IAIH-PG consensus for histological criteria of AIH: Multicentre validation with focus on chronic liver diseases in China.

BACKGROUND AND AIMS: The International AIH Pathology Group (IAIH-PG) put forward the new histological criteria of autoimmune hepatitis (AIH) in 2022, which have not undergone adequate verification. In this study, we verified the applicability of the new histological criteria in the population of Chinese patients with chronic liver disease, comparing it with the simplified criteria. METHODS: The gold standard for diagnosis in all patients was based on histological findings, combined with clinical manifestations and laboratory tests and determined after a follow-up period of at least 3 years. A total of 640 patients with various chronic liver diseases from multiple centres underwent scoring using the new histological criteria and the simplified criteria, comparing their diagnostic performance. RESULTS: In this study, the new histological criteria showed a sensitivity of 73.6% and 100% for likely and possible AIH, with specificities of 100% and 69.0% respectively. The coincidence rates of possible AIH for the new histological criteria, simplified histological criteria and simplified score were 81.7%, 72.8% and 69.7% respectively. For likely AIH, the rates were 89.2%, 75.9% and 65.6% respectively. Based on the new histological criteria, all patients with AIH were correctly diagnosed. Specifically, 73.6% were diagnosed with likely AIH and 26.4% were possible AIH. Additionally, the simplified histological criteria achieved a diagnosis rate of 98.6% for AIH, while the simplified score could only diagnose 53.8% of AIH. CONCLUSIONS: Compared with the simplified score and simplified histological criteria, the sensitivity and specificity of the new histological criteria for AIH were significantly improved. The results indicate that the new histological criteria exhibit high sensitivity and specificity for diagnosing AIH in China.

Integrated biomarker profiling for predicting the response of type 2 diabetes to metformin.

AIM: To explore biomarkers that can predict the response of type 2 diabetes (T2D) patients to metformin at an early stage to provide better treatment for T2D. METHODS: T2D patients with (responders) or without response (non-responders) to metformin were recruited, and their serum samples were used for metabolomic analysis to identify candidate biomarkers. Moreover, the efficacy of metformin was verified by insulin-resistant mice, and the candidate biomarkers were verified to determine the biomarkers. Five different machine learning methods were used to construct the integrated biomarker profiling (IBP) with the biomarkers to predict the response of T2D patients to metformin. RESULTS: A total of 73 responders and 63 non-responders were recruited, and 88 differential metabolites were identified in the serum samples. After being verified in mice, 19 of the 88 were considered as candidate biomarkers. Next, after metformin regulation, nine candidate biomarkers were confirmed as the biomarkers. After comparing five machine learning models, the nine biomarkers were constructed into the IBP for predicting the response of T2D patients to metformin based on the Naïve Bayes classifier, which was verified with an accuracy of 89.70%. CONCLUSIONS: The IBP composed of nine biomarkers can be used to predict the response of T2D patients to metformin, enabling clinicians to start a combined medication strategy as soon as possible if T2D patients do not respond to metformin.

Development and validation of a noninvasive prediction model of autoimmune hepatitis in patients with liver diseases.

BACKGROUND AND AIMS: There is no golden standard for the diagnosis of autoimmune hepatitis which still dependent on liver biopsy currently. So, we developed a noninvasive prediction model to help optimize the diagnosis of autoimmune hepatitis. METHODS: From January 2017 to December 2019, 1739 patients who had undergone liver biopsy were seen in the second hospital of Nanjing, of which 128 were here for consultation. Clinical, laboratory, and histologic data were obtained retrospectively. Multivariable logistic regression analysis was employed to create a nomogram model that predicting the risk of autoimmune hepatitis. Internal and external validation was both performed to evaluate the model. RESULTS: A total of 1288 patients with liver biopsy were enrolled (1184 from the second hospital of Nanjing, the remaining 104 from other centers). After the univariate and multivariate logistic regression analysis, nine variables including ALT, IgG, ALP/AST, ALB, ANA, AMA, HBsAg, age, and gender were selected to establish the noninvasive prediction model. The nomogram model exhibits good prediction in diagnosing autoimmune hepatitis with AUROC of 0.967 (95% CI: 0.776-0.891) in internal validation and 0.835 (95% CI: 0.752-0.919) in external validation. CONCLUSIONS: ALT, IgG, ALP/AST, ALB, ANA, AMA, HBsAg, age, and gender are predictive factors for the diagnosis of autoimmune hepatitis in patients with unexplained liver diseases. The predictive nomogram model built by the nine predictors achieved good prediction for diagnosing autoimmune hepatitis.

3D spheroid HepaRG and fluorescent biphasic tracer for CYP3A4-mediated antibiotic interaction monitoring in sepsis.

Cytochrome P450 3A4 (CYP3A4) is a crucial enzyme in the metabolism of xenobiotics, particularly in drug metabolism interactions (DDIs), making it a significant factor in clinical drug use. However, current assay techniques are both laborious and costly, making it difficult to construct a high-throughput monitoring method that can be used in conjunction with the clinic. This poses certain safety hazards for drug combination. Therefore, it is crucial to develop a synchronized monitoring method for the inhibition and induction of CYP3A4. In this study, we utilized 3D culture technology to develop a HepaRG cells spheroid model. The CYP450 and transporter expression, the albumin secretion, and urea synthesis capacity characteristics were analyzed. The NEN probe was utilized as a tracer molecule for CYP3A4. The fluorescence intensity of metabolites was characterized by laser confocal technique to determine the inhibition and expression of CYP3A4 in the HepaRG cell spheroid model by the antibiotics for sepsis. The results indicate that the HepaRG sphere model successfully possessed the physiological phenotype of the liver, which could be used for drug interaction monitoring. Through positive drug testing, NEN probe was able to achieve bidirectional characterization of CYP3A4 induction and inhibition. The monitoring method described in this paper was successfully applied to drug interaction monitoring of commonly used antibiotics in sepsis patients, which is a convenient and rapid monitoring method. The proposed method offers a new strategy for monitoring CYP3A4-mediated drug-drug interactions with a high-throughput assay, which will help to improve the safety of clinical drug combination.

GLP-1 signaling-regulated SNAP25 is involved in improved insulin secretion in diabetic GK rats after Roux-en-Y gastric bypass surgery.

BACKGROUND: Roux-en-Y gastric bypass surgery (RYGB) improves glucose-stimulated insulin secretion (GSIS) in type 2 diabetes (T2D) patients. SNAP25 plays an essential role in GSIS. Clinical studies indicate that enhanced GLP-1 signaling is an important contributor to the improved ß-cell function in T2D. We aimed to explore whether GLP-1-regulated SNAP25 is involved in the enhanced secretory function of ß-cells in diabetic Goto-Kakizaki (GK) rats after RYGB. METHODS AND RESULTS: RYGB or sham surgery was conducted in GK rats. mRNA and protein expression of SNAP25 was assessed by qPCR and Western blot, respectively. Occupancy of CREB and acetyltransferase CBP and acetylation of histone H3 (ACH3) at the Snap25 promoter were determined using ChIP assay. RYGB led to increased SNAP25 expression and CREB phosphorylation in islets from GK rats. Increased SNAP25 improved GSIS in ß-cells cultured in high glucose conditions. Consistent with increased plasma GLP-1 after RYGB, GLP-1R agonist exendin4 increased SNAP25 expression and CREB phosphorylation in ß-cells. Mechanistically, exendin4 promoted the recruitment of CREB and CBP, thereby increasing ACH3 at the Snap25 promoter. Consistently, inhibition of CBP attenuated the effect of exendin4 on SNAP25 expression. Furthermore, the knockdown of SNAP25 diminished the increase of GSIS potentiated by chronic GLP-1 culture in INS-1 832/13 cells. CONCLUSIONS: Our findings unravel the novel mechanisms of RYGB-enhanced SNAP25 expression in ß-cells, and SNAP25 may contribute to the improved ß-cell secretory function induced by RYGB.

QALY-type preference and willingness-to-pay among end-of-life patients with cancer treatments: a pilot study using discrete choice experiment.

PURPOSE: Quality-adjusted life-year (QALY) is a dominant measurement of health gain in economic evaluations for pricing drugs. However, end-of-life (EoL) patients' preference for QALY gains in life expectancy (LE) and quality of life (QoL) during different disease stages remains unknown and is seldom involved in decision-making. This study aims to measure preferences and willingness-to-pay (WTP) towards different types of QALY gain among EoL cancer patients. METHODS: We attributed QALY gain to four types, gain in LE and QoL, respectively, and during both progression-free survival (PFS) and post-progression survival (PPS). A discrete choice experiment including five attributes (the four QALY attributes and one cost attribute) with three levels each was developed and conducted with 85 Chinese advanced non-small cell lung cancer patients in 2022. All levels were set with QALY gain/cost synthesised from research on anti-lung cancer drugs recently listed by Chinese National Healthcare Security Administration. Each respondent answered six choice tasks in a face-to-face interview. The data were analysed using mixed logit models. RESULTS: Patients valued LE-related QALY gain in PFS most, with a relative importance of 81.8% and a WTP of $43,160 [95% CI 26,751 ~ 59,569] per QALY gain. Respondents consistently preferred LE-related to QoL-related QALY gain regardless of disease stage. Patients with higher income or lower education levels tended to pay more for QoL-related QALY gain. CONCLUSION: Our findings suggest a prioritised resource allocation to EoL-prolonging health technologies. Given the small sample size and large individual heterogeneity, a full-scale study is needed to provide more robust results.

Enhanced adipose-derived stem cells with IGF-1-modified mRNA promote wound healing following corneal injury.

The cornea serves as an important barrier structure to the eyeball and is vulnerable to injuries, which may lead to scarring and blindness if not treated promptly. To explore an effective treatment that could achieve multi-dimensional repair of the injured cornea, the study herein innovatively combined modified mRNA (modRNA) technologies with adipose-derived mesenchymal stem cells (ADSCs) therapy, and applied IGF-1 modRNA (modIGF1)-engineered ADSCs (ADSCmodIGF1) to alkali-burned corneas in mice. The therapeutic results showed that ADSCmodIGF1 treatment could achieve the most extensive recovery of corneal morphology and function when compared not only with simple ADSCs but also IGF-1 protein eyedrops, which was reflected by the healing of corneal epithelium and limbus, the inhibition of corneal stromal fibrosis, angiogenesis and lymphangiogenesis, and also the repair of corneal nerves. In vitro experiments further proved that ADSCmodIGF1 could more significantly promote the activity of trigeminal ganglion cells and maintain the stemness of limbal stem cells than simple ADSCs, which were also essential for reconstructing corneal homeostasis. Through a combinatorial treatment regimen of cell-based therapy with mRNA technology, this study highlighted comprehensive repair in the damaged cornea and showed the outstanding application prospect in the treatment of corneal injury.

A systematic review on the appropriate discounting rates for the economic evaluation of gene therapies: whether a specific approach is justified to tackle the challenges?

OBJECTIVES: Discounting the cost and effect for health intervention is a controversial topic over the last two decades. In particular, the cost-effectiveness of gene therapies is especially sensitive to the discount rate because of the substantial delay between the upfront cost incurred and long-lasing clinical benefits received. This study aims to investigate the influence of employing alternative discount rates on the incremental cost-effectiveness ratio (ICER) of gene therapies. METHODS: A systematic review was conducted to include health economic evaluations of gene therapies that were published until April 2023. RESULTS: Sensitivity or scenario analysis indicated that discount rate represented one of the most influential factors for the ICERs of gene therapies. Discount rate for cost and benefit was positively correlated with the cost-effectiveness of gene therapies, that is, a lower discount rate significantly improves the ICERs. The alternative discount rate employed in some cases could be powerful to alter the conclusion on whether gene therapies are cost-effective and acceptable for reimbursement. CONCLUSIONS: Although discount rate will have substantial influence on the ICERs of gene therapies, there lacks solid evidence to justify a different discounting rule for gene therapies. However, it is proposed that the discount rate in the reference case should be updated to reflect the real-time preference, which in turn will affect the ICERs and reimbursement of gene therapies more profoundly than conventional therapies.

3D-QSAR and Molecular Dynamics Study of Isoxazole Derivatives to Identify the Structural Requirements for Farnesoid X Receptor (FXR) Agonists.

The farnesoid X receptor (FXR) has been recognized as a potential drug target for the treatment of non-alcoholic fatty liver disease (NAFLD). FXR agonists benefit NAFLD by modulating bile acid synthesis and transport, lipid metabolism, inflammation, and fibrosis pathways. However, there are still great challenges involved in developing safe and effective FXR agonists. To investigate the critical factors contributing to their activity on the FXR, 3D-QSAR molecular modeling was applied to a series of isoxazole derivatives, using comparative molecular field analysis (CoMFA (q2 = 0.664, r2 = 0.960, r2pred = 0.872)) and comparative molecular similarity indices analysis (CoMSIA (q2 = 0.706, r2 = 0.969, r2pred = 0.866)) models, which demonstrated strong predictive ability in our study. The contour maps generated from molecular modeling showed that the presence of hydrophobicity at the R2 group and electronegativity group at the R3 group in these compounds is crucial to their agonistic activity. A molecular dynamics (MD) simulation was carried out to further understand the binding modes and interactions between the FXR and its agonists in preclinical or clinical studies. The conformational motions of loops L: H1/H2 and L: H5/H6 in FXR-ligand binding domain (LBD) were crucial to the protein stability and agonistic activity of ligands. Hydrophobic interactions were formed between residues (such as LEU287, MET290, ALA291, HIS294, and VAL297) in helix H3 and ligands. In particular, our study found that residue ARG331 participated in salt bridges, and HIS447 participated in salt bridges and hydrogen bonds with ligands; these interactions were significant to protein-ligand binding. Eight new potent FXR agonists were designed according to our results, and their activities were predicted to be better than that of the first synthetic FXR agonist, GW4064.

Effects of chopping temperature on the gel quality of silver carp (Hypophthalmichthys molitrix) surimi: insight from gel-based proteomics.

BACKGROUND: Morden advanced analytical tools offer valuable information into the understanding of molecular mechanism of traditional food processing. Chopping temperature is well-known to affect the surimi gel quality of silver carp, but the detailed molecular mechanism is not very clear. In this study, a gel-based proteomics was performed on the extracted surimi proteins under different chopping temperatures (0, 5, 10, and 25 °C) along with other physicochemical characterization of surimi proteins and gels. RESULTS: With increased chopping temperature, protein extractability (in 3% sodium chloride) generally decreased, while the extracted protein generally exhibited larger surface hydrophobicity, reduced intrinsic fluorescence intensity, lower sulfhydryl content. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) profile of extracted protein showed a clear difference at 25 °C when compared with the other three temperatures, and more protein fragmentation occurred. Proteomic analysis of selected bands indicated that major myofibrillar proteins react differently with chopping temperatures, especially at 25 °C. The selected bands contained a variety of other proteins or their fragments, including adenosine triphosphate (ATP) synthase, glyceraldehyde-3-phosphate dehydrogenase, glucose-6-phosphate isomerase, heat shock protein, parvalbumin, collagen, and so forth. For the surimi gel, water-holding capacity and gel strength generally decreased with increased chopping temperature. CONCLUSION: Our results suggested that chopping at 0-10 °C is acceptable for the production of silver carp surimi in terms of gel strength and water-holding capacity. However, a chopping temperature near 0 °C led to less protein oxidation and denaturation. The inferior gel quality at 25 °C is linked to a decreased concentration of extracted protein and degradation of major myofibrillar protein, the latter is likely crosslinked with sarcoplasmic proteins. © 2024 Society of Chemical Industry.

The effect of fine particulate matter (PM2.5) pollution on health inequality: an intergenerational perspective.

Air pollution poses a serious challenge to public health and simultaneously exacerbating regional & intergenerational health inequality. This research introduces PM2.5 pollution into the intergenerational health transmission model, and estimates its impact on health inequality in China using Ordered Logit Regression (OLR) and Multi-scale Geographically Weighted Regression (MGWR) model. The results indicate that PM2.5 pollution exacerbate the intergenerational health inequality, and its impacts show inconsistency across family income levels, parental health insurance status, and area of residence. Specifically, it is more difficult for offspring in low-income families to escape from the influence of unhealthy family to become upwardly mobile. Additionally, this health inequality is more significant in households in which at least one parent does not have health insurance. Moreover, the intergenerational solidification caused by PM2.5 pollution is higher in the east and lower in the west. Both the PM2.5 level and solidification effect are high in Beijing-Tianjin-Hebei region, Yangtze River Delta region and central areas of China, which is the focus of air pollution management. These findings suggest that more emphasis should be placed on family-based health promotion. In areas with high PM2.5 pollution levels, resources, subsidies and air pollution protection should be provided for less healthy families with lower incomes and no health insurance.

Constructing Dual Cocatalysts of Ni2P-NiS-Decorated TiO2 for Boosting Photocatalytic H2 Evolution.

The loading of cocatalysts is an effective approach to optimize the separation of carriers during photocatalytic processes. Among them, cocatalysts often work independently during the photocatalytic production of H2. However, an investigation of the synergistic effect of dual cocatalysts is beneficial for further promoting photocatalytic H2 production activity. In this work, dual cocatalyst Ni2P-NiS-modified TiO2 nanosheets were fabricated through a solvent evaporation method. The investigation indicates that Ni2P-NiS can widen the light absorption range and reduce the contact angle between TiO2 and water from 26.71 to 8.27°, which facilitates the adsorption of water molecules. Besides, the introduction of Ni2P-NiS can decrease the overpotential of H2 evolution and induce more electrochemically active surface area. The photocatalytic tests show that the H2 production rate of 15% Ni2P-NiS/TiO2 can reach up to 4891.6 µmol·g-1·h-1, which is 30.2, 4.4, and 1.3 times than pure TiO2 (161.8 µmol·g-1·h-1), 15% Ni2P/TiO2 (1112.1 µmol·g-1·h-1), and 15% NiS/TiO2 (3678.1 µmol·g-1·h-1), respectively. The enhancement mechanism of photocatalytic H2 production is attributed to the Schottky barrier effect between Ni2P-NiS nanoparticles and TiO2 nanosheets, which can enormously promote the interface charge separation and transfer, and enhance the kinetics of H2 production. This work provides a potential strategy for enhancement H2 production using appropriate dual cocatalyst-decorated semiconductor materials.

iPADD: A Computational Tool for Predicting Potential Antidiabetic Drugs Using Machine Learning Algorithms.

Diabetes mellitus is a chronic metabolic disease, which causes an imbalance in blood glucose homeostasis and further leads to severe complications. With the increasing population of diabetes, there is an urgent need to develop drugs to treat diabetes. The development of artificial intelligence provides a powerful tool for accelerating the discovery of antidiabetic drugs. This work aims to establish a predictor called iPADD for discovering potential antidiabetic drugs. In the predictor, we used four kinds of molecular fingerprints and their combinations to encode the drugs and then adopted minimum-redundancy-maximum-relevance (mRMR) combined with an incremental feature selection strategy to screen optimal features. Based on the optimal feature subset, eight machine learning algorithms were applied to train models by using 5-fold cross-validation. The best model could produce an accuracy (Acc) of 0.983 with the area under the receiver operating characteristic curve (auROC) value of 0.989 on an independent test set. To further validate the performance of iPADD, we selected 65 natural products for case analysis, including 13 natural products in clinical trials as positive samples and 52 natural products as negative samples. Except for abscisic acid, our model can give correct prediction results. Molecular docking illustrated that quercetin and resveratrol stably bound with the diabetes target NR1I2. These results are consistent with the model prediction results of iPADD, indicating that the machine learning model has a strong generalization ability. The source code of iPADD is available at https://github.com/llllxw/iPADD.

Transjugular liver biopsy: enlarge the indications for liver biopsy with reliable diagnostic quality.

BACKGROUND: Complications and diagnostic efficiency for liver biopsy are main concerns for clinicians. This study aimed to assess the safety and efficacy of transjugular liver biopsy (TJLB) compared with percutaneous liver biopsy (PLB) when patients had equal level of liver function and number of passes, using propensity score matching (PSM). METHODS: The clinical and pathological data of patients who received TJLB or PLB between January 2012 and October 2022 were collected. Matching factors included age, gender, cirrhosis, portal hypertension, liver function, creatinine, number of passes, hemodialysis, history of anti-coagulation and anti-platelet, and comorbidities. Coagulation indexes were not considered as matching factors due to different indications of the two techniques. RESULTS: 2711 PLBs and 30 TJLBs were evaluated. By PSM, 75 patients (50 PLBs, 25 TJLBs) were matched. The complication rates for TJLB and PLB were 4.0% (1/25) and 10.0% (5/50) (P > 0.05). Two PLBs had hepatic hemorrhage, one of which required only close monitoring (Grade 1) and the other needed hemostasis and rehydration therapy (Grade 2). The other 3 cases presented with mild abdominal pain (Grade 1). And only one TJLB presented with mild pain. The median number of complete portal tracts were 6.0 and 10.0 for TJLBs and PLBs (P < 0.05). Moreover, the median length of sample for TJLBs and PLBs were 10.0 and 16.5 mm (P < 0.05). The diagnostic efficiency of hepatopathy of unknown etiology of TJLB versus PLB groups before and after matching were 96.4% vs. 94.1% and 95.7% vs. 93.2%, respectively (P > 0.05). CONCLUSION: TJLB is an effective invasive diagnostic procedure that expands indications for liver biopsy with reliable diagnostic quality.

Plasma metabolite profiles identify pediatric medulloblastoma and other brain cancer.

Medulloblastoma is a malignancy of the central nervous system that occurs most frequently in childhood and is often difficult to diagnose due to its similarities to conventional imaging findings for other pediatric intracranial tumors such as astrocytomas and ependymomas. The purpose of this study was to identify new metabolites and differential metabolic pathways by analyzing the significantly different metabolites present in the plasma of children with medulloblastoma in comparison with those with other intracranial tumors. Plasma was collected from 37 children with medulloblastoma and 34 children with other intracranial tumors. Targeted and non-targeted metabolomics based on ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) analyses were performed to determine metabolic changes in pediatric medulloblastomas versus other intracranial tumors. Based on multivariate statistical analysis and regression models, we identified differential metabolites in the plasma and investigated different metabolic pathways. A total of 61 differential metabolites in the plasma of children with medulloblastoma were identified by non-targeted metabolomics analysis. In addition, targeted metabolomics analysis identified four differential amino acids, thus allowing us to establish a diagnostic model for children with medulloblastoma. Metabolic pathway analysis showed that there were significant differences in patients with medulloblastoma in terms of glycerophospholipid and α-linolenic acid metabolism pathways as well as several amino acid metabolism pathways (phenylalanine, tyrosine, and tryptophan biosynthesis). We identified differential profiles of key plasma metabolites between children with medulloblastoma and other forms of intracranial tumor, thus providing a basis for identifying early diagnostic markers of medulloblastoma and new therapeutic targets and strategies.

Analysis of water quality indexes and their relationships with vegetation using self-organizing map and geographically and temporally weighted regression.

Natural vegetation has been proved to promote water purification in previous studies, while the relevant laws has not been excavated systematically. This research explored the relationships between vegetation cover and water quality indexes in Liaohe River Basin in China combined with self-organizing map (SOM) and geographically and temporally weighted regression (GTWR) innovatively and systematically based on the distributing heterogeneity of water quality conditions. Results showed that the central and northeast regions of the study area had serious organic and nutrient pollution, which needed targeted treatment. And SOM verified that high vegetation coverage with retention potential of organic and inorganic pollutants as well as nutrients improved water quality to some degree, while the excessive discharges of pollutants still had serious threats to nearby water environment despite the purification function of vegetation. GTWR indicated that the waterside vegetation was beneficial for dissolved oxygen increasing and contributed to the decreasing of organic pollutants and inorganic pollutants with reducibility. Natural vegetation also obsorbed nutrients like TN and TP to some degree. However, the retential potential of nitrogen and organic pollutants became not obvious when there were heavy pollution, which demonstrated that pollution sources should be controlled despite the purification function of vegetation. This study implied that natural vegetation purified water quality to some degree, while this function could not be revealed when there was too heavy pollution. These findings underscore that the pollutant discharge should be controlled though the natural vegetation in ecosystem promoted the purification of water bodies.

Predictive Ability of Systemic Inflammation Response Index for the Risk of Pneumonia in Patients with Acute Ischemic Stroke.

INTRODUCTION: Several studies have examined the crucial role of inflammatory indexes such as the ratio of monocyte and lymphocyte (MLR), systemic-immune-inflammation-index, and the ratio of neutrophil and lymphocyte (NLR) in stroke-associated pneumonia (SAP). However, the function of the systemic inflammation response index (SIRI) in SAP is not known. This study investigated whether SIRI at admission could predict the incidence of SAP in patients with acute ischemic stroke (AIS). PATIENTS AND METHODS: 2,802 AIS patients collected from 2013 to 2021 were divided into the SAP and non-SAP groups. The predictive performance of SIRI in SAP was evaluated by the receiver operating characteristic curve. Multivariate regression analysis and the restricted cubic spline (RCS) were performed to explore the relationship between SIRI and SAP risk. RESULTS: The SIRI at admission in SAP patients was significantly higher than that in non-SAP patients (median [IQR]: 3.75 [2.05, 6.99] vs. 1.51 [0.94, 2.62], p < 0.001). SIRI had a predictive ability for predicting the incidence of SAP with area under the curve of 0.757, better than NLR and MLR (both p < 0.05). SIRI ≥2.74 was an independent risk factor for the incidence of SAP (odds ratio: 5.82, 95% confidence interval: 4.54, 7.49, p < 0.001). The RCS model showed an increasing trend of the SAP risk with the increase of SIRI. CONCLUSION: SIRI showed a good predictive value for SAP. In clinical practice, AIS patients with high SIRI levels (SIRI ≥2.74) should be aware of the risk of SAP.

Identification of genes related to growth traits from transcriptome profiles of duck breast muscle tissue.

The growth and development of duck skeletal muscle is an important economic trait that is genetically regulated. The internal mechanism underlying the regulation of skeletal muscle growth and development in ducks remains unclear. The purpose of this study was to identify candidate genes related to the growth of duck skeletal muscle. RNA-sequencing technology was used to compare the transcriptome of duck breast muscles in an F2 population with the high breast muscle rate (HB) and the low breast muscle rate (LB). A total of 14,522 genes were confirmed to be expressed in the breast muscle, and 173 differentially expressed genes (DEGs) were identified between the HB and LB groups. Functional analysis showed that these DEGs were mainly involved in biological processes and pathways of fat metabolism and muscle growth, especially the FABP3 and MYL4 involved in the PPAR signaling pathway and cardiac muscle contraction pathway. These findings deepened our understanding of the molecular mechanisms involved in muscle growth in ducks and provided a theoretical basis for improving duck production and breeding of ducks.

Comparison of attitudes toward the medical student-led community health education service to support chronic disease self-management among students, faculty and patients.

BACKGROUND: Shortage of health professionals is one of the most important barriers for community health centers to provide quality primary care for chronic disease patients especially after the outbreak of COVID-19. Under such condition, medical students have been well-accepted as a force multiplier for community-based health service. Community service learning (CSL) based on medical student-led community health education service to support chronic disease self-management might be a valuable interactive learning tool in medical education. This study compared the attitudes toward medical student-led community health education service to support chronic disease self-management among three stakeholder roles in CSL, including medical students, faculty and patients. METHODS: This cross-sectional comparative survey was conducted using a self-developed questionnaire among the convenience samples of undergraduate students and faculty members from the Medical College, Wuhan University of Science and Technology, as well as patient volunteers with chronic diseases recruited from a free on-site clinic offered by a community health center. Attitudes toward medical student-led community health education service to support chronic disease self-management were compared among students, faculty and patients. RESULTS: A total of 515 valid questionnaires were obtained (342 were collected from medical students, 54 from faculty respondents, and 119 from patients). Overall positive attitudes toward medical student-led community health education service to support chronic disease self-management were positive. Among the three stakeholder roles, faculty and patients were more supportive of the current inadequate level of primary care provision within the community. However, patient respondents showed more negative attitudes towards using resources in higher medical education system to provide support for primary care practice, and participating in the medical student-led community health education service to support chronic disease self-management, and were most skeptical about the medical students' competency in supporting chronic disease self-management with their professional knowledge and skills. The educational value of CSL for medical undergraduates and the role of faculty instructors were most appreciated by faculty respondents. Additionally, > 62 years old and > 2 kinds of chronic diseases per patient exhibited significant correlations with positive patients' attitudes. CONCLUSIONS: Medical students, faculty and patients had overall positive attitudes towards CSL based on medical student-led community health education service to support chronic disease self-management. However, more should be done to create higher expectations and enthusiasm of patients about CSL.

IMB-BZ as an Inhibitor Targeting ESX-1 Secretion System to Control Mycobacterial Infection.

BACKGROUND: Resistance to anti-tuberculosis (TB) drugs is a major issue in TB control, and demands the discovery of new drugs targeting the virulence factor ESX-1. METHODS: We first established a high-throughput screen (HTS) assay for the discovery of ESX-1 secretion inhibitors. The positive hits were then evaluated for the potency of diminishing the survival of virulent mycobacteria and reducing bacterial virulence. We further investigated the probability of inducing drug resistance and the underlying mechanism using mycobacterial protein fragment complementation. RESULTS: A robust HTS assay was developed to identify small molecules that inhibit ESX-1 secretion without impairing bacterial growth in vitro. A hit named IMB-BZ specifically inhibits the secretion of CFP-10 and reduces virulence in an ESX-1-dependent manner, therefore resulting in significant reduction in intracellular and in vivo survival of mycobacteria. Blocking the CFP-10-EccCb1 interaction directly or indirectly underlies the inhibitory effect of IMB-BZ on the secretion of CFP-10. Importantly, our finding shows that the ESX-1 inhibitors pose low risk of drug resistance development by mycobacteria in vitro as compared with traditional anti-TB drugs, and exhibit high potency against chronic mycobacterial infection. CONCLUSIONS: Targeting ESX-1 may lead to the development of novel therapeutics for tuberculosis. IMB-BZ holds the potential for future development into a new anti-TB drug.