Podocyte-specific Nup160 knockout mice develop nephrotic syndrome and glomerulosclerosis.

More than 60 monogenic genes mutated in steroid-resistant nephrotic syndrome (SRNS) have been identified. Our previous study found that mutations in nucleoporin 160 kD (NUP160) are implicated in SRNS. The NUP160 gene encodes a component of the nuclear pore complex. Recently, two siblings with homozygous NUP160 mutations presented with SRNS and a nervous system disorder. However, replication of nephrotic syndrome (NS)-associated phenotypes in a mammalian model following loss of Nup160 is needed to prove that NUP160 mutations cause SRNS. Here, we generated a podocyte-specific Nup160 knockout (Nup160podKO) mouse model using CRISPR/Cas9 and Cre/loxP technologies. We investigated NS-associated phenotypes in these Nup160podKO mice. We verified efficient abrogation of Nup160 in Nup160podKO mice at both the DNA and protein levels. We showed that Nup160podKO mice develop typical signs of NS. Nup160podKO mice exhibited progression of proteinuria to average albumin/creatinine ratio (ACR) levels of 15.06 ± 2.71 mg/mg at 26 weeks, and had lower serum albumin levels of 13.13 ± 1.34 g/l at 30 weeks. Littermate control mice had urinary ACR mean values of 0.03 mg/mg and serum albumin values of 22.89 ± 0.34 g/l at the corresponding ages. Further, Nup160podKO mice exhibited glomerulosclerosis compared with littermate control mice. Podocyte-specific Nup160 knockout in mice led to NS and glomerulosclerosis. Thus, our findings strongly support that mutations in NUP160 cause SRNS. The newly generated Nup160podKO mice are a reliable mammalian model for future study of the pathogenesis of NUP160-associated SRNS.

Development and validation of a clinical prediction model for the risk of distal metastasis in intrahepatic cholangiocarcinoma: a real-world study.

BACKGROUND: Cholangiocarcinoma (CCA) is a highly malignant and easily metastatic bile duct tumor with poor prognosis. We aimed at studying the associated risk factors affecting distal metastasis of CCA and using nomogram to guide clinicians in predicting distal metastasis of CCA. METHODS: Based on inclusion and exclusion criteria, 345 patients with CCA were selected from the Fifth Medical Center of Chinese PLA General Hospital and were divided into distal metastases (N = 21) and non-distal metastases (N = 324). LASSO regression models were used to screen for relevant parameters and to compare basic clinical information between the two groups of patients. Risk factors for distal metastasis were identified based on the results of univariate and multivariate logistic regression analyses. The nomogram was established based on the results of multivariate logistic regression, and we drawn the corresponding correlation heat map. The predictive accuracy of the nomogram was evaluated by receiver operating characteristic (ROC) curves and calibration plots. The utility of the model in clinical applications was illustrated by applying decision curve analysis (DCA), and overall survival(OS) analysis was performed using the method of Kaplan-meier. RESULTS: This study identified 4 independent risk factors for distal metastasis of CCA, including CA199, cholesterol, hypertension and margin invasion, and developed the nomogram based on this. The result of validation showed that the model had significant accuracy for diagnosis with the area under ROC (AUC) of 0.882 (95% CI: 0.843-0.914). Calibration plots and DCA showed that the model had high clinical utility. CONCLUSIONS: This study established and validated a model of nomogram for predicting distal metastasis in patients with CCA. Based on this, it could guide clinicians to make better decisions and provide more accurate prognosis and treatment for patients with CCA.

Interpretable machine learning-based clinical prediction model for predicting lymph node metastasis in patients with intrahepatic cholangiocarcinoma.

OBJECTIVE: Prediction of lymph node metastasis (LNM) for intrahepatic cholangiocarcinoma (ICC) is critical for the treatment regimen and prognosis. We aim to develop and validate machine learning (ML)-based predictive models for LNM in patients with ICC. METHODS: A total of 345 patients with clinicopathological characteristics confirmed ICC from Jan 2007 to Jan 2019 were enrolled. The predictors of LNM were identified by the least absolute shrinkage and selection operator (LASSO) and logistic analysis. The selected variables were used for developing prediction models for LNM by six ML algorithms, including Logistic regression (LR), Gradient boosting machine (GBM), Extreme gradient boosting (XGB), Random Forest (RF), Decision tree (DT), Multilayer perceptron (MLP). We applied 10-fold cross validation as internal validation and calculated the average of the areas under the receiver operating characteristic (ROC) curve to measure the performance of all models. A feature selection approach was applied to identify importance of predictors in each model. The heat map was used to investigate the correlation of features. Finally, we established a web calculator using the best-performing model. RESULTS: In multivariate logistic regression analysis, factors including alcoholic liver disease (ALD), smoking, boundary, diameter, and white blood cell (WBC) were identified as independent predictors for LNM in patients with ICC. In internal validation, the average values of AUC of six models ranged from 0.820 to 0.908. The XGB model was identified as the best model, the average AUC was 0.908. Finally, we established a web calculator by XGB model, which was useful for clinicians to calculate the likelihood of LNM. CONCLUSION: The proposed ML-based predicted models had a good performance to predict LNM of patients with ICC. XGB performed best. A web calculator based on the ML algorithm showed promise in assisting clinicians to predict LNM and developed individualized medical plans.

Nucleoporin-associated steroid-resistant nephrotic syndrome.

Nucleoporins (Nups) are a class of proteins that assemble to form nuclear pore complexes, which are related to nucleocytoplasmic transport, gene expression, and the cell cycle. Pathogenic variants in six genes encoding Nups, NUP85, NUP93, NUP107, NUP133, NUP160, and NUP205, cause monogenic steroid-resistant nephrotic syndrome (SRNS), referred to as nucleoporin-associated SRNS. In this paper, we review the epidemiology, structure and function of Nups, pathogenesis, phenotypes and genotypes, and management of nucleoporin-associated SRNS as well as implications for genetic counseling. Affected individuals exhibit autosomal recessive isolated and syndromic SRNS, whose extrarenal manifestations include neurological disorders, growth and development disorders, cardiovascular disorders, and congenital malformations. The median ages at onset of NUP85-, NUP93-, NUP107-, NUP133-, NUP160-, and NUP205-associated SRNS are 7, 3, 4.1, 9, 7, and 2 years, respectively. Kidney biopsies reveal focal segmental glomerulosclerosis in 89% of patients. Most affected individuals are resistant to immunosuppressants. For the six subtypes of nucleoporin-associated SRNS, patients show progression to kidney failure at median ages of 8.5, 3.7, 6.9, 13, 15, and 7 years, respectively. Only two patients with NUP93-associated SRNS with nephrotic syndrome relapse post-transplant have been reported, and the recurrence rate is 12.5%. Next-generation sequencing using a targeted gene panel is recommended in cases of suspected nucleoporin-associated SRNS for genetic diagnosis. Renin-angiotensin-aldosterone system inhibitors are recommended for patients with nucleoporin-associated SRNS. Once genetic diagnosis is confirmed, immunosuppressant discontinuation should be considered, and kidney transplant is preferred when patients progress to kidney failure. Genetic counselling should be provided for asymptomatic siblings and future siblings of an affected individual. Further studies on the pathogenesis of nucleoporin-associated SRNS are needed to seek new therapeutic interventions.

Differences in the prevalence of allergy and asthma among US children and adolescents during and before the COVID-19 pandemic.

BACKGROUND: The increasing prevalence of allergies and asthma has led to a growing global socioeconomic burden. Since the outbreak of the COVID-19 pandemic, the health and lifestyles of children and adolescents have changed dramatically. It's unclear how this shift impacted allergy and asthma, with limited studies addressing this question. We aim to explore the difference of the prevalence of allergies and asthma among US children and adolescents during and before the COVID-19 pandemic using a nationally representative sample of US children and adolescents. METHODS: This cross-sectional study included 31,503 participants in the National Health Interview Survey (NHIS) between 2018 and 2021. Allergies and asthma were defined on an affirmative response in the questionnaire by a parent or guardian. Chi-square tests were used to compare baseline characteristics with allergies and asthma for categorical variables. Differences in prevalence during and before the COVID-19 pandemic were estimated with weighted logistic regression, adjusting for demographic factors. Interaction analyses explored variations across strata. RESULTS: In US children and adolescents aged 0 to 17, prevalence of any allergy was 26.1% (95% CI, 24.8%- 27.4%) in 2018 and 27.1% (95% CI, 25.9%- 28.2%) in 2021. Thereinto, in 2018, prevalence of respiratory allergies, food allergies and skin allergies were 14.0% (95% CI, 13.1%- 15.0%), 6.5% (95% CI, 5.8%- 7.1%) and 12.6% (95% CI, 11.6%- 13.5%), respectively, and in 2021, 18.8% (95% CI, 17.8%- 19.9%), 5.8% (95% CI, 5.2%- 6.4%) and 10.7% (95% CI, 9.9%- 11.5%), respectively. And prevalence of asthma was 11.1% (95% CI, 10.5%- 11.7%) in 2018-2019 and 9.8% (95% CI, 9.2%- 10.4%) in 2020-2021. Prevalence of respiratory allergies, skin allergies and asthma during and before the COVID-19 pandemic in children and adolescents had statistically significant differences. The differences persisted after adjusting for demographic and socioeconomic variables. CONCLUSION: Prevalence of respiratory allergies increased and the prevalence of both skin allergies and asthma decreased among US children and adolescents during the COVID-19 pandemic compared with the pre-COVID-19 pandemic. Further research is required to explore the association between allergic diseases and the pandemic, with a particular emphasis on the impact of lifestyle changes resulting from measures to prevent COVID-19 infection.

Predicting osteoporotic fractures post-vertebroplasty: a machine learning approach with a web-based calculator.

PURPOSE: The aim of this study was to develop and validate a machine learning (ML) model for predicting the risk of new osteoporotic vertebral compression fracture (OVCF) in patients who underwent percutaneous vertebroplasty (PVP) and to create a user-friendly web-based calculator for clinical use. METHODS: A retrospective analysis of patients undergoing percutaneous vertebroplasty: A retrospective analysis of patients treated with PVP between June 2016 and June 2018 at Liuzhou People's Hospital was performed. The independent variables of the model were screened using Boruta and modelled using 9 algorithms. Model performance was assessed using the area under the receiver operating characteristic curve (ROC_AUC), and clinical utility was assessed by clinical decision curve analysis (DCA). The best models were analysed for interpretability using SHapley Additive exPlanations (SHAP) and the models were deployed visually using a web calculator. RESULTS: Training and test groups were split using time. The SVM model performed best in both the training group tenfold cross-validation (CV) and validation group AUC, with an AUC of 0.77. DCA showed that the model was beneficial to patients in both the training and test sets. A network calculator developed based on the SHAP-based SVM model can be used for clinical risk assessment ( https://nicolazhang.shinyapps.io/refracture_shap/ ). CONCLUSIONS: The SVM-based ML model was effective in predicting the risk of new-onset OVCF after PVP, and the network calculator provides a practical tool for clinical decision-making. This study contributes to personalised care in spinal surgery.

Deep Eutectic Solvent-Based Dispersive Liquid-Liquid Microextraction Coupled with LC-MS/MS for the Analysis of Two Ochratoxins in Capsicum.

Ochratoxins, a common class of mycotoxin in capsicum, and techniques and methods for the determination of mycotoxins in spices have been increasingly developed in recent years. An innovative and eco-friendly method of dispersive liquid-liquid microextraction (DLLME) was demonstrated in this study, based on a synthesized deep eutectic solvent (DES) combined with LC-MS/MS, for the quantification and analysis of two ochratoxins in capsicum. The DES-DLLME method parameters entail selecting the DES type (thymol:decanoic acid, molar ratio 1:1) and DES volume (100 µL). The volume of water (3 mL) and salt concentration (0 g) undergo optimization following a step-by-step approach to achieve optimal target substance extraction efficiency. The matrix effect associated with the direct detection of the target substance in capsicum was significantly reduced in this study by the addition of isotopic internal standards corresponding to the target substance. This facilitated optimal conditions wherein quantitative analysis using LC-MS/MS revealed a linear range of 0.50-250.00 µg/mL, with all two curves calibrated with internal standards showing correlation coefficients (r2) greater than 0.9995. The method's limits of detection (LODs) and limits of quantification (LOQs) fell in the ranges of 0.14-0.45 µg/kg and 0.45-1.45 µg/kg, respectively. The method's spiked recoveries ranged from 81.97 to 105.17%, indicating its sensitivity and accuracy. The environmental friendliness of the technique was assessed using two green assessment tools, AGREE and complexGAPI, and the results showed that the technique was more in line with the concept of sustainable development compared to other techniques for detecting ochratoxins in capsicum. Overall, this study provides a new approach for the determination of mycotoxins in a complex food matrix such as capsicum and other spices using DES and also contributes to the application of green analytical chemistry methods in the food industry.

Tomato transcriptional repressor MYB70 directly regulates ethylene-dependent fruit ripening.

Ethylene is a key plant hormone controlling the ripening of climacteric fruits, and several transcription factors acting as important regulators of fruit ripening have been identified in tomato (Solanum lycopersicum), a model for climacteric fruits. The vast majority of these transcription factors are transcriptional activators, however, and the associated transcriptional regulatory mechanisms of most regulators are unclear. Here, we report on a tomato transcriptional repressor (termed SlMYB70) that negatively regulates fruit ripening by directly modulating ethylene biosynthesis. As an EAR motif-containing MYB transcription factor-encoding gene, SlMYB70 displayed a ripening-associated expression pattern and was responsive to ethylene. RNA interference (RNAi)-mediated repression of SlMYB70 accelerated fruit ripening, but overexpression of SlMYB70 delayed fruit ripening. Ethylene production was noticeably increased and decreased in SlMYB70-RNAi and SlMYB70-overexpressing lines, respectively, compared with wild-type tomatoes. SlMYB70 was proven to be a transcriptional repressor, dependent on the EAR repression motif, and to repress the transcription of two ethylene biosynthesis genes in fruit ripening, namely SlACS2 and SlACO3. The promoters of SlACS2 and SlACO3 are directly bound by SlMYB70, which was verified using a combination of yeast one-hybrid chromatin immunoprecipitation quantitative polymerase chain reaction and electrophoretic mobility shift assays. These results suggest that SlMYB70 negatively regulates fruit ripening via the direct transcriptional repression of ethylene biosynthesis genes, which provides insights into the ethylene-mediated key regulatory hierarchy in climacteric fruit ripening, and also highlights different types of transcriptional regulation of fruit ripening.

Carotid plague formation is associated with ankle-brachial index in elderly people.

AIMS: This study aimed at examining whether ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV) were independently associated with carotid Intima-media thickness (CIMT) or carotid artery plaque (CAP) in elderly people. METHODS: A cross-sectional analysis was performed in 155 individuals aged over 75 years who underwent the measurements of ABI and baPWV. Low ABI was defined as ABI ≤ 1.0. High baPWV was defined as baPWV > 2000 cm/s. The CIMT and CAP were measured with a B-mode tomographic ultrasound system. RESULTS: Neither ABI nor baPWV was associated with CIMT in this elderly population. The group with low ABI (≤ 1.0) was significantly associated with a higher prevalence of carotid plaque (P = 0.001), while the relationship between baPWV and prevalence of carotid plaque was not found. Linear regression analysis showed that the value of ABI was significantly associated with the thickness of carotid plaque. Even in the full adjusted model, each 0.01unit ABI decreasing still increased 0.1663 mm of carotid plaque thickness (P = 0.004). Logistic Regression Analysis demonstrated that ABI lower than 1.0 had predictive value in the formation of carotid plaque with top quartile thickness (OR 2.834, 95% CI 1.131-7.099, P = 0.026). Furthermore, individuals with low ABI (≤ 1.0) were more likely to form hypoechoic carotid plaques according to ultrasonography. CONCLUSION: Low ABI but not high baPWV was associated with the formation of carotid plaque. Furthermore, ABI was significantly associated with the thickness and morphology of carotid plaque in elderly people.

Specific activation of mGlu2 induced IGF-1R transactivation in vitro through FAK phosphorylation.

Metabotropic glutamate receptor 2 (mGlu2) belongs to the group-II metabotropic glutamate (mGlu) receptors and is a neurotransmitter G protein-coupled receptor. The group-II mGlu receptors are promising antipsychotic targets, but the specific role of mGlu2 signaling remains unclear. Receptor tyrosine kinases (RTKs) are also believed to participate in brain pathogenesis. To investigate whether there is any communication between mGlu2 and RTKs, we generated a CHO-mGlu2 cell line that stably expresses mGlu2 and showed that activation of mGlu2 by LY379268, a group II mGlu agonist, was able to transactivate insulin-like growth factor 1 receptor (IGF-1R). We further determined that the Gi/o protein, Gßγ subunits, phospholipase C, and focal adhesion kinase (FAK) were involved in the IGF-1R transactivation signaling axis, which further induced the phosphorylation of extracellular signal-regulated kinase1/2 (ERK1/2) and cAMP response element-binding protein. In primary mouse cortical neurons, similar signaling pathways were observed when mGlu2 were stimulated by LY487379, an mGlu2 positive allosteric modulator. Transactivation of IGF-1R through FAK in response to mGlu2 should provide a better understanding of the association of mGlu2 with brain disease.

Erythrocyte rheological properties but not whole blood and plasma viscosity are associated with severity of hypertension in older people.

OBJECTIVE: This study was carried out to determine whether changes in hemorheological parameters parallel the severity of essential hypertension. METHODS: A total of 198 older hypertensive patients were recruited and classified into 3 stages of hypertension according to the grading standard of hypertension. The whole blood viscosity (WBV) at various shear rates, plasma viscosity and erythrocyte rheology (including erythrocyte rigidity index, erythrocyte aggregation index and erythrocyte deformation index) were examined. RESULTS: Erythrocyte rheology paralleled the severity of essential hypertension and was significantly correlated to the average 24 h systolic blood pressure and diastolic blood pressure. Logistic analysis revealed that erythrocyte rigidity and the erythrocyte aggregation index were positively correlated with the severity of hypertension, while the erythrocyte deformation index was negatively correlated. No association was found between WBV, plasma viscosity and the severity of hypertension. CONCLUSION: The rheological properties of erythrocyte viscosity were correlated with the severity of hypertension in older people but the WBV and plasma viscosity were not.

Representation of illusory and physical rotations in human MST: A cortical site for the pinna illusion.

Visual illusions have fascinated mankind since antiquity, as they provide a unique window to explore the constructive nature of human perception. The Pinna illusion is a striking example of rotation perception in the absence of real physical motion. Upon approaching or receding from the Pinna-Brelstaff figure, the observer experiences vivid illusory counter rotation of the two rings in the figure. Although this phenomenon is well known as an example of integration from local cues to a global percept, the visual areas mediating the illusory rotary perception in the human brain have not yet been identified. In the current study we investigated which cortical area in the human brain initially mediates the Pinna illusion, using psychophysical tests and functional magnetic resonance imaging (fMRI) of visual cortices V1, V2, V3, V3A, V4, and hMT+ of the dorsal and ventral visual pathways. We found that both the Pinna-Brelstaff figure (illusory rotation) and a matched physical rotation control stimulus predominantly activated subarea MST in hMT+ with a similar response intensity. Our results thus provide neural evidence showing that illusory rotation is initiated in human MST rather than MT as if it were physical rotary motion. The findings imply that illusory rotation in the Pinna illusion is mediated by rotation-sensitive neurons that normally encode physical rotation in human MST, both of which may rely on a cascade of similar integrative processes from earlier visual areas. Hum Brain Mapp 37:2097-2113, 2016. © 2016 Wiley Periodicals, Inc.

GA to HbA1C ratio, but not HbA1C is associated with cognition in Chinese nondiabetic old adults.

OBJECTIVES: To investigate the relationship between glycated albumin (GA) to glycated hemoglobin (HbA1c) ratio and cognitive impairment in old age. Diabetes is associated with cognitive impairment in older people. However, the link between elevated GA/HbA1c levels and the risk of cognitive impairment in nondiabetic individuals is unclear. METHODS: A cross-sectional study of 474 old, nondiabetic adults (192 women, mean age 73.8 years ± 6.9 SD) who had been admitted to our hospital was conducted. Glycemic measures included fasting plasma glucose (FPG), 2-hour post-prandial plasmic glucose (2hPPG), GA and HbA1c. Cognitive function was assessed using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) at the same examination visit in which the glycemic measures were determined. RESULTS: When the individuals were divided into two groups according to the median of GA/HbA1c ratio, old adults with GA/HbA1c ratio ≥ 2.53 showed lower MMSE and MoCA scores compared to those with GA/HbA1c ratio < 2.53. Univariate regression analysis showed that MMSE and MoCA scores were not correlated with HbA1c, but were inversely correlated with GA and GA/HbA1c ratio. Linear regression analysis revealed that there was a significant negative correlation between GA/HbA1c and cognitive function (ß = -0.77, P < 0.01 for MoCA and ß = -0.69, P < 0.05 for MMSE) even after adjustment for age, body mass index, systolic blood pressure, lipoprotein(a) and sex. CONCLUSION: Our results indicate that even in the absence of manifest type 2 diabetes mellitus, GA/HbA1c ratio levels exert a negative influence on cognition and it may be a better predictor for cognitive impairment in the older population.

Kurarinol induces hepatocellular carcinoma cell apoptosis through suppressing cellular signal transducer and activator of transcription 3 signaling.

Kurarinol is a flavonoid isolated from roots of the medical plant Sophora flavescens. However, its cytotoxic activity against hepatocellular carcinoma (HCC) cells and toxic effects on mammalians remain largely unexplored. Here, the pro-apoptotic activities of kurarinol on HCC cells and its toxic impacts on tumor-bearing mice were evaluated. The molecular mechanisms underlying kurarinol-induced HCC cell apoptosis were also investigated. We found that kurarinol dose-dependently provoked HepG2, Huh-7 and H22 HCC cell apoptosis. In addition, kurarinol gave rise to a considerable decrease in the transcriptional activity of signal transducer and activator of transcription 3 (STAT3) in HCC cells. Suppression of STAT3 signaling is involved in kurarinol-induced HCC cell apoptosis. In vivo studies showed that kurarinol injection substantially induced transplanted H22 cell apoptosis with low toxic impacts on tumor-bearing mice. Similarly, the transcriptional activity of STAT3 in transplanted tumor tissues was significantly suppressed after kurarinol treatment. Collectively, our current research demonstrated that kurarinol has the capacity of inducing HCC cell apoptosis both in vitro and in vivo with undetectable toxic impacts on the host. Suppressing STAT3 signaling is implicated in kurarinol-mediated HCC cell apoptosis.

Application effect of case management nursing based on patient safety in patients with prostate cancer.

BACKGROUND: Globally, prostate cancer has become a major threat to men's health, with an increasing incidence and causes serious effects on the quality and length of life of patients. Despite the rapid development of medical technology, which provides treatments, including surgery, radiotherapy, and endocrine therapy, the treatment of patients with prostate cancer, especially with endocrine therapy, has become a major challenge in clinical treatment owing to the lengthy course of treatment, side effects of drugs, and impact of the disease on the psychological and physiological functioning of the patient, producing poor treatment adherence and a decline in quality of life. AIM: To explore effects of nursing intervention prioritizing patient safety and case management in patients with prostate cancer undergoing endocrine therapy. METHODS: Eighty patients with prostate cancer who received endocrine therapy at our hospital between January 2022 and January 2024 were divided into observation and control groups with 40 cases per group. The control group was treated using a routine nursing workflow while the observation group received case management nursing guidance prioritizing patient safety. Scores for anxiety and depression, prostate cancer symptoms, and quality of life and patient compliance and satisfaction were compared between the groups after three months of intervention. RESULTS: After the nursing intervention, the anxiety and depression scores of the observation group were significantly lower than those of the control group (P < 0.05). The quality of life score, sexual function, and hormone function were significantly higher than those in the control group (P < 0.05). CONCLUSION: Case management guidance based on patient safety effectively reduced anxiety and depression in patients undergoing endocrine therapy for prostate cancer and improved their quality of life, treatment compliance, and satisfaction.

Single-cell transcriptomics reveals activation of endothelial cell and identifies LHPP as a potential target in ulcerative colitis.

This study delves into Ulcerative colitis (UC), a persistent gastrointestinal disorder marked by inflammation and ulcers, significantly elevating colorectal cancer risk. The emergence of single-cell RNA sequencing (scRNA-seq) technology has opened new avenues for dissecting the intricate cellular dynamics and molecular mechanisms at play in UC pathology. By analyzing scRNA-seq data from individuals with UC, our study has revealed a consistent enhancement of inflammatory response pathways throughout the course of the disease, alongside detailing the characteristics of endothelial cell damage within colitis environments. A noteworthy finding is the downregulation of Phospholysine Phosphohistidine Inorganic Pyrophosphate Phosphatase (LHPP), which exhibited a inversely correlate with STAT3 expression levels. The markedly reduced expression of LHPP in both the tissues and plasma of UC patients positions LHPP as a compelling target for therapeutic intervention. Our findings highlight the pivotal role LHPP could play in moderating inflammation, spotlighting its potential as a crucial molecular target in the quest to understand and treat UC.

Interventional effects of Pueraria oral liquid on T2DM rats and metabolomics analysis.

Pueraria lobata, commonly known as kudzu, is a medicinal and food plant widely used in the food, health food, and pharmaceutical industries. It has clinical pharmacological effects, including hypoglycemic, antiinflammatory, and antioxidant effects. However, its mechanism of hypoglycemic effect on type 2 diabetes mellitus (T2DM) has not yet been elucidated. In this study, we prepared a Pueraria lobata oral liquid (POL) and conducted a comparative study in a T2DM rat model to evaluate the hypoglycemic effect of different doses of Pueraria lobata oral liquid. Our objective was to investigate the hypoglycemic effect of Puerarin on T2DM rats and understand its mechanism from the perspective of metabolomics. In this study, we assessed the hypoglycemic effect of POL through measurements of FBG, fasting glucose tolerance test, plasma lipids, and liver injury levels. Furthermore, we examined the mechanism of action of POL using hepatic metabolomics. The study's findings demonstrated that POL intervention led to improvements in weight loss, blood glucose, insulin, and lipid levels in T2DM rats, while also providing a protective effect on the liver. Finally, POL significantly affected the types and amounts of hepatic metabolites enriched in metabolic pathways, providing an important basis for revealing the molecular mechanism of Pueraria lobata intervention in T2DM rats. These findings indicate that POL may regulate insulin levels, reduce liver damage, and improve metabolic uptake in the liver. This provides direction for new applications and research on Pueraria lobata to prevent or improve T2DM.

Artificial intelligence-assisted metastasis and prognosis model for patients with nodular melanoma.

OBJECTIVE: The objective of this study was to identify the risk factors that influence metastasis and prognosis in patients with nodular melanoma (NM), as well as to develop and validate a prognostic model using artificial intelligence (AI) algorithms. METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was queried for 4,727 patients with NM based on the inclusion/exclusion criteria. Their clinicopathological characteristics were retrospectively reviewed, and logistic regression analysis was utilized to identify risk factors for metastasis. This was followed by employing Multilayer Perceptron (MLP), Adaptive Boosting (AB), Bagging (BAG), logistic regression (LR), Gradient Boosting Machine (GBM), and eXtreme Gradient Boosting (XGB) algorithms to develop metastasis models. The performance of the six models was evaluated and compared, leading to the selection and visualization of the optimal model. Through integrating the prognostic factors of Cox regression analysis with the optimal models, the prognostic prediction model was constructed, validated, and assessed. RESULTS: Logistic regression analyses identified that marital status, gender, primary site, surgery, radiation, chemotherapy, system management, and N stage were all independent risk factors for NM metastasis. MLP emerged as the optimal model among the six models (AUC = 0.932, F1 = 0.855, Accuracy = 0.856, Sensitivity = 0.878), and the corresponding network calculator (https://shimunana-nm-distant-m-nm-m-distant-8z8k54.streamlit.app/) was developed. The following were examined as independent prognostic factors: MLP, age, marital status, sequence number, laterality, surgery, radiation, chemotherapy, system management, T stage, and N stage. System management and surgery emerged as protective factors (HR < 1). To predict 1-, 3-, and 5-year overall survival (OS), a nomogram was created. The validation results demonstrated that the model exhibited good discrimination and consistency, as well as high clinical usefulness. CONCLUSION: The developed prediction model more effectively reflects the prognosis of patients with NM and differentiates between the risk level of patients, serving as a useful supplement to the classical American Joint Committee on Cancer (AJCC) staging system and offering a reference for clinically stratified individualized treatment and prognosis prediction. Furthermore, the model enables clinicians to quantify the risk of metastasis in NM patients, assess patient survival, and administer precise treatments.

A one-year relapse prediction model for acute ischemic stroke (AIS) based on clinical big data.

Objective: To develop and evaluate a nomogram prediction model for recurrence of acute ischemic stroke (AIS) within one year. Method: Patients with AIS treated at the second affiliated hospital of Xuzhou Medical University from August 2017 to July 2019 were enrolled. Clinical data such as demographic data, risk factors, laboratory tests, TOAST etiological types, MRI features, and treatment methods were collected. Cox regression analysis was done to determine the parameters for entering the nomogram model. The performance of the model was estimated by receiver operating characteristic curves, decision curve analysis, calibration curves, and C-index. Result: A total of 645 patients were enrolled in this study. Side of hemisphere (SOH, Bilateral, HR = 0.35, 95 % CI = 0.15-0.84, p = 0.018), homocysteine (HCY, HR = 1.38, 95 % CI = 1.29-1.47, p < 0.001), c-reactive protein (CRP, HR = 1.04, 95 % CI = 1.01-1.07, p = 0.013) and stroke severity (SS, HR = 3.66, 95 % CI = 2.04-6.57, p < 0.001) were independent risk factors. The C-index of the nomogram model was 0.872 (se = 0.016). The area under the receiver operating characteristic (ROC)curve at one-year recurrence was 0.900. Calibration curve, decision curve analysis showed good performance of the nomogram. The cutoff value for low or high risk of recurrence score was 1.73. Conclusion: The nomogram model for stroke recurrence within one year developed in this study performed well. This useful tool can be used in clinical practice to provide important guidance to healthcare professionals.

Ensemble learning-assisted prediction of prolonged hospital length of stay after spine correction surgery: a multi-center cohort study.

PURPOSE: This research aimed to develop a machine learning model to predict the potential risk of prolonged length of stay in hospital before operation, which can be used to strengthen patient management. METHODS: Patients who underwent posterior spinal deformity surgery (PSDS) from eleven medical institutions in China between 2015 and 2022 were included. Detailed preoperative patient data, including demographics, medical history, comorbidities, preoperative laboratory results, and surgery details, were collected from their electronic medical records. The cohort was randomly divided into a training dataset and a validation dataset with a ratio of 70:30. Based on Boruta algorithm, nine different machine learning algorithms and a stack ensemble model were trained after hyperparameters tuning visualization and evaluated on the area under the receiver operating characteristic curve (AUROC), precision-recall curve, calibration, and decision curve analysis. Visualization of Shapley Additive exPlanations method finally contributed to explaining model prediction. RESULTS: Of the 162 included patients, the K Nearest Neighbors algorithm performed the best in the validation group compared with other machine learning models (yielding an AUROC of 0.8191 and PRAUC of 0.6175). The top five contributing variables were the preoperative hemoglobin, height, body mass index, age, and preoperative white blood cells. A web-based calculator was further developed to improve the predictive model's clinical operability. CONCLUSIONS: Our study established and validated a clinical predictive model for prolonged postoperative hospitalization duration in patients who underwent PSDS, which offered valuable prognostic information for preoperative planning and postoperative care for clinicians. Trial registration ClinicalTrials.gov identifier NCT05867732, retrospectively registered May 22, 2023, https://classic. CLINICALTRIALS: gov/ct2/show/NCT05867732 .