Spatial distribution patterns of human resources allocation in maternal and child healthcare institutions in China from 2016 to 2021.

BACKGROUND: In China, economic, urbanization, and policy differences between the eastern and western regions lead to uneven healthcare resources. This disparity is more pronounced in the west due to fewer healthcare personnel per thousand individuals and imbalanced doctor-to-nurse ratios, which exacerbates healthcare challenges. This study examines the spatial distribution of human resources in maternal and child healthcare from 2016 to 2021, highlighting regional disparities and offering insights for future policy development. METHODS: The data were sourced from the "China Health and Family Planning Statistical Yearbook" (2017) and the "China Health and Health Statistics Yearbook" (2018-2022). This study utilized GeoDa 1.8.6 software to conduct both global and local spatial autocorrelation analyses, using China's administrative map as the base dataset. RESULTS: From 2016 to 2021, there was an upward trend in the number of health personnel and various types of health technical personnel in Chinese maternal and child healthcare institutions. The spatial distribution of these personnel from 2016 to 2021 revealed clusters characterized as high-high, low-low, high-low and low-high. Specifically, high-high clusters were identified in Guangxi, Hunan, Jiangxi, and Guangdong provinces; low-low in Xinjiang Uygur Autonomous Region and Inner Mongolia Autonomous Region; high-low in Sichuan province; and low-high in Fujian and Anhui provinces. CONCLUSIONS: From 2016 to 2021, there was evident spatial clustering of health personnel and various health technical personnel in Chinese maternal and child healthcare institutions, indicating regional imbalances.

Urolithin A promotes atherosclerotic plaque stability by limiting inflammation and hypercholesteremia in Apolipoprotein E-deficient mice.

Urolithin A (UroA), a dietary phytochemical, is produced by gut bacteria from fruits rich in natural polyphenols ellagitannins (ETs). The efficiency of ETs metabolism to UroA in humans depends on gut microbiota. UroA has shown a variety of pharmacological activities. In this study we investigated the effects of UroA on atherosclerotic lesion development and stability. Apolipoprotein E-deficient (ApoE-/-) mice were fed a high-fat and high-cholesterol diet for 3 months to establish atherosclerosis model. Meanwhile the mice were administered UroA (50 mg·kg-1·d-1, i.g.). We showed that UroA administration significantly decreased diet-induced atherosclerotic lesions in brachiocephalic arteries, macrophage content in plaques, expression of endothelial adhesion molecules, intraplaque hemorrhage and size of necrotic core, while increased the expression of smooth muscle actin and the thickness of fibrous cap, implying features of plaque stabilization. The underlying mechanisms were elucidated using TNF-α-stimulated human endothelial cells. Pretreatment with UroA (10, 25, 50 µM) dose-dependently inhibited TNF-α-induced endothelial cell activation and monocyte adhesion. However, the anti-inflammatory effects of UroA in TNF-α-stimulated human umbilical vein endothelial cells (HUVECs) were independent of NF-κB p65 pathway. We conducted RNA-sequencing profiling analysis to identify the differential expression of genes (DEGs) associated with vascular function, inflammatory responses, cell adhesion and thrombosis in UroA-pretreated HUVECs. Human disease enrichment analysis revealed that the DEGs were significantly correlated with cardiovascular diseases. We demonstrated that UroA pretreatment mitigated endothelial inflammation by promoting NO production and decreasing YAP/TAZ protein expression and TEAD transcriptional activity in TNF-α-stimulated HUVECs. On the other hand, we found that UroA administration modulated the transcription and cleavage of lipogenic transcription factors SREBP1/2 in the liver to ameliorate cholesterol metabolism in ApoE-/- mice. This study provides an experimental basis for new dietary therapeutic option to prevent atherosclerosis.

Optimization and Local Cost-Effectiveness of Nasopharyngeal Carcinoma Screening Strategies in Southern China: Secondary Analysis of the Guangdong Randomized Trial.

BACKGROUND: Screening with anti-Epstein-Barr virus (EBV) serology and endoscopy decreased nasopharyngeal carcinoma (NPC) mortality in Guangdong in a randomized trial. We conducted a secondary analysis of this trial using local incidence and cost data to optimize screening programs, hypothesizing that screening could be cost-effective in southern China. METHODS: Screening costs and life-years after NPC diagnosis were obtained from the Guangdong trial's intent-to-screen population (men and women aged 30-69). Seropositive subjects were rescreened annually for 5 years. Thereafter, we evaluated 12 screening strategies in Guangdong and Guangxi using a validated model. Strategies used combinations of serology, nasopharyngeal swab PCR (NP PCR), endoscopy, and MRI from trial subcohorts. Incidence data and costs were obtained from local cancer registries and the provincial healthcare system. RESULTS: In the intent-to-screen population, screening with serology and endoscopy was cost-effective (¥42,366/life-year, 0.52 GDP per capita). Screening for 5 to 15 years between ages 35 and 59 years met a willingness-to-pay threshold of 1.5 GDP/quality-adjusted life-years in all modeled populations. Despite doubling costs, adding MRI could be cost-effective via improved sensitivity. NP PCR triage reduced endoscopy/MRI referrals by 37%. One-lifetime screen could reduce NPC mortality by approximately 20%. CONCLUSIONS: EBV-based serologic screening for NPC is likely to be cost-effective in southern China. Among seropositive subjects, the preferred strategies use endoscopy alone or selective endoscopy triaged by MRI with or without NP PCR. These data may aid the design of screening programs in this region. IMPACT: These findings support population-based screening in southern China by defining the target population, cost-effectiveness, and optimized screening approach.

Computational Modeling to Identify Drugs Targeting Metastatic Castration-Resistant Prostate Cancer Characterized by Heightened Glycolysis.

Metastatic castration-resistant prostate cancer (mCRPC) remains a deadly disease due to a lack of efficacious treatments. The reprogramming of cancer metabolism toward elevated glycolysis is a hallmark of mCRPC. Our goal is to identify therapeutics specifically associated with high glycolysis. Here, we established a computational framework to identify new pharmacological agents for mCRPC with heightened glycolysis activity under a tumor microenvironment, followed by in vitro validation. First, using our established computational tool, OncoPredict, we imputed the likelihood of drug responses to approximately 1900 agents in each mCRPC tumor from two large clinical patient cohorts. We selected drugs with predicted sensitivity highly correlated with glycolysis scores. In total, 77 drugs predicted to be more sensitive in high glycolysis mCRPC tumors were identified. These drugs represent diverse mechanisms of action. Three of the candidates, ivermectin, CNF2024, and P276-00, were selected for subsequent vitro validation based on the highest measured drug responses associated with glycolysis/OXPHOS in pan-cancer cell lines. By decreasing the input glucose level in culture media to mimic the mCRPC tumor microenvironments, we induced a high-glycolysis condition in PC3 cells and validated the projected higher sensitivity of all three drugs under this condition (p < 0.0001 for all drugs). For biomarker discovery, ivermectin and P276-00 were predicted to be more sensitive to mCRPC tumors with low androgen receptor activities and high glycolysis activities (AR(low)Gly(high)). In addition, we integrated a protein-protein interaction network and topological methods to identify biomarkers for these drug candidates. EEF1B2 and CCNA2 were identified as key biomarkers for ivermectin and CNF2024, respectively, through multiple independent biomarker nomination pipelines. In conclusion, this study offers new efficacious therapeutics beyond traditional androgen-deprivation therapies by precisely targeting mCRPC with high glycolysis.

The Impact of Spironolactone Co-administration on Cyclosporin Initial Dosage Optimization for Pediatric Refractory Nephrotic Syndrome.

OBJECTIVES: Cyclosporin has been used for the treatment of pediatric refractory nephrotic syndrome (PRNS). However, the narrow therapeutic window and large pharmacokinetic variability make it difficult to individualize cyclosporin administration. Meanwhile, spironolactone has been reported to affect cyclosporin metabolism in PRNS patients. This study aims to explore the initial dosage optimization of cyclosporin in PRNS based on the impact of spironolactone co-administration. METHODS: Monte Carlo simulation based on a previously established cyclosporin population pharmacokinetic model for PRNS was used to design cyclosporin dosing regimen. RESULTS: In this study, the probability of drug concentration reaching the target and the convenience of times of administration were considered comprehensively. The optimal administration regimen in PRNS without spironolactone was 6, 5, 4 and 3 mg/kg cyclosporin split into two doses for the body weight of 5-8, 8-18, 18-46 and 46-70 kg, respectively. The optimal administration regimen in PRNS with spironolactone was 4, 3, 2 mg/kg cyclosporin split into two doses for body weight of 5-14, 14-65, and 65-70 kg, respectively. CONCLUSION: The cyclosporin dosing regimen for PRNS based on Monte Carlo simulation was systematically developed and the initial dosage optimization of cyclosporin in PRNS was recommended for the first time.

Effects of tacrolimus on proteinuria in Chinese and Indian patients with idiopathic membranous nephropathy: the results of machine learning study.

PURPOSE: The present study aims to explore the effects of tacrolimus on proteinuria in patients with idiopathic membranous nephropathy (IMN) and recommend an appropriate dosage schedule via machine learning method. METHODS: The Emax model was constructed to analyze the effects of tacrolimus on proteinuria in patients with IMN. Data were mined from published literature and machine learning was built up with Emax model, among which the efficacy indicator was proteinuria change rates from baseline. 463 IMN patients were included for modeling, and tacrolimus therapeutic window concentrations were 4-10 ng/ml. RESULTS: In machine learning model, the Emax from tacrolimus effecting proteinuria in IMN patients was -72.7%, the ET50 was 0.43 months, and the time to achieving 25% Emax, 50% Emax, 75% Emax, and 80% (plateau) Emax of tacrolimus on proteinuria in patients with IMN were 0.15, 0.43, 1.29, and 1.72 months, respectively. CONCLUSION: For achieving better therapeutic effects from tacrolimus on proteinuria in patients with IMN, tacrolimus concentration range need to be maintained at 4-10 ng/ml for at least 1.72 months.

Expression of ATP-Binding Cassette Transporter A1 (ABCA1) in Eyelid Tissues and Meibomian Gland Epithelial Cells.

Purpose: To validate the adenosine triphosphate (ATP)-binding cassette transporter A1 (ABCA1) expression and distribution in human eyelid tissues and meibomian gland epithelial cells. Methods: Meibomian gland tissues from human eyelids were isolated by collagenase A digestion and cultured in defined keratinocyte serum-free medium (DKSFM). Infrared imaging was used to analyze the general morphology of meibomian glands. Hematoxylin and eosin (H&E) staining and Oil Red O staining were used to observe the morphological structure and lipid secretion in the human meibomian gland tissues. Quantitative real-time polymerase chain reaction, western blotting, and immunostaining were used to detect the mRNA and protein expression and cytolocalization of ABCA1 in the meibomian gland tissues and cultured cells. Results: The degree of loss of human meibomian gland tissue was related to age. Meibomian gland lipid metabolism was also associated with age. Additionally, human meibomian gland tissues express ABCA1 mRNA and protein; glandular epithelial cells express more ABCA1 mRNA and protein than acinar cells, and their expression in acinar cells decreases with differentiation. Furthermore, the expression of ABCA1 was downregulated in abnormal meibomian gland tissues. ABCA1 was mainly localized on the cell membrane in primary human meibomian gland epithelial cells (pHMGECs), whereas it was localized in the cytoplasm of immortalized human meibomian gland epithelial cells (iHMGECs). The mRNA and protein levels of ABCA1 in pHMGECs were higher than those in iHMGECs. Conclusions: Meibomian gland tissues of the human eyelid degenerate with age. ABCA1 expression in acinar cells decreases after differentiation and plays an important role in meibomian gland metabolism.

Effects of Aripiprazole on Olanzapine Population Pharmacokinetics and Initial Dosage Optimization in Schizophrenia Patients.

Objective: Olanzapine has already been used to treat schizophrenia patients; however, the initial dosage recommendation when multiple drugs are used in combination, remains unclear. The purpose of this study was to explore the drug-drug interaction (DDI) of multiple drugs combined with olanzapine and to recommend the optimal administration of olanzapine in schizophrenia patients. Methods: In this study, we obtained olanzapine concentrations from therapeutic drug monitoring (TDM) database. In addition, related medical information, such as physiological, biochemical indexes, and concomitant drugs was acquired using medical log. Sixty-five schizophrenia patients were enrollmented for analysis using population pharmacokinetic model by means of nonlinear mixed effect (NONMEM). Results: Weight and combined use of aripiprazole significantly affected olanzapine clearance. Without aripiprazole, for once-daily olanzapine administration dosages, 0.6, 0.5 mg/kg/day were recommended for 40-70, and 70-100 kg schizophrenia patients, respectively; for twice-daily olanzapine administration dosages, 0.6, 0.5 mg/kg/day were recommended for 40-60, and 60-100 kg schizophrenia patients, respectively. With aripiprazole, for once-daily olanzapine administration dosages, 0.4, 0.3 mg/kg/day were recommended for 40-53, and 53-100 kg schizophrenia patients, respectively; for twice-daily olanzapine administration dosages, 0.4 mg/kg/day was recommended for 40-100 kg schizophrenia patients, respectively. Conclusion: Aripiprazole significantly affected olanzapine clearance, and when schizophrenia patients use aripiprazole, the olanzapine dosages need adjust. Meanwhile, we firstly recommended the optimal initial dosages of olanzapine in schizophrenia patients.

Association of preschool children behavior and emotional problems with the parenting behavior of both parents.

BACKGROUND: Parental behaviors are key in shaping children's psychological and behavioral development, crucial for early identification and prevention of mental health issues, reducing psychological trauma in childhood. AIM: To investigate the relationship between parenting behaviors and behavioral and emotional issues in preschool children. METHODS: From October 2017 to May 2018, 7 kindergartens in Ma'anshan City were selected to conduct a parent self-filled questionnaire - Health Development Survey of Preschool Children. Children's Strength and Difficulties Questionnaire (Parent Version) was applied to measures the children's behavioral and emotional performance. Parenting behavior was evaluated using the Parental Behavior Inventory. Binomial logistic regression model was used to analyze the association between the detection rate of preschool children's behavior and emotional problems and their parenting behaviors. RESULTS: High level of parental support/participation was negatively correlated with conduct problems, abnormal hyperactivity, abnormal total difficulty scores and abnormal prosocial behavior problems. High level of maternal support/participation was negatively correlated with abnormal emotional symptoms and abnormal peer interaction in children. High level of parental hostility/coercion was positively correlated with abnormal emotional symptoms, abnormal conduct problems, abnormal hyperactivity, abnormal peer interaction, and abnormal total difficulty scores in children (all P < 0.05). Moreover, paternal parenting behaviors had similarly effects on behavior and emotional problems of preschool children compared with maternal parenting behaviors (all P > 0.05), after calculating ratio of odds ratio values. CONCLUSION: Our study found that parenting behaviors are associated with behavioral and emotional issues in preschool children. Overall, the more supportive or involved the parents are, the fewer behavioral and emotional problems the children experience; conversely, the more hostile or controlling the parents are, the more behavioral and emotional problems the children face. Moreover, the impact of fathers' parenting behaviors on preschool children's behavior and emotions is no less significant than that of mothers' parenting behaviors.

Effects of dapagliflozin on body weight in patients with type 2 diabetes mellitus: Evidence­based practice.

The dose-dependent pharmacological response to dapagliflozin in patients with type 2 diabetes mellitus (T2DM) with regard to weight loss remain unknown. The aim of the present study was to investigate the effects of dapagliflozin on weight loss in patients with T2DM. A total of 8,545 patients with T2DM from 24 randomized controlled trials reported in the literature were selected for inclusion in the study. Data from these trials were analyzed using maximal effect (Emax) models with nonlinear mixed effects modeling; the evaluation index was the body weight change rate from baseline values. Patients treated with 2.5 mg/day dapagliflozin exhibited an Emax of -3.04%, and the time taken for therapy to reach half of the Emax (ET50) was estimated to be 30.8 weeks for patients treated with this dose. Patients treated with 5, 10 and 20 mg/day dapagliflozin exhibited Emax values of -6.57, -4.12 and -3.23%, respectively, and their ET50 values were estimated to be 27.3, 20.4 and 4.23 weeks, respectively. The data indicated ideal linear relationships between individual predictions and observations, suggesting the optimal fitting of the final models. The present study is the first systematic analysis of the effect of dapagliflozin on weight loss in patients with T2DM. The application of dapagliflozin at 5 mg/day exhibited a greater weight loss effect compared with the other doses used, and the weight loss onset time shortened as the dose of dapagliflozin increased.

Population pharmacokinetic/pharmacodynamic modeling of H018, a selective JAK1 inhibitor, in healthy Chinese volunteers.

H018 is an orally administered, selective, small-molecule inhibitor of Janus kinase 1 (JAK1) made for the treatment of rheumatoid arthritis. A population pharmacokinetic/pharmacodynamic analysis was conducted to characterize the pharmacokinetic and pharmacodynamic profile of H018 and its active metabolite using data from 48 healthy Chinese volunteers who received a single dose of 10-160 mg of H018 in a phase I clinical study. A two-compartment model with delayed absorption and linear elimination adequately described the pharmacokinetic data of H018. The apparent clearance of H018 was estimated to be 39.0 L/h, and triglyceride was identified as a covariate on it. Pharmacokinetic data of the active metabolite could be well described by a two-compartment model with linear elimination. The exposure-effect relationships in terms of pSTAT1 inhibition were well described by a direct response model, with exposure captured by an active moiety that consisted of H018 and its metabolite, weighted by the ratio of in vitro JAK1 inhibitory activity (1.13). The estimated EC50 value for the active moiety is 601 nM. In the simulation using the final model, the inhibitory effect appeared to have reached a plateau in the high-dose groups, with max inhibition rates of 81.42 %, 88.42 %, and 91.89 % for 80, 120, and 160 mg dose groups, respectively. Taken together, this study will provide an instructive reference of dose selection for subsequent clinical trials.

Remedial Dosing Recommendations for Sirolimus Delayed or Missed Dosages Caused by Poor Medication Compliance in Pediatric Tuberous Sclerosis Complex Patients.

BACKGROUND: Delayed or missed dosages caused by poor medication compliance significantly affected the treatment of diseases in children. AIMS: The present study aimed to investigate the influence of delayed or missed dosages on sirolimus pharmacokinetics (PK) in pediatric tuberous sclerosis complex (TSC) patients and to recommend remedial dosages for nonadherent patients. METHODS: A published sirolimus population PK model in pediatric TSC patients was used to assess the influence of different nonadherence scenarios and recommend optimally remedial dosages based on Monte Carlo simulation. Thirteen nonadherent scenarios were simulated in this study, including delayed 2h, 4 h, 6 h, 8 h, 10 h, 12 h, 14 h, 16 h, 18 h, 20 h, 22 h, 23.5 h, and missed one dosage. Remedial dosing strategies contained 10-200% of scheduled dosages. The optimal remedial dosage was that with the maximum probability of returning the individual therapeutic range. RESULTS: For delayed or missed sirolimus dosages in pediatric TSC patients, when the delayed time was 0-8 h, 8-10 h, 10-18 h, 18-22.7 h, 22.7-24 h, 70%, 60%, 40%, 30%, 20% scheduled dosages were recommended to take immediately. When one dosage was missed, 120% of scheduled dosages were recommended at the next dose. CONCLUSION: It was the first time to recommend remedial dosages for delayed or missed sirolimus therapy caused by poor medication compliance in pediatric TSC patients based on Monte Carlo simulation. Meanwhile, the present study provided a potential solution for delayed or missed dosages in clinical practice.

Predicting pharmacodynamic effects through early drug discovery with artificial intelligence-physiologically based pharmacokinetic (AI-PBPK) modelling.

A mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model links the concentration-time profile of a drug with its therapeutic effects based on the underlying biological or physiological processes. Clinical endpoints play a pivotal role in drug development. Despite the substantial time and effort invested in screening drugs for favourable pharmacokinetic (PK) properties, they may not consistently yield optimal clinical outcomes. Furthermore, in the virtual compound screening phase, researchers cannot observe clinical outcomes in humans directly. These uncertainties prolong the process of drug development. As incorporation of Artificial Intelligence (AI) into the physiologically based pharmacokinetic/pharmacodynamic (PBPK) model can assist in forecasting pharmacodynamic (PD) effects within the human body, we introduce a methodology for utilizing the AI-PBPK platform to predict the PK and PD outcomes of target compounds in the early drug discovery stage. In this integrated platform, machine learning is used to predict the parameters for the model, and the mechanism-based PD model is used to predict the PD outcome through the PK results. This platform enables researchers to align the PK profile of a drug with desired PD effects at the early drug discovery stage. Case studies are presented to assess and compare five potassium-competitive acid blocker (P-CAB) compounds, after calibration and verification using vonoprazan and revaprazan.

Optimizing the initial tacrolimus dosage in Chinese children with lung transplantation within normal hematocrit levels.

Background: The appropriate initial dosage of tacrolimus is undefined in Chinese pediatric lung transplant patients with normal hematocrit values. The purpose of this study is to optimize the initial dose of tacrolimus in Chinese children who are undergoing lung transplantation and have normal hematocrit levels. Methods: The present study is based on a published population pharmacokinetic model of tacrolimus in lung transplant patients and uses the Monte Carlo simulation to optimize the initial tacrolimus dosage in Chinese children with lung transplantation within normal hematocrit levels. Results: Within normal hematocrit levels, for children with lung transplantation who do not carry the CYP3A5*1 gene and have no coadministration with voriconazole, it is recommended to administer tacrolimus at a dosage of 0.02 mg/kg/day, divided into two doses, for children weighing 10-32 kg, and a dosage of 0.03 mg/kg/day, also divided into two doses, for children weighing 32-40 kg. For children with lung transplantation who carry the CYP3A5*1 gene and have no coadministration with voriconazole, tacrolimus dosages of 0.02, 0.03, and 0.04 mg/kg/day split into two doses are recommended for children weighing 10-15, 15-32, and 32-40 kg, respectively. For children with lung transplantation who do not carry the CYP3A5*1 gene and have coadministration with voriconazole, tacrolimus dosages of 0.01 and 0.02 mg/kg/day split into two doses are recommended for children weighing 10-17 and 17-40 kg, respectively. For children with lung transplantation who carry the CYP3A5*1 gene and have coadministration with voriconazole, a tacrolimus dosage of 0.02 mg/kg/day split into two doses is recommended for children weighing 10-40 kg. Conclusions: It is the first time to optimize the initial dosage of tacrolimus in Chinese children undergoing lung transplantation within normal hematocrit.

Multiple isotopes decipher the nitrogen cycle in the cascade reservoirs and downstream in the middle and lower Yellow River: Insight for reservoir drainage period.

Intensive anthropogenic activities, such as excessive nitrogen input and dam construction, have altered the nitrogen cycle in the global river system. However, the focus on the source, transformation and fate of nitrogen in the Yellow River is still scarce. In this study, the multiple isotopes (δ15N-NO3-, δ18O-NO3-, δ15N-NH4+ and δ15N-PN) were deciphered to explore the nitrogen cycling processes and the driving factors in the thermally stratified cascade reservoirs (Sanmenxia Reservoir: SMXR and Xiaolangdi Reservoir: XLDR) and Lower Yellow River (LYR) during the drainage period of the XLDR. In the SMXR, algal bloom triggered the assimilation process in the upper layer before the SMX Dam, followed by remineralization and subsequent nitrification processes in the lower water layers. The nitrification reaction in the XLDR progressively increased along both longitudinal and vertical directions to the lower layer of the XLD Dam, which was linked to the variation in the water residence time of riverine, transition and lentic zones. The robust nitrification rates in the lower layer of the lentic zone coincided with the substantial depletion of nitrate isotopic composition and enrichment of both δ15N-PN and δ15N-NH4+, indicating the longer water residence time not only promoted the growth of the nitrifying population but also facilitated the remineralization to enhance NH4+ availability. In the LYR, the slight nitrate assimilation, as indicated by nitrate isotopic composition and fractionation models, was the predominant nitrogen transformation process. The Bayesian isotope mixing model results showed that manure and sewage was the dominant nitrate source (50 %) in the middle and lower Yellow River. Notably, the in-reservoir nitrification was a significant nitrate source (27 %) in the XLDR and LYR. Our study deepens the understanding of anthropogenic activities impacting the nitrogen cycle in the river-reservoir system, providing valuable insight into water quality management and nitrogen cycle mechanisms in the Yellow River.

A Web Application for Predicting Drug Combination Efficacy Using Monotherapy Data and IDACombo.

We recently reported a computational method (IDACombo) designed to predict the efficacy of cancer drug combinations using monotherapy response data and the assumptions of independent drug action. Given the strong agreement between IDACombo predictions and measured drug combination efficacy in vitro and in clinical trials, we believe IDACombo can be of immediate use to researchers who are working to develop novel drug combinations. While we previously released our method as an R package, we have now created an R Shiny application to allow researchers without programming experience to easily utilize this method. The app provides a graphical interface which enables users to easily generate efficacy predictions with IDACombo using provided data from several high-throughput cell line screens or using custom, user-provided data.

Assessing question characteristic influences on ChatGPT's performance and response-explanation consistency: Insights from Taiwan's Nursing Licensing Exam.

BACKGROUND: Investigates the integration of an artificial intelligence tool, specifically ChatGPT, in nursing education, addressing its effectiveness in exam preparation and self-assessment. OBJECTIVE: This study aims to evaluate the performance of ChatGPT, one of the most promising artificial intelligence-driven linguistic understanding tools in answering question banks for nursing licensing examination preparation. It further analyzes question characteristics that might impact the accuracy of ChatGPT-generated answers and examines its reliability through human expert reviews. DESIGN: Cross-sectional survey comparing ChatGPT-generated answers and their explanations. SETTING: 400 questions from Taiwan's 2022 Nursing Licensing Exam. METHODS: The study analyzed 400 questions from five distinct subjects of Taiwan's 2022 Nursing Licensing Exam using the ChatGPT model which provided answers and in-depth explanations for each question. The impact of various question characteristics, such as type and cognitive level, on the accuracy of the ChatGPT-generated responses was assessed using logistic regression analysis. Additionally, human experts evaluated the explanations for each question, comparing them with the ChatGPT-generated answers to determine consistency. RESULTS: ChatGPT exhibited overall accuracy at 80.75 % for Taiwan's National Nursing Exam, which passes the exam. The accuracy of ChatGPT-generated answers diverged significantly across test subjects, demonstrating a hierarchy ranging from General Medicine at 88.75 %, Medical-Surgical Nursing at 80.0 %, Psychology and Community Nursing at 70.0 %, Obstetrics and Gynecology Nursing at 67.5 %, down to Basic Nursing at 63.0 %. ChatGPT had a higher probability of eliciting incorrect responses for questions with certain characteristics, notably those with clinical vignettes [odds ratio 2.19, 95 % confidence interval 1.24-3.87, P = 0.007] and complex multiple-choice questions [odds ratio 2.37, 95 % confidence interval 1.00-5.60, P = 0.049]. Furthermore, 14.25 % of ChatGPT-generated answers were inconsistent with their explanations, leading to a reduction in the overall accuracy to 74 %. CONCLUSIONS: This study reveals the ChatGPT's capabilities and limitations in nursing exam preparation, underscoring its potential as an auxiliary educational tool. It highlights the model's varied performance across different question types and notable inconsistencies between its answers and explanations. The study contributes significantly to the understanding of artificial intelligence in learning environments, guiding the future development of more effective and reliable artificial intelligence-based educational technologies. TWEETABLE ABSTRACT: New study reveals ChatGPT's potential and challenges in nursing education: Achieves 80.75 % accuracy in exam prep but faces hurdles with complex questions and logical consistency. #AIinNursing #AIinEducation #NursingExams #ChatGPT.

Host genetic variants, Epstein-Barr virus subtypes, and the risk of nasopharyngeal carcinoma: Assessment of interaction and mediation.

Epstein-Barr virus (EBV) and human leukocyte antigen (HLA) polymorphisms are well-known risk factors for nasopharyngeal carcinoma (NPC). However, the combined effects between HLA and EBV on the risk of NPC are unknown. We applied a causal inference framework to disentangle interaction and mediation effects between two host HLA SNPs, rs2860580 and rs2894207, and EBV variant 163364 with a population-based case-control study in NPC-endemic southern China. We discovered the strong interaction effects between the high-risk EBV subtype and both HLA SNPs on NPC risk (rs2860580, relative excess risk due to interaction [RERI] = 4.08, 95% confidence interval [CI] = 2.03-6.14; rs2894207, RERI = 3.37, 95% CI = 1.59-5.15), accounting for the majority of genetic risk effects. These results indicate that HLA genes and the high-risk EBV have joint effects on NPC risk. Prevention strategies targeting the high-risk EBV subtype would largely reduce NPC risk associated with EBV and host genetic susceptibility.

IL-37 dampens immunosuppressive functions of MDSCs via metabolic reprogramming in the tumor microenvironment.

Interleukin-37 (IL-37) has been shown to inhibit tumor growth in various cancer types. However, the immune regulatory function of IL-37 in the tumor microenvironment is unclear. Here, we established a human leukocyte antigen-I (HLA-I)-matched humanized patient-derived xenograft hepatocellular carcinoma (HCC) model and three murine orthotopic HCC models to study the function of IL-37 in the tumor microenvironment. We found that IL-37 inhibited HCC growth and promoted T cell activation. Further study revealed that IL-37 impaired the immunosuppressive capacity of myeloid-derived suppressor cells (MDSCs). Pretreatment of MDSCs with IL-37 before adoptive transfer attenuated their tumor-promoting function in HCC tumor-bearing mice. Moreover, IL-37 promoted both glycolysis and oxidative phosphorylation in MDSCs, resulting in the upregulation of ATP release, which impaired the immunosuppressive capacity of MDSCs. Collectively, we demonstrated that IL-37 inhibited tumor development through dampening MDSCs' immunosuppressive capacity in the tumor microenvironment via metabolic reprogramming, making it a promising target for future cancer immunotherapy.

The novel selective TLR7 agonist GY101 suppresses colon cancer growth by stimulating immune cells.

Toll-like receptor (TLR) 7, a transmembrane signal transduction receptor expressed on the surface of endosomes, has become an attractive target for antiviral and cancer immunotherapies. TLR7 can induce signal transduction by recognizing single-stranded RNA or its analogs, leading to the release of cytokines such as IL-6, IL-12, TNF-α and type-I IFN. Activation of TLR7 helps to enhance immunogenicity and immune memory by stimulating immune cells. Herein, we identified a novel selective TLR7 agonist, GY101, and determined its ability to activate TLR7. In summary, in vitro, compound GY101 significantly induced the secretion of IL-6, IL-12, TNF-α and IFN-γ in mouse splenic lymphocytes; in vivo, peritumoral injection of GY101 significantly suppressed colon cancer CT26, as well as poorly immunogenic B16-F10 and 4T1 cancer cell-derived tumor growth by activating the infiltration of lymphocytes and polarization of M2-like macrophages into M1-like macrophages. These results demonstrate that GY101, as a potent TLR7 agonist, holds great potential for cancer immunotherapy.