Risk prediction for preeclampsia in CKD patients: development of a model in a retrospective cohort.

BACKGROUND: Chronic kidney disease (CKD) may affect women of childbearing age and may lead to substantial maternal and foetal morbidity and mortality in pregnancy. There is a lack of prediction models for  preeclampsia and adverse pregnancy outcomes in pregnant women with CKD. This study aimed to create a prediction nomogram for these issues. METHODS: This retrospective cohort study included clinical data from 627 women with CKD and their 627 pregnancies at Peking University First Hospital between January 1, 2009, and December 31, 2022. Multivariate logistic regression analysis was conducted to identify independent prognostic factors and develop a nomogram for predicting the occurrence of preeclampsia. The identified risk factors were utilised to construct the nomogram, which was subsequently internally validated using receiver operating characteristic (ROC) analysis and calibration curve assessment. RESULTS: According to our multivariate analysis, age, blood urea nitrogen (BUN), serum creatinine (Scr), mean arterial pressure (MAP), 24-h proteinuria, and CKD stage were identified as predictors of preeclampsia. Additionally, Scr, MAP, BUN, and 24-h proteinuria were found to be predictors of adverse pregnancy outcomes. The nomogram for predicting preeclampsia had an area under the ROC curve of 0.910, while the nomogram for predicting adverse pregnancy outcomes had an area under the ROC curve of 0.906. Both models demonstrated excellent discriminatory ability. CONCLUSIONS: A nomogram based on 24-h proteinuria, serum creatinine, serum urea and age, and MAP allows predicting the occurrence of preeclampsia and other adverse pregnancy-related outcomes in CKD patients.

Whole-exome sequencing identifies protein-coding variants associated with brain iron in 29,828 individuals.

Iron plays a fundamental role in multiple brain disorders. However, the genetic underpinnings of brain iron and its implications for these disorders are still lacking. Here, we conduct an exome-wide association analysis of brain iron, measured by quantitative susceptibility mapping technique, across 26 brain regions among 26,789 UK Biobank participants. We find 36 genes linked to brain iron, with 29 not being previously reported, and 16 of them can be replicated in an independent dataset with 3,039 subjects. Many of these genes are involved in iron transport and homeostasis, such as FTH1 and MLX. Several genes, while not previously connected to brain iron, are associated with iron-related brain disorders like Parkinson's (STAB1, KCNA10), Alzheimer's (SHANK1), and depression (GFAP). Mendelian randomization analysis reveals six causal relationships from regional brain iron to brain disorders, such as from the hippocampus to depression and from the substantia nigra to Parkinson's. These insights advance our understanding of the genetic architecture of brain iron and offer potential therapeutic targets for brain disorders.

The effect of preeclampsia on long-term kidney function among pregnant women with chronic kidney disease.

BACKGROUND AND HYPOTHESIS: The association between superimposed preeclampsia and an elevated risk of long-term kidney function decline or end-stage kidney disease (ESKD) in patients with chronic kidney disease (CKD) has not been determined. This study aimed to analyze the association between preeclampsia and kidney function deterioration in CKD patients. METHODS: This was a retrospective cohort study that included the clinical information of 103 pregnant CKD patients with preeclampsia and 103 matched CKD patients without preeclampsia who were followed-up for a minimum of 1 year after their first pregnancy from January 1, 2009, to May 31, 2022. Robust Cox regression analysis was also conducted to evaluate the effects of preeclampsia on long-term kidney function decline or ESKD in CKD patients. K-M curves were used to compare renal survival within different subgroups via the log-rank test. RESULTS: During the follow-up period, 44 (42.72%) CKD patients with preeclampsia and 20 (19.42%) without preeclampsia had an estimated glomerular filtration rate (eGFR) decrease >30% or developed ESKD. Compared with CKD patients without preeclampsia, the eGFR decreased more significantly in patients with preeclampsia [98.43 (79.48, 116.47) to 81.32 (41.20, 102.97) mL/min/1.73 m2 vs. 99.43 (79.00, 118.50) to 89.44 (63.69, 105.30) mL/min/1.73 m2; P=0.034]. The rate of eGFR decrease was more pronounced in patients with preeclampsia (17.38% vs. 10.05%, p<0.05). Multivariate analysis revealed that early-onset preeclampsia (preeclampsia that developed before 34 weeks of gestation) (HR=2.61, 95% CI=1.32-5.16, P=0.006) and late-onset preeclampsia (HR=2.54, 95% CI=1.34-4.83, P=0.004) were both risk factors for an eGFR decrease >30% or ESKD. CONCLUSION: Preeclampsia was associated with a greater risk of long-term kidney function decline or ESKD among CKD patients, especially in patients with early-onset preeclampsia.

Genome-wide meta-analysis identifies ancestry-specific loci for Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD) is a devastating neurological disease with complex genetic etiology. Yet most known loci have only identified from the late-onset type AD in populations of European ancestry. METHODS: We performed a two-stage genome-wide association study (GWAS) of AD totaling 6878 Chinese and 63,926 European individuals. RESULTS: In addition to the apolipoprotein E (APOE) locus, our GWAS of two independent Chinese samples uncovered three novel AD susceptibility loci (KIAA2013, SLC52A3, and TCN2) and a novel ancestry-specific variant within EGFR (rs1815157). More replicated variants were observed in the Chinese (31%) than in the European samples (15%). In combining genome-wide associations and functional annotations, EGFR and TCN2 were prioritized as two of the most biologically significant genes. Phenome-wide Mendelian randomization suggests that high mean corpuscular hemoglobin concentration might protect against AD. DISCUSSION: The current study reveals novel AD susceptibility loci, emphasizes the importance of diverse populations in AD genetic research, and advances our understanding of disease etiology. HIGHLIGHTS: Loci KIAA2013, SLC52A3, and TCN2 were associated with Alzheimer's disease (AD) in Chinese populations. rs1815157 within the EGFR locus was associated with AD in Chinese populations. The genetic architecture of AD varied between Chinese and European populations. EGFR and TCN2 were prioritized as two of the most biologically significant genes. High mean corpuscular hemoglobin concentrations might have protective effects against AD.

Gender differences, academic patenting, and tenure-track reform in China: Evidence from life sciences at elite universities.

This study is the first to examine the gender gap in academic patenting among faculty members in Chinese universities, a critical issue for the sustainable development of scientific research and innovation. Using a unique dataset that includes the patenting activities and professional status of 1,836 faculty members in life science-related departments at 36 top Chinese universities, this research reveals an evolving landscape of patenting dynamics. The trend of male faculty members leading in the annual number of patent applications and patents granted has shifted among newly graduated faculty members. Female faculty submit and receive their first patent applications significantly earlier than male faculty. However, male faculty are more likely to be lead inventors, and this gender gap remains difficult to close, with female faculty more likely to be supporting inventors. This research is contextualized within the broader framework of China's university tenure reform and the growing presence of women in the life sciences. While progress is evident, the study uncovers persistent systemic barriers that prevent women from fully translating their research into patentable innovations. By identifying these social and institutional barriers, our study not only sheds light on the gender gap, but also suggests policy measures to promote gender equity in scientific innovation, making it a critical read for policymakers and academic leaders.

Efficacy of the two-parts wrapping technique in reducing postoperative complications in laparoscopic pancreaticoduodenectomy.

BACKGROUND: The advancement of laparoscopic technology has broadened the application of laparoscopic pancreaticoduodenectomy (LPD) for treating pancreatic head and ampullary tumors. Despite its benefits, postoperative pancreatic fistula (POPF) and postpancreatectomy hemorrhage (PPH) remain significant complications. Ligamentum teres hepatis wrapping around the gastroduodenal artery (GDA) stump show limitations in reducing POPF and PPH. METHODS: This study retrospectively analyzed patients undergoing LPD from January 2016 to October 2023, We compared the effectiveness of the two-parts wrapping (the ligamentum teres hepatis wrapping of the gastroduodenal artery stump and the omentum flap wrapping of the pancreatojejunal anastomosis) and ligamentum teres hepatis wrapping around the gastroduodenal artery (GDA) in reducing postoperative pancreatic fistula (POPF) and postpancreatectomy hemorrhage (PPH), using propensity score matching for the analysis. RESULTS: A total of 172 patients were analyzed, showing that the two-parts wrapping group significantly reduced the rates of overall and severe complications, POPF, and PPH compared to ligamentum teres hepatis wrapping around the GDA group. Specifically, the study found lower rates of grade B/C POPF and no instances of PPH in the two-parts wrapping group, alongside shorter postoperative hospital stays and drainage removal times. These benefits were particularly notable in patients with soft pancreatic textures and pancreatic duct diameters of < 3 mm. CONCLUSION: The two-parts wrapping technique significantly reduce the risks of POPF and PPH in LPD, offering a promising approach for patients with soft pancreas and pancreatic duct diameter of < 3 mm.

A Deep Learning-Based Method for Preventing Data Leakage in Electric Power Industrial Internet of Things Business Data Interactions.

In the development of the Power Industry Internet of Things, the security of data interaction has always been an important challenge. In the power-based blockchain Industrial Internet of Things, node data interaction involves a large amount of sensitive data. In the current anti-leakage strategy for power business data interaction, regular expressions are used to identify sensitive data for matching. This approach is only suitable for simple structured data. For the processing of unstructured data, there is a lack of practical matching strategies. Therefore, this paper proposes a deep learning-based anti-leakage method for power business data interaction, aiming to ensure the security of power business data interaction between the State Grid business platform and third-party platforms. This method combines named entity recognition technologies and comprehensively uses regular expressions and the DeBERTa (Decoding-enhanced BERT with disentangled attention)-BiLSTM (Bidirectional Long Short-Term Memory)-CRF (Conditional Random Field) model. This method is based on the DeBERTa (Decoding-enhanced BERT with disentangled attention) model for pre-training feature extraction. It extracts sequence context semantic features through the BiLSTM, and finally obtains the global optimal through the CRF layer tag sequence. Sensitive data matching is performed on interactive structured and unstructured data to identify privacy-sensitive information in the power business. The experimental results show that the F1 score of the proposed method in this paper for identifying sensitive data entities using the CLUENER 2020 dataset reaches 81.26%, which can effectively prevent the risk of power business data leakage and provide innovative solutions for the power industry to ensure data security.

Effects of gossypol acetate on growth, serum biochemical parameters, and intestinal health of goslings.

Free gossypol (FG), the primary antinutritional component in cottonseed meal, can adversely affect the growth and health of poultry. Although younger geese are particularly sensitive to FG, the precise effects of FG on geese remain elusive. This study aimed to investigate the effects of gossypol acetate (GA), a form of FG, on the growth, serum biochemical parameters, and intestinal health of goslings. Seventy-two healthy male goslings, aged 7-day-old with similar body weight (BW), were randomly divided into 3 groups: a control group and 2 GA-treated groups (GA25 and GA50), which were orally administered GA (25 and 50 mg/kg BW) daily for 14 d. The results showed that oral administration of GA significantly suppressed BW, altered serum parameters, and impaired intestinal health in a dose- and time-dependent manner. Specifically, GA adversely affected intestinal morphology, induced oxidative stress, and inflammation, diminished immune function, and increased intestinal permeability and apoptosis of intestinal cells, consequently impairing nutrient absorption and utilization of goslings. Overall, these data indicate that GA adversely affects the growth, serum parameters, and intestinal health of goslings, providing valuable information further to understand the toxic effects of gossypol on goslings.

Synergic effects and possible mechanism of emodin and stilbene glycosides on colorectal cancer.

BACKGROUND: Polygonum multiflorum (PM) is a core herb that enhances immunity. It can also detoxify, reduce swelling, and intercept malaria. Its main components, emodin (EMD) and 2,3,5,4'-Tetrahydroxy stilbene-2-O-ß-D-glucoside (stilbene glycoside, TSG), have good anti-cancer potential. PURPOSE: The study aims to investigate synergic effects of EMD and TSG on CRC and its possible mechanism. METHODS: Network pharmacology and bioinformatics were used to identify targets. HPLC was used to analyze the effective ingredients in PM and to determine the content of the main ingredients. HT-29 cells were used for in vitro experiments. Cell Counting Kit-8 (CCK8) and scratch test were used to detect the effects of various chemical components of PM on the proliferation and migration of HT-29 cells, and Western Bolt (WB) test was used to evaluate the effects of EMD and TSG on P53 pathway. In vivo experiments, the effects of EMD and TSG were evaluated by measuring tumor weight and tumor volume in CRC mice model and histological analysis were carried out with HE staining. The expressions of HSP90, P53, COX2, and ROS were detected by quantitative reverse transcription polymerase chain reaction (PCR), and IL-1ß, IL-4, IL-6, IL-10, TGF-ß and IFN-γ were detected by enzyme linked immunosorbent assay (ELISA). WB and Immunohistochemistry (IHC) were used to detect the expression of P53 related proteins. RESULTS: Network pharmacology showed PM closely related to colorectal cancer pathway and the core targets included STAT3 and P53; bioinformatics indicated P53 played an important role in the development and prognosis of CRC; chemical analysis showed identified and quantified gallic acid (GA), cis-TSG, trans-TSG, Emodin glucoside(EMDG), physcion glucoside (PHYG), EMD in PM; EMD induced apoptosis and TSG inhibited migration of HT-29 cells; EMD and TSG could coordinately shrink tumor size of CRC mice, elevate expressions of F4/80, decrease the content of IL-6 and TGF-ß, promote tumor oxidized and reduce expression of P53 and STAT3 in the tumor. CONCLUSIONS: In vitro experiments showed that TSG inhibited cancer cell migration and EMD induced apoptosis. EMD and TSG had synergic effects on CRC, whose possible mechanism might be to regulate the expression of cytokines and inhibit P53 pathway.

Decrotonylation of cGAS K254 prompts homologous recombination repair by blocking its DNA binding and releasing PARP1.

Cyclic GMP-AMP synthase (cGAS), a cytosolic DNA sensor, also exhibits nuclear genomic localization and is involved in DNA damage signaling. In this study, we investigated the impact of cGAS crotonylation on the regulation of the DNA damage response, particularly homologous recombination repair, following exposure to ionizing radiation (IR). Lysine 254 of cGAS is constitutively crotonylated by the CREB-binding protein; however, IR-induced DNA damage triggers SIRT3-mediated decrotonylation. Lysine 254 decrotonylation decreased the DNA-binding affinity of cGAS and inhibited its interaction with PARP1, promoting HR repair. Moreover, SIRT3 suppression led to HR repair inhibition and markedly sensitized cancer cells to IR and DNA-damaging chemicals, highlighting SIRT3 as a potential target for cancer therapy. Overall, this study revealed the crucial role of cGAS crotonylation in the DNA damage response. Furthermore, we propose that modulating cGAS and SIRT3 activities could be potential strategies for cancer therapy.

Predicting the distribution of potentially suitable habitat in China for Cirsium japonicum Fisch. ex DC. under future climate scenarios based on the R-optimized MaxEnt model.

Cirsium japonicum contains a variety of medicinal components with good clinical efficacy. With the rapid changes in global climate, it is increasingly important to study the distribution of species habitats and the factors influencing their adaptability. Utilizing the MaxEnt model, we forecasted the present and future distribution regions of suitable habitats for C. japonicum under various climate scenarios. The outcome showed that under the current climate, the total suitable area of C. japonicum is 2,303,624 km2 and the highly suitable area is 79,117 km2. The distribution of C. japonicum is significantly influenced by key environmental factors such as temperature annual range, precipitation of the driest month, and precipitation of the wettest month. In light of future climate change, the suitable habitat for C. japonicum is anticipated to progressively relocate toward the western and northern regions, leading to an expansion in the total suitable area. These findings offer valuable insights into the conservation, sustainable utilization, and standardized cultivation of wild C. japonicum resources.

Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease.

Recent expansion of proteomic coverage opens unparalleled avenues to unveil new biomarkers of Alzheimer's disease (AD). Among 6,361 cerebrospinal fluid (CSF) proteins analysed from the ADNI database, YWHAG performed best in diagnosing both biologically (AUC = 0.969) and clinically (AUC = 0.857) defined AD. Four- (YWHAG, SMOC1, PIGR and TMOD2) and five- (ACHE, YWHAG, PCSK1, MMP10 and IRF1) protein panels greatly improved the accuracy to 0.987 and 0.975, respectively. Their superior performance was validated in an independent external cohort and in discriminating autopsy-confirmed AD versus non-AD, rivalling even canonical CSF ATN biomarkers. Moreover, they effectively predicted the clinical progression to AD dementia and were strongly associated with AD core biomarkers and cognitive decline. Synaptic, neurogenic and infectious pathways were enriched in distinct AD stages. Mendelian randomization did not support the significant genetic link between CSF proteins and AD. Our findings revealed promising high-performance biomarkers for AD diagnosis and prediction, with implications for clinical trials targeting different pathomechanisms.

Gender bias in child custody judgments: Evidence from Chinese family court.

Based on a quantitative analysis of a novel dataset comprising 10,093 publicly available judgments of adjudicated child custody disputes from the China Judgments Online website, this article identifies potential gender bias in Chinese family courts under certain conditions. Key findings include: 1. Mothers are generally more proactive in seeking custody and are awarded custody in the majority of cases compared to fathers. 2. Specifically, mothers have a significant advantage in cases involving daughters, while their advantage in cases involving sons is less pronounced. 3. In rural courts, the results are notably different: mothers are disadvantaged overall, fathers are particularly assertive in seeking custody of sons compared to daughters, and mothers are less likely than fathers to be awarded custody of sons. Building on existing literature, this study highlights potential judicial biases rooted in societal gender norms prevalent in rural areas. This raises questions about whether courts have achieved substantive gender equality and whether the legal principle of 'the best interests of the child' is consistently upheld in every court decision. This study enhances the understanding of gender bias within China's family court system by providing valuable insights for those interested in addressing gender inequality. It not only highlights specific challenges women face in custody cases but also calls for broader societal and policy changes to support women and combat gender discrimination in all its forms.

Energy transition: Cap-and-trade and carbon capture and storage for achieving net-zero emissions with sustainable insurance.

This paper introduces an energy transition model featuring a carbon-intensive manufacturer that adopts sustainable insurance, participates in a cap-and-trade scheme, and implements carbon capture and storage (CCS) transit, all aimed at achieving the net-zero carbon emission target. The model utilizes a down-and-out call (DOC) approach to evaluate the manufacturer's equity, considering the bankruptcy risk prior to maturity due to carbon intensity. The equity of the life insurer providing funds is assessed using a capped DOC method to address the capped credit risk from the manufacturer. The findings reveal that increased adoption of CCS transit diminishes manufacturer equity, heightens default risk, and reduces insurer equity, with these effects exacerbated by advanced CCS technology and stringent cap-and-trade caps. Both stringent cap-and-trade schemes and rapid advancements in CCS transit practices, particularly with the use of advanced CCS technology, deviate from the net-zero target. A critical policy implication is the necessity for the precise calibration of cap-and-trade schemes and the pace of CCS transit adoption to ensure alignment with net-zero targets.

Interventricular septum involvement is related to right ventricular dysfunction in anterior STEMI patients without right ventricular infarction: a cardiovascular magnetic resonance study.

The value of cardiovascular magnetic resonance (CMR) in assessing and predicting acute right ventricular (RV) dysfunction in patients with anterior ST-segment elevation myocardial infarction (STEMI) remains ascertained. Eighty eight patients with anterior STEMI were prospectively recruited and underwent CMR examinations within one week following the coronary intervention. Patients with RV ejection fraction (RVEF) less than 2 standard deviations below the average at the center (RVEF ≤ 45.0%) were defined as having RV dysfunction. The size of infarction, segmental wall motion, and T1 and T2 mapping values of global myocardium and the interventricular septum (IVS) were measured. Predictive performance was calculated using receiver-operating characteristic curve analysis and logistic regression test. Twenty two patients presented with RV dysfunction. The RV dysfunction group had a larger IVS infarct extent (54.28 ± 10.35 vs 33.95 ± 15.09%, P < 0.001) and lower left ventricle stroke volume index (33.93 ± 7.96 vs 42.46 ± 8.14 ml/m2, P < 0.001) compared to the non-RV dysfunction group. IVS infarct extent at 48.8% best predicted the presence of RV dysfunction with an area under the curve of 0.864. Left ventricular stroke volume index (LVSVI) and IVS infarct extent were selected by stepwise multivariable logistic regression analysis. Lower LVSVI (odds ratio [OR] 0.90; 95% confidence interval [CI], 0.79 to 0.99; P = 0.044) and higher IVS infarct extent (OR 1.16; 95% CI 1.05 to 1.33; P = 0.01) were found to be independent predictors for RV dysfunction. In patients with anterior STEMI, those with larger IVS infarct extent and worse LV function are more likely to be associated with RV dysfunction.

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Objective: Atrial fibrillation (AF) is a disease of high heterogeneity, and the association between AF phenotypes and the outcome of different catheter ablation strategies remains unclear. Conventional classification of AF (e.g. according to duration, atrial size, and thromboembolism risk) fails to provide reference for the optimal stratification of the prognostic risks or to guide individualized treatment plan. In recent years, research on machine learning has found that cluster analysis, an unsupervised data-driven approach, can uncover the intrinsic structure of data and identify clusters of patients with pathophysiological similarity. It has been demonstrated that cluster analysis helps improve the characterization of AF phenotypes and provide valuable prognostic information. In our cohort of AF inpatients undergoing radiofrequency catheter ablation, we used unsupervised cluster analysis to identify patient subgroups, to compare them with previous studies, and to evaluate their association with different suitable ablation patterns and outcomes. Methods: The participants were AF patients undergoing radiofrequency catheter ablation at West China Hospital between October 2015 and December 2017. All participants were aged 18 years or older. They underwent radiofrequency catheter ablation during their hospitalization. They completed the follow-up process under explicit informed consent. Patients with AF of a reversible cause, severe mitral stenosis or prosthetic heart valve, congenital heart disease, new-onset acute coronary syndrome within three months prior to the surgery, or a life expectancy less than 12 months were excluded according to the exclusion criteria. The cohort consisted of 1102 participants with paroxysmal or persistent/long-standing persistent AF. Data on 59 variables representing demographics, AF type, comorbidities, therapeutic history, vital signs, electrocardiographic and echocardiographic findings, and laboratory findings were collected. Overall, data for the variables were rarely missing (<5%), and multiple imputation was used for correction of missing data. Follow-up surveys were conducted through outpatient clinic visits or by telephone. Patients were scheduled for follow-up with 12-lead resting electrocardiography and 24-hours Holter monitoring at 3 months and 6 months after the ablation procedure. Early ablation success was defined as the absence of documented AF, atrial flutter, or atrial tachycardia >30 seconds at 6-month follow-up. Hierarchical clustering was performed on the 59 baseline variables. All characteristic variables were standardized to have a mean of zero and a standard deviation of one. Initially, each patient was regarded as a separate cluster, and the distance between these clusters was calculated. Then, the Ward minimum variance method of clustering was used to merge the pair of clusters with the minimum total variance. This process continued until all patients formed one whole cluster. The "NbClust" package in R software, capable of calculating various statistical indices, including pseudo t2 index, cubic clustering criterion, silhouette index etc, was applied to determine the optimal number of clusters. The most frequently chosen number of clusters by these indices was selected. A heatmap was generated to illustrate the clinical features of clusters, while a tree diagram was used to depict the clustering process and the heterogeneity among clusters. Ablation strategies were compared within each cluster regarding ablation efficacy. Results: Five statistically driven clusters were identified: 1) the younger age cluster (n=404), characterized by the lowest prevalence of cardiovascular and cerebrovascular comorbidities but the highest prevalence of obstructive sleep apnea syndrome (14.4%); 2) a cluster of elderly adults with chronic diseases (n=438), the largest cluster, showing relatively higher rates of hypertension, diabetes, stroke, and chronic obstructive pulmonary disease; 3) a cluster with high prevalence of sinus node dysfunction (n=160), with patients showing the highest prevalence of sick sinus syndrome and pacemaker implantation; 4) the heart failure cluster (n=80), with the highest prevalence of heart failure (58.8%) and persistent/long-standing persistent AF (73.7%); 5) prior coronary artery revascularization cluster (n=20), with patients of the most advanced age (median: 69.0 years old) and predominantly male patients, all of whom had prior myocardial infarction and coronary artery revascularization. Patients in cluster 2 achieved higher early ablation success with pulmonary veins isolation alone compared to extensive ablation strategies (79.6% vs. 66.5%; odds ratio [OR]=1.97, 95% confidence interval [CI]: 1.28-3.03). Although extensive ablation strategies had a slightly higher success rate in the heart failure group, the difference was not statistically significant. Conclusions: This study provided a unique classification of AF patients undergoing catheter ablation by cluster analysis. Age, chronic disease, sinus node dysfunction, heart failure and history of coronary artery revascularization contributed to the formation of the five clinically relevant subtypes. These subtypes showed differences in ablation success rates, highlighting the potential of cluster analysis in guiding individualized risk stratification and treatment decisions for AF patients.

Leveraging advances in data-driven deep learning methods for hybrid epidemic modeling.

Mathematical modeling of epidemic dynamics is crucial to understand its underlying mechanisms, quantify important parameters, and make predictions that facilitate more informed decision-making. There are three major types of models: mechanistic models including the SEIR-type paradigm, alternative data-driven (DD) approaches, and hybrid models that combine mechanistic models with DD approaches. In this paper, we summarize our work in the COVID-19 Scenario Modeling Hub (SMH) for more than 12 rounds since early 2021 for informed decision support. We emphasize the importance of deep learning techniques for epidemic modeling via a flexible DD framework that substantially complements the mechanistic paradigm to evaluate various future epidemic scenarios. We start with a traditional curve-fitting approach to model cumulative COVID-19 based on the underlying SEIR-type mechanisms. Hospitalizations and deaths are modeled as binomial processes of cases and hospitalization, respectively. We further formulate two types of deep learning models based on multivariate long short term memory (LSTM) to address the challenges of more traditional DD models. The first LSTM is structurally similar to the curve fitting approach and assumes that hospitalizations and deaths are binomial processes of cases. Instead of using a predefined exponential curve, LSTM relies on the underlying data to identify the most appropriate functions, and is capable of capturing both long-term and short-term epidemic behaviors. We then relax the assumption of dependent inputs among cases, hospitalizations, and death. Another type of LSTM that handles all input time series as parallel signals, the independent multivariate LSTM, is developed. Independent multivariate LSTM can incorporate a wide range of data sources beyond traditional case-based epidemiological surveillance. The DD framework unleashes its potential in big data era with previously neglected heterogeneous surveillance data sources, such as syndromic, environment, genomic, serologic, infoveillance, and mobility data. DD approaches, especially LSTM, complement and integrate with the mechanistic modeling paradigm, provide a feasible alternative approach to model today's complex socio-epidemiological systems, and further leverage our ability to explore different scenarios for more informed decision-making during health emergencies.

Antibody Levels and Infection Status of Pertussis in the Population under Pertussis Resurgence in Guangxi in 2018: A Cross-Sectional Survey.

Objective: Pertussis cases have increased markedly since 2018 in Guangxi. The aim of this study was to evaluate antibody levels and the infection status of pertussis in the resident population. Method: A total of 10,215 serum samples from residents were collected from August-November 2018 and tested for anti-pertussis IgG and toxin IgG using the enzyme-linked immunosorbent assay (ELISA). Results: Of the collected samples, 1,833 (17.94%) tested positive for anti-pertussis IgG, with the median concentration of 16.06 IU/mL. Antibody level < 10 IU/mL accounted for more than 60% in children under 4 years of age, but declined with age, whereas the percentages of the other three levels (10-40, 40-50, and ≥ 50 IU/mL) increased almost with age ( P < 0.001). Moreover, 7,924 samples were selected for anti-pertussis toxin IgG, of which 653 (8.24%) tested positive (≥ 40 IU/mL) with the median concentration of 5.89 IU/mL, and 204 participants (2.56%) had recent pertussis infection (≥ 100 IU/mL). Among the different age groups, the highest rates of positivity and recent infection were observed at 11-20 years of age, the lowest positivity rate at 5 years of age, and the lowest recent infection rate at 4 years of age ( P < 0.001, P = 0.005, respectively). Conclusion: The survey results showed that all age groups in Guangxi lacked immunity against pertussis, which was one of the main factors contributing to the resurgence of pertussis in 2018. In addition, the prevalence of pertussis is relatively high in Guangxi, and its incidence is seriously underestimated, especially in adolescents and adults.

Novel diagnostic and prognostic approach for rapidly progressive dementias: Indicators based on amyloid/tau/neurodegeneration (ATN) framework.

AIMS: Apply established cerebrospinal fluid (CSF) and serum biomarkers and novel combined indicators based on the amyloid/tau/neurodegeneration (ATN) framework to improve diagnostic and prognostic power in patients with rapidly progressive dementias (RPDs). METHODS: CSF and serum biomarkers of Alzheimer's disease (AD) common neuropathology including Aß42, Aß40, p-Tau, and t-Tau were measured in cognitively normal (CN) controls (n = 33) and three RPD groups with rapidly progressive AD (rpAD, n = 23), autoimmune encephalitis (AE, n = 25), and Creutzfeldt-Jakob disease (CJD, n = 28). Logistic regression and multiple linear regression were used for producing combined indicators and prognostic assessment, respectively, including A&T, A&N, T&N, A&T&N, etc. RESULTS: Combined diagnostic indicator with A&T&N had the potential for differentiating AE from other types of RPDs, identifying 62.51% and 75% of AE subjects based on CSF and serum samples, respectively, compared to 39.13% and 37.5% when using autoantibodies. CSF t-Tau was associated with survival in the CJD group (adjusted R-Square = 0.16, p = 0.02), and its prognosis value improved when using combined predictors based on the ATN framework (adjusted R-Square = 0.273, p = 0.014). CONCLUSION: Combined indicators based on the ATN framework provide a novel perspective for establishing biomarkers for early recognition of RPDs due to treatment-responsive causes.

Comparison of vonoprazan bismuth-containing triple therapy with quadruple therapy in Helicobacter pylori-infected treatment-naive patients: a prospective multicenter randomized controlled trial.

BACKGROUND AND AIM: Helicobacter pylori infection is linked to various gastrointestinal conditions, such as chronic active gastritis, peptic ulcers, and gastric cancer. Traditional treatment options encounter difficulties due to antibiotic resistance and adverse effects. Therefore, the aim of this study was to explore the effectiveness of a new treatment plan that combines vonoprazan (VPZ), amoxicillin, and bismuth for the eradication of H. pylori. METHODS: A total of 600 patients infected with H. pylori were recruited for this multicenter randomized controlled trial. Patients treated for H. pylori elimination were randomly assigned at a 1:1 ratio to receive 14 days of vonoprazan-based triple therapy (vonoprazan + amoxicillin + bismuth, group A) or standard quadruple therapy (esomeprazole + clarithromycin + amoxicillin + bismuth, group B). Compliance and adverse effects were tracked through daily medication and side effect records. All patients underwent a 13C/14C-urea breath test 4 weeks after treatment completion. RESULTS: Intention-to-treat (ITT) and per-protocol (PP) analyses revealed no substantial differences in H. pylori eradication rates between groups A and B (ITT: 83.7% vs 83.2%; PP: 90.9% vs 89.7%). However, significant differences were observed in the assessment of side effects (13.7% vs 28.6%, P < 0.001). Specifically, group A had significantly fewer "bitter mouths" than group B did (3.7% vs 16.2%, P < 0.001). CONCLUSION: Triple therapy comprising vonoprazan (20 mg), amoxicillin (750 mg), and bismuth potassium citrate (220 mg) achieved a PP eradication rate ≥90%, paralleling standard quadruple therapy, and had fewer adverse events and lower costs (¥306.8 vs ¥645.8) for treatment-naive patients.