest was Dermabond^® (1.28%) and Dermabond^® + Prineo^® (1.4%), though the difference was not significant. Risk factors for SSI included higher BMI (29.46 kg/m² vs. 26.96 kg/m², p = 0.044), other sites infection (20.00% vs. 2.38%, p = 0.004), and a higher national nosocomial infections surveillance score (p = 0.003). Conclusions: This study showed that a closed protocol with the use of adhesive dressing with or without mesh had a slight tendency to lower infection rates compared to conventional protocol with sutures or staples, although no statistically significant difference was found between the closure techniques. Larger randomized studies are needed to investigate this potential benefit avoiding selection bias. Full article

Background/Objectives: The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), led to significant global health challenges, including the urgent need for accurate symptom severity prediction aimed at optimizing treatment. While machine learning (ML) and deep learning (DL) models have shown promise in predicting COVID-19 severity using imaging and clinical data, there is limited research utilizing comprehensive tabular symptom datasets. This study aims to address this gap by leveraging a detailed symptom dataset to develop robust models for categorizing COVID-19 symptom severity, thereby enhancing clinical decision making. Methods: A unique tabular dataset was created using questionnaire responses from 5654 individuals, including demographic information, comorbidities, travel history, and medical data. Both unsupervised and supervised ML techniques were employed, including k-means clustering to categorize symptom severity into mild, moderate, and severe clusters. In addition, classification models, namely, Support Vector Machine (SVM), Adaptive Boosting (AdaBoost), eXtreme Gradient Boosting (XGBoost), random forest, and a deep neural network (DNN) were used to predict symptom severity levels. Feature importance was analyzed using the random forest model for its robustness with high-dimensional data and ability to capture complex non-linear relationships, and statistical significance was evaluated through ANOVA and Chi-square tests. Results: Our study showed that fatigue, joint pain, and headache were the most important features in predicting severity. SVM, AdaBoost, and random forest achieved an accuracy of 94%, while XGBoost achieved an accuracy of 96%. DNN showed robust performance in handling complex patterns with 98% accuracy. In terms of precision and recall metrics, both the XGBoost and DNN models demonstrated robust performance, particularly for the moderate class. XGBoost recorded 98% precision and 97% recall, while DNN achieved 99% precision and recall. The clustering approach improved classification accuracy by reducing noise and dimensionality. Statistical tests confirmed the significance of additional features like Body Mass Index (BMI), age, and dominant variant type. Conclusions: Integrating symptom data with advanced ML models offers a promising approach for accurate COVID-19 severity classification. This method provides a reliable tool for healthcare professionals to optimize patient care and resource management, particularly in managing COVID-19 and potential future pandemics. Future work should focus on incorporating imaging and clinical data to further enhance model accuracy and clinical applicability. Full article

Background: Treatments that combine both elastic and rigid taping in knee osteoarthritis have not yet been investigated in the literature. Thus, the purpose of the present study is to investigate how the combination taping technique affects functional status, disability, and quadricep isokinetic torque in cases of knee osteoarthritis. Patient Methods: A total of fifty-four patients were assigned to the experimental group or control group. Conventional physical therapy was provided to both groups, in addition, participants in the experimental group also received combination taping. Disability, functional status, and isokinetic quadriceps torque were assessed at baseline, six weeks (post-intervention), and twelve weeks (follow-up). Results: MANOVA showed that post-intervention measurements were significantly better than baseline measurements of both groups, except for isokinetic quadriceps torque, which showed a nonsignificant difference in the control group. The control group’s follow-up measurements revealed nonsignificant differences from those taken after the intervention, whereas the experimental group’s differences were significant excluding isokinetic quadriceps torque. Measurements taken at post-intervention and follow-up revealed that the experimental group had significantly improved compared to the control groups. Conclusion: Combination taping was found to be more beneficial when used in addition to conventional physical therapy than when used alone in knee OA. Full article

This study applies the Multilayer Perceptron (MLP) and Random Forest (RF) models, utilizing remote sensing and ground-based net primary productivity (NPP) data from 1992 to 2020, along with meteorological data and soil properties, to model the NPP in the alpine grassland and alpine meadow ecosystems of the Qinghai-Tibetan Plateau (TP) and assess their sensitivity to climate change. As a vital ecological barrier, the TP’s grassland ecosystems are critical for understanding the impacts of climate change. However, sensitivity analysis of the NPP in the TP grasslands has been limited, which this study aims to address by focusing on the effects of maximum temperature, solar radiation, and wind speed on the NPP. The results show that the MLP model outperforms the RF model in prediction accuracy (R² = 0.98, RMSE = 16.24 g C·m⁻²·a⁻¹, MAE = 9.04 g C·m⁻²·a⁻¹). NPP responses to climate factors are diverse: linear with temperature and nonlinear with solar radiation and wind speed. Under multi-factor scenarios, the NPP in both alpine meadow and alpine grassland exhibit nonlinear trends, with a higher sensitivity to changes in all three factors than to single- or two-factor changes. Spatial distribution analysis revealed that the NPP in alpine meadows was more sensitive to climate change in the southern regions, while alpine grassland showed greater sensitivity in the central regions. This study, using machine learning models and sensitivity analysis, sheds light on the complex response of the NPP in the TP grasslands to climate change, offering valuable insights for carbon cycle research in cold ecosystems and regional climate adaptation management. Full article

Lake ecosystems are increasingly threatened by harmful algal blooms (HABs), which are driven by global warming and rising nutrient inputs. Hydrological and morphometrical characteristics can affect a lake’s sensitivity to the risk of HABs, with factors such as low mean depth and long water residence time favoring their occurrence. However, the impact of these characteristics on bloom occurrence at large scales has not been thoroughly investigated. Here, we examined the influence of climate, land use, and lake hydro-morphometry on the occurrence of algal blooms in global and regional lakes using a remote-sensing-retrieved global bloom database. Our results indicate significant differences in climate and hydro-morphometric variables between bloom-affected and non-bloom lakes. Logistic regression analyses reveal that climate variables such as precipitation, summer air temperature, summer light, and summer wind speed exhibit significant but regional-specific influence on algal bloom occurrence. While the lake surface area and mean discharge show consistent positive influence across most regions, the influence of elevation, mean depth, shoreline development, and water residence time vary regionally. Random forest analyses further highlight the strong relative importance of hydro-morphometric variables in influencing bloom occurrence. These findings highlight the importance of considering regional climate and lake hydro-morphometrical variables when assessing a lake’s sensitivity to eutrophication and HAB risk. Full article

Straw is widely incorporated into conservation agriculture around the world. However, its effects on greenhouse gas emissions (GHGs) and nitrogen dynamics under soils formed by the long-term application of different amounts of nitrogen (N) fertilizer are still unclear. An incubation experiment was conducted on soils collected from a field study after 6 years of contrasting N fertilization of 0 (low N), 187 (medium N), and 337 kg N ha⁻¹ (high N), with and without maize straw. Straw amendment significantly stimulated both nitrous oxide (N₂O) and carbon dioxide (CO₂) fluxes (p < 0.05), and increased cumulative emissions by 0.8 and 19.0 times on average compared to those without straw incorporation. Medium-N soil observably weakened N₂O emissions (23.8 μg kg⁻¹) compared to high-N soil (162.7 μg kg⁻¹), and increased CO₂ emissions (1.9 g kg⁻¹) compared to low-N soils (2.3 g kg⁻¹) with straw amendment. Soil NH₄⁺-N and NO₃⁻-N invariably increased with rising soil N level, whereas straw promoted the turnover of mineral N by enhancing soil N fixation capacity. From the first day until the end of incubation, NH₄⁺-N decreased by 79.0% and 24.7%, while NO₃⁻-N showed a decrease of 58.8% or an increase of 75.2%, depending on whether straw was amended or not, respectively. Moreover, partial least squares path modeling and random forest mean predictor importance were used to find that straw affected GHGs by altering the N turnover capacity. Straw amendment increased GHGs and diminished the risk of losing mineral N by enhancing its turnover. Combining straw with medium-N soil could mitigate the greenhouse effect and improve the N and carbon (C) balance in farming systems compared to low- and high-N soils. This is recommended as a farmland management strategy in Northeast China. Full article

This study examines the evolution of eco-environmental quality and its driving forces in the Qinghai-Tibet Plateau, with a particular focus on the Qinghai Lake region (QLR). By employing principal component analysis (PCA) on nearly 20 years of remote sensing data, we reveal the dynamic characteristics of ecological quality in this sensitive area. The results indicate that the ecological quality of the QLR has exhibited significant fluctuations over the past two decades, influenced by multiple factors such as climate change, human activities, and policy adjustments. Specifically, the fluctuations in ecological quality are closely associated with key ecological indicators, including the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Wetness Index (WET), and Normalized Differential Bare Soil Index (NDBSI). Vegetation cover and moderate humidity have substantial positive effects on ecological quality, while high temperatures and dry soil conditions exert negative impacts. Full article

Physical activity reduces chronic disease risk and enhances immune function, but its causal relationship with thymic tumors—rare neoplasms of the anterior mediastinum—remains unclear. This study investigated whether physical activity reduces thymic tumor risk and whether circulating cytokines mediate this effect. We performed a two-sample Mendelian randomization (MR) analysis using genetic variants as instrumental variables for physical activity and cytokines. Data were obtained from large genome-wide association studies of Europeans, and included the following: physical activity (91,084 individuals), thymic tumors (473,681 individuals with 58 benign and 93 malignant cases), and cytokines (14,824 individuals). The inverse-variance weighted method served as the primary analysis. Genetically predicted physical activity was associated with reduced risks of benign (odds ratio [OR] = 0.381; 95% confidence interval [CI]: 0.158 to 0.921; p = 0.032) and malignant thymic tumors (OR = 0.312; 95% CI: 0.155 to 0.628; p = 0.001). Mediation analysis identified interleukin-10 receptor subunit β (IL10RB) as a partial mediator, accounting for 5.95% of the protective effect on benign tumors. Sensitivity analyses indicated no pleiotropy or heterogeneity. In conclusion, physical activity causally reduces the risk of thymic tumors, partially mediated by IL10RB, highlighting its potential role in cancer prevention through immunomodulation. Full article

Background: Temporomandibular joint disc displacement with reduction is one of the most common types of TMJ arthropathy. This single-blinded, randomized clinical study aimed to evaluate the effectiveness of three different therapeutic methods. Methods: Standard splints (Group 1), modified occlusal splint (Group 2), and conventional physical therapy with exercises (Group 3). A total of 48 patients were randomly assigned by a computer-generated allocation sequence to receive rehabilitation. The outcome was defined as improvements in pain and intermittent locking episodes. The follow-up visits were scheduled as one month and a long-term evaluation at one (T1), two (T2), three (T3), and four years (T4). Magnetic resonance images were also taken to evaluate each patient before treatment and at one year. Image analysis involved the evaluation of morphology and the function of intra-articular structures. Variables such as age, gender, and pre- vs. post-treatment values of VAS and TMJ locks between the three intervention categories were compared for statistical evaluations. p values ≤ 0.05 were taken as being significant. Results: A total of 16 subjects were allocated to each group. At T1, a decrease in pain and TMJ locking episodes was observed, which was maintained throughout the course of the study for four years of follow-ups, with no statistically significant differences. However, there was a tendency for better outcomes in favor of Group 2, with less clicking of the TMJ at opening. Conclusions: The modified mandibular splint seems to be successful as an effective alternative for the management of temporomandibular joint disc displacement with reductions in intermittent locking. Full article

Heart failure (HF) remains a major cause of morbidity and mortality worldwide. While standard treatments primarily target neurohormonal pathways, emerging evidence highlights the significant role of hormonal deficiencies, such as impaired growth hormone (GH) signaling, in HF progression and outcomes. GH is crucial for cardiovascular and skeletal muscle function, and its deficiency has been associated with worse prognosis. This review synthesizes recent findings from randomized controlled trials (RCTs) to explore how GH can contribute to personalized care and improve patient stratification in HF. A comprehensive literature review was conducted using PubMed up to 10 October 2024. Search terms included “growth hormone” combined with “heart failure”, “HFrEF”, “HFpEF”, and “HFmrEF.” Only placebo-controlled RCTs published in English and involving human subjects were considered. Data on study design, participant characteristics, GH dosing, and key clinical outcomes were systematically extracted and analyzed. Several trials demonstrated that GH therapy can transiently improve left ventricular ejection fraction (LVEF), exercise capacity, and reduce inflammatory markers. For example, one study has reported an increase in LVEF from 32 ± 3.8% to 43.8 ± 4.6% (p = 0.002), following three months of GH therapy in post-MI HF patients. However, benefits diminished after discontinuation. Additional studies have observed sustained improvements in peak oxygen consumption and LVEF over four years, with an additional trend towards hard endpoint improvement. Conversely, some studies showed no significant impact on cardiac function, highlighting heterogeneity in outcomes. As a result, GH therapy holds promise for improving cardiac and functional parameters in HF patients, but evidence remains mixed. Larger, long-term RCTs are needed to confirm its efficacy and safety. Precision medicine approaches and biomarker-driven strategies may optimize patient outcomes and guide clinical practice. Full article

Background/Objectives: Mulberries exhibit antioxidant properties that may attenuate metabolic abnormalities. Kamphaeng Saen mulberry (KPS-MB-42-1) contains anthocyanins, polyphenols, and nutrients, but few studies have explored its benefits for human health. This study investigated the effects of a concentrated mulberry drink (CMD) from the KPS-MB-42-1 cultivar on metabolic and cardiovascular risk factors in obese individuals. Methods: A single-blind, randomized crossover clinical pilot trial was performed on individuals with obesity. Participants consumed 100 g of CMD daily, alternating with placebo for 6 weeks. Body composition, blood pressure, and blood samples were assessed at baseline and post-intervention. Results: This study was completed with 12 participants (7 men, 5 women, aged 30–55 years, BMI 32.1 ± 5.98 kg/m²) consuming CMD with 1041.90 mg total phenolic compounds and 35.34 mg total anthocyanins. No significant changes in body composition were observed. CMD consumption significantly reduced systolic and diastolic blood pressure, and mean arterial pressure, compared to baseline and placebo periods (p < 0.05). While total cholesterol, LDL-C, and HDL-C remained unchanged, triglycerides were significantly lower during CMD consumption compared to placebo periods (p < 0.05). Fasting plasma glucose (FPG) levels were stable during CMD consumption but increased significantly with the placebo period (p < 0.05). C-reactive protein levels were also significantly lower during CMD consumption compared to placebo periods (p < 0.05). No changes in blood coagulation indicators (prothrombin time, activated partial thromboplastin time, and the international normalized ratio) were found. Conclusions: CMD improved metabolic markers, particularly regarding its antihypertensive effects. These findings highlight CMD’s potential as a health drink for managing metabolic syndrome and preventing chronic diseases. Full article

A data-efficient training method, namely Q-AL-GPR, is proposed for visible light positioning (VLP) systems with Gaussian process regression (GPR). The proposed method employs the methodology of active learning (AL) to progressively update the effective training dataset with data of low similarity to the existing one. A detailed explanation of the principle of the proposed methods is given. The experimental study is carried out in a three-dimensional GPR-VLP system. The results show the superiority of the proposed method over both the conventional training method based on random draw and a previously proposed line-based AL training method. The impacts of the parameter of active learning on the performance of the GPR-VLP are also presented via experimental investigation, which shows that (1) the proposed training method outperforms the conventional one regardless of the number of final effective training data ($\mathbb{E}$), especially for a small/moderate effective training dataset, (2) a moderate step size (k) should be chosen for updating the effective training dataset to balance the positioning accuracy and computational complexity, and (3) due to the interplay of the reliability of the initialized GPR model and the flexibility in reshaping such a model via active learning, the number of initial effective training data (m) should be optimized. In terms of data efficiency in training, the required number of training data can be reduced by ~27.8% by Q-AL-GPR for a mean positioning accuracy of 3 cm when compared with GPR. The CDF analysis shows that with the proposed training method, the 97th percentile positioning error of GPR-VLP with 300 training data is reduced from 11.8 cm to 7.5 cm, which corresponds to a ~36.4% improvement in positioning accuracy. Full article

Bread is one of the most popular products consumed almost daily and, simultaneously, the most frequently wasted product in large quantities. The factors determining this phenomenon in a household must first be known in order to develop and implement effective programmes to combat consumers throwing away bread. Minimizing bread waste contributes to achieving the UN’s Sustainable Development Goal 12 of “halting food waste by 2030”. The aim of the study was to examine the influence of selected sociodemographic, economic and behavioural characteristics of consumers on the methods of managing stale bread. The study was conducted on a nationwide, random, and representative group of 1115 adult respondents. Over 15% of respondents admitted throwing stale bread into the waste container. Statistical analysis showed that the highest percentage of younger people, residents of large cities, and working people declared throwing unused bread into the waste container. More than 1/3 of respondents declared that they process stale bread into breadcrumbs. A higher percentage of the oldest people, residents of rural areas, and families with more than four adults declared that they manage bread this way. There was no significant relationship between the frequency of bread purchase and all methods of managing stale bread (except for feeding animals). The place of purchase influenced four methods of handling stale bread. Full article

Non-specific low back pain (NSLBP) is a common musculoskeletal issue that can limit function and reduce the patient’s quality of life. Enhancing spinal stabilizer muscle activity through targeted exercises may help improve spinal alignment and alleviate NSLBP symptoms. This study aimed to investigate whether incorporating the abdominal drawing-in maneuver (ADIM) into selected low back exercises influences the electromyographic (EMG) activity of key spinal extensor muscles. Forty participants with NSLBP (n = 29 female and n = 11 male; mean age = 21.42 ± 1.07 years; BMI = 20.65 ± 2.08 kg/m²; 80% right-side dominant) performed three exercises, prone trunk extension, superman, and unstable superman, with and without the ADIM. The EMG amplitudes of the iliocostalis lumborum pars lumborum (ICL), iliocostalis lumborum pars thoracis (ICT), and longissimus thoracis (LT) were measured. A cross-sectional observational study design was employed. Significant main effects were observed for both exercise types and the ADIM on the EMG amplitudes of the ICL, ICT, and LT (ICL: F1,14 = 82.69–114.23, p < 0.001, η² ≥ 0.88; ICT: F1,14 = 100.69–117.13, p < 0.001, η² ≥ 0.90; LT: F1,14 = 62.69–74.88, p < 0.001, η² ≥ 0.81). Under ADIM conditions, the ICL activity decreased significantly (right ICL mean difference: 14.06–20.02; left ICL: 13.06–21.32; p < 0.001), while the ICT and LT activity increased (ICT mean difference: 6.45–8.89; LT: 9.37–12.13; p < 0.001). These changes were most pronounced during the unstable superman exercise (p < 0.01). Integrating the ADIM into specific low back exercises can differentially modulate spinal extensor muscle activity. In particular, the unstable superman exercise demonstrated the greatest changes in the EMG amplitudes. These findings support the inclusion of the ADIM in exercise programs aimed at improving spinal stability and may have implications for NSLBP management. Future research should examine the effects of the ADIM in populations with varying experience levels to enhance its generalizability and refine the clinical recommendations. Full article

Objectives: This study aimed to evaluate the immunogenicity and safety of a 13-valent pneumococcal polysaccharide conjugate vaccine (CRM197/TT) (PCV13i) in infants. Methods: A total of 1200 infants were randomly assigned to either the experimental PCV13i group or the control PCV13 group in a 1:1 ratio. Each group received a three-dose series of the vaccine at 2, 4, and 6 months of age, followed by a booster dose at 12–15 months. Blood samples were collected before and 30 days after both primary and booster vaccinations. The primary immunogenicity endpoints were the seropositive rate and the geometric mean concentration (GMC) of IgG antibodies against the 13 pneumococcal serotypes. The primary safety endpoint was the incidence of adverse reactions within 0–7 days and 0–30 days after vaccination. Results: Results showed that the experimental PCV13i was well tolerated, with a safety profile comparable to that of the control vaccine. Following primary vaccination, the GMCs of IgG responses against serotypes 1, 5, 6A, 6B, 14, and 18C in the experimental group were lower than those in the control group, while responses against serotypes 3, 4, 7F, 9V, 19A, 19F, and 23F were higher. The experimental group exhibited higher opsonophagocytic killing assay (OPA) geometric mean titers (GMTs) for serotypes 3, 7F, 19A, and 19F compared to the control group, while GMTs for serotypes 1, 5, 6A, and 18C were lower. Following booster vaccination, OPA GMTs of the experimental group remained higher than those of the control group for serotypes 3, 7F, and 19F, while GMTs for serotype 5 were lower. Both vaccines induced robust immune responses, with high seropositive rates and significant increases in antibody levels following vaccination. Conclusions: The experimental PCV13i demonstrated non-inferiority to the control PCV13 in terms of immunogenicity. Full article