Association between sarcopenic obesity and mortality in patients on peritoneal dialysis: a prospective cohort study

BackgroundWhether sarcopenic obesity had unfavorable effect on survival of peritoneal dialysis (PD) patients is unknown. We aimed to investigate the association between sarcopenic obesity and survival in PD patients.MethodsThis was a prospective observational study. Eligible PD patients from November 2016 to December 2017 were enrolled and followed until August 31, 2023. Sarcopenia was defined following the recommendations of the Asian Working Group for Sarcopenia (AWGS) as low appendicular skeletal muscle mass index (ASMI) and handgrip strength (HGS). Obesity was defined using the percentage of body fat (PBF). Survival analysis was conducted using the Kaplan–Meier and log-rank test. The Cox regression and the cumulative incidence competing risk (CICR) analyzes were used to investigate the association between sarcopenic obesity and all-cause mortality.ResultsA total of 223 patients were enrolled with 133 (59.6%) males, a median age of 57.5 (44.6, 65.7) years, a median dialysis vintage of 20.3 (6.4, 57.7) months and 48 (21.5%) who had comorbid diabetes mellitus. Among them, 46 (20.6%) patients were sarcopenic, and 25 (11.2%) patients were diagnosed with sarcopenic obesity. After followed up for 51.6 (25.6, 73.9) months, the Kaplan–Meier curve showed the sarcopenic obesity (log-rank = 13.527, p < 0.001) group had significant lower survival rate compared to the nonsarcopenic non-obesity group. For multivariate analysis, the CICR method showed patients with sarcopenic obesity had significantly higher mortality rate (HR: 2.190, 95% CI: 1.011–4.743, p = 0.047) compared to those with nonsarcopenic non-obesity.ConclusionSarcopenia is not uncommon in PD patients, with a considerable proportion having sarcopenic obesity. There is a significant association between sarcopenic obesity and an increased risk of mortality in PD patients

A Hidden Markov Model for Copy Number Variant prediction from whole genome resequencing data

Motivation: Copy Number Variants (CNVs) are important genetic factors for studying human diseases. While high-throughput whole genome re-sequencing provides multiple lines of evidence for detecting CNVs, computational algorithms need to be tailored for different type or size of CNVs under different experimental designs. Results: To achieve optimal power and resolution of detecting CNVs at low depth of coverage, we implemented a Hidden Markov Model that integrates both depth of coverage and mate-pair relationship. The novelty of our algorithm is that we infer the likelihood of carrying a deletion jointly from multiple mate pairs in a region without the requirement of a single mate pairs being obvious outliers. By integrating all useful information in a comprehensive model, our method is able to detect medium-size deletions (200-2000bp) at low depth (<10× per sample). We applied the method to simulated data and demonstrate the power of detecting medium-size deletions is close to theoretical values. Availability: A program implemented in Java, Zinfandel, is available at http://www.cs.columbia.edu/~itsik/zinfandel

Epithelial to Mesenchymal Transition Is Mechanistically Linked with Stem Cell Signatures in Prostate Cancer Cells

Current management of patients diagnosed with prostate cancer (PCa) is very effective; however, tumor recurrence with Castrate Resistant Prostate Cancer (CRPC) and subsequent metastasis lead to poor survival outcome, suggesting that there is a dire need for novel mechanistic understanding of tumor recurrence, which would be critical for designing novel therapies. The recurrence and the metastasis of PCa are tightly linked with the biology of prostate cancer stem cells or cancer-initiating cells that is reminiscent of the acquisition of Epithelial to Mesenchymal Transition (EMT) phenotype. Increasing evidence suggests that EMT-type cells share many biological characteristics with cancer stem-like cells.In this study, we found that PCa cells with EMT phenotype displayed stem-like cell features characterized by increased expression of Sox2, Nanog, Oct4, Lin28B and/or Notch1, consistent with enhanced clonogenic and sphere (prostasphere)-forming ability and tumorigenecity in mice, which was associated with decreased expression of miR-200 and/or let-7 family. Reversal of EMT by re-expression of miR-200 inhibited prostasphere-forming ability of EMT-type cells and reduced the expression of Notch1 and Lin28B. Down-regulation of Lin28B increased let-7 expression, which was consistent with repressed self-renewal capability.These results suggest that miR-200 played a pivotal role in linking the characteristics of cancer stem-like cells with EMT-like cell signatures in PCa. Selective elimination of cancer stem-like cells by reversing the EMT phenotype to Mesenchymal-Epithelial Transition (MET) phenotype using novel agents would be useful for the prevention of tumor recurrence especially by eliminating those cells that are the "Root Cause" of tumor development and recurrence

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays.

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.This work is part of the ‘‘SpatioTemporal Omics Consortium’’ (STOC) paper package. A list of STOC members is available at: http://sto-consortium.org. We would like to thank the MOTIC China Group, Rongqin Ke (Huaqiao University, Xiamen, China), Jiazuan Ni (Shenzhen University, Shenzhen, China), Wei Huang (Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China), and Jonathan S. Weissman (Whitehead Institute, Boston, USA) for their help. This work was supported by the grant of Top Ten Foundamental Research Institutes of Shenzhen, the Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), and the Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011); Longqi Liu was supported by the National Natural Science Foundation of China (31900466) and Miguel A. Esteban’s laboratory at the Guangzhou Institutes of Biomedicine and Health by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), National Natural Science Foundation of China (92068106), and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075).S

Cell transcriptomic atlas of the non-human primate Macaca fascicularis.

Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell-cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M. fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.We thank W. Liu and L. Xu from the Huazhen Laboratory Animal Breeding Centre for helping in the collection of monkey tissues, D. Zhu and H. Li from the Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) for technical help, G. Guo and H. Sun from Zhejiang University for providing HCL and MCA gene expression data matrices, G. Dong and C. Liu from BGI Research, and X. Zhang, P. Li and C. Qi from the Guangzhou Institutes of Biomedicine and Health for experimental advice or providing reagents. This work was supported by the Shenzhen Basic Research Project for Excellent Young Scholars (RCYX20200714114644191), Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), Shenzhen Bay Laboratory (SZBL2019062801012) and Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011). In addition, L.L. was supported by the National Natural Science Foundation of China (31900466), Y. Hou was supported by the Natural Science Foundation of Guangdong Province (2018A030313379) and M.A.E. was supported by a Changbai Mountain Scholar award (419020201252), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), a Chinese Academy of Sciences–Japan Society for the Promotion of Science joint research project (GJHZ2093), the National Natural Science Foundation of China (92068106, U20A2015) and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075). M.L. was supported by the National Key Research and Development Program of China (2021YFC2600200).S