Glycyrrhizic acid and patchouli alcohol in Huoxiang Zhengqi attenuate intestinal inflammation and barrier injury via regulating endogenous corticosterone metabolism mediated by 11ß-HSD1.

ETHNOPHARMACOLOGICAL RELEVANCE: Ulcerative colitis (UC), a chronic inflammatory bowel disease, has become a significant public health challenge due to the limited effectiveness of available therapies. Huoxiang Zhengqi (HXZQ), a well-established traditional Chinese formula, shows potential in managing UC, as suggested by clinical and pharmacological studies. However, the active components and mechanisms responsible for its effects remain unclear. AIM OF STUDY: This study aimed to identify the bioactive components of HXZQ responsible for its therapeutic effects on UC and to elucidate their underlying mechanisms. MATERIALS AND METHODS: The effect of HXZQ against dextran sodium sulfate (DSS) -induced colitis was investigated. Ingredients in HXZQ were characterized and analyzed in colitic mice using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). In vitro, biological activity of compounds was assessed using lipopolysaccharide (LPS)-induced Ana-1 cells and bone marrow-derived macrophages (BMDMs), tumor necrosis factor-alpha-induced Caco-2 cells, and isolated intestinal crypts from colitic mice. These results were confirmed in vivo. The targets of the components were identified through bioinformatics analysis and validated via molecular docking, enzyme inhibition assays, and in vivo experiments. Hematoxylin and eosin (HE) staining, periodic acid-Schiff (PAS) staining, immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), western blotting, and quantitative real-time polymerase chain reaction (qPCR) were employed to confirm the pharmaceutical effects. RESULTS: A clinical equivalent dose of HXZQ (2.5 mL/kg) effectively treated DSS-induced colitis. 113 compounds were identified in HXZQ, with 35 compounds detected in colitic mice. Glycyrrhizic acid (GA) and patchouli alcohol (PA) emerged as key contributors to the anti-colitic effects of HXZQ. Further investigation revealed that HXZQ and its active components decreased the levels of pro-inflammatory cytokines TNF-α, interleukin-1ß (IL-1ß), and interleukin-6 (IL-6) in colon, likely by inhibiting nuclear factor kappa-B (NF-κB) signaling pathway. This inhibition indirectly activated the intestinal farnesoid X receptor (FXR) signaling pathway, correcting bile acid imbalances caused by colitis. Additionally, these components significantly enhanced the expression of tight junction proteins ZO-1 and Occludin, as well as the adhesion protein E-cadherin, and reduced goblet cell loss, thereby repairing intestinal barrier injury. Mechanistically, GA and PA were found to inhibit 11ß-hydroxysteroid dehydrogenase 1 (11ß-HSD1) activity, leading to increased local active corticosterone levels in the intestine to exert anti-inflammatory effects. Notably, the inhibition of 11ß-HSD1 with the selective inhibitor BVT ameliorated colitis in mice. CONCLUSIONS: HXZQ exhibits therapeutic effects on UC, primarily through GA and PA inhibiting 11ß-HSD1. This suggests new natural therapy approaches for UC and positions 11ß-HSD1 as a potential target for colitis treatment.

Impact of diversion ileostomy on postoperative complications and recovery in the treatment of locally advanced upper-half rectal cancer.

The efficacy of diversion ileostomy followed by radical surgery for locally advanced upper-half rectal cancer remains uncertain. This study seeks to compare the effectiveness of treatment with and without diversion ileostomy in preventing anastomotic leakage (AL) and to identify a subset who may benefit from diversion ileostomy after AL occurs in Chinese patients with stage II and III upper-half rectal cancer. A retrospective study enrolled a total of 809 patients with locally advanced upper-half rectal cancer between 2017 and 2021, with 27.6% (n = 223) treated with diversion ileostomy and 72.4% (n = 586) treated without diversion ileostomy. The Diversion(+) group (n = 172) and Diversion(-) group (n = 172) were compared for perioperative outcomes through 1:1 propensity score matching (PSM). The selection of variables for multivariable logistic regression was determined through bivariate logistic regression analysis. Additionally, optimal cutoff values for risk factors were identified using ROC curve analysis. Within the entire cohort, patients in the Diversion(+) group exhibited a lower distance from the anal verge (DAV) and higher rates of chemoradiotherapy (CRT), diabetes, cN2 stage, mrCRM positivity, EMVI positivity, and CEA elevation compared to those in the Diversion(-) group. Following PSM, a satisfactory balance of baseline variables was achieved between the two groups. There were no statistically significant differences in AL rates (7.0% vs. 5.8%, p = 0.659) or AL grade distribution (Grade A: 0.6% vs. 0%, Grade B: 5.2% vs. 4.1%, Grade C: 1.2% vs. 1.7%, p = 0.691) between the two groups. However, the Diversion(+) group demonstrated a higher incidence of postoperative complications (30.8% vs. 17.4%, p = 0.004), Clavien‒Dindo III-IV complications (2.9% vs. 2.3%, p = 0.013), particularly wound infections (8.1% vs. 1.2%, p = 0.002), and early postoperative inflammatory small bowel obstruction (EPISBO) (8.7% vs. 1.2%, p = 0.001) compared to the Diversion(-) group. Results from multivariate logistic regression analysis revealed that male gender (OR = 2.354, p = 0.014) was the only independent risk factor associated with AL, while the presence of diversion ileostomy (with vs. without, OR = 1.144, p = 0.686) did not show significant associations. In patients with AL, the onset of the AL was observed to occur later in the Diversion(+) group compared to the Diversion(-) group (7.0 ± 3.3 vs. 3.4 ± 1.4 days, p < 0.001), while the recovery time was significantly shorter (11.3 ± 4.7 vs. 20.3 ± 7.2 days, p < 0.001). Similarly, in Grade C AL patients, the occurence time was delayed in the Diversion(+) group compared to the Diversion(-) group (8.7 ± 4.7 vs. 3.2 ± 1.5 days, p = 0.008), with a shorter recovery time (19.3 ± 2.1 vs. 25.7 ± 6.7 days, p = 0.031). A trend was observed indicating a longer interval before ileostomy restoration in the AL patients compared to the non-AL patients (7.6 ± 4.9 months vs. 5.5 ± 2.9 months, p = 0.079). In addition, DAV (OR = 0.078, p = 0.002) was identified as the only independent factor associated with potential-diversion-benefit in patients with AL, with an optimal cutoff point of 8.6 cm. The utilization of diversion ileostomy as a preventative measure for AL in cases of locally advanced upper-half rectal cancer is not universally endorsed due to potential complications such as small bowel obstruction and wound infection. Nevertheless, in the occurrence of AL, diversion ileostomy may prove advantageous for patient recuperation. Particularly, male patients with a DAV ranging from 7 to 8.6 cm may experience benefits from undergoing diversion ileostomy subsequent to AL in cases of locally advanced upper-half rectal cancer.

Lipid metabolism disorders and albuminuria risk: insights from National Health and Nutrition Examination Survey 2001-2018 and Mendelian randomization analyses.

BACKGROUND: Previous studies have revealed an underlying connection between abnormal lipid metabolism and albuminuria. We aim to investigate the causal relationship between lipid metabolism disorders and the risk of albuminuria from both a population and genetic perspective. METHODS: A cross-sectional study was conducted by using data from the National Health and Nutrition Examination Survey (NHANES) 2001-2018. Multivariable-adjusted logistic regression, subgroup analysis, interaction tests and restricted cubic spline (RCS) were employed statistically. Mendelian randomization (MR) analysis was performed to validate the causal relationship between exposure and outcome to mitigate confounding factors and reverse causation interference. RESULTS: After adjusting for confounders, HDL levels (1.03-2.07 nmol/L) were associated with a reduced risk of albuminuria. In contrast, elevated cholesterol levels (>6.2 nmol/L) and triglyceride levels (>2.3 nmol/L) were associated with an increased risk of albuminuria. Serum triglyceride concentration emerged as a potential risk factor for albuminuria. In MR analysis, a reduced risk of albuminuria was associated with serum total HDL level (IVW: OR = 0.91, 95% CI = 0.86-0.97, p = 0.002). In contrast, cholesterol esters in medium VLDL (IVW: OR = 1.05, 95% CI = 1.00-1.10, p = 0.032), chylomicrons and extremely large VLDL (IVW: OR = 1.08, 95% CI = 1.03-1.14, p = 0.003), and triglycerides (IVW: OR = 1.14, 95% CI = 1.09-1.19, p < 0.001) were associated with an increased risk of albuminuria. CONCLUSION: A causal relationship exists between serum lipid metabolism disorder and albuminuria risk. Further validation of additional blood lipid metabolism biomarkers is imperative for future studies.

Family involvement in preventing delirium in critically ill patients: A systematic review and meta-analysis.

BACKGROUND: Humanized care is a novel concept in the prevention of delirium, with family involvement being a crucial component. Currently, there is controversy regarding the effectiveness of family involvement in preventing delirium among critically ill patients, and the impact of varying levels of family involvement on delirium prevention remains unclear. OBJECTIVE: The purpose of this study is twofold: (a) to investigate the influence of family involvement on delirium among critically ill patients, and (b) to explore the effectiveness of different levels of family involvement in preventing delirium in these patients. DESIGN: A systematic review and meta-analysis. METHODS: From database inception to July 2024, a comprehensive search was conducted across PubMed, EMBASE, CINAHL, Web of Science, and the Cochrane CENTRAL database. Randomized controlled trials that examined family involvement were included in the review. RESULTS: This review included a total of 11 randomized controlled trials, encompassing 3113 critically ill patients. Family involvement was found to significantly reduce the incidence of delirium among critically ill patients (RR = 0.46, 95%CI = 0.31 to 0.69), decrease the duration of delirium (WMD = -2.18, 95 % CI = -4.14 to -0.22), and shorten the length of Intensive Care Unit (ICU) stay (WMD = -1.46, 95%CI = -2.43 to -0.50). Three different levels of family involvement-direct participation in care (RR = 0.37, 95%CI = 0.26 to 0.51), family visits and companionship (RR = 0.56, 95 % CI = 0.25 to 1.25), and indirect participation (RR = 0.77, 95 % CI = 0.29 to 2.07)-varies in their effectiveness for delirium prevention. CONCLUSIONS: Family involvement significantly impacts delirium prevention in critically ill patients. The effectiveness of delirium prevention varies depending on the level of family involvement, with direct participation of family members in caregiving demonstrating a more pronounced effect in reducing delirium incidence among critically ill patients. REGISTRATION: The review protocol has been registered in the PROSPERO International prospective register of systematic reviews (CRD42024563095).

NecroGlobalGCN: Integrating micronecrosis information in HCC prognosis prediction via graph convolutional neural networks.

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) ranks fourth in cancer mortality, underscoring the importance of accurate prognostic predictions to improve postoperative survival rates in patients. Although micronecrosis has been shown to have high prognostic value in HCC, its application in clinical prognosis prediction requires specialized knowledge and complex calculations, which poses challenges for clinicians. It would be of interest to develop a model to help clinicians make full use of micronecrosis to assess patient survival. METHODS: To address these challenges, we propose a HCC prognosis prediction model that integrates pathological micronecrosis information through Graph Convolutional Neural Networks (GCN). This approach enables GCN to utilize micronecrosis, which has been shown to be highly correlated with prognosis, thereby significantly enhancing prognostic stratification quality. We developed our model using 3622 slides from 752 patients with primary HCC from the FAH-ZJUMS dataset and conducted internal and external validations on the FAH-ZJUMS and TCGA-LIHC datasets, respectively. RESULTS: Our method outperformed the baseline by 8.18% in internal validation and 9.02% in external validations. Overall, this paper presents a deep learning research paradigm that integrates HCC micronecrosis, enhancing both the accuracy and interpretability of prognostic predictions, with potential applicability to other pathological prognostic markers. CONCLUSIONS: This study proposes a composite GCN prognostic model that integrates information on HCC micronecrosis, collecting large dataset of HCC histopathological images. This approach could assist clinicians in analyzing HCC patient survival and precisely locating and visualizing necrotic tissues that affect prognosis. Following the research paradigm outlined in this paper, other prognostic biomarker integration models with GCN could be developed, significantly enhancing the predictive performance and interpretability of prognostic model.

Global research trends in postoperative ileus from 2011 to 2023: A scientometric study.

BACKGROUND: Postoperative ileus (POI) is a common complication after abdominal surgery with high morbidity, which hinders patient recovery, prolongs hospitalization, and increases healthcare costs. Therefore, POI has become a global public health challenge. POI triggering is multifactorial. Autonomic and hormonal mechanisms are generally involved in POI pathogenesis. Recent studies have shown that beta adrenergic signaling of enteric glia is a POI trigger. Currently, the status quo, trends, and frontiers of global research on POI remain unclear. AIM: To explore the current status, trends, and frontiers of POI research from 2011 to the present based on bibliometric analysis. METHODS: Publications published on POI research from 2011 to 2023 were retrieved on June 1, 2023, from the Web of Science Core Collection. CiteSpace 6.2.R2 and VOSviewer were used to conduct bibliometric visualization. RESULTS: In total, 778 POI records published from 2011 to 2023 were retrieved. Over the past few decades, the annual cumulative number of related articles has linearly increased, with China and the United States of America contributing prominently. All publications were from 59 countries and territories. China and the University of Bonn were the top contributing country and institution, respectively. Neurogastroenterology & Motility was the most prolific journal. The Journal of Gastrointestinal Surgery had the highest number of citations. Wehner Sven was the most productive author. Burst keywords (e.g., colon, prolonged ileus, acupuncture, paralytic ileus, pathophysiology, rectal cancer, gastrointestinal function, risk) and a series of reference citation bursts provided evidence for the research frontiers in recent years. CONCLUSION: This study demonstrates trends in the published literature on POI and provides new insights for researchers. It emphasizes the importance of multidisciplinary cooperation in the development of this field.

Research on Road Internal Disease Identification Algorithm Based on Attention Fusion Mechanisms.

Internal disease in asphalt pavement is a crucial indicator of pavement health and serves as a vital basis for maintenance and rehabilitation decisions. It is closely related to the optimization and allocation of funds by highway maintenance management departments. Accurate and rapid identification of internal pavement diseases is essential for improving overall pavement quality. This study aimed to identify internal pavement diseases using deep learning algorithms, thereby improving the efficiency of determining internal pavement diseases. In this work, a multi-view recognition algorithm model based on deep learning is proposed, with attention fusion mechanisms embedded both between channels and between views. By comparing and analyzing the training and recognition results of different neural networks, it was found that the multi-view recognition algorithm model based on attention fusion demonstrates the best performance in identifying internal pavement diseases.

Magnetic response and bioaccessibility of toxic metal pollution in outdoor dustfall in Shanghai, China.

Toxic metal content testing, environmental magnetic monitoring and in vitro bioaccessibility experiments each have their own advantages and are often used independently for environmental monitoring, but there are few studies that combine the three to evaluate the hazards of toxic metals to humans. This paper investigated the total content, magnetic properties and bioaccessibility of nine potentially toxic metal elements (Zn, Sn, Pb, Cu, Fe, Ni, Cr, Sr, Mn) in dustfall from different functional zones in Shanghai, China, and systematically compared the related results. The results show that these nine metal elements have different degrees of contamination and enrichment in outdoor dustfall, and their content distribution shows the following trend: Zn > Sn > Pb > Cu > Fe > Ni > Cr > Sr > Mn. Magnetic characteristics χlf and SIRM are mostly positively correlated with the metal elements, indicating that the higher the content of magnetic minerals in the sample, the higher the concentration of metal elements. It was also found that χlf, SIRM, and χARM can well reflect the characteristics of dustfall pollution. The magnetic minerals have a certain degree of enrichment, and the particle size of the magnetic minerals is relatively coarse, mainly in the form of coarse multi-domain and pseudo-single-domain particles, which are largely derived from anthropogenic pollution. The χlf and PM10 concentrations in the precipitation show relatively similar spatial trends, so χlf, SIRM, and χARM can be used as air pollution indices to facilitate the evaluation of metal elements pollution in dustfall. The overall trend in gastric bioaccessibility is Pb > Zn > Mn > Cu > Cr. Due to the increase in the pH of digestive fluid, the bioavailability of toxic metals decreases significantly from the gastric stage to the intestinal stage. χlf, SIRM, and χARM/SIRM are all related to the bioaccessibility of toxic metals in the intestinal stage, so they can be used as toxicity indicators to evaluate the bioaccessibility of toxic metals in dustfall.

Nedl1 knockout impaired the learning and memory of mice.

BACKGROUND: Protein ubiquitination is a common post-translational modification involved in protein degradation and various life processes in cells. NEDL1 is a ubiquitin ligase that is highly expressed primarily in the brain. However, the functions of NEDL1 in social approach/novelty preference, anxiety, learning and memory remain poorly understood. METHODS: Nedl1 knockout mice (Nedl1-/-) and wild-type mice (Nedl1+/+) were tested using three-chamber test, elevated plus maze, and Barnes maze. Then, brain tissue was stained, and blood was collected for metabolic analysis. RESULTS: Compared with Nedl1+/+ mice, Nedl1-/- mice showed no differences in social approach/novelty preference and anxiety behavior. Nedl1-/- mice displayed impaired learning and memory. Nedl1 knockout did not affect the number of neurons and oligodendrocytes in the hippocampus. Astrocytes proliferated in the hippocampus of Nedl1-/- mice. The amino acid metabolism of Nedl1+/+and Nedl1-/- mice is different, especially the increase in proline and tryptophan. CONCLUSION: This study showed that Nedl1 knockout impaired learning and memory, which may be related to astrocyte proliferation and amino acid metabolism change. Nedl1 knockout did not affect social style/novelty preference and anxiety behavior in mice. The preliminary study of NEDL1 in neurobehavioral function could help understand the role of NEDL1 in the nervous system.

ROI constrained optimal online allocation in sponsored search.

Sponsored search plays a major role in the revenue contribution of e-commerce platforms. Advertising systems are designed to maximize platform revenue, but other goals also need to be considered, such as user experience, advertiser utility, and how to achieve the long-term revenue goal. A key component of a sponsored search system is online allocation, which makes real-time decisions to match users' search requests with relevant ad campaigns to maximize platform revenue within constraints such as campaign budgets. Although much progress has been made, most of the research work on allocation problem has focused on satisfying guaranteed deals for display ads, and those challenges for allocation problems in sponsored search are not properly addressed. In this paper, we develop a framework to solve the large-scale sponsored search ad allocation problem, consisting of two main parts. One is an optimization problem solved offline by a parameter-server based architecture, and the other is an online strategy to alleviate the conflict with the auction mechanism during online service. Comprehensive offline evaluation on real production data and online A/B testing on real production system have been made. The experimental results demonstrate that through better allocating user queries to appropriate ads, the proposed model can significantly increase the platform's revenue without sacrificing advertisers' ROI.

Customizing H2O-Poor Electric Double Layer and Boosting Texture Exposure of Zn (101) Plane towards Super-High Areal Capacity Zinc Metal Batteries.

The catastrophic dendrite hyperplasia and parasitic reactions severely impede the future deployment of aqueous Zn-ion batteries. Controlling zinc orientation growth is considered to be an effective method to overcome the aforementioned concerns, especially for regulating the (002) plane of deposited Zn. Unfortunately, Zn (002) texture is difficult to obtain stable cycling under high deposition capacity resulting from its large lattice distortion and nonuniform distribution in electric field. Herein, different from traditional cognition, a crystallization orientation regulation tactic is proposed to boost Zn (101) texture exposure and inhibit zinc dendrite proliferation during plating/stripping. Experimental results and theoretical calculations demonstrate the malate molecules preferentially adsorb on the Zn (002) facet, leading to the texture exposure of distinctive Zn (101) plane. Meanwhile, the -COOH and -OH groups of malate molecules exhibit strong adsorption on the Zn anode surface and chelate with Zn2+, achieving H2O-poor electrical double layer. Very impressively, the multifunctional malate additive enlists zinc anode to survive for 600 h under a harsh condition of 15 mAh cm-2/15 mAh cm-2. Moreover, the symmetric cell harvests highly-reversible cycling life of 6600 h at 5 mA cm-2/1.25 mAh cm-2, remarkably outperforming the ZnSO4 electrolyte. The assembled Zn//MnO2 full cells also demonstrate prominent electrochemical reversibility.

Source-specific probabilistic health risk assessment of dust PAHs in urban parks based on positive matrix factorization and Monte Carlo simulation.

Understanding the health risks of polycyclic aromatic hydrocarbons (PAHs) in dust from city parks and prioritizing sources for control are essential for public health and pollution management. The combination of Source-specific and Monte Carlo not only reduces management costs, but also improves the accuracy of assessments. To evaluate the sources of PAHs in urban park dust and the possible health risks caused by different sources, dust samples from 13 popular parks in Kaifeng City were analyzed for PAHs using gas chromatograph-mass spectrometer (GC-MS). The results showed that the surface dust PAH content in the study area ranged from 332.34 µg·kg-1 to 7823.03 µg·kg-1, with a mean value of 1756.59 µg·kg-1. Nemerow Composite Pollution Index in the study area ranged from 0.32 to 14.41, with a mean of 2.24, indicating that the overall pollution warrants attention. Four pollution sources were identified using the positive matrix factorization (PMF) model: transportation source, transportation-coal and biomass combustion source, coke oven emission source, and petroleum source, with contributions of 33.74%, 25.59%, 22.14%, and 18.54%, respectively. The Monte Carlo cancer risk simulation results indicated that park dust PAHs pose a potential cancer risk to all three populations (children, adult male and adult female). Additionally, the cancer risk for children was generally higher than that for adult males and females, with transportation sources being the main contributor to the carcinogenic risk. Lastly, sensitivity analyses results showed that the toxic equivalent concentration (CS) is the parameter contributing the most to carcinogenic risk, followed by Exposure duration (ED).

Trusted artificial intelligence for environmental assessments: An explainable high-precision model with multi-source big data.

Environmental assessments are critical for ensuring the sustainable development of human civilization. The integration of artificial intelligence (AI) in these assessments has shown great promise, yet the "black box" nature of AI models often undermines trust due to the lack of transparency in their decision-making processes, even when these models demonstrate high accuracy. To address this challenge, we evaluated the performance of a transformer model against other AI approaches, utilizing extensive multivariate and spatiotemporal environmental datasets encompassing both natural and anthropogenic indicators. We further explored the application of saliency maps as a novel explainability tool in multi-source AI-driven environmental assessments, enabling the identification of individual indicators' contributions to the model's predictions. We find that the transformer model outperforms others, achieving an accuracy of about 98% and an area under the receiver operating characteristic curve (AUC) of 0.891. Regionally, the environmental assessment values are predominantly classified as level II or III in the central and southwestern study areas, level IV in the northern region, and level V in the western region. Through explainability analysis, we identify that water hardness, total dissolved solids, and arsenic concentrations are the most influential indicators in the model. Our AI-driven environmental assessment model is accurate and explainable, offering actionable insights for targeted environmental management. Furthermore, this study advances the application of AI in environmental science by presenting a robust, explainable model that bridges the gap between machine learning and environmental governance, enhancing both understanding and trust in AI-assisted environmental assessments.

Promoting smartphone-based keratitis screening using meta-learning: A multicenter study.

OBJECTIVE: Keratitis is the primary cause of corneal blindness worldwide. Prompt identification and referral of patients with keratitis are fundamental measures to improve patient prognosis. Although deep learning can assist ophthalmologists in automatically detecting keratitis through a slit lamp camera, remote and underserved areas often lack this professional equipment. Smartphones, a widely available device, have recently been found to have potential in keratitis screening. However, given the limited data available from smartphones, employing traditional deep learning algorithms to construct a robust intelligent system presents a significant challenge. This study aimed to propose a meta-learning framework, cosine nearest centroid-based metric learning (CNCML), for developing a smartphone-based keratitis screening model in the case of insufficient smartphone data by leveraging the prior knowledge acquired from slit-lamp photographs. METHODS: We developed and assessed CNCML based on 13,009 slit-lamp photographs and 4,075 smartphone photographs that were obtained from 3 independent clinical centers. To mimic real-world scenarios with various degrees of sample scarcity, we used training sets of different sizes (0 to 20 photographs per class) from the HUAWEI smartphone to train CNCML. We evaluated the performance of CNCML not only on an internal test dataset but also on two external datasets that were collected by two different brands of smartphones (VIVO and XIAOMI) in another clinical center. Furthermore, we compared the performance of CNCML with that of traditional deep learning models on these smartphone datasets. The accuracy and macro-average area under the curve (macro-AUC) were utilized to evaluate the performance of models. RESULTS: With merely 15 smartphone photographs per class used for training, CNCML reached accuracies of 84.59%, 83.15%, and 89.99% on three smartphone datasets, with corresponding macro-AUCs of 0.96, 0.95, and 0.98, respectively. The accuracies of CNCML on these datasets were 0.56% to 9.65% higher than those of the most competitive traditional deep learning models. CONCLUSIONS: CNCML exhibited fast learning capabilities, attaining remarkable performance with a small number of training samples. This approach presents a potential solution for transitioning intelligent keratitis detection from professional devices (e.g., slit-lamp cameras) to more ubiquitous devices (e.g., smartphones), making keratitis screening more convenient and effective.

Spin Manipulation of Heterogeneous Molecular Electrocatalysts by an Integrated Magnetic Field for Efficient Oxygen Redox Reactions.

Understanding the spin-dependent activity of nitrogen-coordinated single metal atom (M-N-C) electrocatalysts for oxygen reduction and evolution reactions (ORR and OER) remains challenging due to the lack of structure-defined catalysts and effective spin manipulation tools. Herein, both challenges using a magnetic field integrated heterogeneous molecular electrocatalyst prepared by anchoring cobalt phthalocyanine (CoPc) deposited carbon black on polymer-protected magnet nanoparticles, are addressed. The built-in magnetic field can shift the Co center from low- to high-spin (HS) state without atomic structure modification, affording one-order higher turnover frequency, a 50% increased H2O2 selectivity for ORR, and a ≈4000% magnetocurrent enhancement for OER. This catalyst can significantly minimize magnet usage, enabling safe and continuous production of a pure H2O2 solution for 100 h from a 100 cm2 electrolyzer. The new strategy demonstrated here also applies to other metal phthalocyanine-based catalysts, offering a universal platform for studying spin-related electrochemical processes.

Urban traffic tiny object detection via attention and multi-scale feature driven in UAV-vision.

The unmanned aerial vehicle (UAV) city patrol is of great significance in ensuring the safety of residents' lives and properties, as well as maintaining the normal operation of the city. However, the detection of UAV images faces challenges such as numerous small-scale objects, complex backgrounds, and high requirements for detection speed. In response to these issues, we introduce a Real-time Small Object Detection network in UAV-vision (RTS-Net), tailored for UAV patrols. Initially, we introduce a multiscale feature fusion module (MFFM) designed to augment the expressiveness of features across scales, thereby enhancing the detection of smaller objects. Subsequently, leveraging attention mechanisms, we present the coordinated attention detection module (CADM), which bolsters the detection model's ability to accurately segregate objects from the background in expansive, complex scenarios. Lastly, a lightweight real-time feature extraction module (RFEM) is crafted to diminish model computational complexity and boost inference speed. On the UAV road patrol image dataset we constructed, our proposed method attains a detection accuracy of 89.9 % mAP, breaking previous records. It surpasses all prevailing detection methods, particularly for small-scale objects. Simultaneously, it achieves an inference speed of 163.9 FPS. The experimental results show that RTS-Net can satisfy the accurate and efficient detection of ground objects by various different UAV platforms in different complex scenarios.

Unlocking the potential of LHPP: Inhibiting glioma growth and cell cycle via the MDM2/p53 pathway.

The recurrence of glioma after treatment has remained an intractable problem for many years. Recently, numerous studies have explored the pivotal role of the mouse double minute 2 (MDM2)/p53 pathway in cancer treatment. Lysine phosphate phosphohistidine inorganic pyrophosphate phosphatase (LHPP), a newly discovered tumor suppressor, has been confirmed in numerous studies on tumors, but its role in glioma remains poorly understood. Expression matrices in The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases were analyzed using gene set enrichment analysis (GSEA), revealing significant alterations in the p53 pathway among glioma patients with high LHPP expression. The overexpression of LHPP in glioma cells resulted in a reduction in cell proliferation, migration, and invasive ability, as well as an increase in apoptosis and alterations to the cell cycle. The present study has identified a novel inhibitory mechanism of LHPP against glioma, both in vivo and in vitro. The results demonstrate that LHPP exerts anti-glioma effects via the MDM2/p53 pathway. These findings may offer a new perspective for the treatment of glioma in the clinic.

Exploratory research on the effective chemical basis of tanreqing injection for treating acute lung injury: In vivo, in vitro and in silico.

ETHNOPHARMACOLOGICAL RELEVANCE: Sepsis-induced acute lung injury (ALI) presents with significant morbidity and mortality in clinical settings. Tanreqing Injection (TRQI) has been clinically recommended for the treatment of ALI; however, the specific active chemical constituents remain unidentified. AIM OF THE STUDY: This study aimed to elucidate the potential pharmacologically active components and the underlying mechanisms of TRQI in the treatment of sepsis-induced ALI. MATERIALS AND METHODS: High-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) techniques were employed to identify the effective chemical constituents of TRQI. Additionally, an in vitro study was conducted using Raw264.7 macrophage cells stimulated with lipopolysaccharide (LPS) to evaluate the inhibitory effects of TRQI. An acute lung injury model produced by LPS was intraperitoneal injection in mice to assess the ALI-inhibitory effect of TRQI. The lung's pathological characteristics were examined using hematoxylin and eosin staining. Enzyme-linked immunosorbent assay (ELISA) and QPCR were performed to confirm the pharmaceutical effect. Network pharmacology was employed for mechanistic exploration, incorporating GO, and PPI analyses of targets. Src inhibitor and JNK agonist used to investigate the dependence of associated signaling pathways. RESULTS: Combining pharmacokinetic characteristics, lung first-pass effect and anti-inflammatory effects, the main components of TRQI for treating sepsis induced ALI were narrowed down to seven compounds: chlorogenic acid, scutellarin, wogonoside, oroxyloside, oroxylin A and baicalein. Network pharmacology indicated that Src/JNK signaling pathway, may be the main regulatory pathway for treatment of actue lung injury. Next by using Src inhibitor, Src inhibition partly diminished the protective effects of TRQI in LPS-injected mice. Pretreatment with JNK agonist anisomycin abolished the protective effects of lung injury in vivo. CONCLUSIONS: TRQI is injected, the seven compounds could be presented in vivo, which can improve ALI by inhibiting Src-JNK signaling.

MLKL-mediated endothelial necroptosis drives vascular damage and mortality in systemic inflammatory response syndrome.

The hypersecretion of cytokines triggers life-threatening systemic inflammatory response syndrome (SIRS), leading to multiple organ dysfunction syndrome (MODS) and mortality. Although both coagulopathy and necroptosis have been identified as important factors in the pathogenesis of SIRS, the specific cell types that undergo necroptosis and the interrelationships between coagulopathy and necroptosis remain unclear. In this study, we utilized visualization analysis via intravital microscopy to demonstrate that both anticoagulant heparin and nonanticoagulant heparin (NAH) pretreatment protect mice against TNF-α-induced mortality in SIRS. Moreover, the deletion of Mlkl or Ripk3 resulted in decreased coagulation and reduced mortality in TNF-α-induced SIRS. These findings suggest that necroptosis plays a key role upstream of coagulation in SIRS-related mortality. Furthermore, using a genetic lineage tracing mouse model (Tie2-Cre;Rosa26-tdT), we tracked endothelial cells (ECs) and verified that EC necroptosis is responsible for the vascular damage observed in TNF-α-treated mice. Importantly, Mlkl deletion in vascular ECs in mice had a similar protective effect against lethal SIRS by blocking EC necroptosis to protect the integrity of the endothelium. Collectively, our findings demonstrated that RIPK3-MLKL-dependent necroptosis disrupted vascular integrity, resulting in coagulopathy and multiorgan failure, eventually leading to mortality in SIRS patients. These results highlight the importance of targeting vascular EC necroptosis for the development of effective treatments for SIRS patients.

Effects of intrauterine infusion of autologous platelet-rich plasma gel on endometrial thickness and outcomes of frozen-thawed embryo transfer in women with thin endometrium.

PURPOSE: The purpose of this study is to determine whether intrauterine infusion of autologous platelet-rich plasma (PRP) gel increases endometrial thickness (EMT) and improves the outcomes of frozen-thawed embryo transfer (FET) in women with thin endometrium. METHODS: This study included 111 women (aged 25-44 years) who had thin endometrium. All patients had at least one previous cycle canceled because of thin endometrium or previous embryo transfer cycles and an EMT < 7 mm. Forty-seven women underwent intrauterine infusion of autologous PRP gel on three occasions during endometrial preparation and the remaining women served as controls. The final EMT was measured by ultrasound before the start of the luteal phase, and FET-related outcome parameters were monitored. RESULTS: Mean EMT was greater in women who received PRP gel than in those who did not (6.7 mm vs. 6.3 mm, respectively, p < 0.05). FET was attempted in all women. The 47 women who underwent infusion of PRP had a significantly higher pregnancy rate (18 pregnancies (38.3%), with 17 (36.2%) ongoing) compared with 64 control women (ten pregnancies (18.5%), nine (16.7%) ongoing). However, there was no significant reduction in the miscarriage rate. CONCLUSION: Intrauterine infusion of autologous PRP gel during endometrial preparation for FET cycles can improve the EMT, clinical pregnancy rate, and ongoing pregnancy rate in women with thin endometrium.