MRI T2w Radiomics-Based Machine Learning Models in Imaging Simulated Biopsy Add Diagnostic Value to PI-RADS in Predicting Prostate Cancer: A Retrospective Diagnostic Study.

BACKGROUND: Currently, prostate cancer (PCa) prebiopsy medical image diagnosis mainly relies on mpMRI and PI-RADS scores. However, PI-RADS has its limitations, such as inter- and intra-radiologist variability and the potential for imperceptible features. The primary objective of this study is to evaluate the effectiveness of a machine learning model based on radiomics analysis of MRI T2-weighted (T2w) images for predicting PCa in prebiopsy cases. METHOD: A retrospective analysis was conducted using 820 lesions (363 cases, 457 controls) from The Cancer Imaging Archive (TCIA) Database for model development and validation. An additional 83 lesions (30 cases, 53 controls) from Hong Kong Queen Mary Hospital were used for independent external validation. The MRI T2w images were preprocessed, and radiomic features were extracted. Feature selection was performed using Cross Validation Least Angle Regression (CV-LARS). Using three different machine learning algorithms, a total of 18 prediction models and 3 shape control models were developed. The performance of the models, including the area under the curve (AUC) and diagnostic values such as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were compared to the PI-RADS scoring system for both internal and external validation. RESULTS: All the models showed significant differences compared to the shape control model (all p < 0.001, except SVM model PI-RADS+2 Features p = 0.004, SVM model PI-RADS+3 Features p = 0.002). In internal validation, the best model, based on the LR algorithm, incorporated 3 radiomic features (AUC = 0.838, sensitivity = 76.85%, specificity = 77.36%). In external validation, the LR (3 features) model outperformed PI-RADS in predictive value with AUC 0.870 vs. 0.658, sensitivity 56.67% vs. 46.67%, specificity 92.45% vs. 84.91%, PPV 80.95% vs. 63.64%, and NPV 79.03% vs. 73.77%. CONCLUSIONS: The machine learning model based on radiomics analysis of MRI T2w images, along with simulated biopsy, provides additional diagnostic value to the PI-RADS scoring system in predicting PCa.

An early scoring system to predict mechanical ventilation for botulism: a single-center-based study.

BACKGROUND: Early identification of patients requiring ventilator support will be beneficial for the outcomes of botulism. The present study aimed to establish a new scoring system to predict mechanical ventilation (MV) for botulism patients. METHODS: A single-center retrospective study was conducted to identify risk factors associated with MV in botulism patients from 2007 to 2022. Univariate analysis and multivariate logistic regression analysis were used to screen out risk factors for constructing a prognostic scoring system. The area under the receiver operating characteristic (ROC) curve was calculated. RESULTS: A total of 153 patients with botulism (66 males and 87 females, with an average age of 43 years) were included. Of these, 49 patients (32.0%) required MV, including 21 (13.7%) with invasive ventilation and 28 (18.3%) with non-invasive ventilation. Multivariate analysis revealed that botulinum toxin type, pneumonia, incubation period, degree of hypoxia, and severity of muscle involvement were independent risk factors for MV. These risk factors were incorporated into a multivariate logistic regression analysis to establish a prognostic scoring system. Each risk factor was scored by allocating a weight based on its regression coefficient and rounded to whole numbers for practical utilization ([botulinum toxin type A: 1], [pneumonia: 2], [incubation period ≤1 day: 2], [hypoxia <90%: 2], [severity of muscle involvement: grade II, 3; grade III, 7; grade IV, 11]). The scoring system achieved an area under the ROC curve of 0.82 (95% CI 0.75-0.89, P<0.001). At the optimal threshold of 9, the scoring system achieved a sensitivity of 83.7% and a specificity of 70.2%. CONCLUSION: Our study identified botulinum toxin type, pneumonia, incubation period, degree of hypoxia, and severity of muscle involvement as independent risk factors for MV in botulism patients. A score ≥9 in our scoring system is associated with a higher likelihood of requiring MV in botulism patients. This scoring system needs to be validated externally before it can be applied in clinical settings.

Dual isotope analysis reveals the COVID-19 lockdown impact on nitrate aerosol sources and formation pathways in Shanghai.

Nitrate (NO3-) is an important contributor to PM2.5 which can adversely affect the environment and human health. A noticeable decrease in NOx concentrations has been reported due to the lockdown measures implemented to curb the spread of Corona Virus Disease 2019 (COVID-19). However, questions remain, regarding the nonlinear relationship between NOx and NO3-. Here, we collected PM2.5 samples in two periods, before and during the lockdown of COVID-19 in Shanghai. Dual isotopes (δ18O-NO3- and δ15N-NO3-) of NO3- were measured to investigate the formation pathways and potential sources of NO3-. The results showed that the concentration of NO3- decreased significantly during the lockdown period compared to the period before the lockdown. Additionally, the hydroxyl pathway was the dominant contributor to NO3- production during the lockdown period, while N2O5 hydrolyses dominated the formation of NO3- before the lockdown. This change is largely attributable to alterations in the oxidative potential of the environment. In comparison to the period preceding the lockdown, the relative contributions of each NOx source remained largely unchanged throughout the lockdown periods. Nevertheless, the concentration of NO3- contributed by each NOx source exhibited a notable decline, particularly the mobile sources and coal combustion. Furthermore, the reduction extent of NO3- due to the lockdown period was also greater than the reduction during the Clean Air Actions (2013-2017). Our findings provide evidence that the COVID-19 lockdown led to a decrease in NO3- concentration due to changes in the formation pathway and reductions in NOx emissions from various sources.

Effect of Dietary Standardized Ileal Digestible Arginine to Lysine Ratio on Reproductive Performance, Plasma Biochemical Index, and Immunity of Gestating Sows.

The aim of this study was to determine the optimal SID Arg: Lys ratio for maximizing the reproductive performance, immunity and biochemical parameters of sows during gestation, the colostrum composition, and the performance of their offspring. A total of 174 multiparous sows were randomly allocated to five treatment groups varying in dietary SID Arg: Lys ratios (0.91, 1.02, 1.14, 1.25 and 1.38) through modification of the levels of Arg or alanine supplementation (the total level of nitrogen was the same in all treatments). The results showed that increasing the dietary SID Arg: Lys ratio increased the number of piglets born alive (p < 0.05, linear and quadratic). The number of stillborn piglets, the birth weight variation of born alive piglets, the birth interval (p < 0.05, linear and quadratic) and the number of mummies (p < 0.05, quadratic) reduced with increasing the dietary SID Arg: Lys ratio. Broken-line regression analysis indicated that the optimal SID Arg: Lys ratio requirement for gestating sows to maximize the number of piglets born alive was 1.25. The content of non-fat solid, total solid, protein, and energy in colostrum increased linearly and quadratically (p < 0.05) with increasing dietary SID Arg: Lys ratio. Additionally, when increasing the dietary SID Arg: Lys ratio, the concentration of IgA (p < 0.05, quadratic) and IgM (p < 0.05, linear and quadratic) of plasma increased at day 90 of gestation; IgG (p < 0.05, linear and quadratic) concentration increased at day 110 of gestation of sows. The dietary SID Arg: Lys ratio had an increasing effect (p < 0.05, linear and quadratic) on plasma insulin levels at day 90 of gestation. Furthermore, there were increases in plasma concentrations of nitric oxide and ornithine at day 110 of gestation, Arg at day 90 and 110 of gestation (p < 0.05, linear and quadratic) and total protein at day 110 of gestation (p < 0.05, linear) with increasing dietary SID Arg: Lys ratio. The results of our study indicated that increases in the dietary SID Arg: Lys ratio during gestation resulted in an increase in the number of piglets born alive, a decrease in birth intervals, and an improvement in immunity and colostrum composition. The optimal SID Arg: Lys ratio for gestating sows to maximize the number of piglets born alive was 1.25.

The Increased Apoptosis of Mesenchymal Stem Cells Mediated Osteopenia Due to Prenatal Nicotine Exposure in Female Offspring Rats via IGF1 Pathway.

Nicotine exposure is a common adverse environment during pregnancy and causes developmental toxicity of long bones in offspring. However, the effect of prenatal nicotine exposure (PNE) on bone mass accumulation in female offspring and its mechanism remained to be further investigated. In this study, we constructed a PNE rat model and collected the long bone and the bone marrow mesenchymal stem cells (BMSCs) from female offspring rats for the detection of bone mass, cell apoptosis, and the expressions of osteogenesis- and apoptosis-related genes. The results revealed that PNE induced low bone mass in female offspring rats and was associated with the suppression of osteogenic function. Moreover, the apoptosis of BMSCs derived from the PNE female offspring rats was raised, and the expression ratio of apoptosis marker genes BAX/BCL-2 was significantly increased. Further, PNE inhibited the expression and function of insulin-like growth factor l (IGF1) signaling pathway in BMSCs. However, the exogenous IGF1 treatment partially ameliorated the increased apoptosis of BMSCs derived from the PNE female offspring rats. In conclusion, PNE induced low bone mass in female offspring rats, which was attributed to the increased apoptosis of BMSCs due to functional inhibition of IGF1 signaling pathway.

BiVO4 Film Coupling with CoAl2O4 Nanoparticles for Photoelectrochemical Water Splitting Utilizing Broad Solar Spectrum through p-n Heterojunction, Photothermal, and Cocatalytic Synergism.

Water oxidation is an endothermic and kinetics-sluggish reaction; the research of photoanodes with photothermal and cocatalytic properties is of great significance. Herein, BiVO4/CoAl2O4 film photoanodes were studied for solar water splitting through coupling spinel p-type CoAl2O4 nanoparticles on n-type BiVO4 films. Compared to the BiVO4 photoanode, better performance was observed on the BiVO4/CoAl2O4 photoanode during water oxidation. A photocurrent of 3.47 mA/cm2 was produced on the BiVO4/CoAl2O4 photoanode at 1.23 V vs RHE, which is two-fold to the BiVO4 photoanode (1.70 mA/cm2). Additionally, the BiVO4/CoAl2O4 photoanodes showed an acceptable stability for water oxidation. The BiVO4/CoAl2O4 photoanode being of higher water oxidation performance could be attributed to the presence of p-n heterojunction, cocatalytic, and photothermal effects. In specific, under the excitation of λ < 520 nm light, the holes produced in/on BiVO4 can be transferred to CoAl2O4 owing to the p-n heterojunctions of BiVO4/CoAl2O4. Meanwhile, the temperature on the BiVO4/CoAl2O4 photoanode rises quickly up to ∼53 °C under AM 1.5 G irradiation due to the photothermal property of CoAl2O4 through capturing the 520 < λ < 720 nm light. The temperature rising on the BiVO4/CoAl2O4 photoanode improves the cocatalytic activity of CoAl2O4 and modifies the wettability of BiVO4/CoAl2O4 for effective water oxidation.

Structures of Mature and Urea-Treated Empty Bacteriophage T5: Insights into Siphophage Infection and DNA Ejection.

T5 is a siphophage that has been extensively studied by structural and biochemical methods. However, the complete in situ structures of T5 before and after DNA ejection remain unknown. In this study, we used cryo-electron microscopy (cryo-EM) to determine the structures of mature T5 (a laboratory-adapted, fiberless T5 mutant) and urea-treated empty T5 (lacking the tip complex) at near-atomic resolutions. Atomic models of the head, connector complex, tail tube, and tail tip were built for mature T5, and atomic models of the connector complex, comprising the portal protein pb7, adaptor protein p144, and tail terminator protein p142, were built for urea-treated empty T5. Our findings revealed that the aforementioned proteins did not undergo global conformational changes before and after DNA ejection, indicating that these structural features were conserved among most myophages and siphophages. The present study elucidates the underlying mechanisms of siphophage infection and DNA ejection.

Penicillin Allergy in China: Consequences of Inappropriate Skin Testing Practices and Policies.

Penicillins are the most frequently prescribed class of medications worldwide and first-line antibiotic of choice for most bacterial infections. They are also commonly labelled as the culprit of drug 'allergy'; leading to obligatory use of second-line antibiotics, suboptimal antibiotic therapy and increased antimicrobial resistance. However, the majority of reported penicillin 'allergy' labels are found to be incorrect after allergy testing, emphasising the importance of proper drug allergy testing and evaluation. Penicillin skin testing (PST) remains an important component of drug allergy diagnosis; however, its practice and policies significantly differ across the world. Inappropriate and non-evidence-based PST practices can lead to consequences associated with allergy mislabelling. Even within different regions of China, with a population exceeding 1.4 billion, there are marked differences in the implementation, execution and interpretation of PST. This review aims to examine the differences in PST between Mainland China, Hong Kong and the rest of the world. We critically analyse the current practice of 'pre-emptive' PST in Mainland China, which has a significant false-positive rate leading to high levels of penicillin allergy mislabelling. Non-evidence-based practices further compound the high false-positive rates of indiscriminatory PST. We postulate that inappropriate PST policies and practices may exacerbate the mislabelling of penicillin allergy, leading to unnecessary overuse of inappropriate second-line antibiotics, increasing antimicrobial resistance and healthcare costs. We advocate for the importance of more collaborative research to improve the contemporary workflow of penicillin allergy diagnosis, reduce mislabelling and promote the dissemination of evidence-based methods for allergy diagnosis.

Predictive model for CAR-T cell therapy success in patients with relapsed/refractory B-cell acute lymphoblastic leukaemia.

Chimeric antigen receptor T-cell (CAR-T) therapy has demonstrated remarkable efficacy in treating relapsed/refractory acute B-cell lymphoblastic leukaemia (R/R B-ALL). However, a subset of patients does not benefit from CAR-T therapy. Our study aims to identify predictive indicators and establish a model to evaluate the feasibility of CAR-T therapy. Fifty-five R/R B-ALL patients and 22 healthy donors were enrolled. Peripheral blood lymphocyte subsets were analysed using flow cytometry. Sensitivity, specificity, accuracy, positive and negative predictive values and receiver operating characteristic (ROC) areas under the curve (AUC) were determined to evaluate the predictive values of the indicators. We identified B lymphocyte, regulatory T cell (Treg) and peripheral blood minimal residual leukaemia cells (B-MRD) as indicators for predicting the success of CAR-T cell preparation with AUC 0.936, 0.857 and 0.914. Furthermore, a model based on CD3+ T count, CD4+ T/CD8+ T ratio, Treg and extramedullary diseases (EMD) was used to predict the response to CAR-T therapy with AUC of 0.938. Notably, a model based on CD4+ T/CD8+ T ratio, B, Treg and EMD were used in predicting the success of CAR-T therapy with AUC 0.966 [0.908-1.000], with specificity (92.59%) and sensitivity (91.67%). In the validated group, the predictive model predicted the success of CAR-T therapy with specificity (90.91%) and sensitivity (100%). We have identified several predictive indicators for CAR-T cell therapy success and a model has demonstrated robust predictive capacity for the success of CAR-T therapy. These results show great potential for guiding informed clinical decisions in the field of CAR-T cell therapy.

Kinetic nitrogen isotope effects of 18 amino acids degradation during burning processes.

Understanding the nitrogen isotopic variations of individual amino acids (AAs) is essential for utilizing the nitrogen isotope values of individual amino acids (δ15N-AA) as source indicators to identify proteinaceous matter originating from biomass combustion processes. However, the nitrogen isotope effects (ε) associated with the degradation of individual amino acids during combustion processes have not been previously explored. In this study, we measured the nitrogen isotope values of residual free amino acids -following a series of controlled combustion experiments at temperatures of 160-240 °C and durations of 2 min to 8 h, as described in Part 1. δ15N values of proline, aspartate, alanine, valine, glycine, leucine, and isoleucine are more positive than their initial δ15N values after prolonged combustion. Variations in δ15N values of the most AAs conform to the Rayleigh fractionation during combustion and their nitrogen isotope effects (ε) are greatly impacted by their respective combustion degradation pathways. This is the first time the ε values associated with the degradation pathways of AAs during combustion have been characterized. Only the ε values associated with Pathway 1 (dehydration to form dipeptide) and 2 (simultaneous deamination and decarboxylation) are found to be significant and temperature-dependent, ranging from + 2.9 to 6.4‰ and + 0.9‰ to + 3.8‰, respectively. Conversely, ε values associated with other pathways are minor. This improves the current understanding on the degradation mechanisms of protein nitrogen during biomass burning.

Lysosome-Targeted and pH-Activatable Phototheranostics for NIR-II Fluorescence Imaging-Guided Nasopharyngeal Carcinoma Phototherapy.

Currently, clinical therapeutic strategies for nasopharyngeal carcinoma (NPC) confront insurmountable dilemmas in which surgical resection is incomplete and chemotherapy/radiotherapy has significant side effects. Phototherapy offers a maneuverable, effective, and noninvasive pattern for NPC therapy. Herein, we developed a lysosome-targeted and pH-responsive nanophototheranostic for near-infrared II (NIR-II) fluorescence imaging-guided photodynamic therapy (PDT) and photothermal therapy (PTT) of NPC. A lysosome-targeted S-D-A-D-S-type NIR-II phototheranostic molecule (IRFEM) is encapsulated within the acid-sensitive amphiphilic DSPE-Hyd-PEG2k to form IRFEM@DHP nanoparticles (NPs). The prepared IRFEM@DHP exhibits a good accumulation in the acidic lysosomes for facilitating the release of IRFEM, which could disrupt lysosomal function by generating an amount of heat and ROS under laser irradiation. Moreover, the guidelines of NIR-II fluorescence enhance the accuracy of PTT/PDT for NPC and avoid damage to normal tissues. Remarkably, IRFEM@DHP enable efficient antitumor effects both in vitro and in vivo, opening up a new avenue for precise NPC theranostics.

The effect of illness perception on psychosocial adjustment of patients with breast cancer and their spouses: actor-partner independence model.

OBJECTIVE: With the increase in the prevalence rate and improvements in the survival of breast cancer patients, there is a growing interest in understanding the level of psychosocial adjustment in these patients. The study aimed to describe the illness perception and psychosocial adjustment levels of both breast cancer patients and their spouses, to use the Actor-Partner Interdependence Model (APIM) to clarify the actor-partner relationships between spouses, and to explore the impact of illness perception on psychosocial adjustment to the disease within the joint actions of both spouses. METHODS: A total of 216 female patients with breast cancer and their spouses participated in the study. They were selected from two tertiary hospitals in Guangdong Province, China from October 2022 to May 2023 using a convenience sampling method. The participants were assessed using the Brief Illness Perception Questionnaire and the Psychosocial Adjustment to Illness Scale to examine the relationship between illness perception and psychosocial adjustment. AMOS24.0 was used to test and analyze the actor-partner interdependence model. RESULTS: The illness perception score (57.75 ± 10.91) was slightly higher than that of the spouse (57.10 ± 11.00), and the psychosocial adjustment score (64.67 ± 6.33) was slightly lower than that of the spouse (64.76 ± 7.49). The results of the actor-partner interdependence model indicated that there was a couple partner between breast cancer patients and their spouses: the spouse's illness perception significantly affected the patient's psychosocial adjustment (ß = 0.095, p = 0.015); the patient's illness perception also significantly affected the spouse's psychosocial adjustment (ß = 0.106, p = 0.033). Among them, the patient's psychosocial adjustment was found to be related to the patient's illness comprehensibility or coherence of illness (ß = 0.433, p = 0.009), the spouse's emotional illness representation (ß = 0.218, p = 0.037), and the spouse's illness comprehensibility or coherence of illness (ß = 0.416, p = 0.007), while the spouse's psychosocial adjustment was only related to the spouse's illness comprehensibility or coherence of illness (ß = 0.528, p = 0.007). CONCLUSIONS: The psychosocial adjustment of breast cancer patients is affected by both their own and spouse's illness perception. Therefore, in the future, the healthcare staff can implement early psychological interventions for patients diagnosed with breast cancer and their spouses as a unit to promote the psychosocial adjustment of them.

Comparison of systematic and combined biopsy for the detection of prostate cancer.

ABSTRACT: Systematic prostate biopsy has limitations, such as overdiagnosis of clinically insignificant prostate cancer and underdiagnosis of clinically significant prostate cancer. Magnetic resonance imaging (MRI)-guided biopsy, a promising alternative, might improve diagnostic accuracy. To compare the cancer detection rates of systematic biopsy and combined biopsy (systematic biopsy plus MRI-targeted biopsy) in Asian men, we conducted a retrospective cohort study of men who underwent either systematic biopsy or combined biopsy at two medical centers (Queen Mary Hospital and Tung Wah Hospital, Hong Kong, China) from July 2015 to December 2022. Descriptive statistics were calculated, and univariate and multivariate logistic regression analyses were performed. The primary and secondary outcomes were prostate cancer and clinically significant prostate cancer. A total of 1391 participants were enrolled. The overall prostate cancer detection rates did not significantly differ between the two groups (36.3% vs 36.6%, odds ratio [OR] = 1.01, 95% confidence interval [CI]: 0.81-1.26, P = 0.92). However, combined biopsy showed a significant advantage in detecting clinically significant prostate cancer (Gleason score ≥ 3+4) in patients with a total serum prostate-specific antigen (tPSA) concentration of 2-10 ng ml -1 (systematic vs combined: 11.9% vs 17.5%, OR = 1.58, 95% CI: 1.08-2.31, P = 0.02). Specifically, in the transperineal biopsy subgroup, combined biopsy significantly outperformed systematic biopsy in the detection of clinically significant prostate cancer (systematic vs combined: 12.6% vs 24.0%, OR = 2.19, 95% CI: 1.21-3.97, P = 0.01). These findings suggest that in patients with a tPSA concentration of 2-10 ng ml -1 , MRI-targeted biopsy may be of greater predictive value than systematic biopsy in the detection of clinically significant prostate cancer.

Identification and validation of lipid metabolism-related key genes as novel biomarkers in acute myocardial infarction and pan-cancer analysis.

BACKGROUND: Acute myocardial infarction (AMI) is associated with high morbidity and mortality, and is associated with abnormal lipid metabolism. We identified lipid metabolism related genes as biomarkers of AMI, and explored their mechanisms of action. METHODS: Microarray datasets were downloaded from the GEO database and lipid metabolism related genes were obtained from Molecular Signatures Database. WGCNA was performed to identify key genes. We evaluated differential expression and performed ROC and ELISA analyses. We also explored the mechanism of AMI mediated by key genes using gene enrichment analysis. Finally, immune infiltration and pan-cancer analyses were performed for the identified key genes. RESULTS: TRL2, S100A9, and HCK were identified as key genes related to lipid metabolism in AMI. Internal and external validation (including ELISA) showed that these were good biomarkers of AMI. In addition, the results of gene enrichment analysis showed that the key genes were enriched in inflammatory response, immune system process, and tumor-related pathways. Finally, the results of immune infiltration showed that key genes were concentrated in neutrophils and macrophages, and pan-cancer analysis showed that the key genes were highly expressed in most tumors and were associated with poor prognosis. CONCLUSIONS: TLR2, S100A9, and HCK were identified as lipid metabolism related novel diagnostic biomarkers of AMI. In addition, AMI and tumors may be related through the inflammatory immune response.

MOF-Derived CeO2 Nanorod as a Separator Coating Enabling Enhanced Performance for Lithium-Sulfur Batteries.

The deployment of Li-S batteries in the commercial sector faces obstacles due to their low electrical conductivity, slow redox reactions, quick fading of capacity, and reduced coulombic efficiency. These issues stem from the "shuttle effect" associated with lithium polysulfides (LiPSs). In this work, a haystack-like CeO2 derived from a cerium-based metal-organic framework (Ce-MOF) is obtained for the modification of a polypropylene separator. The carbon framework and CeO2 coexist in this haystack-like structure and contribute to a synergistic effect on the restriction of LiPSs shuttling. The carbon network enhances electron transfer in the conversion of LiPSs, improving the rate performance of the battery. Moreover, CeO2 enhances the redox kinetics of LiPSs, effectively reducing the "shuttle effect" in Li-S batteries. The Li-S battery with the optimized CeO2 modified separator shows an initial discharge capacity of 870.7 mAh/g at 2 C, maintaining excellent capacity over 500 cycles. This research offers insights into designing functional separators to mitigate the "shuttle effect" in Li-S batteries.

Analysis of the fatigue status of medical security personnel during the closed-loop period using multiple machine learning methods: a case study of the Beijing 2022 Olympic Winter Games.

Using machine learning methods to analyze the fatigue status of medical security personnel and the factors influencing fatigue (such as BMI, gender, and wearing protective clothing working hours), with the goal of identifying the key factors contributing to fatigue. By validating the predicted outcomes, actionable and practical recommendations can be offered to enhance fatigue status, such as reducing wearing protective clothing working hours. A questionnaire was designed to assess the fatigue status of medical security personnel during the closed-loop period, aiming to capture information on fatigue experienced during work and disease recovery. The collected data was then preprocessed and used to determine the structural parameters for each machine learning algorithm. To evaluate the prediction performance of different models, the mean relative error (MRE) and goodness of fit (R2) between the true and predicted values were calculated. Furthermore, the importance rankings of various parameters in relation to fatigue status were determined using the RF feature importance analysis method. The fatigue status of medical security personnel during the closed-loop period was analyzed using multiple machine learning methods. The prediction performance of these methods was ranked from highest to lowest as follows: Gradient Boosting Regression (GBM) > Random Forest (RF) > Adaptive Boosting (AdaBoost) > K-Nearest Neighbors (KNN) > Support Vector Regression (SVR). Among these algorithms, four out of the five achieved good prediction results, with the GBM method performing the best. The five most critical parameters influencing fatigue status were identified as working hours in protective clothing, a customized symptom and disease score (CSDS), physical exercise, body mass index (BMI), and age, all of which had importance scores exceeding 0.06. Notably, working hours in protective clothing obtained the highest importance score of 0.54, making it the most critical factor impacting fatigue status. Fatigue is a prevalent and pressing issue among medical security personnel operating in closed-loop environments. In our investigation, we observed that the GBM method exhibited superior predictive performance in determining the fatigue status of medical security personnel during the closed-loop period, surpassing other machine learning techniques. Notably, our analysis identified several critical factors influencing the fatigue status of medical security personnel, including the duration of working hours in protective clothing, CSDS, and engagement in physical exercise. These findings shed light on the multifaceted nature of fatigue among healthcare workers and emphasize the importance of considering various contributing factors. To effectively alleviate fatigue, prudent management of working hours for security personnel, along with minimizing the duration of wearing protective clothing, proves to be promising strategies. Furthermore, promoting regular physical exercise among medical security personnel can significantly impact fatigue reduction. Additionally, the exploration of medication interventions and the adoption of innovative protective clothing options present potential avenues for mitigating fatigue. The insights derived from this study offer valuable guidance to management personnel involved in organizing large-scale events, enabling them to make informed decisions and implement targeted interventions to address fatigue among medical security personnel. In our upcoming research, we will further expand the fatigue dataset while considering higher precisionprediction algorithms, such as XGBoost model, ensemble model, etc., and explore their potential contributions to our research.

Arginine and its metabolites stimulate proliferation, differentiation, and physiological function of porcine trophoblast cells through ß-catenin and mTOR pathways.

Arginine, which is metabolized into ornithine, proline, and nitric oxide, plays an important role in embryonic development. The present study was conducted to investigate the molecular mechanism of arginine in proliferation, differentiation, and physiological function of porcine trophoblast cells (pTr2) through metabolic pathways. The results showed that arginine significantly increased cell viability (P < 0.05). The addition of arginine had a quadratic tendency to increase the content of progesterone (P = 0.06) and protein synthesis rate (P = 0.03), in which the maximum protein synthesis rate was observed at 0.4 mM arginine. Arginine quadratically increased (P < 0.05) the intracellular contents of spermine, spermidine and putrescine, as well as linearly increased (P < 0.05) the intracellular content of NO in a dose-dependent manner. Arginine showed a quadratic tendency to increase the content of putrescine (P = 0.07) and a linear tendency to increase NO content (P = 0.09) in cell supernatant. Moreover, increasing arginine activated (P < 0.05) the mRNA expressions for ARG, ODC, iNOS and PCNA. Furthermore, inhibitors of arginine metabolism (L-NMMA and DFMO) both inhibited cell proliferation, while addition of its metabolites (NO and putrescine) promoted the cell proliferation and cell cycle, the mRNA expressions of PCNA, EGF and IGF-1, and increased (P < 0.05) cellular protein synthesis rate, as well as estradiol and hCG secretion (P < 0.05). In conclusion, our results suggested that arginine could promote cell proliferation and physiological function by regulating the metabolic pathway. Further studies showed that arginine and its metabolites modulate cell function mainly through ß-catenin and mTOR pathways.

Strategic control of combustion-induced ammonia emissions: A key initiative for substantial PM2.5 reduction in Tianjin, North China Plain.

Information on the temporal and spatial variations in the sources of ammonium salts (NH4+), a crucial alkaline component in PM2.5, is limited. Here, we simultaneously collected PM2.5 and gaseous ammonia (NH3) samples in both summer and winter from two sites in Tianjin: an urban site (Tianjin University, TJU) and a suburban site (Binhai New-region, BH). NH3 concentrations, the contents of major water-soluble inorganic ions in PM2.5, and the compositions of ammonium­nitrogen isotopes (δ15N-NH4+) were measured. As a result, (NH4)2SO4 and NH4NO3 were the predominant forms of NH4+ in PM2.5 during summer and winter, respectively. However, the NH4NO3 concentrations were notably greater at TJU (6.2 ± 7.3 µg m-3) than at BH (3.8 ± 4.7 µg m-3) in summer, with no regional differences observed in winter. Both sites displayed almost half the contribution of c-NH3 (combustion-related NH3) to NH4+, differing from the finding of previous isotope-based studies. This discrepancy could be attributed to the combined effects of NHx isotope fractionation and seasonal δ15N value variations in NH3 sources. The contribution fractions of v-NH3 (volatile NH3) and c-NH3 exhibited similar patterns at both sites seasonally, probably caused by coal combustion for heating in winter and temperature fluctuations. However, the contribution fraction of c-NH3 was lower at BH than at TJU in summer but greater in winter than at TJU. In summer, NH4NO3 was unstable and limited its delivery to TJU from BH, and the high contribution of c-NH3 to NH4+ at TJU could be attributed to local vehicle emissions. In winter, the stable particulate NH4NO3 that formed from the c-NH3 in the upwind area could be transported to the downwind area, increasing the NH4+ concentration at BH. Our study provides valuable insights for devising emission mitigation strategies to alleviate the increasing burden of NH3 in the local atmosphere.