Longitudinal associations of social jetlag with obesity indicators among adolescents - Shanghai adolescent cohort.

OBJECTIVE: To explore the longitudinal association between social-jetlag (SJL) and obesity development among adolescents, sex-difference and related modifying factors in the association. METHODS: Based on Shanghai-Adolescent-Cohort during 2017-2021, a total of 609 students were investigated. In grade 6, 7 and 9, the information on SJL was collected using questionnaires, and anthropometric measures were conducted. The fingernail cortisol and progesterone levels in grade 6 (using LC-MS/MS) and body composition in grade 9 (using Inbody-S10) were measured. By the latent-class-mixture-modeling, two trajectories for SJL (high-level vs. low-level) throughout 4 years were developed. The prospective associations of SJL trajectories and weight/fat gains were analyzed by sex and under different (high/moderate/low) cortisol/progesterone stratifications. RESULTS: In grades 6-9, 39.00%-44.50 % of adolescents experienced at least 1 h of SJL. Compared with the low-level SJL trajectory, the high-level SJL trajectory was associated with greater differences in body-mass-index Z-scores and waist-to-height ratios across 4 years, higher levels of body-fat-percentage and fat-mass-index in grade 9 (P-values<0.05), and such associations were stronger among girls and under moderate-to-high (vs. low) baseline cortisol and progesterone levels. However, no significant associations among boys were observed. CONCLUSIONS: High-level SJL in adolescents may be associated with the development of obesity, especially among adolescent girls and under relatively high baseline cortisol and progesterone levels.

Rapid increases in BMI waist to height ratio during adolescence and subsequent neurobehavioral deficits.

OBJECTIVE: The aim of this study was to explore prospective relationships between changing patterns of BMI/waist to height ratio (WHtR) during adolescence and subsequent neurobehavioral development. METHODS: In this prospective cohort study, randomized stratified sampling was used to recruit six middle schools and 609 students in Shanghai, China. In Grades 6, 7, and 9, the Youth Self Report scale was used to assess student neurobehavioral status and anthropometric measurements were conducted to calculate BMI z scores and WHtRs. Longitudinal data were analyzed using latent class mixture modeling to delineate trajectories of BMI z scores ("stable," "decreasing," "rapidly increasing") and WHtRs ("stable," "rapidly increasing"), and their associations with neurobehavioral status in Grade 9 were assessed. RESULTS: In Grades 6 through 9 (ages 11-15 years), the prevalence of overall obesity and abdominal obesity ranged from 10.7% to 13.0% and 13.0% to 19.8%, respectively. Compared with the stable BMI z score trajectory, the rapidly increasing BMI z score trajectory was longitudinally associated with delinquent behavior, aggressive behavior, and externalizing problems (incidence rate ratio: 1.564-1.613, adjusted p < 0.05). Compared with the stable WHtR trajectory, the rapidly increasing WHtR trajectory significantly predicted increased risks of social problems and delinquent behavior (incidence rate ratios: 1.776-1.967, adjusted p < 0.05). Significant associations of the rapidly increasing BMI z score/WHtR trajectories with subsequent neurobehavioral deficits were observed among girls (adjusted p < 0.05) but not among boys (adjusted p > 0.05). CONCLUSIONS: Rapid increases in BMI or WHtR during adolescence could predict subsequent neurobehavioral deficits, especially for externalizing behaviors. Timely intervention for weight control may be considered to promote adolescent mental health.

Homework, sleep insufficiency and adolescent neurobehavioral problems: Shanghai Adolescent Cohort.

BACKGROUND: The prospective associations between homework burdens and adolescent neurobehavioral problems, and whether sleep-durations mediated and sex modified such associations remained unclear. METHODS: Using Shanghai-Adolescent-Cohort study, 609 middle-school students were recruited and investigations took place at Grade 6, 7 and 9. Information on homework burdens (defined by homework completion-time and self-perceived homework difficulty), bedtime/wake-up-time and neurobehavioral problems was collected. Two patterns of comprehensive homework burdens ('high' vs. 'low') were identified by latent-class-analysis and two distinct neurobehavioral trajectories ('increased-risk' vs. 'low-risk') were formed by latent-class-mixture-modeling. RESULTS: Among the 6th-9th graders, the prevalence-rates of sleep-insufficiency and late-bedtime ranged from 44.0 %-55.0 % and 40.3 %-91.6 %, respectively. High homework burdens were concurrently associated with increased-risks of neurobehavioral problems (IRRs: 1.345-1.688, P < 0.05) at each grade, and such associations were mediated by reduced sleep durations (IRRs for indirect-effects: 1.105-1.251, P < 0.05). High homework burden at the 6th-grade (ORs: 2.014-2.168, P < 0.05) or high long-term (grade 6-9) homework burden (ORs: 1.876-1.925, P < 0.05) significantly predicted increased-risk trajectories of anxiety/depression and total-problems, with stronger associations among girls than among boys. The longitudinal associations between long-term homework burdens and increased-risk trajectories of neurobehavioral problems were mediated by reduced sleep-durations (ORs for indirect-effects: 1.189-1.278, P < 0.05), with stronger mediation-effects among girls. LIMITATIONS: This study was restricted to Shanghai adolescents. CONCLUSIONS: High homework burden had both short-term and long-term associations with adolescent neurobehavioral problems, with stronger associations among girls, and sleep-insufficiency may mediate such associations in a sex-specific manner. Approaches targeting appropriate homework-load/difficulty and sleep restoration may help prevent adolescent neurobehavioral problems.

Immune checkpoint inhibitors plus chemotherapy in patients with locally advanced or metastatic pulmonary sarcomatoid carcinoma: a multicentric real-world study.

Introduction: Immune checkpoint inhibitors (ICIs) have demonstrated promising efficacy as monotherapy in patients with pulmonary sarcomatoid carcinoma (PSC). We performed the current multi-institutional, real-world study to assess the efficacy of ICIs plus chemotherapy in patients with PSC. Methods: All consecutive patients with locally advanced or metastatic PSC from three centers treated with ICIs between January 2018 and July 2021 were enrolled. Programmed death ligand 1 (PD-L1) expression was stained and evaluated using immunohistochemical with 22C3. Single-cell RNA sequencing (scRNA-seq) was performed in two patients with PSC and two patients with adenocarcinoma to understand the cell-type-specific transcriptome landscape of cancer cells and tumor microenvironment (TME) of PSC. Results: A cohort of 42 PSC patients was identified. In the overall population, the objective response rate (ORR) was 73.8%, median progression-free survival (mPFS) was 10.3 months and median overall survival was not reached and 2-year survival rate was 51.2%. For 34 treatment-naïve patients who received first-line ICIs plus chemotherapy, the ORR was 70.6%, mPFS was 10.3 months and 2-year survival rate was 57.8%. In patients with PD-L1 tumor proportion score (TPS) < 1%, 1-49%, and ⩾50%, the ORR was 33.3%, 72.7%, and 85.7% and mPFS was 6.0, 6.7, and 10.3 months, respectively. Notably, two patients with transformed PSC from lung adenocarcinoma after epidermal growth factor receptor-tyrosine kinase inhibitor treatment also responded well to ICIs plus chemotherapy. scRNA-seq revealed immune-cell-inflamed TME, lower intratumoral heterogeneity, and activated immune response pathway in PSC. Conclusions: Our study demonstrated remarkable efficacy of ICIs plus chemotherapy as first-line therapy for patient with locally advanced or metastatic PSC.

The potential effects and mechanisms of breast inflammatory lesions on the occurrence and development of breast cancer.

Breast cancer as the most common cancer in women has become the leading cause of cancer death for women. Although many inflammatory factors increase the risk of breast cancer, there are very few studies on the mechanisms by which inflammation affects the initiation and progression of breast cancer. Here, we profiled and compared the transcriptome of normal tissues, inflammatory breast tissues, benign breast tumors, and malignant breast tumors. To find key regulatory factors, a protein interaction network between characteristic modules in inflammatory lesions and ER-negative (ER-) breast cancer was constructed and inflammation-cancer interface genes were identified. We found that the transcriptional profile of inflammatory breast tissues was similar with ER- malignant tumors, featured with low ER expression levels and similar immune signaling pathway activation. Through comprehensive protein network analysis, we identified the interface genes and chemokine signaling pathway that have the potential to promote inflammatory cancer transformation. These interface genes could be used as a risk factor to provide a certain basis for the clinical early detection and treatment of breast cancer. This is the first study to explore the association between breast inflammatory lesions and breast cancer at the transcriptome level. Our inflammation data and research results provide a basis for future inflammation-cancer transformation analysis.

Human obstructive (postvasectomy) and nonobstructive azoospermia - Insights from scRNA-Seq and transcriptome analysis.

A substantial number of male infertility is caused by azoospermia. However, the underlying etiology and the molecular basis remain largely unknown. Through single-cell (sc)RNA sequencing, we had analyzed testis biopsy samples from two patients with obstructive azoospermia (OA) and nonobstructive azoospermia (NOA). We found only somatic cells in the NOA samples and explored the transcriptional changes in Sertoli cells in response to a loss of interactions with germ cells. Moreover, we observed a germ cell population discrepancy between an OA (postvasectomy) patient and a healthy individual. We confirmed this observation in a secondary study with two datasets at GSM3526588 and GSE124263 for detailed analysis wherein the regulatory mechanisms at the transcriptional level were identified. These findings thus provide valuable information on human spermatogenesis, and we also identified insightful information for further research on reproduction-related diseases.

Single-cell transcriptomics reveal the heterogeneity and dynamic of cancer stem-like cells during breast tumor progression.

Breast cancer stem-like cells (BCSCs) play vital roles in tumorigenesis and progression. However, the origin and dynamic changes of BCSCs are still to be elucidated. Using the breast cancer mouse model MMTV-PyMT, we constructed a single-cell atlas of 31,778 cells from four distinct stages of tumor progression (hyperplasia, adenoma/MIN, early carcinoma and late carcinoma), during which malignant transition occurs. We identified that the precise cell type of ERlow epithelial cell lineage gave rise to the tumors, and the differentiation of ERhigh epithelial cell lineage was blocked. Furthermore, we discovered a specific signature with a continuum of gene expression profiles along the tumor progression and significantly correlated with clinical outcomes, and we also found a stem-like cell cluster existed among ERlow epithelial cells. Further clustering on this stem-like cluster showed several sub-clusters indicating heterogeneity of stem-like epithelial cells. Moreover, we distinguished normal and cancer stem-like cells in this stem-like epithelial cell cluster and profiled the molecular portraits from normal stem-like cell to cancer stem-like cells during the malignant transition. Finally, we found the diverse immune cell infiltration displayed immunosuppressive characteristics along tumor progression. We also found the specific expression pattern of cytokines and their corresponding cytokine receptors in BCSCs and immune cells, suggesting the possible cross-talk between BCSCs and the immune cells. These data provide a useful resource for illuminating BCSC heterogeneity and the immune cell remodeling during breast tumor progression, and shed new light on transcriptomic dynamics during the progression at the single-cell level.

Single-cell profiling of tumor heterogeneity and the microenvironment in advanced non-small cell lung cancer.

Lung cancer is a highly heterogeneous disease. Cancer cells and cells within the tumor microenvironment together determine disease progression, as well as response to or escape from treatment. To map the cell type-specific transcriptome landscape of cancer cells and their tumor microenvironment in advanced non-small cell lung cancer (NSCLC), we analyze 42 tissue biopsy samples from stage III/IV NSCLC patients by single cell RNA sequencing and present the large scale, single cell resolution profiles of advanced NSCLCs. In addition to cell types described in previous single cell studies of early stage lung cancer, we are able to identify rare cell types in tumors such as follicular dendritic cells and T helper 17 cells. Tumors from different patients display large heterogeneity in cellular composition, chromosomal structure, developmental trajectory, intercellular signaling network and phenotype dominance. Our study also reveals a correlation of tumor heterogeneity with tumor associated neutrophils, which might help to shed light on their function in NSCLC.

Single-cell analysis of angiotensin-converting enzyme II expression in human kidneys and bladders reveals a potential route of 2019 novel coronavirus infection.

BACKGROUND: Since 2019, a novel coronavirus named 2019 novel coronavirus (2019-nCoV) has emerged worldwide. Apart from fever and respiratory complications, acute kidney injury has been observed in a few patients with coronavirus disease 2019. Furthermore, according to recent findings, the virus has been detected in urine. Angiotensin-converting enzyme II (ACE2) has been proposed to serve as the receptor for the entry of 2019-nCoV, which is the same as that for the severe acute respiratory syndrome. This study aimed to investigate the possible cause of kidney damage and the potential route of 2019-nCoV infection in the urinary system. METHODS: We used both published kidney and bladder cell atlas data and new independent kidney single-cell RNA sequencing data generated in-house to evaluate ACE2 gene expression in all cell types in healthy kidneys and bladders. The Pearson correlation coefficients between ACE2 and all other genes were first generated. Then, genes with r values larger than 0.1 and P values smaller than 0.01 were deemed significant co-expression genes with ACE2. RESULTS: Our results showed the enriched expression of ACE2 in all subtypes of proximal tubule (PT) cells of the kidney. ACE2 expression was found in 5.12%, 5.80%, and 14.38% of the proximal convoluted tubule cells, PT cells, and proximal straight tubule cells, respectively, in three published kidney cell atlas datasets. In addition, ACE2 expression was also confirmed in 12.05%, 6.80%, and 10.20% of cells of the proximal convoluted tubule, PT, and proximal straight tubule, respectively, in our own two healthy kidney samples. For the analysis of public data from three bladder samples, ACE2 expression was low but detectable in bladder epithelial cells. Only 0.25% and 1.28% of intermediate cells and umbrella cells, respectively, had ACE2 expression. CONCLUSION: This study has provided bioinformatics evidence of the potential route of 2019-nCoV infection in the urinary system.

Patients With Short PFS to EGFR-TKIs Predicted Better Response to Subsequent Anti-PD-1/PD-L1 Based Immunotherapy in EGFR Common Mutation NSCLC.

BACKGROUND: Despite disappointing outcomes from immuno-monotherapy, studies reported that NSCLC patients with EGFR mutation may possibly benefit from combined immunotherapy. Whether the response to prior EGFR-TKI has association with the outcomes of subsequent immunotherapy remains unclear. PATIENTS AND METHODS: Advanced NSCLC patients with resistance to EGFR-TKIs and received ICI treatment from January 2016 to June 2019 were retrospectively analyzed. Single cell sequencing and flow cytometry were conducted to explore the difference of cell components in tumor microenvironments (TME). A 1:3 matched case-control study was conducted to compare the clinical effects of combined immunotherapy with standard chemotherapy as second-line treatment. RESULTS: Fifty-eight patients treated with anti-PD-1/PD-L1 based immunotherapy behind EGFR-TKI treatment were enrolled. Correlation analysis showed TKI-PFS had a significantly negative association with corresponding IO-PFS (r = -0.35, p = 0.006). TKI-PFS cutoff 10 months had the most significant predictive function for posterior immunotherapy and was validated to be an independent predictor by uni- and multivariate analyses. Kaplan-Meier analysis showed that patients with TKI-PFS less than 10 months had significantly prolonged IO-PFS and higher ORR than those with long (median PFS, 15.1 vs 3.8 months; HR, 0.26, p = 0.0002; ORR, 31.8 versus 10%, p = 0.04). Single cell RNA-seq revealed that the cell components were varied among patients after treatment with EGFR-TKI. Patients with short TKI-PFS demonstrated a relatively higher proportion of CD8 effector cells and lower ratio of M2 like macrophage to M1 like macrophages, which was validated by flow cytometry. Case-control study demonstrated that combined immunotherapy achieved significantly longer PFS (HR, 0.51, 95% CI: 0.31-0.85, p = 0.02), longer OS (HR, 0.48, 95% CI: 0.26-0.89, p = 0.05) and higher ORR (33.3 vs 10.0%, p = 0.02) than traditional chemotherapy for patients with short TKI-PFS. CONCLUSION: Patients with short TKI-PFS conferred better response to immunotherapy than those with long. The status of TME were different among those two populations. Combined ICI treatment could promisingly be a better choice than classical chemotherapy in second-line setting for patients with short TKI-PFS and no T790M mutation. Underlying mechanisms need to be further explored.

Single Cell Sequencing: A New Dimension in Cancer Diagnosis and Treatment.

Cancer is one of the leading causes of death worldwide and well known for its complexity. Cancer cells within the same tumor or from different tumors are highly heterogeneous. Furthermore, stromal and immune cells within tumor microenvironment interact with cancer cells to play important roles in how tumors progress and respond to different treatments. Recent advances in single cell technologies, especially massively parallel single cell sequencing, have made it possible to analyze cancer cells and cells in its tumor microenvironment in parallel with unprecedented high resolution. In this chapter, we will review recent developments in single cell sequencing technologies and their applications in cancer research. We will also explain how insights generated from single cell sequencing can be used to develop novel diagnostic and therapeutic approaches to conquer cancer.

Unraveling epigenomic abnormality in azoospermic human males by WGBS, RNA-Seq, and transcriptome profiling analyses.

PURPOSE: To determine associations between genomic DNA methylation in testicular cells and azoospermia in human males. METHODS: This was a case-control study investigating the differences and conservations in DNA methylation, genome-wide DNA methylation, and bulk RNA-Seq for transcriptome profiling using testicular biopsy tissues from NOA and OA patients. Differential methylation and different conserved methylation regions associated with azoospermia were identified by comparing genomic DNA methylation of testicular seminiferous cells derived from NOA and OA patients. RESULTS: The genome methylation modification of testicular cells from NOA patients was disordered, and the reproductive-related gene expression was significantly different. CONCLUSION: Our findings not only provide valuable knowledge of human spermatogenesis but also paved the way for the identification of genes/proteins involved in male germ cell development. The approach presented in this report provides a powerful tool to identify responsible biomolecules, and/or cellular changes (e.g., epigenetic abnormality) that induce male reproductive dysfunction such as OA and NOA.

Evaluation of single-cell classifiers for single-cell RNA sequencing data sets.

Single-cell RNA sequencing (scRNA-seq) has been rapidly developing and widely applied in biological and medical research. Identification of cell types in scRNA-seq data sets is an essential step before in-depth investigations of their functional and pathological roles. However, the conventional workflow based on clustering and marker genes is not scalable for an increasingly large number of scRNA-seq data sets due to complicated procedures and manual annotation. Therefore, a number of tools have been developed recently to predict cell types in new data sets using reference data sets. These methods have not been generally adapted due to a lack of tool benchmarking and user guidance. In this article, we performed a comprehensive and impartial evaluation of nine classification software tools specifically designed for scRNA-seq data sets. Results showed that Seurat based on random forest, SingleR based on correlation analysis and CaSTLe based on XGBoost performed better than others. A simple ensemble voting of all tools can improve the predictive accuracy. Under nonideal situations, such as small-sized and class-imbalanced reference data sets, tools based on cluster-level similarities have superior performance. However, even with the function of assigning 'unassigned' labels, it is still challenging to catch novel cell types by solely using any of the single-cell classifiers. This article provides a guideline for researchers to select and apply suitable classification tools in their analysis workflows and sheds some lights on potential direction of future improvement on classification tools.

Modulation of hippocampal neuronal resilience during aging by the Hsp70/Hsp90 co-chaperone STI1.

Chaperone networks are dysregulated with aging, but whether compromised Hsp70/Hsp90 chaperone function disturbs neuronal resilience is unknown. Stress-inducible phosphoprotein 1 (STI1; STIP1; HOP) is a co-chaperone that simultaneously interacts with Hsp70 and Hsp90, but whose function in vivo remains poorly understood. We combined in-depth analysis of chaperone genes in human datasets, analysis of a neuronal cell line lacking STI1 and of a mouse line with a hypomorphic Stip1 allele to investigate the requirement for STI1 in aging. Our experiments revealed that dysfunctional STI1 activity compromised Hsp70/Hsp90 chaperone network and neuronal resilience. The levels of a set of Hsp90 co-chaperones and client proteins were selectively affected by reduced levels of STI1, suggesting that their stability depends on functional Hsp70/Hsp90 machinery. Analysis of human databases revealed a subset of co-chaperones, including STI1, whose loss of function is incompatible with life in mammals, albeit they are not essential in yeast. Importantly, mice expressing a hypomorphic STI1 allele presented spontaneous age-dependent hippocampal neurodegeneration and reduced hippocampal volume, with consequent spatial memory deficit. We suggest that impaired STI1 function compromises Hsp70/Hsp90 chaperone activity in mammals and can by itself cause age-dependent hippocampal neurodegeneration in mice. Cover Image for this issue: doi: 10.1111/jnc.14749.

QTG-Finder: A Machine-Learning Based Algorithm To Prioritize Causal Genes of Quantitative Trait Loci in Arabidopsis and Rice.

Linkage mapping is one of the most commonly used methods to identify genetic loci that determine a trait. However, the loci identified by linkage mapping may contain hundreds of candidate genes and require a time-consuming and labor-intensive fine mapping process to find the causal gene controlling the trait. With the availability of a rich assortment of genomic and functional genomic data, it is possible to develop a computational method to facilitate faster identification of causal genes. We developed QTG-Finder, a machine learning based algorithm to prioritize causal genes by ranking genes within a quantitative trait locus (QTL). Two predictive models were trained separately based on known causal genes in Arabidopsis and rice. An independent validation analysis showed that the models could recall about 64% of Arabidopsis and 79% of rice causal genes when the top 20% ranked genes were considered. The top 20% ranked genes can range from 10 to 100 genes, depending on the size of a QTL. The models can prioritize different types of traits though at different efficiency. We also identified several important features of causal genes including paralog copy number, being a transporter, being a transcription factor, and containing SNPs that cause premature stop codon. This work lays the foundation for systematically understanding characteristics of causal genes and establishes a pipeline to predict causal genes based on public data.

Detection of Active Caspase-3 in Mouse Models of Stroke and Alzheimer's Disease with a Novel Dual Positron Emission Tomography/Fluorescent Tracer [68Ga]Ga-TC3-OGDOTA.

Apoptosis is a feature of stroke and Alzheimer's disease (AD), yet there is no accepted method to detect or follow apoptosis in the brain in vivo. We developed a bifunctional tracer [68Ga]Ga-TC3-OGDOTA containing a cell-penetrating peptide separated from fluorescent Oregon Green and 68Ga-bound labels by the caspase-3 recognition peptide DEVD. We hypothesized that this design would allow [68Ga]Ga-TC3-OGDOTA to accumulate in apoptotic cells. In vitro, Ga-TC3-OGDOTA labeled apoptotic neurons following exposure to camptothecin, oxygen-glucose deprivation, and ß-amyloid oligomers. In vivo, PET showed accumulation of [68Ga]Ga-TC3-OGDOTA in the brain of mouse models of stroke or AD. Optical clearing revealed colocalization of [68Ga]Ga-TC3-OGDOTA and cleaved caspase-3 in brain cells. In stroke, [68Ga]Ga-TC3-OGDOTA accumulated in neurons in the penumbra area, whereas in AD mice [68Ga]Ga-TC3-OGDOTA was found in single cells in the forebrain and diffusely around amyloid plaques. In summary, this bifunctional tracer is selectively associated with apoptotic cells in vitro and in vivo in brain disease models and represents a novel tool for apoptosis detection that can be used in neurodegenerative diseases.

Relationship between the after-school schedule and bone mineral density in middle-school students in Shanghai / 中国学校卫生

Objective@#To investigate the relationship between after-school schedule and bone mineral density in middle-school students in Shanghai, to provide a reference for taking targeted measures.@*Methods@#From November 2017 to April 2018，eighteen classes of six middle schools in Shanghai (from urban districts, urban-suburb combined districts and suburban districts, respectively) were selected based on cluster random sampling. In each school, 2-4 classes were further randomly chosen in the 6th grade. Questionnaires were completed by 518 students and their parents, as well as physical examination and bone mineral density assessment.@*Results@#The average time spent on after-school academic learning during weekends was 4.0 (IQR: 2.0, 6.0) h. The Z-score of bone density was 0.3 (IQR: -0.7, 1.0). The smooth curve fit model showed a non-linear relationship between after-school academic learning time during weekends and the Z-scores of bone mineral densities. A two-stage multiple linear regression analysis was further applied according to the fit results, and the results showed that when total afterschool academic learning time <4.5 hours during weekends, the learning time was inversely correlated with the bone density Z-scores (β=-0.11,P=0.01), and when the learning time ≥4.5 hours, there was no significant correlation between the learning time and bone density Z-scores (β=0.02, P=0.65). Parent and student questionnaires showed that there was a non-linear relationship between students’ daily time spent on outdoor sports-related activities and bone density Z-scores. When time spent on the outdoor activities ≥45 minutes per day, outdoor activities were positively correlated with bone density Z-scores (P<0.05). However, when the time spent on outdoor activities <45 minutes per day, there was no significant relationship between outdoor activities and bone density Z-scores (P>0.05).@*Conclusion@#Too much time on after-school academic learning during weekends or limited time on outdoor activities are both related to impaired bone mineral densities. Therefore, a reasonable after-school schedule for middle-school students is important for physical development, especially during weekends.

An interpretable framework for clustering single-cell RNA-Seq datasets.

BACKGROUND: With the recent proliferation of single-cell RNA-Seq experiments, several methods have been developed for unsupervised analysis of the resulting datasets. These methods often rely on unintuitive hyperparameters and do not explicitly address the subjectivity associated with clustering. RESULTS: In this work, we present DendroSplit, an interpretable framework for analyzing single-cell RNA-Seq datasets that addresses both the clustering interpretability and clustering subjectivity issues. DendroSplit offers a novel perspective on the single-cell RNA-Seq clustering problem motivated by the definition of "cell type", allowing us to cluster using feature selection to uncover multiple levels of biologically meaningful populations in the data. We analyze several landmark single-cell datasets, demonstrating both the method's efficacy and computational efficiency. CONCLUSION: DendroSplit offers a clustering framework that is comparable to existing methods in terms of accuracy and speed but is novel in its emphasis on interpretabilty. We provide the full DendroSplit software package at https://github.com/jessemzhang/dendrosplit .

Mechanisms of neuroprotection against ischemic insult by stress-inducible phosphoprotein-1/prion protein complex.

Stress-inducible phosphoprotein 1 (STI1) acts as a neuroprotective factor in the ischemic brain and its levels are increased following ischemia. Previous work has suggested that some of these STI1 actions in a stroke model depend on the recruitment of bone marrow-derived stem cells to improve outcomes after ischemic insult. However, STI1 can directly increase neuroprotective signaling in neurons by engaging with the cellular prion protein (PrPC ) and activating α7 nicotinic acetylcholine receptors (α7nAChR). Given that α7nAChR activation has also been involved in neuroprotection in stroke, it is possible that STI1 can have direct actions on neurons to prevent deleterious consequences of ischemic insults. Here, we tested this hypothesis by exposing primary neuronal cultures to 1-h oxygen-glucose deprivation (OGD) and reperfusion and assessing signaling pathways activated by STI1/PrPC . Our results demonstrated that STI1 treatment significantly decreased apoptosis and cell death in mouse neurons submitted to OGD in a manner that was dependent on PrPC and α7nAChR, but also on the activin A receptor 1 (ALK2), which has emerged as a signaling partner of STI1. Interestingly, pharmacological inhibition of the ALK2 receptor prevented neuroprotection by STI1, while activation of ALK2 receptors by bone morphogenetic protein 4 (BMP4) either before or after OGD was effective in decreasing neuronal death induced by ischemia. We conclude that PrPC /STI1 engagement and its subsequent downstream signaling cascades involving α7nAChR as well as the ALK2 receptor may be activated in neurons by increased levels of STI1. This signaling pathway protects neurons from ischemic insults.