Using PRECIS-2 in Chinese herbal medicine randomized controlled trials for irritable bowel syndrome: A methodological exploration based on literature.

Background: The pragmatism levels of randomized controlled trials (RCTs) mean how similar the interventions delivered in the trial setting match those in the setting where the results will be applied. We aimed to investigate the association between the consistency of pragmatism among the characteristics of RCT design and its effect size of results in Chinese herbal medicine (CHM) for irritable bowel syndrome (IBS). Methods: Eight English and Chinese language databases were searched for RCTs on CHM for IBS. Six reviewers independently assessed the pragmatism of trials using the pragmatic-explanatory continuum indicator summary 2 (PRECIS-2) tool. The consistency of pragmatism levels among the characteristics of RCT design was calculated using the coefficient of variation. Linear regression models were adopted to explore influence factors of the pragmatism of RCTs. Results: 78 RCTs were included. The level of consistency in the pragmatism for RCT's design was significantly correlated with the effect size of the results (binary outcome, r = -0.413; P = 0.005; continuous outcome, r = -0.779, P < 0.001). PRECIS-2 score was higher in trials with individualized interventions than fixed interventions (3.29 [0.32] vs 2.90 [0.32]; Cohen's d relative effect size, 0.52; P < 0.001) and in standard or usual-treatment-controlled trials than placebo-controlled (3.05 [0.37] vs 2.83 [0.28]; Cohen's d relative effect size, 0.32; P = 0.048). Conclusion: The consistency of pragmatism level across the 9 domains of the PRECIS-2 tool in CHM IBS RCTs was positively correlated with the effect size of the results.

How fragile the positive results of Chinese herbal medicine randomized controlled trials on irritable bowel syndrome are?

OBJECTIVE: The fragility index (FI), which is the minimum number of changes in status from "event" to "non-event" resulting in a loss of statistical significance, serves as a significant supplementary indicator for clinical physicians in interpreting clinical trial results and aids in understanding the outcomes of randomized controlled trials (RCTs). In this systematic literature survey, we evaluated the FI for RCTs evaluating Chinese herbal medicine (CHM) for irritable bowel syndrome (IBS), and explored potential associations between study characteristics and the robustness of RCTs. METHODS: A comprehensive search was conducted in four databases in Chinese and four databases in English from their inception to January 1, 2023. RCTs encompassed 1:1 ratio into two parallel arms and reported at least one binary outcome that demonstrated statistical significance were included. FI was calculated by the iterative reduction of a target outcome event in the treatment group and concomitant subtraction of a non-target event from that group, until positive significance (defined as P < 0.05 by Fisher's exact test) is lost. The lower the FI (minimum 1) of a trial outcome, the more fragile the positive result of the outcome was. Linear regression models were adopted to explore influence factors of the value of FI. RESULTS: A total of 30 trials from 2 4118 potentially relevant citations were finally included. The median FI of total trials included was 1.5 (interquartile range [IQR], 1-5), and half of the trials (n = 15) had a FI equal to 1. In 12 trials (40%), the total number of participants lost to follow-up surpassed the respective FI. The study also identified that increased FI was significantly associated with no TCM syndrome differentiation for inclusion criteria of the patients, larger total sample size, low risk of bias, and larger numbers of events. CONCLUSIONS: The majority of CHM IBS RCTs with positive results were found to be fragile. Ensuring adequate sample size, scientifically rigorous study design, proper control of confounding factors, and a quality control calibration for consistency of TCM diagnostic results among clinicians should be addressed to increase the robustness of the RCTs. We recommend reporting the FI as one of the components of sensitivity analysis in future RCTs to facilitate the assessment of the fragility of trials.

Interpretable prediction, classification and regulation of water quality: A case study of Poyang Lake, China.

Effective identification and regulation of water quality impact factors is essential for water resource management and environmental protection. However, the complex coupling of water quality systems poses a significant challenge to this task. This study proposes coherent model for water quality prediction, classification and regulation based on interpretable machine learning. The decomposition-reconstruction module is used to transform non-stationary water quality series into stationary series while effectively reducing the feature dimensions. Spatiotemporal multi-source data is introduced by using the Maximum Information Coefficient (MIC) for feature selection. The Temporal Convolutional Network (TCN) is used to extract the temporal features of different variables, followed by the introduction of External Attention mechanism (EA) to construct the relationship between these features. Finally, the target water quality sequence is simulated using Gated Recurrent Unit (GRU). The proposed model was applied to Poyang Lake in China to predict six water quality indicators: ammonia nitrogen (NH3-N), dissolved oxygen (DO), pH, total nitrogen (TN), total phosphorus (TP), water temperature (WT). The water quality was then classified based on the prediction results using the XGBoost algorithm. The findings indicate that the proposed model's Nash-Sutcliff Efficiency (NSE) value ranges from 0.88 to 0.99, surpassing that of the benchmark model, and demonstrates strong interval prediction performance. The results highlight the superior performance of the XGBoost algorithm (with an accuracy of 0.89) in addressing water quality classification issues, particularly in cases of category imbalance. Subsequently, interpretability analysis using the SHapley Additive exPlanation (SHAP) method revealed that the model is capable of learning relationships between different variables and there exists a possibility of learning the physical laws. Ultimately, this study proposes a water quality regulation mechanism that improves TN and DO levels by stepwise changing the magnitude of water temperature, which significantly improves in the case of data limitations. In conclusion, this study presents an overall framework for integrating water quality prediction, classification and improvement for the first time, forming a complete set of water quality early warning and improvement management strategies. This framework provides new ideas and ways for lake water quality management.

[Mutation of the envelope stress-responsive protein CpxA capable of regulating the antimicrobial resistance and virulence of bacteria].

CpxA is a key member of the envelope stress-responsive Cpx two-component system ubiquitous in Gram-negative bacteria. It is responsible for signal sensing and has dual activities of phosphatase and kinase. CpxA has been revealed to participate in the regulation of physiological processes such as virulence and antimicrobial resistance of bacteria. In recent years, the development of novel antimicrobials targeting CpxA has attracted much attention. Drugs developed based on inhibition of the phosphatase activity of CpxA have shown effectiveness in the treatment of urinary tract infections caused by Escherichia coli. This review introduces the structure and functional domains of CpxA and the activation of Cpx pathways by CpxA. Furthermore, it summarizes the roles of CpxA in the development of antimicrobial resistance and the regulation of bacterial virulence and reviews the latest progress in the development of new antimicrobials targeting this protein. It is expected to assist in the exploration of CpxA-targeting anti-infection strategies for severely antimicrobial-resistant bacteria whose clinical infections are of urgent need to be controlled.

Hospital-Treated Infectious Diseases, Infection Burden, and Risk of Lung Cancer: An Observational and Mendelian Randomization Study.

BACKGROUND: Although infections play a role in the development of lung cancer, the longitudinal association between infection and the risk of lung cancer is disputed, and data relating to pathogen types and infection sites are sparse. RESEARCH QUESTION: How do infections affect subsequent lung cancer risk, and is the impact limited to specific microbes rather than infection burden? STUDY DESIGN AND METHODS: Data on > 900 infectious diseases were gathered from the UK Biobank study. Short- and long-term effects of infections were assessed by using time-varying Cox proportional hazards models. The analysis was repeated, excluding patients with concurrent multi-pathogen infections or outcomes within the 10 years following the initial hospitalization for the index infection. A life table approach was used to estimate years of life lost from lung cancer. Infection burden was defined as the sum of the number of infection episodes over time and co-occurring infections. The genome-wide association studies used in two-sample Mendelian randomization were obtained from mostly European ancestry. RESULTS: Hospital-treated infectious disease was associated with a greater risk of lung cancer (adjusted hazard ratio [aHR], 1.79; 95% CI, 1.74-1.83). aHRs for lung cancer ranged from 1.39 to 2.82 across pathogen types. The impact of lower respiratory tract infections (LRTIs) on lung cancer was the strongest, with an aHR of 3.22 (95% CI, 2.64-3.92); the aHR for extra-LRTIs was 1.29 (95% CI, 1.16-1.44). A dose-response association was observed between infection burden and lung cancer risk across different FEV1 percent predicted (Ptrend < .001). Multiple infections led to significant life lost from lung cancer at the age of 50 years. Mendelian randomization analysis reaffirmed the causal association. INTERPRETATION: Both observational and genetic analyses suggest that infectious diseases could increase the risk of lung cancer. The dual perspective on the LRTIs and extra-LRTIs impacts may inform lung cancer prevention strategies.

The association between circulating CD34+CD133+ endothelial progenitor cells and reduced risk of Alzheimer's disease in the Framingham Heart Study.

Aim: Endothelial dysfunction has been associated with both cerebrovascular pathology and Alzheimer's disease (AD). However, the connection between circulating endothelial cells and the risk of AD remains uncertain. The objective was to leverage data from the Framingham Heart Study to investigate various circulating endothelial subtypes and their potential correlations with the risk of AD. Methods: The study conducted data analyses using Cox proportional hazard regression and linear regression methods. Additionally, genome-wide association study (GWAS) was carried out to further explore the data. Results: Among the eleven distinct circulating endothelial subtypes, only circulating endothelial progenitor cells (EPCs) expressing CD34+CD133+ were found to be negatively and dose-dependently associated with reduced AD risk. This association persisted even after adjusting for age, sex, years of education, apolipoprotein E (APOE) ε4 status, and various vascular diseases. Particularly noteworthy was the significant association observed in individuals with hypertension and cerebral microbleeds. Consistently, positive associations were identified between CD34+CD133+ EPCs and specific brain regions, such as higher proportions of circulating CD34+CD133+ cells correlating with increased volumes of white matter and the hippocampus. Additionally, a GWAS study unveiled that CD34+CD133+ cells influenced AD risk specifically in individuals with homozygous genotypes for variants in two stem cell-related genes: kirre like nephrin family adhesion molecule 3 (KIRREL3, rs580382 CC and rs4144611 TT) and exocyst complex component 6B (EXOC6B, rs61619102 CC). Conclusions: The findings suggest that circulating CD34+CD133+ EPCs possess a protective effect and may offer a new therapeutic avenue for AD, especially in individuals with vascular pathology and those carrying specific genotypes of KIRREL3 and EXOC6B genes.

Hospital-treated infectious diseases, genetic susceptibility and risk of type 2 diabetes: A population-based longitudinal study.

BACKGROUND: The longitudinal association between infectious diseases and the risk of type 2 diabetes (T2D) remains unclear. METHODS: Based on the UK Biobank, the prospective cohort study included a total of 396,080 participants without diabetes at baseline. We determined the types and sites of infectious diseases and incident T2D using the International Classification of Diseases 10th Revision codes (ICD-10). Time-varying Cox proportional hazard model was used to assess the association. Infection burden was defined as the number of infection episodes over time and the number of co-occurring infections. Genetic risk score (GRS) for T2D consisted of 424 single nucleotide polymorphisms. RESULTS: During a median of 9.04 [IQR, 8.3-9.7] years of follow-up, hospital-treated infectious diseases were associated with a greater risk of T2D (adjusted HR [aHR] 1.54 [95 % CI 1.46-1.61]), with risk difference per 10,000 individuals equal to 154.1 [95 % CI 140.7-168.2]. The heightened risk persisted after 5 years following the index infection. Bacterial infection with sepsis had the strongest risk of T2D (aHR 2.95 [95 % CI 2.53-3.44]) among different infection types. For site-specific analysis, bloodstream infections posed the greatest risk (3.01 [95 % CI 2.60-3.48]). A dose-response association was observed between infection burden and T2D risk within each GRS tertile (p-trend <0.001). High genetic risk and infection synergistically increased the T2D risk. CONCLUSION: Infectious diseases were associated with an increased risk of subsequent T2D. The risk showed specificity according to types, sites, severity of infection and the period since infection occurred. A potential accumulative effect of infection was revealed.

Hospital-treated infectious diseases, infection burden and risk of Parkinson disease: An observational and Mendelian randomization study.

BACKGROUND: Experimental and cross-sectional evidence has suggested a potential role of infection in the ethology of Parkinson's disease (PD). We aim to examine the longitudinal association of infections with the incidence of PD and to explore whether the increased risk is limited to specific infection type rather than infection burden. METHODS: Based on the UK Biobank, hospital-treated infectious diseases and incident PD were ascertained through record linkage to national hospital inpatient registers. Infection burden was defined as the sum of the number of infection episodes over time and the number of co-occurring infections. The polygenic risk score (PRS) for PD was calculated. The genome-wide association studies (GWAS) used in two-sample Mendelian Randomization (MR) were obtained from observational cohort participants of mostly European ancestry. RESULTS: Hospital-treated infectious diseases were associated with an increased risk of PD (adjusted HR [aHR] 1.35 [95 % CI 1.20-1.52]). This relationship persisted when analyzing new PD cases occurring more than 10 years post-infection (aHR 1.22 [95 % CI 1.04-1.43]). The greatest PD risk was observed in neurological/eye infection (aHR 1.72 [95 % CI 1.32-2.34]), with lower respiratory tract infection (aHR 1.43 [95 % CI 1.02-1.99]) ranked the second. A dose-response association was observed between infection burden and PD risk within each PD-PRS tertile (p-trend < 0.001). Multivariable MR showed that bacterial and viral infections increase the PD risk. CONCLUSIONS: Both observational and genetic analysis suggested a causal association between infections and the risk of developing PD. A dose-response relationship between infection burden and incident PD was revealed.

Association of hospital-treated infectious diseases and infection burden with cardiovascular diseases and life expectancy.

BACKGROUND: The association of a broad spectrum of infectious diseases with cardiovascular outcomes remains unclear. OBJECTIVES: We aim to provide the cardiovascular risk profiles associated with a wide range of infectious diseases and explore the extent to which infections reduce life expectancy. METHODS: We ascertained exposure to 900+ infectious diseases before cardiovascular disease (CVD) onset in 453,102 participants from the UK Biobank study. Time-varying Cox proportional hazard models were used. Life table was used to estimate the life expectancy of individuals aged ≥50 with different levels of infection burden (defined as the number of infection episodes over time and the number of co-occurring infections). RESULTS: Infectious diseases were associated with a greater risk of CVD events (adjusted HR [aHR] 1.79 [95% confidence interval {CI} 1.74-1.83]). For type-specific analysis, bacterial infection with sepsis had the strongest risk of CVD events [aHR 4.76 (4.35-5.20)]. For site-specific analysis, heart and circulation infections posed the greatest risk of CVD events [aHR 4.95 (95% CI 3.77-6.50)], whereas noncardiac infections also showed excess risk [1.77 (1.72-1.81)]. Synergistic interactions were observed between infections and genetic risk score. A dose-response relationship was found between infection burden and CVD risks (p-trend <0.001). Infection burden >1 led to a CVD-related life loss at age 50 by 9.3 years [95% CI 8.6-10.3]) for men and 6.6 years [5.5-7.8] for women. CONCLUSIONS: The magnitude of the infection-CVD association showed specificity in sex, pathogen type, infection burden, and infection site. High genetic risk and infection synergistically increased the CVD risk.

Does increasing forest age lead to greater trade-offs in ecosystem services? A study of a Robinia pseudoacacia artificial forest on the Loess Plateau, China.

Artificial forest ecosystems offer various ecosystem services (ES) and help mitigate climate change effects. Trade-offs or synergies exist among ES in artificial forests. Although forest age influences ES and ecosystem processes, the long-term dynamics of trade-offs among ES in artificial forests and during vegetation restorations remain unclear, complicating vegetation and sustainable management. We studied a Robinia pseudoacacia plantation on the Loess Plateau, China, with a restoration time of 10-44 years. The entropy weight method was used to assess five ES (carbon sequestration, water conservation, soil conservation, understory plant diversity, and runoff and sediment reduction) and investigate how ES change with forest age. The root mean square deviation (RMSD) was used to quantify the trade-offs among ES, and redundancy analysis (RDA) analysis was used to identify the key factors influencing the ES and trade-offs. The results showed that (1) as forest age increased, ES scores initially increased and then decreased. The optimal range for ES values was observed during the middle-aged to mature stages of the forest. (2) Before reaching maturity, the planted forests primarily delivered services related to water conservation and runoff and sediment reduction. (3) In young forests, ES showed a synergistic relationship (RMSD = 0.06), whereas trade-offs occurred in forests at other ages. The largest trade-off was observed in middle-aged forests. (4) The ES pairs with the dominant trade-offs in planted forests differed at different forest age stages. The largest trade-off occurred between carbon sequestration and water conservation (RMSD = 0.28). RDA analysis showed that understory vegetation coverage had a positive correlation with all ES. The ES indicators that significantly (P < 0.001) affected the water­carbon trade-off were tree carbon storage, soil organic carbon storage, soil total nitrogen, and soil total phosphorus. Thus, the water and carbon relationship must be balanced, and the key factors affecting ES trade-offs in forest management must be regulated to support ES multifunctionality.

A water quality prediction model based on signal decomposition and ensemble deep learning techniques.

Accurate water quality predictions are critical for water resource protection, and dissolved oxygen (DO) reflects overall river water quality and ecosystem health. This study proposes a hybrid model based on the fusion of signal decomposition and deep learning for predicting river water quality. Initially, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is employed to split the internal series of DO into numerous internal mode functions (IMFs). Subsequently, we employed multi-scale fuzzy entropy (MFE) to compute the entropy values for each IMF component. Time-varying filtered empirical mode decomposition (TVFEMD) is used to further extract features in high-frequency subsequences after linearly aggregating the high-frequency sequences. Finally, support vector machine (SVM) and long short-term memory (LSTM) neural networks are used to predict low- and high-frequency subsequences. Moreover, by comparing it with single models, models based on 'single layer decomposition-prediction-ensemble' and combination models using different methods, the feasibility of the proposed model in predicting water quality data for the Xinlian section of Fuhe River and the Chucha section of Ganjiang River was verified. As a result, the combined prediction approach developed in this work has improved generalizability and prediction accuracy, and it may be used to forecast water quality in complicated waters.

A literature review: mechanisms of antitumor pharmacological action of leonurine alkaloid.

Leonurine refers to the desiccated aerial portion of a plant in the Labiatae family. The primary bioactive constituent of Leonurine is an alkaloid, Leonurine alkaloid (Leo), renowned for its substantial therapeutic efficacy in the treatment of gynecological disorders, in addition to its broad-spectrum antineoplastic capabilities. Over recent years, the pharmacodynamic mechanisms of Leo have garnered escalating scholarly interest. Leo exhibits its anticancer potential by means of an array of mechanisms, encompassing the inhibition of neoplastic cell proliferation, induction of both apoptosis and autophagy, and the containment of oncogenic cell invasion and migration. The key signal transduction pathways implicated in these processes include the Tumor Necrosis Factor-Related Apoptosis-Inducing Ligand (TRAIL), the Phosphoinositide3-Kinase/Serine/Threonine Protein Kinase (PI3K/AKT), the Signal Transducer and Activator of Transcription 3 (STAT3), and the Mitogen-Activated Protein/Extracellular Signal-Regulated Kinase (MAP/ERK). This paper commences with an exploration of the principal oncogenic cellular behaviors influenced by Leo and the associated signal transduction pathways, thereby scrutinizing the mechanisms of Leo in the antineoplastic sequence of events. The intention is to offer theoretical reinforcement for the elucidation of more profound mechanisms underpinning Leo's anticancer potential and correlating pharmaceutical development.

The impact of blood MCP-1 levels on Alzheimer's disease with genetic variation of UNC5C and NAV3 loci.

Background: Previous study shows that monocyte chemoattractant protein-1 (MCP-1), which is implicated in the peripheral proinflammatory cascade and blood-brain barrier (BBB) disruption, modulates the genetic risks of AD in established AD loci. Methods: In this study, we hypothesized that blood MCP-1 impacts the AD risk of genetic variants beyond known AD loci. We thus performed a genome-wide association study (GWAS) using the logistic regression via generalized estimating equations (GEE) and the Cox proportional-hazards models to examine the interactive effects between single nucleotide polymorphisms (SNPs) and blood MCP-1 level on AD in three cohorts: the Framingham Heart Study (FHS), Alzheimer's Disease Neuroimaging Initiative (ADNI) and Religious Orders Study/Memory and Aging Project (ROSMAP). Results: We identified SNPs in two genes, neuron navigator 3 (NAV3, also named Unc-53 Homolog 3, rs696468) (p < 7.55×10- 9) and Unc-5 Netrin Receptor C (UNC5C rs72659964) (p < 1.07×10- 8) that showed an association between increasing levels of blood MCP-1 and AD. Elevating blood MCP-1 concentrations increased AD risk and AD pathology in genotypes of NAV3 (rs696468-CC) and UNC5C (rs72659964-AT + TT), but did not influence the other counterpart genotypes of these variants. Conclusions: NAV3 and UNC5C are homologs and may increase AD risk through dysregulating the functions of neurite outgrowth and guidance. Overall, the association of risk alleles of NAV3 and UNC5C with AD is enhanced by peripheral MCP-1 level, suggesting that lowering the level of blood MCP-1 may reduce the risk of developing AD for people with these genotypes.

Dietary Supplement with Tribulus terrestris L. Extract Exhibits Protective Effects on Ischemic Stroke Rats.

SCOPE: Among herbal dietary supplements, the extract of Tribulus terrestris L. (TT) has been used as a commercially registered product in multiple studies. The previous studies demonstrate the protective effect of gross saponins of TT (GSTTF) on ischemic stroke. However, the mechanism by which GSTTF protects against ischemic stroke is still unclear. METHODS AND RESULTS: The study applies molecular biology and unbiased transcriptomics to explore the pathways and targets underlying the therapeutic impact of GSTTF in treating ischemic stroke. The mRNA of brain tissues from different groups is analyzed using a transcriptomics method. The data reveal that treatment with GSTTF significantly reduces elevated CRP, IL-6, and Ca2+ levels induced by middle cerebral artery occlusion (MCAO). A total of 61 differentially expressed genes (DEGs) are identified, GSTTF is found to effectively reverse the abnormal mRNA expression levels in rat brain tissues affected by ischemic stroke models. These positive effects of GSTTF are likely achieved through the suppression of calcium ion and the MyD88/IKK/NF-κB signaling pathway. CONCLUSIONS: This study uncovers the mechanisms behind the efficacy of GSTTF in treating ischemic stroke, which not only expands its potential medicinal applications but also confirmed its potential as a dietary supplement.

Association Between Glucosamine Use and the Risk of Incident Heart Failure: The UK Biobank Cohort Study and Mendelian Randomization Analysis.

OBJECTIVE: To evaluate the association between regular glucosamine intake and heart failure (HF) and to explore whether the association is mediated by relevant cardiovascular disease. PATIENTS AND METHODS: We included 479,650 participants with data available for supplement use and without HF at baseline from the UK Biobank study. Using 12 single-nucleotide polymorphisms linked to HF, a weighted genetic risk score was calculated. We evaluated the association between glucosamine use and HF by Cox regression models after inverse probability of treatment weighting. A validation and mediation analysis were performed through two-sample Mendelian randomization. The study was from May 18, 2006, to February 16, 2018. RESULTS: During a median follow-up of 9.0 (IQR, 8.3-9.8) years, we documented 5501 incident cases of HF. In multivariable analysis, the HR of glucosamine users for HF was 0.87 (95% CI, 0.81 to 0.94). The inverse associations were stronger in males and participants with unfavorable lifestyle (P<.05 for interaction). Genetic risk categories did not modify this association (P>.05 for interaction). Multivariable Mendelian randomization showed that taking glucosamine was protective against HF (HR, 0.92; 95% CI, 0.87 to 0.96). The mediated proportion of coronary heart disease and stroke were 10.5% (95% CI, 7.6% to 13.4%) and 14.4% (95% CI, 10.8% to 18.0%), respectively. The two-mediator combination accounted for 22.7% (95% CI, 17.2% to 28.2%) of the effect of glucosamine use. CONCLUSION: Regular glucosamine supplementation was associated with a lower risk of HF regardless of genetic risk status, and to a lesser extent, coronary heart disease and stroke mediated this effect. The results may inform novel pathway for prevention and intervention toward HF.

Association of regular glucosamine use with incident dementia: evidence from a longitudinal cohort and Mendelian randomization study.

BACKGROUND: Emerging data suggests the neuroprotective and anti-neuroinflammatory effects of glucosamine. We aimed to examine the association between regular glucosamine use and risk of incident dementia, including dementia subtypes. METHODS: We conducted large-scale observational and two-sample Mendelian randomization (MR) analyses. Participants in UK Biobank having accessible data for dementia incidence and who did not have dementia at baseline were included in the prospective cohort. Through the Cox proportional hazard model, we examined the risks of incident all-cause dementia, Alzheimer's disease (AD), and vascular dementia among glucosamine users and non-users. To further test the causal association between glucosamine use and dementia, we conducted a 2-sample MR utilizing summary statistics from genome-wide association studies (GWAS). The GWAS data were obtained from observational cohort participants of mostly European ancestry. RESULTS: During a median follow-up of 8.9 years, there were 2458 cases of all-cause dementia, 924 cases of AD, and 491 cases of vascular dementia. In multivariable analysis, the hazard ratios (HR) of glucosamine users for all-cause dementia, AD, and vascular dementia were 0.84 (95% CI 0.75-0.93), 0.83 (95% CI 0.71-0.98), and 0.74 (95% CI 0.58-0.95), respectively. The inverse associations between glucosamine use and AD appeared to be stronger among participants aged below 60 years than those aged above 60 years (p = 0.04 for interaction). The APOE genotype did not modify this association (p > 0.05 for interaction). Single-variable MR suggested a causal relationship between glucosamine use and lower dementia risk. Multivariable MR showed that taking glucosamine continued to protect against dementia after controlling for vitamin, chondroitin supplement use and osteoarthritis (all-cause dementia HR 0.88, 95% CI 0.81-0.95; AD HR 0.78, 95% CI 0.72-0.85; vascular dementia HR 0.73, 95% CI 0.57-0.94). Single and multivariable inverse variance weighted (MV-IVW) and MR-Egger sensitivity analyses produced similar results for these estimations. CONCLUSIONS: The findings of this large-scale cohort and MR analysis provide evidence for potential causal associations between the glucosamine use and lower risk for dementia. These findings require further validation through randomized controlled trials.

Pyroptosis-based risk score predicts prognosis and drug sensitivity in lung adenocarcinoma.

Pyroptosis is a recently identified form of programmed cell death; however, its role in lung adenocarcinoma (LUAD) remains unclear. Therefore, we set out to explore the prognostic potential of pyroptosis-related genes in LUAD. The pyroptosis-related risk score (PRRS) was developed by least absolute shrinkage and selection operator Cox regression and multivariate Cox regression. We found that PRRS was an independent prognostic factor for LUAD. LUAD patients in the high-PRRS group showed a significantly shorter overall survival (OS) and enriched in cell proliferation-related pathways. Then pathway enrichment analyses, mutation profile, tumor microenvironment, and drug sensitivity analysis were further studied in PRRS stratified LUAD patients. Tumor purity (TP) analyses revealed that L-PRRS LUAD patients had a lower TP, and patients in L-TP + L-PRRS subgroup had the most prolonged OS. Mutation analyses suggested that the L-PRRS LUAD patients had a lower tumor mutation burden (TMB), and patients in H-TMB + L-PRRS subgroup had the most prolonged OS. Drug sensitivity analyses showed that PRRS was significantly negatively correlated with the sensitivity of cisplatin, besarotene, etc., while it was significantly positively correlated with the sensitivity of kin001-135. Eventually, a nomogram was constructed based on PRRS and clinical characters of LUAD. Overall, the pyroptosis-related signature is helpful for prognostic prediction and in guiding treatment for LUAD patients.

ClusterSeg: A crowd cluster pinpointed nucleus segmentation framework with cross-modality datasets.

The detection and segmentation of individual cells or nuclei is often involved in image analysis across a variety of biology and biomedical applications as an indispensable prerequisite. However, the ubiquitous presence of crowd clusters with morphological variations often hinders successful instance segmentation. In this paper, nuclei cluster focused annotation strategies and frameworks are proposed to overcome this challenging practical problem. Specifically, we design a nucleus segmentation framework, namely ClusterSeg, to tackle nuclei clusters, which consists of a convolutional-transformer hybrid encoder and a 2.5-path decoder for precise predictions of nuclei instance mask, contours, and clustered-edges. Additionally, an annotation-efficient clustered-edge pointed strategy pinpoints the salient and error-prone boundaries, where a partially-supervised PS-ClusterSeg is presented using ClusterSeg as the segmentation backbone. The framework is evaluated with four privately curated image sets and two public sets with characteristic severely clustered nuclei across a variety range of image modalities, e.g., microscope, cytopathology, and histopathology images. The proposed ClusterSeg and PS-ClusterSeg are modality-independent and generalizable, and superior to current state-of-the-art approaches in multiple metrics empirically. Our collected data, the elaborate annotations to both public and private set, as well the source code, are released publicly at https://github.com/lu-yizhou/ClusterSeg.

Circulating Endothelial Progenitor Cells Reduce the Risk of Alzheimer's Disease.

Cerebrovascular damage coexists with Alzheimer's disease (AD) pathology and increases AD risk. However, it is unclear whether endothelial progenitor cells reduce AD risk via cerebrovascular repair. By using the Framingham Heart Study (FHS) offspring cohort, which includes data on different progenitor cells, the incidence of AD dementia, peripheral and cerebrovascular pathologies, and genetic data (n = 1,566), we found that elevated numbers of circulating endothelial progenitor cells with CD34+CD133+ co-expressions had a dose-dependent association with decreased AD risk (HR = 0.67, 95% CI: 0.46-0.96, p = 0.03) after adjusting for age, sex, years of education, and APOE ε4. With stratification, this relationship was only significant among those individuals who had vascular pathologies, especially hypertension (HTN) and cerebral microbleeds (CMB), but not among those individuals who had neither peripheral nor central vascular pathologies. We applied a genome-wide association study (GWAS) and found that the number of CD34+CD133+ cells impacted AD risk depending on the homozygous genotypes of two genes: KIRREL3 rs580382 CC carriers (HR = 0.31, 95% CI: 0.17-0.57, p<0.001), KIRREL3 rs4144611 TT carriers (HR = 0.29, 95% CI: 0.15-0.57, p<0.001), and EXOC6B rs61619102 CC carriers (HR = 0.49, 95% CI: 0.31-0.75, p<0.001) after adjusting for confounders. In contrast, the relationship did not exist in their counterpart genotypes, e.g. KIRREL3 TT/CT or GG/GT carriers and EXOC6B GG/GC carriers. Our findings suggest that circulating CD34+CD133+ endothelial progenitor cells can be therapeutic in reducing AD risk in the presence of cerebrovascular pathology, especially in KIRREL3 and EXOC6B genotype carriers.