The repertoire of copy number alteration signatures in human cancer.

Copy number alterations (CNAs) are a predominant source of genetic alterations in human cancer and play an important role in cancer progression. However comprehensive understanding of the mutational processes and signatures of CNA is still lacking. Here we developed a mechanism-agnostic method to categorize CNA based on various fragment properties, which reflect the consequences of mutagenic processes and can be extracted from different types of data, including whole genome sequencing (WGS) and single nucleotide polymorphism (SNP) array. The 14 signatures of CNA have been extracted from 2778 pan-cancer analysis of whole genomes WGS samples, and further validated with 10 851 the cancer genome atlas SNP array dataset. Novel patterns of CNA have been revealed through this study. The activities of some CNA signatures consistently predict cancer patients' prognosis. This study provides a repertoire for understanding the signatures of CNA in cancer, with potential implications for cancer prognosis, evolution and etiology.

Transcription factor DIVARICATA1 positively modulates seed germination in response to salinity stress.

Seed germination is a critical checkpoint for plant growth under unfavorable environmental conditions. In Arabidopsis (Arabidopsis thaliana), the abscisic acid (ABA) and gibberellic acid (GA) signaling pathways play important roles in modulating seed germination. However, the molecular links between salinity stress and ABA/GA signaling are not well understood. Herein, we showed that the expression of DIVARICATA1 (DIV1), which encodes a MYB-like transcription factor, was induced by GA and repressed by ABA, salinity, and osmotic stress in germinating seeds. DIV1 positively regulated seed germination in response to salinity stress by directly regulating the expression of DELAY OF GERMINATION 1-LIKE 3 (DOGL3) and GA-STIMULATED ARABIDOPSIS 4 (GASA4) and indirectly regulating the expression of several germination-associated genes. Moreover, NUCLEAR FACTOR-YC9 (NF-YC9) directly repressed the expression of DIV1 in germinating seeds in response to salinity stress. These results help reveal the function of the NF-YC9-DIV1 module and provide insights into the regulation of ABA and GA signaling in response to salinity stress during seed germination in Arabidopsis.

FLOWERING LOCUS T1 and TERMINAL FLOWER1 regulatory networks mediate flowering initiation in apple.

Flower bud formation is a critical process that directly determines yield and fruit quality in fruit crops. Floral induction is modulated by the balance between 2 flowering-related proteins, FLOWERING LOCUS T (FT) and TERMINAL FLOWER1 (TFL1); however, the mechanisms underlying the establishment and maintenance of this dynamic balance remain largely elusive. Here, we showed that in apple (Malus × domestica Borkh.), MdFT1 is predominantly expressed in spur buds and exhibits an increase in expression coinciding with flower induction; in contrast, MdTFL1 exhibited downregulation in apices during flower induction, suggesting that MdTFL1 has a role in floral repression. Interestingly, both the MdFT1 and MdTFL1 transcripts are directly regulated by transcription factor basic HELIX-LOOP-HELIX48 (MdbHLH48), and overexpression of MdbHLH48 in Arabidopsis (Arabidopsis thaliana) and tomato (Solanum lycopersicum) results in accelerated flowering. Binding and activation analyses revealed that MdbHLH48 functions as a positive regulator of MdFT1 and a negative regulator of MdTFL1. Further studies established that both MdFT1 and MdTFL1 interact competitively with MdWRKY6 protein to facilitate and inhibit, respectively, MdWRKY6-mediated transcriptional activation of target gene APPLE FLORICAULA/LFY (AFL1, an apple LEAFY-like gene), ultimately regulating apple flower bud formation. These findings illustrate the fine-tuned regulation of flowering by the MdbHLH48-MdFT1/MdTFL1-MdWRKY6 module and provide insights into flower bud formation in apples.

Deciphering clonal dynamics and metastatic routines in a rare patient of synchronous triple-primary tumors and multiple metastases with MPTevol.

Multiple primary tumor (MPT) is a special and rare cancer type, defined as more than two primary tumors presenting at the diagnosis in a single patient. The molecular characteristics and tumorigenesis of MPT remain unclear due to insufficient approaches. Here, we present MPTevol, a practical computational framework for comprehensively exploring the MPT from multiregion sequencing (MRS) experiments. To verify the utility of MPTevol, we performed whole-exome MRS for 33 samples of a rare patient with triple-primary tumors and three metastatic sites and systematically investigated clonal dynamics and metastatic routines. MPTevol assists in comparing genomic profiles across samples, detecting clonal evolutionary history and metastatic routines and quantifying the metastatic history. All triple-primary tumors were independent origins and their genomic characteristics were consistent with corresponding sporadic tumors, strongly supporting their independent tumorigenesis. We further showed two independent early monoclonal seeding events for the metastases in the ovary and uterus. We revealed that two ovarian metastases were disseminated from the same subclone of the primary tumor through undergoing whole-genome doubling processes, suggesting metastases-to-metastases seeding occurred when tumors had similar microenvironments. Surprisingly, according to the metastasis timing model of MPTevol, we found that primary tumors of about 0.058-0.124 cm diameter have been disseminating to distant organs, which is much earlier than conventional clinical views. We developed MPT-specialized analysis framework MPTevol and demonstrated its utility in explicitly resolving clonal evolutionary history and metastatic seeding routines with a rare MPT case. MPTevol is implemented in R and is available at https://github.com/qingjian1991/MPTevol under the GPL v3 license.

Hiplot: a comprehensive and easy-to-use web service for boosting publication-ready biomedical data visualization.

Complex biomedical data generated during clinical, omics and mechanism-based experiments have increasingly been exploited through cloud- and visualization-based data mining techniques. However, the scientific community still lacks an easy-to-use web service for the comprehensive visualization of biomedical data, particularly high-quality and publication-ready graphics that allow easy scaling and updatability according to user demands. Therefore, we propose a community-driven modern web service, Hiplot (https://hiplot.org), with concise and top-quality data visualization applications for the life sciences and biomedical fields. This web service permits users to conveniently and interactively complete a few specialized visualization tasks that previously could only be conducted by senior bioinformatics or biostatistics researchers. It covers most of the daily demands of biomedical researchers with its equipped 240+ biomedical data visualization functions, involving basic statistics, multi-omics, regression, clustering, dimensional reduction, meta-analysis, survival analysis, risk modelling, etc. Moreover, to improve the efficiency in use and development of plugins, we introduced some core advantages on the client-/server-side of the website, such as spreadsheet-based data importing, cross-platform command-line controller (Hctl), multi-user plumber workers, JavaScript Object Notation-based plugin system, easy data/parameters, results and errors reproduction and real-time updates mode. Meanwhile, using demo/real data sets and benchmark tests, we explored statistical parameters, cancer genomic landscapes, disease risk factors and the performance of website based on selected native plugins. The statistics of visits and user numbers could further reflect the potential impact of this web service on relevant fields. Thus, researchers devoted to life and data sciences would benefit from this emerging and free web service.

The MYB59 transcription factor negatively regulates salicylic acid- and jasmonic acid-mediated leaf senescence.

Leaf senescence is the final stage of leaf development and is affected by various exogenous and endogenous factors. Transcriptional regulation is essential for leaf senescence, however, the underlying molecular mechanisms remain largely unclear. In this study, we report that the transcription factor MYB59, which was predominantly expressed in early senescent rosette leaves, negatively regulates leaf senescence in Arabidopsis (Arabidopsis thaliana). RNA sequencing revealed a large number of differentially expressed genes involved in several senescence-related biological processes in myb59-1 rosette leaves. Chromatin immunoprecipitation and transient dual-luciferase reporter assays demonstrated that MYB59 directly repressed the expression of SENESCENCE ASSOCIATED GENE 18 and indirectly inhibited the expression of several other senescence-associated genes to delay leaf senescence. Moreover, MYB59 was induced by salicylic acid (SA) and jasmonic acid (JA). MYB59 inhibited SA production by directly repressing the expression of ISOCHORISMATE SYNTHASE 1 and PHENYLALANINE AMMONIA-LYASE 2 and restrained JA biosynthesis by directly suppressing the expression of LIPOXYGENASE 2, thus forming two negative feedback regulatory loops with SA and JA and ultimately delaying leaf senescence. These results help us understand the novel function of MYB59 and provide insights into the regulatory network controlling leaf senescence in Arabidopsis.

Government-enterprise green collaborative governance and urban carbon emission reduction: Empirical evidence from green PPP programs.

The reliance solely on the government or enterprises to promote climate governance is contingent upon the vested interests of economic entities and the regulatory bodies' efficiency in governance. Can the model of government-enterprise green collaborative governance evolve into a long-term mechanism for addressing the climate crisis and achieving the goals of sustainable development? By crawling data on public-private partnerships (PPP), employing ChatGPT to identify green PPP projects, and building a generalized difference-in-differences framework based on the Guidance on Building a Green Financial System issued in 2016, this present study investigates whether the involvement of private capital in government-led environmental and climate governance can effectively facilitate government-enterprise green collaborative governance, thereby mitigating urban carbon emissions. The study finds government-enterprise green collaborative governance can significantly reduce urban carbon emissions. The conclusion remains valid even after several rounds of robustness tests, including removing the influence of pertinent climate policies, adjusting the settings of independent and dependent variables, and removing self-selection issues. Heterogeneity tests show, on the first hand, the carbon emission reduction effect of government-enterprise green collaborative governance differs due to the differences in the characteristics of green PPP(Pubic-private partnership) projects such as project return mechanism, project investment volume, and project cooperation term; on the other hand, the carbon emission reduction effect also shows heterogeneity with various urban characteristics such as geographical location, city type and city size. Mechanism tests indicate government-enterprise green collaborative governance affects urban carbon emissions mainly through structural effects, technological effects and co-investment effects. This paper offers a valuable framework for effectively promoting environmental and climate co-governance between governmental bodies and enterprises, while enhancing the market's role in resource benefit allocation within climate governance to mitigate the risks associated with climate change.

Copy number signature analysis tool and its application in prostate cancer reveals distinct mutational processes and clinical outcomes.

Genome alteration signatures reflect recurring patterns caused by distinct endogenous or exogenous mutational events during the evolution of cancer. Signatures of single base substitution (SBS) have been extensively studied in different types of cancer. Copy number alterations are important drivers for the progression of multiple cancer. However, practical tools for studying the signatures of copy number alterations are still lacking. Here, a user-friendly open source bioinformatics tool "sigminer" has been constructed for copy number signature extraction, analysis and visualization. This tool has been applied in prostate cancer (PC), which is particularly driven by complex genome alterations. Five copy number signatures are identified from human PC genome with this tool. The underlying mutational processes for each copy number signature have been illustrated. Sample clustering based on copy number signature exposure reveals considerable heterogeneity of PC, and copy number signatures show improved PC clinical outcome association when compared with SBS signatures. This copy number signature analysis in PC provides distinct insight into the etiology of PC, and potential biomarkers for PC stratification and prognosis.

Antagonistic MADS-box transcription factors SEEDSTICK and SEPALLATA3 form a transcriptional regulatory network that regulates seed oil accumulation.

Transcriptional regulation is essential for balancing multiple metabolic pathways that influence oil accumulation in seeds. Thus far, the transcriptional regulatory mechanisms that govern seed oil accumulation remain largely unknown. Here, we identified the transcriptional regulatory network composed of MADS-box transcription factors SEEDSTICK (STK) and SEPALLATA3 (SEP3), which bridges several key genes to regulate oil accumulation in seeds. We found that STK, highly expressed in the developing embryo, positively regulates seed oil accumulation in Arabidopsis (Arabidopsis thaliana). Furthermore, we discovered that SEP3 physically interacts with STK in vivo and in vitro. Seed oil content is increased by the SEP3 mutation, while it is decreased by SEP3 overexpression. The chromatin immunoprecipitation, electrophoretic mobility shift assay, and transient dual-luciferase reporter assays showed that STK positively regulates seed oil accumulation by directly repressing the expression of MYB5, SEP3, and SEED FATTY ACID REDUCER 4 (SFAR4). Moreover, genetic and molecular analyses demonstrated that STK and SEP3 antagonistically regulate seed oil production and that SEP3 weakens the binding ability of STK to MYB5, SEP3, and SFAR4. Additionally, we demonstrated that TRANSPARENT TESTA 8 (TT8) and ACYL-ACYL CARRIER PROTEIN DESATURASE 3 (AAD3) are direct targets of MYB5 during seed oil accumulation in Arabidopsis. Together, our findings provide the transcriptional regulatory network antagonistically orchestrated by STK and SEP3, which fine tunes oil accumulation in seeds.

Single-cell and transcriptome analysis reveals TAL cells in diabetic nephropathy.

Diabetic nephropathy is a global public health concern with multifaceted pathogenesis, primarily involving hypertension. Excessive activation of AT1R has been strongly associated with hypertension onset and progression in diabetic nephropathy. This study aimed to conduct thick ascending limb cell single-cell and transcriptomic analysis in diabetic nephropathy, including screening for biological markers, cellular communication, and immune infiltration, to identify potential biomarkers and effective means for prevention and treatment. By using high-dimensional weighted gene co-expression network analysis, least absolute shrinkage and selection operator, machine learning, neural deconvolution, quasi-chronological analysis, non-negative matrix factorization clustering, and monocyte chemotactic protein-induced counter, we identified 7 potential thick ascending limb cell biomarkers for diabetic nephropathy and elucidated the bone morphogenetic protein pathway's regulation of thick ascending limb cells through podocyte epithelial cells and podocyte cells. The study also highlighted the role of COBL, PPARGC1A, and THSD7A in non-negative matrix factorization clustering and their relationship with thick ascending limb cell immunity in diabetic nephropathy. Our findings provide new insights and avenues for managing diabetic nephropathy, ultimately alleviating the burden on patients and society.

UCSCXenaShiny: an R/CRAN package for interactive analysis of UCSC Xena data.

SUMMARY: UCSC Xena platform provides huge amounts of processed cancer omics data from large cancer research projects (e.g. TCGA, CCLE and PCAWG) or individual research groups and enables unprecedented research opportunities. However, a graphical user interface-based tool for interactively analyzing UCSC Xena data and generating elegant plots is still lacking, especially for cancer researchers and clinicians with limited programming experience. Here, we present UCSCXenaShiny, an R Shiny package for quickly searching, downloading, exploring, analyzing and visualizing data from UCSC Xena data hubs. This tool could effectively promote the practical use of public data, and can serve as an important complement to the current Xena genomics explorer. AVAILABILITY AND IMPLEMENTATION: UCSCXenaShiny is an open source R package under GPLv3 license and it is freely available at https://github.com/openbiox/UCSCXenaShiny or https://cran.r-project.org/package=UCSCXenaShiny. The docker image is available at https://hub.docker.com/r/shixiangwang/ucscxenashiny. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Ultra-precision manufacturing of microlens arrays using an optimum machining process chain.

There are still significant challenges in the accurate and uniform manufacturing of microlens arrays (MLAs) with advanced ultra-precision diamond cutting technologies due to increasingly stringent requirements and shape complexity. In this paper, an optimum machining process chain is proposed based on the integration of a micro-abrasive fluid jet polishing (MAFJP) process to improve the machining quality by single point diamond turning (SPDT). The MLAs were first machined and compensated by SPDT until the maximum possible surface quality was obtained. The MAFJP was used to correct the surface form error and reduce the nonuniformity for each lens. The polishing characterization was analyzed based on the computational fluid dynamics (CFD) method to enhance the polishing efficiency. To better polish the freeform surface, two-step tool path generation using a regional adaptive path and a raster and cross path was employed. Moreover, the compensation error map was also investigated by revealing the relationship between the material removal mechanism and the surface curvature and polishing parameters. A series of experiments were conducted to prove the reliability and capability of the proposed method. The results indicate that the two integrated machining processes are capable of improving the surface form accuracy with a decrease in PV value from 1.67 µm to 0.56 µm and also elimination of the nonuniform surface error for the lenses.

The kidney reabsorption-related magnesium depletion score is associated with increased likelihood of abdominal aortic calcification among US adults.

BACKGROUND: Kidney reabsorption plays a vital role in magnesium homeostasis. This study aimed to determine the relationship between the kidney reabsorption-related magnesium depletion score (MDS) and abdominal aortic calcification (AAC). METHODS: We obtained data for 2640 individuals from the National Health and Nutrition Examination Survey database and analysed the relationship between the MDS and AAC score. The MDS is a scoring system developed to predict the status of magnesium deficiency that fully considers the pathophysiological factors influencing the kidneys' reabsorption capability. AAC was quantified by the Kauppila score system based on dual-energy X-ray absorptiometry. We performed stratified analysis and multiple equation regression analysis. R and EmpowerStats were used for data analysis. RESULTS: A total of 2640 participants were included with the mean AAC score of 1.47 ± 0.07. Participants with higher MDSs tended to have higher AAC scores [MDS 0: 0.75 (0.56-0.93), MDS 1: 1.02 (0.84-1.21), MDS 2: 2.34 (1.80-2.87), MDS 3: 3.19 (2.46-3.92), MDS ≥4: 4.99 (3.49-6.49)]. Compared with those with an MDS of 0, the highest subgroup (MDS ≥4) was associated with a higher AAC score {ß = 4.24 [95% confidence interval (CI) 2.78-5.70], P < .001} and the association was not altered [ß = 1.81 (95% CI 0.54-3.09), P = .002] after adjusting for numerous covariates. Subgroup analyses showed that stronger associations between the MDS and AAC score were detected in adults with lower levels of magnesium intake and older age (all P for interaction <.05). CONCLUSIONS: The MDS is a promising tool for identifying individuals with magnesium deficiency status who may benefit from dietary magnesium supplementation to reduce the risks of AAC.

Interaction effect of psoriasis and chronic kidney disease on the risk of all-cause mortality: a prospective cohort study of NHANES data.

BACKGROUND: The association between psoriasis, chronic kidney disease (CKD) and mortality remains unclear. This study aimed to examine the combined impact of psoriasis and CKD on mortality in a representative sample of US adults. METHODS: The data for this analysis came from 13 208 participants of the National Health and Nutrition Examination Survey conducted between 2003-06 and 2009-14. Psoriasis was determined through self-reported questionnaire data, while CKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 or urinary albumin to creatinine ratio (UACR) ≥30 mg/g. A four-level variable was created using the information on psoriasis and CKD, and survival probability was estimated using the Kaplan-Meier method. The survival analysis was conducted using weighted Cox proportional hazards regression models. RESULTS: In a 9.83-year average follow-up period, 539 deaths occurred, with a prevalence of psoriasis in CKD at 2.94% and an all-cause mortality rate of 33.30%. In the multivariable analyses, individuals with both psoriasis and CKD had hazard ratios (HRs) of 5.38 (95% CI 2.43-11.91) for all-cause mortality compared with those with neither psoriasis nor CKD. Participants with both psoriasis and low eGFR had an HR of 6.40 (95% CI 2.01-20.42), while those with both psoriasis and albuminuria had an HR of 5.30 (95% CI 2.24-12.52). A significant interaction between psoriasis, CKD and all-cause mortality was found in the fully adjusted model (P = .026), and a significant synergistic effect between psoriasis and albuminuria was discovered (P = .002). However, the interaction effects between psoriasis, low eGFR and all-cause mortality were only observed in the unadjusted model (P = .036). CONCLUSIONS: Screening for psoriasis in individuals at risk for developing CKD may help in risk stratification for all-cause mortality related to psoriasis. The assessment of UACR may be useful in identifying psoriasis at increased risk for all-cause mortality.

Elucidating Multiple Electron-Transfer Pathways for Metavanadate Bioreduction by Actinomycetic Streptomyces microflavus.

While microbial reduction has gained widespread recognition for efficiently remediating environments polluted by toxic metavanadate [V(V)], the pool of identified V(V)-reducing strains remains rather limited, with the vast majority belonging to bacteria and fungi. This study is among the first to confirm the V(V) reduction capability of Streptomyces microflavus, a representative member of ubiquitous actinomycetes in environment. A V(V) removal efficiency of 91.0 ± 4.35% was achieved during 12 days of operation, with a maximum specific growth rate of 0.073 d-1. V(V) was bioreduced to insoluble V(IV) precipitates. V(V) reduction took place both intracellularly and extracellularly. Electron transfer was enhanced during V(V) bioreduction with increased electron transporters. The electron-transfer pathways were revealed through transcriptomic, proteomic, and metabolomic analyses. Electrons might flow either through the respiratory chain to reduce intracellular V(V) or to cytochrome c on the outer membrane for extracellular V(V) reduction. Soluble riboflavin and quinone also possibly mediated extracellular V(V) reduction. Glutathione might deliver electrons for intracellular V(V) reduction. Bioaugmentation of the aquifer sediment with S. microflavus accelerated V(V) reduction. The strain could successfully colonize the sediment and foster positive correlations with indigenous microorganisms. This study offers new microbial resources for V(V) bioremediation and improve the understanding of the involved molecular mechanisms.

High serum ß2-microglobulin is a significant predictor of mortality in maintenance hemodialysis patients.

BACKGROUND: Beta2-microglobulin, a novel marker of kidney function, predicts kidney failure and mortality in the general population. However, few studies have evaluated the association of serum ß2-MG level with clinical outcome in maintenance hemodialysis (MHD) patients. METHODS: This prospective cohort study enrolled 303 MHD patients to investigate the factors related to ß2-MG and its relationship to mortality in MHD patients. Multivariate linear regression analysis was used to examine the factors related to ß2-MG level. Multivariable Cox regression was used to calculate the hazard ratios for ß2-MG on all-cause and cardiovascular mortality. RESULTS: The median value of serum ß2-MG was 44.6 mg/L (interquartile range 37.60-50.40 mg/L). During the follow-up period of 24 months, there were 48 all-cause deaths (23.0%), including 36 cardiovascular causes (75.0% of all deaths). Multiple linear regression showed that dialysis duration, serum creatinine, and alkaline phosphatase were independent predictors of serum ß2-MG level. Kaplan-Meier analysis revealed that mortality in MHD patients was significantly higher in low albumin patients with ß2-MG > 44.6 mg/L. Cox regression analysis showed that ß2-MG was a significant predictor of all-cause mortality (HR = 1.122, 95% CI: 1.058-1.190, 𝑃 < 0.001) and cardiovascular mortality (HR = 1.145, 95%CI: 1.065-1.123, P < 0.001) in MHD patients with low albumin level after adjusting for confounding factors. However, our results showed that serum ß2-MG was not associated with mortality in MHD patients with normal albumin level. CONCLUSION: These results are supportive of the potential role of the serum ß2-MG level as a predictor of mortality in MHD patients with low albumin.

Prognostic value of red cell distribution width and mean corpuscular volume on mortality in hemodialysis patients.

BACKGROUND: Anemia is a common consequence of chronic kidney disease (CKD). Red cell distribution width (RDW) and mean corpuscular volume (MCV) are principally used for differential diagnosis of anemia. Limited evidence is available for its prognostic value for mortality in hemodialysis (HD) patients. We aimed to definite the relationship between RDW and MCV and mortality in HD patients. METHOD: This cohort study examined all-cause and cardiovascular (CV) mortality with 181 maintenance HD patients from February 2015. Patients were divided into four groups according to the median of RDW and MCV. Pearson analysis was conducted to determine the related factors of RDW and MCV. The independent association of RDW and MCV with mortality was examined with Kaplan-Meier curve and Cox regression analysis. RESULTS: This study included 181 HD patients for a median follow-up of 71 months. We found RDW was positively related to neutrophil count, C-reaction protein, and ferritin, while negatively related to hemoglobin, albumin, and creatinine. Only neutrophil count and ferritin were significantly related to MCV in this study. In the multivariate Cox regression analysis, the high RDW group was associated with higher risk of all-cause mortality (odds ratio, 3.787; 95% confidence interval, 1.037 to 13.834; p = 0.044). The relationship between RDW and MCV and CV mortality was not significant. CONCLUSIONS: RDW could emerge as an additive risk factor for all-cause mortality in maintenance HD patients, independent of other factors. An absolute value of MCV to predict mortality and the underlying pathophysiologic mechanisms should be confirmed in the future.

Clinical Outcomes of Prolonged Antiplatelet Therapy after Percutaneous Coronary Intervention in Chronic Kidney Disease Patients: A Systematic Review and Meta-Analysis.

BACKGROUND: The optimal duration of dual antiplatelet therapy (DAPT) after percutaneous coronary intervention (PCI) is not established in chronic kidney disease (CKD) patients. OBJECTIVE: In this meta-analysis, we evaluated the efficacy and safety of long duration DAPT compared with short duration DAPT in CKD patients after PCI. METHODS: We searched PubMed, Cochrane, and Embase to identify studies assessing the effect of DAPT duration in CKD patients with PCI. Endpoints included all-cause mortality, major adverse cardiovascular events (MACE), death or myocardial infarction (MI), revascularization, and bleeding. Event rates were compared with a random-effects model expressed by odds ratio (OR) and 95% confidence interval (CI). RESULTS: Six studies were included. CKD patients with extended DAPT duration were at a lower risk of mortality (OR 1.40, 95% CI: 1.11-1.77), MACE (OR 1.33, 95% CI: 1.17-1.51), mortality or MI (OR 1.24, 95% CI: 1.10-1.40), and stroke (OR 1.28, 95% CI: 1.05-1.56). However, there was no significant difference in revascularization and bleeding events between the two groups. Mortality was higher in patients with dialysis or drug-eluting stent comparing short- to long-term DAPT. CONCLUSIONS: Prolonged DAPT might decrease the risk of mortality, MACE, and stroke in patients with CKD without any significant difference in bleeding or revascularization. Additional studies are required to determine whether long-term DAPT could be considered for most CKD patients after PCI.

Higher Serum Magnesium Is a Survival Advantage in Maintenance Hemodialysis Patients.

INTRODUCTION: Elevated serum magnesium is common and associated with survival in maintenance hemodialysis (MHD) patients by observational studies. However, the results of these studies were underpowered and inconclusive. This work was designed to explore the predictive value of serum magnesium on the mortality of patients with MHD. METHODS: We retrospectively analyzed mortality rates in 267 patients with MHD. The collected parameters included anthropometrics and laboratory parameters. Serum magnesium included baseline serum magnesium (BS-Mg) and average serum magnesium (AS-Mg). Receiver operator characteristic (ROC) curves were drawn, and multivariate Cox proportional hazards models were applied to identify the predictive value of serum magnesium on patient mortality. RESULTS: During the 64-month follow-up period, 121 (45.3%) all-cause and 75 (28.1%) cardiovascular disease (CVD) deaths were recorded. The predictability of death of AS-Mg yielded results similar to those of serum albumin, secondary only to age, and superior to those of the high-sensitivity C-reactive protein (Hs-CRP), BS-Mg, by ROC curves. There were significant differences in all-cause and CVD mortality between the four groups (by quartile). Kaplan-Meier survival analyses revealed that the lowest 25th percentile had the poorest prognosis for both all-cause mortality (p < 0.001) and CVD mortality (p = 0.011). Finally, multivariate Cox proportional hazards models showed that increased age, increased Hs-CRP, decreased serum albumin, and AS-Mg were independent predictors of all-cause and CVD mortality. The hazard ratios of AS-Mg (per 0.01 mmol/L) were 0.925 (95% confidence interval, 0.884-0.968, p = 0.001) for all-cause mortality and 0.976 (95% confidence interval, 0.954-0.999, p = 0.040) for CVD mortality. CONCLUSION: AS-Mg was a good indicator for assessing all-cause and CVD mortality in patients with MHD in China. Higher serum magnesium had a survival advantage. Further studies with larger sample sizes should be needed to clarify the best reference value for maximizing the beneficial effects of magnesium.

Sigflow: an automated and comprehensive pipeline for cancer genome mutational signature analysis.

SUMMARY: Mutational signatures are recurring DNA alteration patterns caused by distinct mutational events during the evolution of cancer. In recent years, several bioinformatics tools are available for mutational signature analysis. However, most of them focus on specific type of mutation or have limited scope of application. A pipeline tool for comprehensive mutational signature analysis is still lacking. Here we present Sigflow pipeline, which provides an one-stop solution for de novo signature extraction, reference signature fitting, signature stability analysis, sample clustering based on signature exposure in different types of genome DNA alterations including single base substitution, doublet base substitution, small insertion and deletion and copy number alteration. A Docker image is constructed to solve the complex and time-consuming installation issues, and this enables reproducible research by version control of all dependent tools along with their environments. Sigflow pipeline can be applied to both human and mouse genomes. AVAILABILITY AND IMPLEMENTATION: Sigflow is an open source software under academic free license v3.0 and it is freely available at https://github.com/ShixiangWang/sigflow or https://hub.docker.com/r/shixiangwang/sigflow. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.