Efficacy of jing Si herbal tea in functional dyspepsia: A double-blind, randomized, placebo-controlled study.

BACKGROUND: Functional dyspepsia (FD) is prevalent worldwide and is associated with gastrointestinal inflammation, mucosal anomalies, and shifts in microbiota metabolites like short chain fatty acids. This study assesses the efficacy of Jing Si herbal tea (JSHT) in alleviating FD symptoms, psychological distress, and influencing metabolites. METHODS: Adults with FD based on Rome IV criteria were included. Participants underwent physical and psychological evaluations, pre-treatment blood sampling, and were randomly assigned to JSHT or placebo groups for four weeks. Post-treatment, evaluations and Liquid Chromatography-Mass Spectrometry for gut metabolites were done. Successful response was defined by a 50% symptom reduction. Symptom intensity, sleep, depression, anxiety, and stress were measured using questionnaires. RESULTS: 26 patients (median age 55.5 years, range 22-77 years, 60.6% female) were studied. Both JSHT and placebo groups were similar at baseline. JSHT showed a higher response rate (69.2%) than placebo (23.1%, P = 0.018). JSHT recipients experienced notable reduction in upper gastrointestinal symptoms and anxiety (P = 0.005; P = 0.037). Increased serum butyrate was observed in improved patients (P = 0.01), whereas no major changes were detected in the placebo group. CONCLUSION: Four weeks of JSHT treatment ameliorated FD symptoms and anxiety, potentially linked to increased serum butyrate. This study suggests that JSHT has potential therapeutic role in patients with FD.

Clinical outcomes and predictors in patients with acute on chronic liver failure in Southern Taiwan.

BACKGROUND/AIMS: The study is to analyze the clinical characteristics and identify prognostic factors as well as evaluate predictive models in patients with acute-on-chronic liver failure (ACLF) from Southern Taiwan. METHODS: The cohort study was conducted using the Chang Gung Research Database. We included patients with ACLF based on the definition provided by the Asian-Pacific Association for the Study of the Liver ACLF Research Consortium (AARC). RESULTS: A total of 231 patients diagnosed with ACLF were included in this study, out of which 26 patients underwent liver transplantation (LT). The primary cause of ACLF was acute exacerbation of hepatitis B virus (HBV) in 68.4% of cases and followed by severe alcoholic hepatitis (20.8%). Among LT-free patients, the 28-day mortality rate was observed to be 31%. Older age, higher INR and ammonia levels, and the presence of severe hepatic encephalopathy on 3-6 days of treatment were independent predictors of 28-day mortality. The CLIF-C ACLF and COSSH-ACLF scores, evaluated on 3-6 days, demonstrated the highest predictive performance for 28-day mortality. The optimal cut-off values for the CLIF-C ACLF and COSSH-ACLF scores were determined to be 47 and 6.3, respectively. Patients with CLIF-C ACLF score >63 or COSSH-ACLF score >8.1 experienced 100% mortality by day 28. CONCLUSIONS: The CLIF-C ACLF and COSSH-ACLF scores, evaluated within one week after treatment, exhibit strong predictive capabilities for short-term mortality in ACLF patients. These models are valuable tools for guiding timely decision-making, including the consideration of liver transplantation or withdrawal from treatment.

Genetic polymorphisms in FABP2, CYP2E1, and TP53 genes are potentially associated with colorectal cancer susceptibility.

Colorectal cancer (CRC) is among the most prevalent cancers with a high mortality rate. Both genetic and environmental factors contribute to CRC development. This study aimed to assess the association of single nucleotide polymorphisms (SNPs) in the fatty acid binding protein-2 (rs1799883), Cytochrome P450 2E1 (rs3813865), TP53 (rs1042522), and Murine double minute 2 (rs1042522) genes with CRC. A cross-sectional case-control study was conducted at the Institute of Molecular Biology and Biotechnology from May 2020 to March 2021, involving CRC patients (N = 100) and controls (N = 100) recruited from the Multan district in Pakistan. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and tetra-primer amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) were employed to investigate the studied SNPs. The association of SNPs in all genes with CRC was examined either individually or in various combinations. Genotypes at three SNPs, rs1799883 in FABP2, rs3813865 in CYP2E1, and rs1042522 in TP53, were found to be associated with the development of CRC, while rs1042522 in MDM2 was not. Patients who were married, smoked, lacked exercise habits or had a family history of CRC were at a greater risk of acquiring the disease. FABP2 gene rs1799883, CYP2E1 gene rs3813865, and TP53 gene rs1042522 polymorphisms are significant in the development of CRC in Pakistani participants.

THE LYON SCORE: A NOVEL REFLUX SCORING SYSTEM BASED ON THE LYON CONSENSUS 2.0 THAT ASSOCIATES WITH TREATMENT OUTCOME FROM ANTI-REFLUX THERAPY.

BACKGROUND: We explored if a score derived from parameters from esophageal testing could increase confidence in diagnosing conclusive gastroesophageal reflux disease and in predicting outcome. METHODS: A prediction score was developed using metrics based on Lyon Consensus 2.0 thresholds extracted from endoscopy and pH-impedance monitoring. The Lyon score was the sum of weighted scores derived from a logistic regression model. The outcome was response to anti-reflux therapy, defined as 50% reduction in global symptoms on validated questionnaires. An existing database of endoscopy-negative patients with typical reflux symptoms undergoing esophageal testing from two centers (Europe and US) constituted the developmental cohort, while two separate cohorts (Europe and Asia) served as validation cohorts. Receiver operating characteristics (ROC) analysis determined performance of the Lyon score in predicting treatment response. RESULTS: In 281 developmental cohort patients (median age 53 years, 57.7% female), the Lyon score demonstrated an AUC of 0.819 in predicting 50% symptom improvement (p<0.001) on ROC, with an optimal threshold of 6.25 (sensitivity 81.2%, specificity 73.4%). Of the individual components, only acid exposure time (AUC 0.799, p<0.001), mean nocturnal baseline impedance (AUC 0.785, p<0.001) and reflux episodes (AUC 0.764, p<0.001) approached the Lyon score performance. The Lyon score segregated treatment response in both the European (AUC 0.908, p<0.001) and Asian validation cohorts (AUC 0.637, p<0.001), and outperformed the DeMeester score in sensitivity for predicting outcome in the developmental and Asian validation cohorts. CONCLUSION: The novel Lyon score segregates reflux phenotypes, and identifies likelihood of symptom response from antireflux therapy.

Evaluating a Natural Language Processing-Driven, AI-Assisted International Classification of Diseases, 10th Revision, Clinical Modification, Coding System for Diagnosis Related Groups in a Real Hospital Environment: Algorithm Development and Validation Study.

BACKGROUND: International Classification of Diseases codes are widely used to describe diagnosis information, but manual coding relies heavily on human interpretation, which can be expensive, time consuming, and prone to errors. With the transition from the International Classification of Diseases, Ninth Revision, to the International Classification of Diseases, Tenth Revision (ICD-10), the coding process has become more complex, highlighting the need for automated approaches to enhance coding efficiency and accuracy. Inaccurate coding can result in substantial financial losses for hospitals, and a precise assessment of outcomes generated by a natural language processing (NLP)-driven autocoding system thus assumes a critical role in safeguarding the accuracy of the Taiwan diagnosis related groups (Tw-DRGs). OBJECTIVE: This study aims to evaluate the feasibility of applying an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM), autocoding system that can automatically determine diagnoses and codes based on free-text discharge summaries to facilitate the assessment of Tw-DRGs, specifically principal diagnosis and major diagnostic categories (MDCs). METHODS: By using the patient discharge summaries from Kaohsiung Medical University Chung-Ho Memorial Hospital (KMUCHH) from April 2019 to December 2020 as a reference data set we developed artificial intelligence (AI)-assisted ICD-10-CM coding systems based on deep learning models. We constructed a web-based user interface for the AI-assisted coding system and deployed the system to the workflow of the certified coding specialists (CCSs) of KMUCHH. The data used for the assessment of Tw-DRGs were manually curated by a CCS with the principal diagnosis and MDC was determined from discharge summaries collected at KMUCHH from February 2023 to April 2023. RESULTS: Both the reference data set and real hospital data were used to assess performance in determining ICD-10-CM coding, principal diagnosis, and MDC for Tw-DRGs. Among all methods, the GPT-2 (OpenAI)-based model achieved the highest F1-score, 0.667 (F1-score 0.851 for the top 50 codes), on the KMUCHH test set and a slightly lower F1-score, 0.621, in real hospital data. Cohen κ evaluation for the agreement of MDC between the models and the CCS revealed that the overall average κ value for GPT-2 (κ=0.714) was approximately 12.2 percentage points higher than that of the hierarchy attention network (κ=0.592). GPT-2 demonstrated superior agreement with the CCS across 6 categories of MDC, with an average κ value of approximately 0.869 (SD 0.033), underscoring the effectiveness of the developed AI-assisted coding system in supporting the work of CCSs. CONCLUSIONS: An NLP-driven AI-assisted coding system can assist CCSs in ICD-10-CM coding by offering coding references via a user interface, demonstrating the potential to reduce the manual workload and expedite Tw-DRG assessment. Consistency in performance affirmed the effectiveness of the system in supporting CCSs in ICD-10-CM coding and the judgment of Tw-DRGs.

Artificial intelligence-clinical decision support system for enhanced infectious disease management: Accelerating ceftazidime-avibactam resistance detection in Klebsiella pneumoniae.

BACKGROUND: Effective and rapid diagnostic strategies are required to manage antibiotic resistance in Klebsiella pneumonia (KP). This study aimed to design an artificial intelligence-clinical decision support system (AI-CDSS) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and machine learning for the rapid detection of ceftazidime-avibactam (CZA) resistance in KP to improve clinical decision-making processes. METHODS: Out of 107,721 bacterial samples, 675 specimens of KP with suspected multi-drug resistance were selected. These specimens were collected from a tertiary hospital and four secondary hospitals between 2022 and 2023 to evaluate CZA resistance. We used MALDI-TOF MS and machine learning to develop an AI-CDSS with enhanced speed of resistance detection. RESULTS: Machine learning models, especially light gradient boosting machines (LGBM), exhibited an area under the curve (AUC) of 0.95, indicating high accuracy. The predictive models formed the core of our newly developed AI-CDSS, enabling clinical decisions quicker than traditional methods using culture and antibiotic susceptibility testing by a day. CONCLUSIONS: The study confirms that MALDI-TOF MS, integrated with machine learning, can swiftly detect CZA resistance. Incorporating this insight into an AI-CDSS could transform clinical workflows, giving healthcare professionals immediate, crucial insights for shaping treatment plans. This approach promises to be a template for future anti-resistance strategies, emphasizing the vital importance of advanced diagnostics in enhancing public health outcomes.

Targeting Yezo Virus Structural Proteins for Multi-Epitope Vaccine Design Using Immunoinformatics Approach.

A novel tick-borne orthonairovirus called the Yezo virus (YEZV), primarily transmitted by the Ixodes persulcatus tick, has been recently discovered and poses significant threats to human health. The YEZV is considered endemic in Japan and China. Clinical symptoms associated with this virus include thrombocytopenia, fatigue, headache, leukopenia, fever, depression, and neurological complications ranging from mild febrile illness to severe outcomes like meningitis and encephalitis. At present, there is no treatment or vaccine readily accessible for this pathogenic virus. Therefore, this research employed an immunoinformatics approach to pinpoint potential vaccine targets within the YEZV through an extensive examination of its structural proteins. Three structural proteins were chosen using specific criteria to pinpoint T-cell and B-cell epitopes, which were subsequently validated through interferon-gamma induction. Six overlapping epitopes for cytotoxic T-lymphocytes (CTL), helper T-lymphocytes (HTL), and linear B-lymphocytes (LBL) were selected to construct a multi-epitope vaccine, achieving a 92.29% coverage of the global population. These epitopes were then fused with the 50S ribosomal protein L7/L12 adjuvant to improve protection against international strains. The three-dimensional structure of the designed vaccine construct underwent an extensive evaluation through structural analysis. Following molecular docking studies, the YEZV vaccine construct emerged as a candidate for further investigation, showing the lowest binding energy (-78.7 kcal/mol) along with favorable physiochemical and immunological properties. Immune simulation and molecular dynamics studies demonstrated its stability and potential to induce a strong immune response within the host cells. This comprehensive analysis indicates that the designed vaccine construct could offer protection against the YEZV. It is crucial to conduct additional in vitro and in vivo experiments to verify its safety and effectiveness.

Impact of NHI copayment adjustments on healthcare seeking behavior: the mediating role of health facility identification.

OBJECTIVE: This study investigates the impact of healthcare consumers' involvement, price perception, and attitude toward National Health Insurance (NHI) copayment adjustments on their healthcare-seeking behavior, focusing on the mediating role of health facility identification. METHODS: A questionnaire survey was conducted among outpatient customers in Taiwan from October 2023 to March 2024, resulting in 746 valid responses. The survey included demographic variables, involvement, price perception, attitude, health facility identification, and healthcare-seeking behavior. Data were analyzed using descriptive statistics, correlation analysis, and multiple regression analysis with SPSS 20.0. RESULTS: The study found that involvement, price perception, and attitude significantly influence healthcare-seeking behavior. Health facility identification was identified as a significant mediator in the relationship between copayment perception and healthcare-seeking behavior. The regression analysis also highlighted the impact of demographic factors such as age, education level, marital status, and annual income on healthcare-seeking behavior. The path model illustrated the complex interplay between perceptual factors and their influence on healthcare-seeking behavior. CONCLUSION: This study emphasizes the importance of consumer involvement, price perception, and attitude in shaping healthcare utilization patterns. Health facility identification plays a crucial mediating role, suggesting that stronger patient-provider relationships can mitigate potential negative impacts of copayment adjustments. Policymakers and healthcare providers should enhance patient engagement, foster strong patient-facility identification, and provide targeted support for vulnerable groups to ensure equitable access to healthcare services despite copayment changes.

Viral Load-Based Prediction of Hepatocellular Carcinoma Risk in Noncirrhotic Patients With Chronic Hepatitis B : A Multinational Study for the Development and External Validation of a New Prognostic Model.

BACKGROUND: A nonlinear association between serum hepatitis B virus (HBV) DNA levels and hepatocellular carcinoma (HCC) risk has been suggested in patients with chronic hepatitis B (CHB). OBJECTIVE: To develop and externally validate a prognostic model for HCC risk in noncirrhotic adult patients with CHB and no notable alanine aminotransferase (ALT) elevation. DESIGN: Multinational cohort study. SETTING: A community-based cohort in Taiwan (REVEAL-HBV [Risk Evaluation of Viral Load Elevation and Associated Liver Disease/Cancer-Hepatitis B Virus]; REACH-B [Risk Estimation for HCC in CHB] model cohort) and 8 hospital-based cohorts from Korea and Hong Kong (GAG-HCC [Guide with Age, Gender, HBV DNA-HCC] and CU-HCC [Chinese University-HCC] cohorts). PARTICIPANTS: Model development: 6949 patients with CHB from a Korean hospital-based cohort. External validation: 7429 patients with CHB combined from the Taiwanese cohort and 7 cohorts from Korea and Hong Kong. MEASUREMENTS: Incidence of HCC. RESULTS: Over median follow-up periods of 10.0 and 12.2 years, the derivation and validation cohorts identified 435 and 467 incident HCC cases, respectively. Baseline HBV DNA level was one of the strongest predictors of HCC development, demonstrating a nonlinear parabolic association in both cohorts, with moderate viral loads (around 6 log10 IU/mL) showing the highest HCC risk. Additional predictors included in the new model (Revised REACH-B) were age, sex, platelet count, ALT levels, and positive hepatitis B e antigen result. The model exhibited satisfactory discrimination and calibration, with c-statistics of 0.844 and 0.813 in the derivation and validation cohorts with multiple imputation, respectively. The model yielded a greater positive net benefit compared with other strategies in the 0% to 18% threshold. LIMITATION: Validation in cohorts of other races and receiving antiviral treatment was lacking. CONCLUSION: Our new prognostic model, based on the nonlinear association between HBV viral loads and HCC risk, provides a valuable tool for predicting and stratifying HCC risk in noncirrhotic patients with CHB who are not currently indicated for antiviral treatment. PRIMARY FUNDING SOURCE: Korean government.

Acarbose might be associated with reduced risk of gastric cancer in patients with diabetes mellitus: A nationwide population-based cohort study.

BACKGROUND: Several epidemiologic studies have revealed a higher risk of cancer in patients with diabetes mellitus (DM) relative to the general population. To investigate whether the use of acarbose was associated with higher/lower risk of new-onset cancers. METHOD: We conducted a retrospective cohort study, using a population-based National Health Insurance Research Database of Taiwan. Both inpatients and outpatients with newly onset DM diagnosed between 2000 and 2012 were collected. The Adapted Diabetes Complications Severity Index (aDCSI) was used to adjust the severity of DM. The Cox proportional hazards regression model was used to estimate the hazard ratio (HR) of disease. RESULTS: A total of 22 502 patients with newly diagnosed DM were enrolled. The Cox proportional hazards regression model indicating acarbose was neutral for risk for gastroenterological malignancies, when compared to the acarbose non-acarbose users group. However, when gastric cancer was focused, acarbose-user group had significantly lowered HR than non-acarbose users group (p = 0.003). After adjusted for age, sex, cancer-related comorbidity, severity of DM, and co-administered drugs, the HR of gastric cancer risk was 0.43 (95% CI = 0.25-0.74) for acarbose-user patients. CONCLUSION: This long-term population-based study demonstrated that acarbose might be associated with lowered risk of new-onset gastric cancer in diabetic patients after adjusting the severity of DM.

Optical Coherence Tomography as a Diagnosis-Assisted Tool for Guiding the Treatment of Melasma: A Case Series Study.

Background/Objectives: Multiple underlying pathomechanisms may lead to melasma, but there has been no report on the use of optical coherence tomography (OCT) to reveal specific pathomechanisms in individual patients and provide individualized treatments accordingly. Using real-time OCT images, we studied the pathomechanisms of melasma in 12 female patients and the effects of individualized treatments. Methods: Patients were divided into good and bad improved groups according to the improvement in hyperpigmentation at month 4. Results: In the bad improved group, all melanin or confetti melanin had significantly decreased at month 2 or month 4 while granular melanin ratio at month or month 4 significantly increased, the most parameters of dendritic-sharped cells (DCs) before and after treatment were not significantly different, the collagen area or collagen density at month 4 significantly decreased. In the good improved group, there was slightly low all melanin/confetti melanin at month 4 and high granular melanin at month 4 in comparison to the bad improved group. Moreover, most of the parameters in the DCs at month 4 significantly increased while most parameters in collagen at month 4 significantly decreased. Conclusions: OCT is useful in revealing the involved pathomechanisms of melasma in individualized patients. Positive treatment results can be achieved through individualized therapy regimen targeting the pathomechanisms.

Glucosamine inhibits myoblast proliferation and differentiation, and stimulates myotube atrophy through distinct signal pathways.

Glucosamine (GlcN) is one of the dietary supplements used in the treatment of osteoarthritis. Endogenously, GlcN is synthesized from glucose through the hexosamine pathway. In addition to ameliorating arthritis, several biological functions of GlcN have been reported, including insulin resistance in skeletal muscle. However, the regulatory role of GlcN in skeletal muscle development is not clear. We therefore investigated the effect of GlcN on myoblast proliferation, differentiation, and myotube development and their underlying mechanisms in C2C12 cells. Myoblast proliferation was measured by MTT assay. The expressions of MyoD, myogenin (MyoG), and myosin heavy chain (MyHC) were identified as determinants of myoblast differentiation. Expressions of atrogin-1 and muscle RING-finger protein-1 (MuRF-1) were identified as markers of myotube atrophy. The results show that treatment with GlcN significantly reduced myoblast proliferation and phosphorylation of Stat3 and S6K. These findings suggest that GlcN can inhibit growth of myoblasts through inhibiting phosphorylation of Stat3 and S6K. In addition, GlcN significantly suppressed the expression of MyoD, MyoG, and MyHC, as well as myotube formation. Pretreatment of C2C12 myoblast cells with ER stress inhibitors significantly blocked GlcN-inhibited MyHC expression and myotube formation. It can be concluded that GlcN suppressed myogenic differentiation via a pathway that involved ER stress. Moreover, GlcN decreased myotube diameter and expression of MyHC, as well as increased MuRF-1 in C2C12 myotubes. Meanwhile, GlcN also reduced the expressions of phosphorylated Akt and mTOR were stimulated after GlcN treatment in C2C12 myotubes. Thus, GlcN induced skeletal muscle atrophy by inhibiting the protein synthesis pathway. Chronic GlcN infusion also caused skeletal muscle atrophy in mice. In conclusion, GlcN regulated important stages of skeletal muscle development through different signaling pathways.

Genetic complexity of killer-cell immunoglobulin-like receptor genes in human pangenome assemblies.

The killer-cell immunoglobulin-like receptor (KIR) gene complex, a highly polymorphic region of the human genome that encodes proteins involved in immune responses, poses strong challenges in genotyping owing to its remarkable genetic diversity and structural intricacy. Accurate analysis of KIR alleles, including their structural variations, is crucial for understanding their roles in various immune responses. Leveraging the high-quality genome assemblies from the Human Pangenome Reference Consortium (HPRC), we present a novel bioinformatic tool, the structural KIR annoTator (SKIRT), to investigate gene diversity and facilitate precise KIR allele analysis. In 47 HPRC-phased assemblies, SKIRT identifies a recurrent novel KIR2DS4/3DL1 fusion gene in the paternal haplotype of HG02630 and maternal haplotype of NA19240. Additionally, SKIRT accurately identifies eight structural variants and 15 novel nonsynonymous alleles, all of which are independently validated using short-read data or quantitative polymerase chain reaction. Our study has discovered a total of 570 novel alleles, among which eight haplotypes harbor at least one KIR gene duplication, six haplotypes have lost at least one framework gene, and 75 out of 94 haplotypes (79.8%) carry at least five novel alleles, thus confirming KIR genetic diversity. These findings are pivotal in providing insights into KIR gene diversity and serve as a solid foundation for understanding the functional consequences of KIR structural variations. High-resolution genome assemblies offer unprecedented opportunities to explore polymorphic regions that are challenging to investigate using short-read sequencing methods. The SKIRT pipeline emerges as a highly efficient tool, enabling the comprehensive detection of the complete spectrum of KIR alleles within human genome assemblies.

Adherence to Nutritional Practice Guideline in Premature Infants: A Nationwide Survey in Taiwan.

OBJECTIVES: This study aimed to assess the current neonatal nutritional practices in Taiwan and promote consensus on standardized protocols. METHODS: An online questionnaire comprising 95 items on parenteral nutrition (PN) and enteral nutrition (EN) practices was distributed to neonatal care units across Taiwan via email between August and December 2022. The responses were compared with the recommendations from the European Society for Pediatric Gastroenterology Hepatology and Nutrition for preterm infant care. RESULTS: Most of the 35 neonatal units, comprising 17 level III and 18 level II units, that participated in this study adhered to standard PN protocols; however, only 30% of units used protein-containing solutions as the initial fluid. Over half of the neonatal units provided calcium, phosphate, and magnesium at less than the recommended dosage. Trophic feeding commenced within 48 h in 88% of the units, with the mother's milk used as the first choice. All the units preferred commencing advanced feeding at <25 mL/kg/day. CONCLUSIONS: Most nutrient protocols for preterm infants in neonatal units in Taiwan meet recent guidelines, but discrepancies such as lower mineral supplements in PN and a slower advancement of enteral feeding increase nutritional risk. These issues warrant further research.

MTA2 knockdown suppresses human osteosarcoma metastasis by inhibiting uPA expression.

The relationship between metastasis-associated protein 2 (MTA2) overexpression and tumor growth and metastasis has been extensively studied in a variety of tumor cells but not in human osteosarcoma cells. This study aims to elucidate the clinical significance, underlying molecular mechanisms, and biological functions of MTA2 in human osteosarcoma in vitro and in vivo. Our results show that MTA2 was elevated in osteosarcoma cell lines and osteosarcoma tissues and was associated with tumor stage and overall survival of osteosarcoma patients. Knockdown of MTA2 inhibited osteosarcoma cell migration and invasion by reducing the expression of urokinase-type plasminogen activator (uPA). Bioinformatic analysis demonstrated that high levels of uPA in human osteosarcoma tissues correlated positively with MTA2 expression. Furthermore, treatment with recombinant human uPA (Rh-uPA) caused significant restoration of OS cell migration and invasion in MTA2 knockdown osteosarcoma cells. We found that ERK1/2 depletion increased the expression of uPA, facilitating osteosarcoma cell migration and invasion. Finally, MTA2 depletion significantly reduced tumor metastasis and the formation of lung nodules in vivo. Overall, our study suggests that MTA2 knockdown suppresses osteosarcoma cell metastasis by decreasing uPA expression via ERK signaling. This finding provides new insight into potential treatment strategies against osteosarcoma metastasis by targeting MTA2.

Predicting the T790M mutation in non-small cell lung cancer (NSCLC) using brain metastasis MR radiomics: a study with an imbalanced dataset.

BACKGROUND: Early detection of T790M mutation in exon 20 of epidermal growth factor receptor (EGFR) in non-small cell lung cancer (NSCLC) patients with brain metastasis is crucial for optimizing treatment strategies. In this study, we developed radiomics models to distinguish NSCLC patients with T790M-positive mutations from those with T790M-negative mutations using multisequence MR images of brain metastasis despite an imbalanced dataset. Various resampling techniques and classifiers were employed to identify the most effective strategy. METHODS: Radiomic analyses were conducted on a dataset comprising 125 patients, consisting of 18 with EGFR T790M-positive mutations and 107 with T790M-negative mutations. Seventeen first- and second-order statistical features were selected from CET1WI, T2WI, T2FLAIR, and DWI images. Four classifiers (logistic regression, support vector machine, random forest [RF], and extreme gradient boosting [XGBoost]) were evaluated under 13 different resampling conditions. RESULTS: The area under the curve (AUC) value achieved was 0.89, using the SVM-SMOTE oversampling method in combination with the XGBoost classifier. This performance was measured against the AUC reported in the literature, serving as an upper-bound reference. Additionally, comparable results were observed with other oversampling methods paired with RF or XGBoost classifiers. CONCLUSIONS: Our study demonstrates that, even when dealing with an imbalanced EGFR T790M dataset, reasonable predictive outcomes can be achieved by employing an appropriate combination of resampling techniques and classifiers. This approach has significant potential for enhancing T790M mutation detection in NSCLC patients with brain metastasis.

Exploration of Klebsiella aerogenes derived secondary metabolites and their antibacterial activities against multidrug-resistant bacteria.

As the effectiveness of current treatments against the development of antimicrobial resistance is declining, new strategies are required. A great source of novel secondary metabolites with therapeutics effects are the endophytic bacteria present in medicinal plants. In this study, Klebsiella aerogenes (an endophytic bacteria belonging to the Enterobacteriaceae family) was isolated from Kalanchoe blossfeldiana (a medicinal plant". The bacterial secondary metabolites were identified using GC-MS techniques. Furthermore, the antibacterial potentials were investigated against multi-drug resistance (MDR) Salmonella typhi and Staphylococcus aureus. The GC-MS chromatogram of K. aerogenes secondary metabolites extract displayed total of 36 compounds. Ethyl acetate extracts of K. aerogenes, showed mean zone of growth inhibition of 15.00 ± 1.00 against S. typhi and 7.00 ± 1.00mm against S. aureus, respectively. The extract demonstrated significant antibacterial effectiveness against S. typhi and moderate antibacterial efficacy against S. aureus, with minimum inhibitory concentration (MIC) values ranging from 0.089 to 0.39 mg/mL. The time-kill kinetics profile of the ethyl acetate extract against S. typhi revealed a decrease in the number of viable cells during the initial 5, 6, and 24 hours. Conversely, there was a sudden increase in viable cells up to 6 hours for S. aureus. The identified secondary metabolite with high percentage than others, benzeneethanamine exhibited favorable interactions (-7.2 kcal/mol) with the penicillin-binding protein (PBP2a) of S. aureus and (-7.5 kcal/mol) osmoporin (OmpC) of S. typhi, indicating its potential as a candidate for drug development against these MDR bacteria. This study reported for the first time, bacterial endophytes associated with K. blossfeldiana with antibacterial activities.

Hepsin as a potential therapeutic target for alleviating acetaminophen-induced hepatotoxicity via gap-junction regulation and oxidative stress modulation.

Acetaminophen (APAP) overdose is a leading cause of drug-induced liver damage, highlighting the limitations of current emergency treatments that primarily involve administering the glutathione precursor N-acetylcysteine and supportive therapy. This study highlights the essential protective role of the type II transmembrane serine protease (TTSP), hepsin, in mitigating acetaminophen-induced liver injury, particularly through its regulation of gap junction (GJ) abundance in response to reactive oxygen stress in the liver. We previously reported that reduced levels of activated hepatocyte growth factor and the c-Met receptor tyrosine kinase-both of which are vital for maintaining cellular redox balance-combined with increased expression of GJ proteins in hepsin-deficient mice. Here, we show that hepsin deficiency in mice exacerbates acetaminophen toxicity compared to wild-type mice, leading to more severe liver pathology, elevated oxidative stress, and greater mortality within 6 h after exposure. Administering hepsin had a protective effect in both mouse models, reducing hepatotoxicity by modulating GJ abundance. Additionally, transcriptome analysis and a functional GJ inhibitor have highlighted hepsin's mechanism for managing oxidative stress. Combining hepsin with relatively low doses of N-acetylcysteine had a synergistic effect that was more efficacious than high-dose N-acetylcysteine alone. Our results illustrate the crucial role of hepsin in modulating the abundance of hepatic GJs and reducing oxidative stress, thereby offering early protection against acetaminophen-induced hepatotoxicity and a new, combination approach. Emerging as a promising therapeutic target, hepsin holds potential for combination therapy with N-acetylcysteine, paving the way for novel approaches in managing drug-induced liver injury.

Exploring the role of spinal astrocytes in the onset of hyperalgesic priming signals in acid-induced chronic muscle pain.

Hyperalgesic priming, a form of pain plasticity initiated by initial injury, leads to heightened sensitivity to subsequent noxious stimuli, contributing to chronic pain development in animals. While astrocytes play active roles in modulating synaptic transmission in various pain models, their specific involvement in hyperalgesic priming remains elusive. Here, we show that spinal astrocytes are essential for hyperalgesic priming formation in a mouse model of acid-induced muscle pain. We observed spinal astrocyte activation 4 h after initial acid injection, and inhibition of this activation prevented chronic pain development upon subsequent acid injection. Chemogenetic activation of spinal astrocytes mimicked the first acid-induced hyperalgesic priming. We also demonstrated that spinal phosphorylated extracellular regulated kinase (pERK)-positive neurons were mainly vesicular glutamate transporter-2 positive (Vglut2+) neurons after the first acid injection, and inhibition of spinal pERK prevented astrocyte activation. Furthermore, pharmacological inhibition of astrocytic glutamate transporters glutamate transporter-1 and glutamate-aspartate transporter abolished the hyperalgesic priming. Collectively, our results suggest that pERK activation in Vglut2+ neurons activate astrocytes through astrocytic glutamate transporters. This process eventually establishes hyperalgesic priming through spinal D-serine. We conclude that spinal astrocytes play a crucial role in the transition from acute to chronic pain.