Transplantation of chemically induced pluripotent stem-cell-derived islets under abdominal anterior rectus sheath in a type 1 diabetes patient.

We report the 1-year results from one patient as the preliminary analysis of a first-in-human phase I clinical trial (ChiCTR2300072200) assessing the feasibility of autologous transplantation of chemically induced pluripotent stem-cell-derived islets (CiPSC islets) beneath the abdominal anterior rectus sheath for type 1 diabetes treatment. The patient achieved sustained insulin independence starting 75 days post-transplantation. The patient's time-in-target glycemic range increased from a baseline value of 43.18% to 96.21% by month 4 post-transplantation, accompanied by a decrease in glycated hemoglobin, an indicator of long-term systemic glucose levels at a non-diabetic level. Thereafter, the patient presented a state of stable glycemic control, with time-in-target glycemic range at >98% and glycated hemoglobin at around 5%. At 1 year, the clinical data met all study endpoints with no indication of transplant-related abnormalities. Promising results from this patient suggest that further clinical studies assessing CiPSC-islet transplantation in type 1 diabetes are warranted.

Mediation analysis in longitudinal study with high-dimensional methylation mediators.

Mediation analysis has been widely utilized to identify potential pathways connecting exposures and outcomes. However, there remains a lack of analytical methods for high-dimensional mediation analysis in longitudinal data. To tackle this concern, we proposed an effective and novel approach with variable selection and the indirect effect (IE) assessment based on both linear mixed-effect model and generalized estimating equation. Initially, we employ sure independence screening to reduce the dimension of candidate mediators. Subsequently, we implement the Sobel test with the Bonferroni correction for IE hypothesis testing. Through extensive simulation studies, we demonstrate the performance of our proposed procedure with a higher F$_{1}$ score (0.8056 and 0.9983 at sample sizes of 150 and 500, respectively) compared with the linear method (0.7779 and 0.9642 at the same sample sizes), along with more accurate parameter estimation and a significantly lower false discovery rate. Moreover, we apply our methodology to explore the mediation mechanisms involving over 730 000 DNA methylation sites with potential effects between the paternal body mass index (BMI) and offspring growing BMI in the Shanghai sleeping birth cohort data, leading to the identification of two previously undiscovered mediating CpG sites.

Algorithm-agnostic significance testing in supervised learning with multimodal data.

MOTIVATION: Valid statistical inference is crucial for decision-making but difficult to obtain in supervised learning with multimodal data, e.g. combinations of clinical features, genomic data, and medical images. Multimodal data often warrants the use of black-box algorithms, for instance, random forests or neural networks, which impede the use of traditional variable significance tests. RESULTS: We address this problem by proposing the use of COvariance MEasure Tests (COMETs), which are calibrated and powerful tests that can be combined with any sufficiently predictive supervised learning algorithm. We apply COMETs to several high-dimensional, multimodal data sets to illustrate (i) variable significance testing for finding relevant mutations modulating drug-activity, (ii) modality selection for predicting survival in liver cancer patients with multiomics data, and (iii) modality selection with clinical features and medical imaging data. In all applications, COMETs yield results consistent with domain knowledge without requiring data-driven pre-processing, which may invalidate type I error control. These novel applications with high-dimensional multimodal data corroborate prior results on the power and robustness of COMETs for significance testing. AVAILABILITY AND IMPLEMENTATION: COMETs are implemented in the cometsR package available on CRAN and pycometsPython library available on GitHub. Source code for reproducing all results is available at https://github.com/LucasKook/comets. All data sets used in this work are openly available.

Using conditional independence tests to elucidate causal links in cell cycle regulation in Escherichia coli.

How cells regulate their cell cycles is a central question for cell biology. Models of cell size homeostasis have been proposed for bacteria, archaea, yeast, plant, and mammalian cells. New experiments bring forth high volumes of data suitable for testing existing models of cell size regulation and proposing new mechanisms. In this paper, we use conditional independence tests in conjunction with data of cell size at key cell cycle events (birth, initiation of DNA replication, and constriction) in the model bacterium Escherichia coli to select between the competing cell cycle models. We find that in all growth conditions that we study, the division event is controlled by the onset of constriction at midcell. In slow growth, we corroborate a model where replication-related processes control the onset of constriction at midcell. In faster growth, we find that the onset of constriction is affected by additional cues beyond DNA replication. Finally, we also find evidence for the presence of additional cues triggering initiations of DNA replication apart from the conventional notion where the mother cells solely determine the initiation event in the daughter cells via an adder per origin model. The use of conditional independence tests is a different approach in the context of understanding cell cycle regulation and it can be used in future studies to further explore the causal links between cell events.

Powerful Rare-Variant Association Analysis of Secondary Phenotypes.

Most genome-wide association studies are based on case-control designs, which provide abundant resources for secondary phenotype analyses. However, such studies suffer from biased sampling of primary phenotypes, and the traditional statistical methods can lead to seriously distorted analysis results when they are applied to secondary phenotypes without accounting for the biased sampling mechanism. To our knowledge, there are no statistical methods specifically tailored for rare variant association analysis with secondary phenotypes. In this article, we proposed two novel joint test statistics for identifying secondary-phenotype-associated rare variants based on prospective likelihood and retrospective likelihood, respectively. We also exploit the assumption of gene-environment independence in retrospective likelihood to improve the statistical power and adopt a two-step strategy to balance statistical power and robustness. Simulations and a real-data application are conducted to demonstrate the superior performance of our proposed methods.

Speeding up interval estimation for R2-based mediation effect of high-dimensional mediators via cross-fitting.

Mediation analysis is a useful tool in investigating how molecular phenotypes such as gene expression mediate the effect of exposure on health outcomes. However, commonly used mean-based total mediation effect measures may suffer from cancellation of component-wise mediation effects in opposite directions in the presence of high-dimensional omics mediators. To overcome this limitation, we recently proposed a variance-based R-squared total mediation effect measure that relies on the computationally intensive nonparametric bootstrap for confidence interval estimation. In the work described herein, we formulated a more efficient two-stage, cross-fitted estimation procedure for the R2 measure. To avoid potential bias, we performed iterative Sure Independence Screening (iSIS) in two subsamples to exclude the non-mediators, followed by ordinary least squares regressions for the variance estimation. We then constructed confidence intervals based on the newly derived closed-form asymptotic distribution of the R2 measure. Extensive simulation studies demonstrated that this proposed procedure is much more computationally efficient than the resampling-based method, with comparable coverage probability. Furthermore, when applied to the Framingham Heart Study, the proposed method replicated the established finding of gene expression mediating age-related variation in systolic blood pressure and identified the role of gene expression profiles in the relationship between sex and high-density lipoprotein cholesterol level. The proposed estimation procedure is implemented in R package CFR2M.

A rapid and versatile reverse genetics approach for generating recombinant positive-strand RNA viruses that use IRES-mediated translation.

Reverse genetics systems have played a central role in developing recombinant viruses for a wide spectrum of virus research. The circular polymerase extension reaction (CPER) method has been applied to studying positive-strand RNA viruses, allowing researchers to bypass molecular cloning of viral cDNA clones and thus leading to the rapid generation of recombinant viruses. However, thus far, the CPER protocol has only been established using cap-dependent RNA viruses. Here, we demonstrate that a modified version of the CPER method can be successfully applied to positive-strand RNA viruses that use cap-independent, internal ribosomal entry site (IRES)-mediated translation. As a proof-of-concept, we employed mammalian viruses with different types (classes I, II, and III) of IRES to optimize the CPER method. Using the hepatitis C virus (HCV, class III), we found that inclusion in the CPER assembly of an RNA polymerase I promoter and terminator, instead of those from polymerase II, allowed greater viral production. This approach was also successful in generating recombinant bovine viral diarrhea virus (class III) following transfection of MDBK/293T co-cultures to overcome low transfection efficiency. In addition, we successfully generated the recombinant viruses from clinical specimens. Our modified CPER could be used for producing hepatitis A virus (HAV, type I) as well as de novo generation of encephalomyocarditis virus (type II). Finally, we generated recombinant HCV and HAV reporter viruses that exhibited replication comparable to that of the wild-type parental viruses. The recombinant HAV reporter virus helped evaluate antivirals. Taking the findings together, this study offers methodological advances in virology. IMPORTANCE: The lack of versatility of reverse genetics systems remains a bottleneck in viral research. Especially when (re-)emerging viruses reach pandemic levels, rapid characterization and establishment of effective countermeasures using recombinant viruses are beneficial in disease control. Indeed, numerous studies have attempted to establish and improve the methods. The circular polymerase extension reaction (CPER) method has overcome major obstacles in generating recombinant viruses. However, this method has not yet been examined for positive-strand RNA viruses that use cap-independent, internal ribosome entry site-mediated translation. Here, we engineered a suitable gene cassette to expand the CPER method for all positive-strand RNA viruses. Furthermore, we overcame the difficulty of generating recombinant viruses because of low transfection efficiency. Using this modified method, we also successfully generated reporter viruses and recombinant viruses from a field sample without virus isolation. Taking these findings together, our adapted methodology is an innovative technology that could help advance virologic research.

P-CSN: single-cell RNA sequencing data analysis by partial cell-specific network.

Although many single-cell computational methods proposed use gene expression as input, recent studies show that replacing 'unstable' gene expression with 'stable' gene-gene associations can greatly improve the performance of downstream analysis. To obtain accurate gene-gene associations, conditional cell-specific network method (c-CSN) filters out the indirect associations of cell-specific network method (CSN) based on the conditional independence of statistics. However, when there are strong connections in networks, the c-CSN suffers from false negative problem in network construction. To overcome this problem, a new partial cell-specific network method (p-CSN) based on the partial independence of statistics is proposed in this paper, which eliminates the singularity of the c-CSN by implicitly including direct associations among estimated variables. Based on the p-CSN, single-cell network entropy (scNEntropy) is further proposed to quantify cell state. The superiorities of our method are verified on several datasets. (i) Compared with traditional gene regulatory network construction methods, the p-CSN constructs partial cell-specific networks, namely, one cell to one network. (ii) When there are strong connections in networks, the p-CSN reduces the false negative probability of the c-CSN. (iii) The input of more accurate gene-gene associations further optimizes the performance of downstream analyses. (iv) The scNEntropy effectively quantifies cell state and reconstructs cell pseudo-time.

Cultural Psychology: Beyond East and West.

Research in cultural psychology over the last three decades has revealed the profound influence of culture on cognitive, emotional, and motivational processes shaping individuals into active agents. This article aims to show cultural psychology's promise in three key steps. First, we review four notable cultural dimensions believed to underlie cultural variations: independent versus interdependent self, individualism versus collectivism, tightness versus looseness of social norms, and relational mobility. Second, we examine how ecology and geography shape human activities and give rise to organized systems of cultural practices and meanings, called eco-cultural complexes. In turn, the eco-cultural complex of each zone is instrumental in shaping a wide range of psychological processes, revealing a psychological diversity that extends beyond the scope of the current East-West literature. Finally, we examine some of the non-Western cultural zones present today, including Arab, East Asian, Latin American, and South Asian zones, and discuss how they may have contributed, to varying degrees, to the formation of the contemporary Western cultural zone.

Adjudin improves beta cell maturation, hepatic glucose uptake and glucose homeostasis.

AIMS/HYPOTHESIS: Recovering functional beta cell mass is a promising approach for future diabetes therapies. The aim of the present study is to investigate the effects of adjudin, a small molecule identified in a beta cell screen using zebrafish, on pancreatic beta cells and diabetes conditions in mice and human spheroids. METHODS: In zebrafish, insulin expression was examined by bioluminescence and quantitative real-time PCR (qPCR), glucose levels were examined by direct measurements and distribution using a fluorescent glucose analogue, and calcium activity in beta cells was analysed by in vivo live imaging. Pancreatic islets of wild-type postnatal day 0 (P0) and 3-month-old (adult) mice, as well as adult db/db mice (i.e. BKS(D)-Leprdb/JOrlRj), were cultured in vitro and analysed by qPCR, glucose stimulated insulin secretion and whole mount staining. RNA-seq was performed for islets of P0 and db/db mice. For in vivo assessment, db/db mice were treated with adjudin and subjected to analysis of metabolic variables and islet cells. Glucose consumption was examined in primary human hepatocyte spheroids. RESULTS: Adjudin treatment increased insulin expression and calcium response to glucose in beta cells and decreased glucose levels after beta cell ablation in zebrafish. Adjudin led to improved beta cell function, decreased beta cell proliferation and glucose responsive insulin secretion by decreasing basal insulin secretion in in vitro cultured newborn mouse islets. RNA-seq of P0 islets indicated that adjudin treatment resulted in increased glucose metabolism and mitochondrial function, as well as downstream signalling pathways involved in insulin secretion. In islets from db/db mice cultured in vitro, adjudin treatment strengthened beta cell identity and insulin secretion. RNA-seq of db/db islets indicated adjudin-upregulated genes associated with insulin secretion, membrane ion channel activity and exocytosis. Moreover, adjudin promoted glucose uptake in the liver of zebrafish in an insulin-independent manner, and similarly promoted glucose consumption in primary human hepatocyte spheroids with insulin resistance. In vivo studies using db/db mice revealed reduced nonfasting blood glucose, improved glucose tolerance and strengthened beta cell identity after adjudin treatment. CONCLUSIONS/INTERPRETATION: Adjudin promoted functional maturation of immature islets, improved function of dysfunctional islets, stimulated glucose uptake in liver and improved glucose homeostasis in db/db mice. Thus, the multifunctional drug adjudin, previously studied in various contexts and conditions, also shows promise in the management of diabetic states. DATA AVAILABILITY: Raw and processed RNA-seq data for this study have been deposited in the Gene Expression Omnibus under accession number GSE235398 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE235398 ).

Phenotype and predictors of insulin independence in adults presenting with diabetic ketoacidosis: a prospective cohort study.

AIMS/HYPOTHESIS: The aim of this work was to describe the phenotype of adults presenting with a first episode of diabetic ketoacidosis (DKA) in Cape Town, South Africa, and identify predictors of insulin independence at 12 and 60 months after presentation. METHODS: A prospective, descriptive cohort study of all individuals, 18 years or older, presenting for the first time with DKA to four public-sector hospitals of the Groote Schuur Academic Health Complex was performed. Clinical, biochemical and laboratory data including GAD antibody and C-peptide status were collected at baseline. Insulin was systematically weaned and stopped in individuals who achieved normoglycaemia within the months after DKA. Individuals were followed for 12 months and then annually until 5 years after initial presentation with ketoacidosis. RESULTS: Eighty-eight individuals newly diagnosed with diabetes when presenting with DKA were included and followed for 5 years. The mean ± SD age was 35±10 years and the median (IQR) BMI at diagnosis was 28.5 (23.3-33.4) kg/m2. Overall, 46% were insulin independent 12 months after diagnosis and 26% remained insulin independent 5 years after presentation. Forty-one participants (47%) tested negative for anti-GAD and anti-IA-2 antibodies and had C-peptide levels >0.3 nmol/l; in this group, 68% were insulin independent at 12 months and 37% at 5 years after diagnosis. The presence of acanthosis nigricans was strongly associated with insulin independence (OR 27.1 [95% CI 7.2, 102.2]; p<0.001); a positive antibody status was associated with a lower likelihood of insulin independence at 12 months (OR 0.10 [95% CI 0.03, 0.36]; p<0.001). On multivariable analysis only acanthosis (OR 11.5 [95% CI 2.5, 53.2]; p=0.004) was predictive of insulin independence 5 years after diagnosis. CONCLUSIONS/INTERPRETATION: The predominant phenotype of adults presenting with a first episode of DKA in Cape Town, South Africa, was that of ketosis-prone type 2 diabetes. These individuals presented with obesity, acanthosis nigricans, negative antibodies and normal C-peptide and could potentially be weaned off insulin at follow-up. Classic type 1 diabetes (lower weight, antibody positivity, low or unrecordable C-peptide levels and long-term insulin dependence) was less common. The simple clinical sign of acanthosis nigricans is a strong predictor of insulin independence at 12 months and 5 years after initial presentation.

Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study.

The statistical analysis of omics data poses a great computational challenge given their ultra-high-dimensional nature and frequent between-features correlation. In this work, we extended the iterative sure independence screening (ISIS) algorithm by pairing ISIS with elastic-net (Enet) and 2 versions of adaptive elastic-net (adaptive elastic-net (AEnet) and multistep adaptive elastic-net (MSAEnet)) to efficiently improve feature selection and effect estimation in omics research. We subsequently used genome-wide human blood DNA methylation data from American Indian participants in the Strong Heart Study (n = 2235 participants; measured in 1989-1991) to compare the performance (predictive accuracy, coefficient estimation, and computational efficiency) of ISIS-paired regularization methods with that of a bayesian shrinkage and traditional linear regression to identify an epigenomic multimarker of body mass index (BMI). ISIS-AEnet outperformed the other methods in prediction. In biological pathway enrichment analysis of genes annotated to BMI-related differentially methylated positions, ISIS-AEnet captured most of the enriched pathways in common for at least 2 of all the evaluated methods. ISIS-AEnet can favor biological discovery because it identifies the most robust biological pathways while achieving an optimal balance between bias and efficient feature selection. In the extended SIS R package, we also implemented ISIS paired with Cox and logistic regression for time-to-event and binary endpoints, respectively, and a bootstrap approach for the estimation of regression coefficients.

Vertical mother-to-infant transmission of herpes simplex virus 2 is correlated with tropism due to mutations in viral UL13.

Although neonates are commonly exposed to vaginal herpes simplex virus (HSV)-2, neonatal herpes is rare. Therefore, we analyzed paired infant and maternal HSV-2 isolates from two cases of mother-to-infant transmission to identify viral factors contributing to vertical transmission. Sixteen infant isolates with neonatal herpes and 27 genital isolates in their third trimester were included. The infant isolates were significantly more temperature-independent than the maternal isolates. Sequence comparison revealed viral UL13 protein kinase (UL13-PK) mutation in the infant isolates in both cases. In the expanded cohort, infant isolates (5/18) had significantly more UL13-PK mutations than genital isolates (1/29). Isolates within 8 days post-birth (3/4) had a significantly higher frequency of UL13-PK mutation than those after 9 days (2/14), suggesting a close association between UL13-PK mutations and vertical transmission. Elongation factor 1-delta was identified as a target of UL13-PK by proteomic analysis of UL13-PK-positive and -negative HepG2 cells. The mixed infant isolates with the intact and mutated UL13-PK conferred altered cell tropism, temperature independence adapting to fetal temperature, and better growth properties in Vero and hepatoblastoma HepG2 cells than in HSV-2 with intact and mutated UL13-PK alone, indicating that viral UL13-PK mutation is essential for vertical HSV-2 transmission.

miR-129-5p inhibits anchorage-independent growth through silencing of ACTN1 and the ELK4/c-FOS axis in HPV-transformed keratinocytes.

A persistent infection with human papillomavirus (HPV) can induce precancerous lesions of the cervix that may ultimately develop into cancer. Cervical cancer development has been linked to altered microRNA (miRNA) expression, with miRNAs regulating anchorage-independent growth being particularly important for the progression of precancerous lesions to cancer. In this study, we set out to identify and validate targets of miR-129-5p, a previously identified tumor suppressive miRNA involved in anchorage-independent growth and HPV-induced carcinogenesis. We predicted 26 potential miR-129-5p targets using online databases, followed by KEGG pathway enrichment analysis. RT-qPCR and luciferase assays confirmed that 3'UTR regions of six genes (ACTN1, BMPR2, CAMK4, ELK4, EP300, and GNAQ) were targeted by miR-129-5p. Expressions of ACTN1, CAMK4, and ELK4 were inversely correlated to miR-129-5p expression in HPV-transformed keratinocytes, and their silencing reduced anchorage-independent growth. Concordantly, miR-129-5p overexpression decreased protein levels of ACTN1, BMPR2, CAMK4 and ELK4 in anchorage-independent conditions. Additionally, c-FOS, a downstream target of ELK4, was downregulated upon miR-129-5p overexpression, suggesting regulation through the ELK4/c-FOS axis. ACTN1 and ELK4 expression was also upregulated in high-grade precancerous lesions and cervical cancers, supporting their clinical relevance. In conclusion, we identified six targets of miR-129-5p involved in the regulation of anchorage-independent growth, with ACTN1, BMPR2, ELK4, EP300, and GNAQ representing novel targets for miR-129-5p. For both ACTN1 and ELK4 functional and clinical relevance was confirmed, indicating that miR-129-5p-regulated ACTN1 and ELK4 expression contributes to HPV-induced carcinogenesis.

An algorithm for discontinuing mechanical ventilation in boys with x-linked myotubular myopathy after positive response to gene therapy: the ASPIRO experience.

X-linked myotubular myopathy (XLMTM) is a rare, life-threatening congenital myopathy. Most (80%) children with XLMTM have profound muscle weakness and hypotonia at birth resulting in severe respiratory insufficiency, the inability to sit up, stand or walk, and early mortality. At birth, 85-90% of children with XLMTM require mechanical ventilation, with more than half requiring invasive ventilator support. Historically, ventilator-dependent children with neuromuscular-derived respiratory failure of this degree and nature, static or progressive, are not expected to achieve complete independence from mechanical ventilator support. In the ASPIRO clinical trial (NCT03199469), participants receiving a single intravenous dose of an investigational gene therapy (resamirigene bilparvovec) started showing significant improvements in daily hours of ventilation support compared with controls by 24 weeks post-dosing, and 16 of 24 dosed participants achieved ventilator independence between 14 and 97 weeks after dosing. At the time, there was no precedent or published guidance for weaning chronically ventilated children with congenital neuromuscular diseases off mechanical ventilation. When the first ASPIRO participants started showing dramatically improved respiratory function, the investigators initiated efforts to safely wean them off ventilator support, in parallel with primary protocol respiratory outcome measures. A group of experts in respiratory care and physiology and management of children with XLMTM developed an algorithm to safely wean children in the ASPIRO trial off mechanical ventilation as their respiratory muscle strength increased. The algorithm developed for this trial provides recommendations for assessing weaning readiness, a stepwise approach to weaning, and monitoring of children during and after the weaning process.

Protecting and promoting editorial independence.

We argue that editorial independence, through robust practice of publication ethics and research integrity, promotes good science and prevents bad science. We elucidate the concept of research integrity, and then discuss the dimensions of editorial independence. Best practice guidelines exist, but compliance with these guidelines varies. Therefore, we make recommendations for protecting and strengthening editorial independence.

Summary statistics knockoffs inference with family-wise error rate control.

Testing multiple hypotheses of conditional independence with provable error rate control is a fundamental problem with various applications. To infer conditional independence with family-wise error rate (FWER) control when only summary statistics of marginal dependence are accessible, we adopt GhostKnockoff to directly generate knockoff copies of summary statistics and propose a new filter to select features conditionally dependent on the response. In addition, we develop a computationally efficient algorithm to greatly reduce the computational cost of knockoff copies generation without sacrificing power and FWER control. Experiments on simulated data and a real dataset of Alzheimer's disease genetics demonstrate the advantage of the proposed method over existing alternatives in both statistical power and computational efficiency.

Testing conditional quantile independence with functional covariate.

We propose a new non-parametric conditional independence test for a scalar response and a functional covariate over a continuum of quantile levels. We build a Cramer-von Mises type test statistic based on an empirical process indexed by random projections of the functional covariate, effectively avoiding the "curse of dimensionality" under the projected hypothesis, which is almost surely equivalent to the null hypothesis. The asymptotic null distribution of the proposed test statistic is obtained under some mild assumptions. The asymptotic global and local power properties of our test statistic are then investigated. We specifically demonstrate that the statistic is able to detect a broad class of local alternatives converging to the null at the parametric rate. Additionally, we recommend a simple multiplier bootstrap approach for estimating the critical values. The finite-sample performance of our statistic is examined through several Monte Carlo simulation experiments. Finally, an analysis of an EEG data set is used to show the utility and versatility of our proposed test statistic.

From local to global gene co-expression estimation using single-cell RNA-seq data.

In genomics studies, the investigation of gene relationships often brings important biological insights. Currently, the large heterogeneous datasets impose new challenges for statisticians because gene relationships are often local. They change from one sample point to another, may only exist in a subset of the sample, and can be nonlinear or even nonmonotone. Most previous dependence measures do not specifically target local dependence relationships, and the ones that do are computationally costly. In this paper, we explore a state-of-the-art network estimation technique that characterizes gene relationships at the single cell level, under the name of cell-specific gene networks. We first show that averaging the cell-specific gene relationship over a population gives a novel univariate dependence measure, the averaged Local Density Gap (aLDG), that accumulates local dependence and can detect any nonlinear, nonmonotone relationship. Together with a consistent nonparametric estimator, we establish its robustness on both the population and empirical levels. Then, we show that averaging the cell-specific gene relationship over mini-batches determined by some external structure information (eg, spatial or temporal factor) better highlights meaningful local structure change points. We explore the application of aLDG and its minibatch variant in many scenarios, including pairwise gene relationship estimation, bifurcating point detection in cell trajectory, and spatial transcriptomics structure visualization. Both simulations and real data analysis show that aLDG outperforms existing ones.

Determinants of low satisfaction with life among wheelchair users with spinal cord injury in Egypt: a cross-sectional study.

BACKGROUND: Spinal cord injury (SCI) is one of the most catastrophic injuries that might lead to permanent use of a wheelchair and severely affects the quality of life, hence SCI patients report lower satisfaction with life (SWL) than the general population. Therefore, it is important to identify factors that determine SWL among wheelchair users with SCI. Our study aimed to assess the prevalence of low SWL and to identify its determinants among wheelchair users with SCI in Egypt. METHODS: A cross-sectional study included 105 wheelchair users with SCI from the Al Hassan Foundation for wheelchair users in Egypt. The main outcome measure was low SWL, while the independent variables included sociodemographic characteristics, injury-related characteristics, anxiety, depression, neuropathic pain, functional independence, and environmental barriers. RESULTS: The prevalence of low SWL among study participants was 57.1%. We found significant associations between SWL and age, area of living, and age at injury. Additionally, SWL correlated negatively with anxiety, depression, neuropathic pain, and environmental barriers, and positively with functional independence. Finally, the binary multiple logistic regression revealed that living in Upper Egypt (p = 0.017, OR = 13.7), depression (p = 0.034, OR = 6.08), older age (p = 0.002, OR = 1.21), and work and school environmental barriers (p = 0.022, OR = 0.46) were the predictors of low SWL. CONCLUSION: To improve the SWL for wheelchair users with SCI we need to effectively manage neuropathic pain, depression, and anxiety, and promote functional independence. There is an urgent need to reinforce legislation to improve the living conditions for wheelchair users with SCI in Egypt, especially in Upper Egypt.