AI driven analysis of MRI to measure health and disease progression in FSHD.

Facioscapulohumeral muscular dystrophy (FSHD) affects roughly 1 in 7500 individuals. While at the population level there is a general pattern of affected muscles, there is substantial heterogeneity in muscle expression across- and within-patients. There can also be substantial variation in the pattern of fat and water signal intensity within a single muscle. While quantifying individual muscles across their full length using magnetic resonance imaging (MRI) represents the optimal approach to follow disease progression and evaluate therapeutic response, the ability to automate this process has been limited. The goal of this work was to develop and optimize an artificial intelligence-based image segmentation approach to comprehensively measure muscle volume, fat fraction, fat fraction distribution, and elevated short-tau inversion recovery signal in the musculature of patients with FSHD. Intra-rater, inter-rater, and scan-rescan analyses demonstrated that the developed methods are robust and precise. Representative cases and derived metrics of volume, cross-sectional area, and 3D pixel-maps demonstrate unique intramuscular patterns of disease. Future work focuses on leveraging these AI methods to include upper body output and aggregating individual muscle data across studies to determine best-fit models for characterizing progression and monitoring therapeutic modulation of MRI biomarkers.

Rhodamine and related substances in food: Recent updates on pretreatment and analysis methods.

Rhodamine, a colorant prohibited in various consumer products due to its demonstrated carcinogenic, mutagenic, and toxic properties, necessitates the development of a straightforward, efficient, sensitive, environmentally friendly, and cost-effective analytical method. This review provides an overview of recent advancements in the pretreatment and determination techniques for rhodamine across diverse sample matrices since 2017. Sample preparation methods encompass both commonly used pretreatment techniques such as filtration, centrifugation, solvent extraction, and cloud point extraction, as well as innovative approaches including solid phase extraction, dispersive liquid-liquid microextraction, hollow fiber liquid phase microextraction, magnetic solid phase extraction, and matrix solid phase dispersion. The analytical techniques encompass high performance liquid chromatography, surface-enhanced Raman scattering, and sensor-based methods. Furthermore, a comprehensive examination is conducted to offer insights for future research on rhodamine regarding the advantages, disadvantages, and advancements in various pretreatment and determination methodologies.

Women's experience of adopting lateral positions during the second stage of labour compared with conventional lithotomy positions: A cross-sectional study.

AIMS: Maternal positions during childbirth play an important role in safe vaginal births and might also influence women's childbirth experiences greatly. Lateral positions, as a potential position to reduce negative maternal and neonatal outcomes, have become popular in recent years, especially in China where the adoption of conventional lithotomy positions is still common. However, the childbirth experience of those who gave birth in lateral positions has been rarely studied. This study aimed to describe and compare women's childbirth experiences of adopting the newly introduced lateral positions and the conventional lithotomy positions during the second stage of labour. STUDY DESIGN: A cross-sectional study was conducted in two tertiary hospitals in China involving a total of 658 primiparous and parous women who adopted lateral and lithotomy positions during the second stage of labour from July to November 2020. Sociodemographic characteristics, maternal and neonatal outcomes as well as childbirth experience assessed by the Childbirth Experience Questionnaire (CEQ) were collected. This study followed the STROBE guidelines. RESULTS: Women who once adopted lateral positions during the second stage of labour had better positive childbirth experiences compared with those in the lithotomy positions group, as demonstrated by their overall higher CEQ scores. Women in the lateral position group also reported better participation and perceived safety, and a greater sense of control during childbirth. Lateral positions remained an influential factor in CEQ scores after controlling for potential confounders. In this study, adverse maternal and neonatal outcomes were rare. Women in lateral positions had comparatively better perineal outcomes. CONCLUSION: This study described and compared women's childbirth experiences of adopting conventional lithotomy positions and lateral positions during the second stage of labour using a valid instrument. Women who adopted lateral positions during the second stage of labour reported better childbirth experiences than those giving birth in the conventional lithotomy positions. Thus, assisting women in giving birth in lateral positions might be a promising way to improve women's childbirth experience.

Baduanjin for ischemic heart failure with mildly reduced/preserved ejection fraction (BEAR Trial): A randomized controlled trial.

AIM: While Baduanjin, a traditional Chinese mind-body exercise, has shown potential health benefits, its efficacy in improving outcomes for heart failure patients with mildly reduced or preserved ejection fraction (HFmrEF/HFpEF) has not been well documented. We aimed to investigate the adjunctive impact of Baduanjin on exercise capacity and quality of life for HFmrEF/HFpEF. METHODS: Patients with HFmrEF/HFpEF were enrolled in this multicenter randomized clinical trial. All participants were randomized to conventional cardiac rehabilitation with or without an additional 12-week Baduanjin exercise. The primary endpoint was the distance covered in a 6-min walk test (6MWD), while key secondary outcomes included quality of life measured by the Minnesota Living with Heart Failure Questionnaire (MLHFQ) and cardiopulmonary function including anaerobic threshold (VO2 AT). RESULTS: A total of 120 patients were enrolled, and 109 completed all session and tests. The mean age of the 120 patients was 60.5 years (SD, 9.21 years), and 23 (19.2%) were women. The Baduanjin group exhibited a 6.14% improvement in 6MWD compared to a 1.32% improvement in the control group (median improvement, 25.0 vs. 5.0 m; p < 0.001) at 12th week. The VO2 AT increased by 25.87% in the Baduanjin group versus 3.94% in the control group (p < 0.001). Quality of life also significantly improved in the Baduanjin group as indicated by MLHFQ score changes (-16.8% vs. -3.99%; p < 0.001). CONCLUSIONS: Adding Baduanjin to exercise-based cardiac rehabilitation for patients with ischemic HFmrEF or HFpEF are generally safe and could provide significant improvements in exercise capacity and quality of life.

Designing Small Molecule PI3Kγ Inhibitors: A Review of Structure-Based Methods and Computational Approaches.

The PI3K/AKT/mTOR pathway plays critical roles in a wide array of biological processes. Phosphatidylinositol 3-kinase gamma (PI3Kγ), a class IB PI3K family member, represents a potential therapeutic opportunity for the treatment of cancer, inflammation, and autoimmunity. In this Perspective, we provide a comprehensive overview of the structure, biological function, and regulation of PI3Kγ. We also focus on the development of PI3Kγ inhibitors over the past decade and emphasize their binding modes, structure-activity relationships, and pharmacological activities. The application of computational technologies and artificial intelligence in the discovery of novel PI3Kγ inhibitors is also introduced. This review aims to provide a timely and updated overview on the strategies for targeting PI3Kγ.

Facile Synthesis of Ultra-Small Silver Nanoparticles Stabilized on Carbon Nanospheres for the Etherification of Silanes.

The dehydrocoupling reaction between alcohols and hydrosilanes is considered to be one of the most atom-economical ways to produce Si-O coupling compounds because its byproduct is only hydrogen (H2), which make it extremely environmentally friendly. In past decades, various kinds of homogeneous catalysts for the dehydrocoupling of alcohols and hydrosilanes, such as transition metal complexes, alkaline earth metals, alkali metals, and noble metal complexes, have been reported for their good activity and selectivity. Nevertheless, the practical applications of these catalysts still remain unsatisfactory, which is mainly restricted by environmental impact and non-reusability. A facile and recyclable heterogeneous catalyst, ultra-small Ag nanoparticles supported on porous carbon (Ag/C) for the etherification of silanes, has been developed. It has high catalytic activity for the Si-O coupling reaction, and the apparent activation energy of the reaction is about 30 kJ/mol. The ultra-small Ag nanoparticles dispersed in the catalyst through the carrier C have an enrichment effect on all reactants, which makes the reactants reach the adsorption saturation state on the surface of Ag nanoparticles, thus accelerating the coupling reaction process and verifying that the kinetics of the reaction of the catalyst indicate a zero-grade reaction.

Associations between the choroid plexus and tau in Alzheimer's disease using an active learning segmentation pipeline.

BACKGROUND: The cerebrospinal fluid (CSF), primarily generated by the choroid plexus (ChP), is the major carrier of the glymphatic system. The alternations of CSF production and the ChP can be associated with the Alzheimer's disease (AD). The present work investigated the roles of the ChP in the AD based on a proposed ChP image segmentation pipeline. METHODS: A human-in-the-loop ChP image segmentation pipeline was implemented with intermediate and active learning datasets. The performance of the proposed pipeline was evaluated on manual contours by five radiologists, compared to the FreeSurfer and FastSurfer toolboxes. The ChP volume and blood flow were investigated among AD groups. The correlations between the ChP volume and AD CSF biomarkers including phosphorylated tau (p-tau), total tau (t-tau), amyloid-ß42 (Aß42), and amyloid-ß40 (Aß40) was investigated using three models (univariate, multiple variables, and stepwise regression) on two datasets with 806 and 320 subjects. RESULTS: The proposed ChP segmentation pipeline achieved superior performance with a Dice coefficient of 0.620 on the test dataset, compared to the FreeSurfer (0.342) and FastSurfer (0.371). Significantly larger volumes (p < 0.001) and higher perfusion (p = 0.032) at the ChP were found in AD compared to CN groups. Significant correlations were found between the tau and the relative ChP volume (the ChP volume and ChP/parenchyma ratio) in each patient groups and in the univariate regression analysis (p < 0.001), the multiple regression model (p < 0.05 except for the t-tau in the LMCI), and in the step-wise regression model (p < 0.021). In addition, the correlation coefficients changed from - 0.32 to - 0.21 along with the AD progression in the multiple regression model. In contrast, the Aß42 and Aß40 shows consistent and significant associations with the lateral ventricle related measures in the step-wise regression model (p < 0.027). CONCLUSIONS: The proposed pipeline provided accurate ChP segmentation which revealed the associations between the ChP and tau level in the AD. The proposed pipeline is available on GitHub ( https://github.com/princeleeee/ChP-Seg ).

Efficient segmentation of fetal brain MRI based on the physical resolution.

BACKGROUND: The image resolution of fetal brain magnetic resonance imaging (MRI) is a critical factor in brain development measures, which is mainly determined by the physical resolution configured in the MRI sequence. However, fetal brain MRI are commonly reconstructed to 3D images with a higher apparent resolution, compared to the original physical resolution. PURPOSE: This work is to demonstrate that accurate segmentation can be achieved based on the MRI physical resolution, and the high apparent resolution segmentation can be achieved by a simple deep learning module. METHODS: This retrospective study included 150 adult and 80 fetal brain MRIs. The adult brain MRIs were acquired at a high physical resolution, which were downsampled to visualize and quantify its impacts on the segmentation accuracy. The physical resolution of fetal images was estimated based on MRI acquisition settings and the images were downsampled accordingly before segmentation and restored using multiple upsampling strategies. Segmentation accuracy of ConvNet models were evaluated on the original and downsampled images. Dice coefficients were calculated, and compared to the original data. RESULTS: When the apparent resolution was higher than the physical resolution, the accuracy of fetal brain segmentation had negligible degradation (accuracy reduced by 0.26%, 1.1%, and 1.8% with downsampling factors of 4/3, 2, and 4 in each dimension, without significant differences from the original data). Using a downsampling factor of 4 in each dimension, the proposed method provided 7× smaller and 10× faster models. CONCLUSION: Efficient and accurate fetal brain segmentation models can be developed based on the physical resolution of MRI acquisitions.

A risk prediction model for efficient intubation in the emergency department: A 4-year single-center retrospective analysis.

Objective: To analyze the risk factors associated with intubated critically ill patients in the emergency department (ED) and develop a prediction model by machine learning algorithms. Methods: This study was conducted in an academic tertiary hospital in Hangzhou, China. Critically ill patients admitted to the ED were retrospectively analyzed from May 2018 to July 2022. The demographic characteristics, distribution of organ dysfunction, parameters for different organs' examination, and status of mechanical ventilation were recorded. These patients were assigned to the intubation and non-intubation groups according to ventilation support. We used the eXtreme Gradient Boosting (XGBoost) algorithm to develop the prediction model and compared it with other algorithms, such as logistic regression, artificial neural network, and random forest. SHapley Additive exPlanations was used to analyze the risk factors of intubated critically ill patients in the ED. Results: Of 14,589 critically ill patients, 10,212 comprised the training group and 4377 comprised the test group; 2289 intubated patients were obtained from the electronic medical records. The mean age, mean scores of vital signs, parameters of different organs, and blood oxygen examination results differed significantly between the two groups (p < 0.05). The white blood cell count, international normalized ratio, respiratory rate, and pH are the top four risk factors for intubation in critically ill patients. Based on the risk factors in different predictive models, the XGBoost model showed the highest area under the receiver operating characteristic curve (0.84) for predicting ED intubation. Conclusions: For critically ill patients in the ED, the proposed model can predict potential intubation based on the risk factors in the clinically predictive model.

Mowing aggravates the adverse effects of nitrogen addition on soil acid neutralizing capacity in a meadow steppe.

Soil acidification induced by reactive nitrogen (N) inputs is a major environmental issue in grasslands, as it lowers the acid neutralizing capacity (ANC). The specific impacts of different N compound forms on ANC remain unclear. Grassland management practices like mowing and grazing can remove a considerable amount of soil N and other nutrients, potentially mitigating soil acidification by removing N from the ecosystem or aggravating it by removing base cations. However, empirical evidence regarding the joint effects of adding different forms of N compounds and mowing on ANC changes in different-sized soil aggregates is still lacking. This study aimed to address this knowledge gap by examining the effects of three N compounds (urea, ammonium nitrate, and ammonium sulfate) combined with mowing (mown vs. unmown) on soil ANC in different soil aggregate sizes (>2000 µm, 250-2000 µm, and <250 µm) through a 6-year field experiment in Inner Mongolia grasslands. We found that the average decline in soil ANC caused by ammonium sulfate (AS) addition (-78.9%) was much greater than that by urea (-25.0%) and ammonium nitrate (AN) (-52.1%) as compared to control. This decline was attributed to increased proton (H+) release from nitrification and the leaching of exchangeable Ca2+ and Mg2+. Mowing aggravated the adverse effects of urea and AN on ANC, primarily due to the reduction in soil organic matter (SOM) contents and the removal of exchangeable Ca2+, K+, and Na + via plant biomass harvest. This pattern was consistent across all aggregate fractions. The lack of variation in soil ANC among different soil aggregate fractions is likely due to the contrasting trend in the distribution of exchangeable Ca2+ and Mg2+. Specifically, the concentration of exchangeable Ca2+ increased with increasing aggregate size, while the opposite was true for that of exchangeable Mg2+. These findings underscore the importance of considering the forms of N compounds when assessing the declines of ANC induced by N inputs, which also calls for an urgent need to reduce N emissions to ensure the sustainable development of the meadow ecosystems.

Machine-learning-aided decision-making model for the discontinuation of continuous renal replacement therapy.

BACKGROUND: Continuous renal replacement therapy (CRRT) is a primary form of renal support for patients with acute kidney injury in an intensive care unit. Making an accurate decision of discontinuation is crucial for the prognosis of patients. Previous research has mostly focused on the univariate and multivariate analysis of factors in CRRT, without the capacity to capture the complexity of the decision-making process. The present study thus developed a dynamic, interpretable decision model for CRRT discontinuation. METHODS: The study adopted a cohort of 1234 adult patients admitted to an intensive care unit in the MIMIC-IV database. We used the extreme gradient boosting (XGBoost) machine learning algorithm to construct dynamic discontinuation decision models across four time points. Shapley additive explanation (SHAP) analysis was conducted to show the contribution of an individual feature to the model output. RESULTS: Of the 1234 included patients with CRRT, 596 (48.3%) successfully discontinued CRRT. The dynamic prediction by the XGBoost model produced an area under the curve of 0.848 and accuracy, sensitivity, and specificity of 0.782, 0.786, and 0.776, respectively. The XGBoost model was thus far superior to other test models. SHAP demonstrated that the features that contributed most to the model results were the sequential organ failure assessment score, serum lactate level, and 24-hour urine output. CONCLUSIONS: Dynamic decision models supported by machine learning are capable of dealing with complex factors in CRRT and effectively predicting the outcome of discontinuation.

MRI-Based Prediction of Clinical Improvement Following Ventricular Shunt Placement for Normal Pressure Hydrocephalus (NPH): Development and Evaluation of an Integrated Multi-Sequence Machine Learning Algorithm.

BACKGROUND AND PURPOSE: Symptoms of normal pressure hydrocephalus (NPH) are sometimes refractory to shunt placement, with limited ability to predict improvement for individual patients. We evaluated an MRI-based artificial intelligence method to predict post-shunt NPH symptom improvement. MATERIALS AND METHODS: NPH patients who underwent magnetic resonance imaging (MRI) prior to shunt placement at a single center (2014-2021) were identified. Twelve-month post-shunt improvement in modified Rankin Scale (mRS), incontinence, gait, and cognition were retrospectively abstracted from clinical documentation. 3D deep residual neural networks were built on skull stripped T2-weighted and fluid attenuated inversion recovery (FLAIR) images. Predictions based on both sequences were fused by additional network layers. Patients from 2014-2019 were used for parameter optimization, while those from 2020-2021 were used for testing. Models were validated on an external validation dataset from a second institution (n=33). RESULTS: Of 249 patients, n=201 and n=185 were included in the T2-based and FLAIR-based models according to imaging availability. The combination of T2-weighted and FLAIR sequences offered the best performance in mRS and gait improvement predictions relative to models trained on imaging acquired using only one sequence, with AUROC values of 0.7395 [0.5765-0.9024] for mRS and 0.8816 [0.8030-0.9602] for gait. For urinary incontinence and cognition, combined model performances on predicting outcomes were similar to FLAIR-only performance, with AUROC values of 0.7874 [0.6845-0.8903] and 0.7230 [0.5600-0.8859]. CONCLUSIONS: Application of a combined algorithm using both T2-weighted and FLAIR sequences offered the best image-based prediction of post-shunt symptom improvement, particularly for gait and overall function in terms of mRS. ABBREVIATIONS: NPH = normal pressure hydrocephalus; iNPH = idiopathic NPH; sNPH = secondary NPH; AI = artificial intelligence; ML = machine learning; CSF = cerebrospinal fluid; AUROC = area under the receiver operating characteristic; FLAIR = fluid attenuated inversion recovery; BMI = body mass index; CCI = Charlson Comorbidity Index; SD = standard deviation; IQR = interquartile range.

Combining bioinformatics and multiomics strategies to investigate the key microbiota and active components of Liupao tea ameliorating hyperlipidemia.

ETHNOPHARMACOLOGICAL RELEVANCE: Hyperlipidemia as a major health issue has attracted much public attention. As a geographical indication product of China, Liupao tea (LPT) is a typical representative of traditional Chinese dark tea that has shown good potential in regulating glucose and lipid metabolism. LPT has important medicinal value in hyperlipidemia prevention. However, the active ingredients and metabolic mechanisms by which LPT alleviates hyperlipidemia remain unclear. AIM OF THE STUDY: This study aimed to systematically investigate the metabolic mechanisms and active ingredients of LPT extract in alleviating hyperlipidemia. MATERIALS AND METHODS: Firstly, we developed a mouse model of hyperlipidemia to study the pharmacodynamics of LPT. Subsequently, network pharmacology and molecular docking were performed to predict the potential key active ingredients and core targets of LPT against hyperlipidemia. LC-MS/MS was used to validate the identity of key active ingredients in LPT with chemical standards. Finally, the effect and metabolic mechanisms of LPT extract in alleviating hyperlipidemia were investigated by integrating metabolomic, lipidomic, and gut microbiome analyses. RESULTS: Results showed that LPT extract effectively improved hyperlipidemia by suppressing weight gain, remedying dysregulation of glucose and lipid metabolism, and reducing hepatic damage. Network pharmacology analysis and molecular docking suggested that four potential active ingredients and seven potential core targets were closely associated with roles for hyperlipidemia treatment. Ellagic acid, catechin, and naringenin were considered to be the key active ingredients of LPT alleviating hyperlipidemia. Additionally, LPT extract modulated the mRNA expression levels of Fxr, Cyp7a1, Cyp8b1, and Cyp27a1 associated with bile acid (BA) metabolism, mitigated the disturbances of BA and glycerophospholipid (GP) metabolism in hyperlipidemia mice. Combining fecal microbiota transplantation and correlation analysis, LPT extract effectively improved species diversity and abundance of gut microbiota, particularly the BA and GP metabolism-related gut microbiota, in the hyperlipidemia mice. CONCLUSIONS: LPT extract ameliorated hyperlipidemia by modulating GP and BA metabolism by regulating Lactobacillus and Dubosiella, thereby alleviating hyperlipidemia. Three active ingredients of LPT served as the key factors in exerting an improvement on hyperlipidemia. These findings provide new insights into the active ingredients and metabolic mechanisms of LPT in improving hyperlipidemia, suggesting that LPT can be used to prevent and therapeutic hyperlipidemia.

Prognostic implication and immunotherapy response prediction of a novel ubiquitination-related gene signature in liver cancer.

HCC, also known as hepatocellular carcinoma, is a frequently occurring form of cancer with an unfavorable prognosis. This research constructed a prognostic signature related to ubiquitination and investigated its correlation with the response to immunotherapy in HCC. The Molecular Signatures Database provided a compilation of genes associated with ubiquitination. A gene signature related to ubiquitination was obtained through Cox regression using the Least Absolute Shrinkage and Selection Operator method. The genetic factors CPY26B1, MCM10, SPINK4, and TRIM54 notably impacted the outcomes of HCC. The patients were divided into two groups: one group had a high risk of poor survival while the other had a low risk but a greater chance of controlling HCC progression. Both univariate and multivariate analyses using Cox regression found the risk score to be an independent predictor of HCC prognosis. Gene set enrichment analysis (GSEA) indicated enrichment in cell cycle and cancer-related microRNAs in high-risk groups. The tumor microenvironment (TME), response to immunotherapy, and effectiveness of chemotherapy medications positively correlated with the risk score. In the high-risk group, erlotinib showed higher IC50 values compared to the low-risk group which exhibited higher IC50 values for VX-11e, AKT inhibitor VIII, AT-7519, BMS345541, Bortezomib, CP466722, FMK, and JNK-9L. The results of RT-qPCR revealed that the expression of four UEGs was higher in tumor tissue as compared to normal tissue. Based on the genes that were expressed differently and associated with ubiquitination-related tumor categorization, we have developed a pattern of four genes and a strong nomogram that can predict the prognosis of HCC, which could be useful in identifying and managing HCC.

Carrier-free chemo-phototherapeutic nanomedicines with endo/lysosomal escape function enhance the therapeutic effect of drug molecules in tumors.

Carrier-free nanomedicines offer advantages of extremely high drug loading capacity (>80%), minimal non-drug constituent burden, and facile preparation processes. Numerous studies have proved that multimodal cancer therapy can enhance chemotherapy efficiency and mitigate multi-drug resistance (MDR) through synergistic therapeutic effects. Upon penetration into the tumor matrix, nanoparticles (NPs) are anticipated to be uptaken by cancer cells, primarily through clathrin-meditated endocytosis pathways, leading to their accumulation in endosomes/lysosomes within cells. However, endo/lysosomes exhibit a highly degradative environment for organic NPs and drug molecules, often resulting in treatment failure. Hence, this study designed a lysosomal escape mechanism with carrier-free nanomedicine, combining the chemotherapeutic drug, curcumin (Cur), and the photothermal/photodynamic therapeutic drug, indocyanine green (ICG), for synergistic cancer treatment (ICG-Cur NPs) via a facile preparation process. To facilitate endo/lysosomal escape, ICG-Cur NPs were modified with metal-phenolic networks (MPNs) of different thickness. The results indicate that a thick MPN coating promotes rapid endo/lysosomal escape of ICG-Cur NPs within 4 h and enhances the photothermal conversion efficiency of ICG-Cur NPs by 55.8%, significantly improving anticancer efficacy in both chemo- and photo-therapies within 3D solid tumor models. This finding underscores the critical role of endo/lysosomal escape capacity in carrier-free drug NPs for therapeutic outcomes and offers a facile solution to achieve it.

Effect of proton pump inhibitors versus histamine-2 receptor antagonists on acute kidney injury in septic patients at high risk for developing stress ulcers.

BACKGROUND: To compare the effects of proton pump inhibitor (PPI) and histamine-2 receptor antagonist (H2RA) use on the occurrence of acute kidney injury (AKI) in septic patients at high risk for developing stress ulcers. METHODS: Using the Medical Information Mart for Intensive Care IV version 2.2 database, septic patients with high-risk factors for stress ulcers (i.e., shock, coagulopathy, invasive mechanical ventilation, or chronic liver diseases) were included. Exposures included PPIs and H2RAs within 24 h of intensive care unit (ICU) admission or prior to ICU admission. The primary end point was severe sepsis-associated AKI as defined by the Kidney Disease Improving Global Outcomes criteria stage 3 (KDIGO-3). Propensity score matching (PSM) was performed to balance baseline characteristics. Multivariable Cox proportional hazards regression was used to estimate the effect size. RESULTS: 4731 PPI users and 4903 H2RA users were included. After PSM, there were 1785 pairs exposed to PPIs and H2RAs. In the PSM cohort, the cumulative incident KDIGO-3 rate was higher in the PPI group than in the H2RA group (log-rank test, p = 0.009). Regression analyses showed that PPI exposure [adjusted hazard ratio 1.32, 95% confidence interval (CI) 1.11-1.58, p = 0.002] was associated with incident KDIGO-3 compared with H2RA use. This association remained consistent in sensitivity analyses. Additionally, the PPI group had a higher need for kidney replacement therapy compared with the H2RA group (3.6% vs. 2.1%, P = 0.012). CONCLUSIONS: Among septic patients at high risk for developing stress ulcers, PPI exposure was associated with incident KDIGO-3 AKI compared with H2RA use.

Nitrophenols in the environment: An update on pretreatment and analysis techniques since 2017.

Nitrophenols, a versatile intermediate, have been widely used in leather, medicine, chemical synthesis, and other fields. Because these components are widely applied, they can enter the environment through various routes, leading to many hazards and toxicities. There has been a recent surge in the development of simple, rapid, environmentally friendly, and effective techniques for determining these environmental pollutants. This review provides a comprehensive overview of the latest research progress on the pretreatment and analysis methods of nitrophenols since 2017, with a focus on environmental samples. Pretreatment methods include liquid-liquid extraction, solid-phase extraction, dispersive extraction, and microextraction methods. Analysis methods mainly include liquid chromatography-based methods, gas chromatography-based methods, supercritical fluid chromatography. In addition, this review also discusses and compares the advantages/disadvantages and development prospects of different pretreatment and analysis methods to provide a reference for further research.

A Qualitative Study of the Care Experience of Mothers of Asthmatic Children from Low-Income Families.

Objectives: This study aimed to explore the experiences and caregiving perspectives of mothers from low-income families who have children with asthma,and to establish a foundation for the development of tailored nursing strategies specifically designed for families facing similar circumstances. Method: A descriptive qualitative research method was employed. Fifteen mothers of asthmatic children from low-income families receiving treatment at the Respiratory Centre of Chongqing Children's Hospital were purposefully sampled from June to December 2021. Semi-structured interviews were conducted to gather data on their caregiving experiences, and thematic analysis was utilized to analyze the interview data. Results: The interviewees were 27-42 years old (SD=32.3 years), 33.3% were full-time mothers(A woman who quit work, in order to focus on taking care of the child and the family ), 53.3% had one child, 46.6% had a college degree or higher, and 100% had health insurance. Through in-depth interviews, four main themes and eight sub-themes were identified, including (a) insufficient knowledge about the disease, (b) anxiety and uncertainty, (c) insufficient social support system, and (d) insufficient resources for medical services. The first theme describes a weak willingness to learn and medication discontinuation at will. The second theme describes financial burden and psychological stress, the third theme describes lack of family support and low social participation, and the fourth theme describes insufficient health insurance support and unequal distribution of healthcare resources. Conclusion: Mothers from low-income families with asthmatic children face substantial psychological burdens and familial pressures. It is crucial for healthcare professionals to actively engage with and deepen their understanding of these mothers' caregiving experiences and psychological well-being. By doing so, positive coping strategies can be developed, promoting the physical and mental health of these mothers and improving asthma control in their children.

Different roads, same destination: The shared future of plant ecophysiology and ecohydrology.

Terrestrial water fluxes are substantially mediated by vegetation, while the distribution, growth, health, and mortality of plants are strongly influenced by the availability of water. These interactions, playing out across multiple spatial and temporal scales, link the disciplines of plant ecophysiology and ecohydrology. Despite this connection, the disciplines have provided complementary, but largely independent, perspectives on the soil-plant-atmosphere continuum since their crystallization as modern scientific disciplines in the late 20th century. This review traces the development of the two disciplines, from their respective origins in engineering and ecology, their largely independent growth and maturation, and the eventual development of common conceptual and quantitative frameworks. This common ground has allowed explicit coupling of the disciplines to better understand plant function. Case studies both illuminate the limitations of the disciplines working in isolation, and reveal the exciting possibilities created by consilience between the disciplines. The histories of the two disciplines suggest opportunities for new advances will arise from sharing methodologies, working across multiple levels of complexity, and leveraging new observational technologies. Practically, these exchanges can be supported by creating shared scientific spaces. This review argues that consilience and collaboration are essential for robust and evidence-based predictions and policy responses under global change.

Effects of Crocus sativus on glycemic control and cardiometabolic parameters among patients with metabolic syndrome and related disorders: a systematic review and meta-analysis of randomized controlled trials.

Metabolic syndrome (MetS) is a cluster of clinical syndromes that is closely associated with an elevated risk of developing atherosclerotic cardiovascular disease. In a series of animal experiments and clinical trials, crocus sativus and its component crocin have demonstrated promising hypoglycemic effects. However, there is currently insufficient evidence regarding their impact on cardiometabolic parameters. Our study aimed to assess the impact of Crocus sativus and crocin on glycemic control in individuals with metabolic syndrome and associated disorders, as well as their potential effects on improving cardiometabolic parameters. We searched Cochrane Library, PubMed, Embase, and Web of Science databases to ascertain the pertinent randomized controlled trials (RCTs) until December 30, 2023. Q-test and I2 statistics were utilized to evaluate heterogeneity among the included studies. Data were merged using a random-effects model and presented as (WMD) with a 95% confidence interval (CI). The current comprehensive review and meta-analysis, encompassing 13 RCTs involving a total of 840 patients diagnosed with metabolic syndrome and associated disorders, demonstrates that Crocus sativus was superior to placebo on Hemoglobin A1c(HbA1c) (WMD: -0.31;95% CI [-0.44,-0.19]. P = 0.002) and systolic blood pressure(SBP) (WMD:-7.49;95% CI [-11.67,-3.30]. P = 0.99) respectively. Moreover, Crocus sativus improved fasting blood glucose (FBG) (WMD:-7.25;95% CI [-11.82, -2.57]. P = 0.002) when used crocin and on other chronic diseases. Crocus sativus reduced the total cholesterol (TC) among the metabolic syndromepatients (WMD:-13.64;95%CI [-26.26, -1.03]. P = 0.03). We demonstrated that Crocus sativus exerts beneficial effects on glycemic control and cardiometabolic parameters in individuals with metabolic syndrome and related disorders.