Joint trajectory inference for single-cell genomics using deep learning with a mixture prior.

Trajectory inference methods are essential for analyzing the developmental paths of cells in single-cell sequencing datasets. It provides insights into cellular differentiation, transitions, and lineage hierarchies, helping unravel the dynamic processes underlying development and disease progression. However, many existing tools lack a coherent statistical model and reliable uncertainty quantification, limiting their utility and robustness. In this paper, we introduce VITAE (Variational Inference for Trajectory by AutoEncoder), a statistical approach that integrates a latent hierarchical mixture model with variational autoencoders to infer trajectories. The statistical hierarchical model enhances the interpretability of our framework, while the posterior approximations generated by our variational autoencoder ensure computational efficiency and provide uncertainty quantification of cell projections along trajectories. Specifically, VITAE enables simultaneous trajectory inference and data integration, improving the accuracy of learning a joint trajectory structure in the presence of biological and technical heterogeneity across datasets. We show that VITAE outperforms other state-of-the-art trajectory inference methods on both real and synthetic data under various trajectory topologies. Furthermore, we apply VITAE to jointly analyze three distinct single-cell RNA sequencing datasets of the mouse neocortex, unveiling comprehensive developmental lineages of projection neurons. VITAE effectively reduces batch effects within and across datasets and uncovers finer structures that might be overlooked in individual datasets. Additionally, we showcase VITAE's efficacy in integrative analyses of multiomic datasets with continuous cell population structures.

Infernape uncovers cell type-specific and spatially resolved alternative polyadenylation in the brain.

Differential polyadenylation sites (PAs) critically regulate gene expression, but their cell type-specific usage and spatial distribution in the brain have not been systematically characterized. Here, we present Infernape, which infers and quantifies PA usage from single-cell and spatial transcriptomic data and show its application in the mouse brain. Infernape uncovers alternative intronic PAs and 3'-UTR lengthening during cortical neurogenesis. Progenitor-neuron comparisons in the excitatory and inhibitory neuron lineages show overlapping PA changes in embryonic brains, suggesting that the neural proliferation-differentiation axis plays a prominent role. In the adult mouse brain, we uncover cell type-specific PAs and visualize such events using spatial transcriptomic data. Over two dozen neurodevelopmental disorder-associated genes such as Csnk2a1 and Mecp2 show differential PAs during brain development. This study presents Infernape to identify PAs from scRNA-seq and spatial data, and highlights the role of alternative PAs in neuronal gene regulation.

Long-term sorbitol consumption affects the hippocampus and alters cognitive function in aged mice.

The systemic effects of the artificial sweetener sorbitol on older adult individuals have not been elucidated. We assessed the effects of sorbitol consumption on cognitive and gingival health in a mouse model. Aged mice were fed 5% sorbitol for 3 months before their behavior was assessed, and brain and gingival tissues were collected. Long-term sorbitol consumption inhibited gingival tissue aging in aged mice. However, it caused cognitive decline and decreased brain-derived neurotrophic factor (BDNF) in the hippocampus. Sorbitol consumption did not affect homeostatic function; however, it may exert effects within the brain, particularly in the hippocampus.

Premature gray hair development in the interbrow region owing to the loss of maxillary first molars in young mice.

The exact sites of premature hair graying and whether tooth loss causes this condition remain unknown. In this study, we aimed to explore the effect of reduced mastication on premature hair graying. Maxillary first molars were extracted from young mice, and the mice were observed for 3 months, along with non-extraction control group mice. After 3 months, gray hair emerged in the interbrow region of mice in the tooth extraction group but not in the control group. The expression of tyrosinase-related protein-2 (TRP-2) mRNA was lower in the interbrow tissues of young mice without maxillary molars than in those with maxillary molars. Tooth loss leads to interbrow gray hair growth, possibly because of weakened trigeminal nerve input, suggesting that reduced mastication causes premature graying. Thus, prompt prosthetic treatment after molar loss is highly recommended.

Capsaicin modulates TRPV1, induces ß-defensin expression, and regulates NF-κB in oral senescent cells and a murine model.

Aging is associated with a decline in oral immune function, marked by reduced levels of antimicrobial peptides such as defensins. Capsaicin, a bioactive component found in chili peppers, has been theorized to modulate immune responses through specific receptor pathways. This study examined the effects of aging on oral defensin levels and the potential mitigating role of capsaicin, mediated by the immune response in oral tissues. We conducted a comparative analysis between young and aged mice, with or without capsaicin supplementation, for 3 months. The effect of capsaicin was also studied in vitro in senescence-induced human oral keratinocytes. We found that aging did not reduce defensin levels uniformly but did so in some instances. Capsaicin treatment increased defensin levels in these cases, potentially through transient receptor potential cation channel subfamily V member 1 (TRPV1)-mediated pathways in the oral cavity. Capsaicin supplementation may counteract age-related declines in oral defensin levels, enabling the maintenance of oral immune function during aging.

Integrating cfDNA liquid biopsy and organoid-based drug screening reveals PI3K signaling as a promising therapeutic target in colorectal cancer.

BACKGROUND: The current precision medicine relies on biomarkers, which are mainly obtained through next-generation sequencing (NGS). However, this model failed to find effective drugs for most cancer patients. This study tried to combine liquid biopsy with functional drug tests using organoid models to find potential drugs for cancer patients. METHODS: Colorectal cancer (CRC) patients were prospectively enrolled and blood samples were collected from patients before the start of treatment. Targeted deep sequencing of cfDNA samples was performed using a 14-gene panel. Gastrointestinal (GI) cancer organoids were established and PI3K and mTOR inhibitors were evaluated on organoid models. RESULTS: A total of 195 mutations were detected across 58 cfDNA samples. The most frequently mutated genes were KRAS, TP53, PIK3CA, and BRAF, all of which exhibited higher mutation rates than tissue biopsy. Although 81% of variants had an allele frequency of less than 1%, certain mutations in KRAS, TP53, and SMAD4 had high allele frequencies exceeding 10%. Notably, among the seven patients with high allele frequency mutations, six had metastatic tumors, indicating that a high allele frequency of ctDNA could potentially serve as a biomarker of later-stage cancer. A high rate of PIK3CA mutation (31 out of 67, or 46.3%) was discovered in CRC patients, suggesting possible tumor progression mechanisms and targeted therapy opportunities. To evaluate the value of anti PI3K strategy in GI cancer, different lines of GI cancer organoids were established. The organoids recapitulated the morphologies of the original tumors. Organoids were generally insensitive to PI3K inhibitors. However, CRC-3 and GC-4 showed response to mTOR inhibitor Everolimus, and GC-3 was sensitive to PI3Kδ inhibitor Idelalisib. The CRC organoid with a PIK3CA mutation showed greater sensitivity to the PI3K inhibitor Alpelisib than wildtype organoids, suggesting potential treatment options for the corresponding patients. CONCLUSION: Liquid biopsy holds significant promise for improving precision treatment and tumor prognosis in colorectal cancer patients. The combination of biomarker-based drug prediction with organoid-based functional drug sensitivity assay may lead to more effective cancer treatment.

Progenitor cell diversity in the developing mouse neocortex.

In the mammalian neocortex, projection neuron types are sequentially generated by the same pool of neural progenitors. How neuron type specification is related to developmental timing remains unclear. To determine whether temporal gene expression in neural progenitors correlates with neuron type specification, we performed single-cell RNA sequencing (scRNA-Seq) analysis of the developing mouse neocortex. We uncovered neuroepithelial cell enriched genes such as Hmga2 and Ccnd1 when compared to radial glial cells (RGCs). RGCs display dynamic gene expression over time; for instance, early RGCs express higher levels of Hes5, and late RGCs show higher expression of Pou3f2 Interestingly, intermediate progenitor cell marker gene Eomes coexpresses temporally with known neuronal identity genes at different developmental stages, though mostly in postmitotic cells. Our results delineate neural progenitor cell diversity in the developing mouse neocortex and support that neuronal identity genes are transcriptionally evident in Eomes-positive cells.

Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments.

Over a decade of genome-wide association studies (GWAS) have led to the finding of extreme polygenicity of complex traits. The phenomenon that "all genes affect every complex trait" complicates Mendelian Randomization (MR) studies, where natural genetic variations are used as instruments to infer the causal effect of heritable risk factors. We reexamine the assumptions of existing MR methods and show how they need to be clarified to allow for pervasive horizontal pleiotropy and heterogeneous effect sizes. We propose a comprehensive framework GRAPPLE to analyze the causal effect of target risk factors with heterogeneous genetic instruments and identify possible pleiotropic patterns from data. By using GWAS summary statistics, GRAPPLE can efficiently use both strong and weak genetic instruments, detect the existence of multiple pleiotropic pathways, determine the causal direction and perform multivariable MR to adjust for confounding risk factors. With GRAPPLE, we analyze the effect of blood lipids, body mass index, and systolic blood pressure on 25 disease outcomes, gaining new information on their causal relationships and potential pleiotropic pathways involved.

Weak-Coordination Electrolyte Enabling Fast Li+ Transport in Lithium Metal Batteries at Ultra-Low Temperature.

Lithium metal batteries (LMBs) are promising for next-generation high-energy-density batteries owing to the highest specific capacity and the lowest potential of Li metal anode. However, the LMBs are normally confronted with drastic capacity fading under extremely cold conditions mainly due to the freezing issue and sluggish Li+ desolvation process in commercial ethylene carbonate (EC)-based electrolyte at ultra-low temperature (e.g., below -30 °C). To overcome the above challenges, an anti-freezing carboxylic ester of methyl propionate (MP)-based electrolyte with weak Li+ coordination and low-freezing temperature (below -60 °C) is designed, and the corresponding LiNi0.8 Co0.1 Mn0.1 O2 (NCM811) cathode exhibits a higher discharge capacity of 84.2 mAh g-1 and energy density of 195.0 Wh kg-1 cathode than that of the cathode (1.6 mAh g-1 and 3.9 Wh kg-1 cathode ) working in commercial EC-based electrolytes for NCM811‖ Li cell at -60 °C. Molecular dynamics simulation, Raman spectra, and nuclear magnetic resonance characterizations reveal that rich mobile Li+ and the unique solvation structure with weak Li+ coordination are achieved in MP-based electrolyte, which collectively facilitate the Li+ transference process at low temperature. This work provides fundamental insights into low-temperature electrolytes by regulating solvation structure, and offers the basic guidelines for the design of low-temperature electrolytes for LMBs.

Data denoising with transfer learning in single-cell transcriptomics.

Single-cell RNA sequencing (scRNA-seq) data are noisy and sparse. Here, we show that transfer learning across datasets remarkably improves data quality. By coupling a deep autoencoder with a Bayesian model, SAVER-X extracts transferable gene-gene relationships across data from different labs, varying conditions and divergent species, to denoise new target datasets.

Synchronous N and P Removal in Carbon-Coated Nanoscale Zerovalent Iron Autotrophic Denitrification─The Synergy of the Carbon Shell and P Removal.

Fe0 is a promising electron donor for autotrophic denitrification in the simultaneous removal of nitrate and phosphorus in low C/N wastewater. However, P removal may inevitably inhibit bio-denitrification. It has not been well recognized and led to an overdose of iron materials. This study employed carbon-coated zerovalent iron (Fe0@C) to support autotrophic denitrification to mitigate the inhibition effects of P removal and enhance both N and P removal. The critical role of the carbon shell in Fe0@C was to block the direct contact between Fe0 and P and NO3--N, to maintain the Fe0 activity. Besides, P inhibited the chemical reduction of NO3--N by competing for Fe0 active sites. This indirectly boosted H2 generation and promoted bio-denitrification. P removal displayed negligible effects on microbial species but indirectly enhanced the nitrogen metabolic activities because of promoted H2 in Fe0@C-based autotrophic denitrification. Bio-denitrification, in turn, strengthened Fe-P co-precipitation by promoting the formation of ferric hydroxide as a secondary adsorbent for P removal. This study demonstrated an efficient method for simultaneous N and P removal in autotrophic denitrification and revealed the synergistic interactions among N and P removal processes.

DETECTING MULTIPLE REPLICATING SIGNALS USING ADAPTIVE FILTERING PROCEDURES.

Replicability is a fundamental quality of scientific discoveries: we are interested in those signals that are detectable in different laboratories, different populations, across time etc. Unlike meta-analysis which accounts for experimental variability but does not guarantee replicability, testing a partial conjunction (PC) null aims specifically to identify the signals that are discovered in multiple studies. In many contemporary applications, for example, comparing multiple high-throughput genetic experiments, a large number M of PC nulls need to be tested simultaneously, calling for a multiple comparisons correction. However, standard multiple testing adjustments on the M PC p -values can be severely conservative, especially when M is large and the signals are sparse. We introduce AdaFilter, a new multiple testing procedure that increases power by adaptively filtering out unlikely candidates of PC nulls. We prove that AdaFilter can control FWER and FDR as long as data across studies are independent, and has much higher power than other existing methods. We illustrate the application of AdaFilter with three examples: microarray studies of Duchenne muscular dystrophy, single-cell RNA sequencing of T cells in lung cancer tumors and GWAS for metabolomics.

Seasonal and short-term variations of bacteria and pathogenic bacteria on road deposited sediments.

The bacteria (including pathogenic bacteria) attached to road deposited sediments (RDS) may interrelate with the microbe in the atmosphere, soil and water through resuspension and wash-off, and is of great significance to human and ecological health. However, the characteristics of bacterial communities with different time scale on RDS were unknown to dates. Climate change prolonged the dry days between rain events in many areas, making the varied trend of bacterial communities might be more significant in short term. This study revealed the characteristics of bacterial communities on RDS in urban and suburban areas through seasonal and daily scale. The correlations between other factors (land use, particle size, and chemical components) and the bacterial communities were also analyzed. It was found that the season showed a higher association with the bacterial community diversity than land use and particle size in urban areas. The bacterial community diversity increased substantially throughout the short-term study period (41 days) and the variation of dominant bacteria could be fitted by quadratic function in suburbs. In addition, urbanization notably increased the bacterial community diversity, while the potential pathogenic bacteria were more abundant in the suburban areas, coarse RDS (>75 µm), and in spring. The chemical components on RDS showed special correlations with the relative abundance of dominant bacteria. The research findings would fill the knowledge gap on RDS bacterial communities and be helpful for the future research on the assembly process of bacterial communities.

Study on Spatial and Temporal Characteristics of Surface Albedo at the Northern Edge of the Badain Jaran Desert Based on C + STNLFFM Model.

Obtaining surface albedo data with high spatial and temporal resolution is essential for measuring the factors, effects, and change mechanisms of regional land-atmosphere interactions in deserts. In order to obtain surface albedo data with higher accuracy and better applicability in deserts, we used MODIS and OLI as data sources, and calculated the daily surface albedo data, with a spatial resolution of 30 m, of Guaizi Lake at the northern edge of the Badain Jaran Desert in 2016, using the Spatial and Temporal Non-Local Filter-based Fusion Model (STNLFFM) and topographical correction model (C model). We then compared the results of STNLFFM and C + STNLFFM for fusion accuracy, and for spatial and temporal distribution differences in surface albedo over different underlying surfaces. The results indicated that, compared with STNLFFM surface albedo and MODIS surface albedo, the relative error of C + STNLFFM surface albedo decreased by 2.34% and 3.57%, respectively. C + STNLFFM can improve poor applicability of MODIS in winter, and better responds to the changes in the measured value over a short time range. After the correction of the C model, the spatial difference in surface albedo over different underlying surfaces was enhanced, and the spatial differences in surface albedo between shifting dunes and semi-shifting dunes, fixed dunes and saline-alkali land, and the Gobi and saline-alkali land were significant. C + STNLFFM maintained the spatial and temporal distribution characteristics of STNLFFM surface albedo, but the increase in regional aerosol concentration and thickness caused by frequent dust storms weakened the spatial difference in surface albedo over different underlying surfaces in March, which led to the overcorrection of the C model.

Impact of bamboo sphere amendment on composting performance and microbial community succession in food waste composting.

The purpose of this study was to find an economical and effective amendment for improving composting performance and product quality, as well as to analyze the microbial community succession in the whole phase of composting. Therefore, the effect of reusable amendment bamboo sphere on composting performance and microbial community succession during food waste composting was investigated. The results showed that 6% bamboo sphere treatment had the highest degree of polymerization (3.7) and humification index (0.18). Compared with control, 6% bamboo sphere amendment increased total nitrogen (TN), phosphorus (TP) and potassium (TK) contents by 13.61%, 19% and 17.42%, respectively. Furthermore, bamboo sphere enhanced bacterial-fungal diversity and improved microbial community composition by enhancing the relative abundance of thermo-tolerance and lignocellulolytic bacteria and fungi. The five most abundant genera in bamboo sphere composting comprised Bacillus (0-71.47%), Chloroplast-norank (0-47.17%), Pusillimonas (0-33.24%), Acinetobacter (0-27.98%) and unclassified Sphingobacteriaceae (0-22.62%). Linear discriminant analysis effect size showed that Firmicutes, Thermoascaceae and Actinobacteriota, which have a relationship with the decomposition of soluble organic matter and lignocellulose, were significantly enriched in bamboo sphere treatment. Canonical correspondence analysis illustrated that total organic carbon (TOC), TK, and TP were the most important environmental factors on microbial community succession in the two composting systems. Together these results suggest that bamboo sphere as a reusable amendment can shorten maturity period, improve humification degree, increase the contents of nutrient and contribute to the succession of microbial community during food waste composting. These findings provide a theoretical basis for improving the efficiency of food waste composting.

Exploring the dynamic of microbial community and metabolic function in food waste composting amended with traditional Chinese medicine residues.

The aim of this study was to explore the dynamic of microbial community and metabolic function in food waste composting amended with traditional Chinese medicine residues (TCMRs). Results suggested that TCMRs addition at up to 10% leads to a higher peak temperature (60.5 °C), germination index (GI) value (119.26%), and a greater reduction in total organic carbon (TOC) content (8.08%). 10% TCMRs significantly induced the fluctuation of bacterial community composition, as well as the fungal community in the thermophilic phase. The addition of 10% TCMRs enhanced the abundance of bacterial genera such as Acetobacter, Bacillus, and Brevundimonas, as well as fungal genera such as Chaetomium, Thermascus, and Coprinopsis, which accelerated lignocellulose degradation and humification degree. Conversely, the growth of Lactobacillus and Pseudomonas was inhibited by 10% TCMRs to weaken the acidic environment and reduce nitrogen loss. Metabolic function analysis revealed that 10% TCMRs promoted the metabolism of carbohydrate and amino acid, especially citrate cycle, glycolysis/gluconeogenesis, and cysteine and methionine metabolism. Redundancy analysis showed that the carbon to nitrogen (C/N) ratio was the most significant environmental factor influencing the dynamic of bacterial and fungal communities.

SAVER: gene expression recovery for single-cell RNA sequencing.

In single-cell RNA sequencing (scRNA-seq) studies, only a small fraction of the transcripts present in each cell are sequenced. This leads to unreliable quantification of genes with low or moderate expression, which hinders downstream analysis. To address this challenge, we developed SAVER (single-cell analysis via expression recovery), an expression recovery method for unique molecule index (UMI)-based scRNA-seq data that borrows information across genes and cells to provide accurate expression estimates for all genes.

Gene expression distribution deconvolution in single-cell RNA sequencing.

Single-cell RNA sequencing (scRNA-seq) enables the quantification of each gene's expression distribution across cells, thus allowing the assessment of the dispersion, nonzero fraction, and other aspects of its distribution beyond the mean. These statistical characterizations of the gene expression distribution are critical for understanding expression variation and for selecting marker genes for population heterogeneity. However, scRNA-seq data are noisy, with each cell typically sequenced at low coverage, thus making it difficult to infer properties of the gene expression distribution from raw counts. Based on a reexamination of nine public datasets, we propose a simple technical noise model for scRNA-seq data with unique molecular identifiers (UMI). We develop deconvolution of single-cell expression distribution (DESCEND), a method that deconvolves the true cross-cell gene expression distribution from observed scRNA-seq counts, leading to improved estimates of properties of the distribution such as dispersion and nonzero fraction. DESCEND can adjust for cell-level covariates such as cell size, cell cycle, and batch effects. DESCEND's noise model and estimation accuracy are further evaluated through comparisons to RNA FISH data, through data splitting and simulations and through its effectiveness in removing known batch effects. We demonstrate how DESCEND can clarify and improve downstream analyses such as finding differentially expressed genes, identifying cell types, and selecting differentiation markers.

Cost-effectiveness analysis of pembrolizumab compared to standard of care as first line treatment for patients with advanced melanoma in Hong Kong.

BACKGROUND: Pembrolizumab has been shown to improve overall survival (OS) and progression free survival (PFS) compared to ipilimumab in patients with ipilimumab-naïve advanced melanoma; however, there are no published data on the cost-effectiveness for pembrolizumab compared to standard-of-care treatments currently used in Hong Kong for advanced melanoma. METHODS: A partitioned-survival model based on data from a recent randomized phase 3 study (KEYNOTE-006) and meta-analysis was used to derive time in PFS, OS, and post-progression survival for pembrolizumab and chemotherapy, such as dacarbazine (DTIC), temozolomide (TMZ), and the paclitaxel-carboplatin combination (PC). A combination of clinical trial data, published data, results of meta-analysis, and melanoma registry data was used to extrapolate PFS and OS curves. The base-case time horizon for the model was 30 years with costs and health outcomes discounted at a rate of 5% per year. Individual patient level data on utilities and frequencies of adverse events were obtained from the final analysis of KEYNOTE-006 (cut-off date: 3-Dec-15) for pembrolizumab. Cost data included drug acquisition, treatment administration, adverse event management, and clinical management of advanced melanoma. The distribution of patient weight from the Hong Kong population was applied to calculate the drug costs. Analyses were performed from a payer's perspective. The incremental cost effectiveness ratio (ICER) expressed as cost in US Dollars (USD) per quality-adjusted life years (QALYs) was the main outcome. RESULTS: In base-case scenario, the ICER for pembrolizumab as a first-line treatment for advanced melanoma was USD49,232 compared to DTIC, with the ICER values lower than cost-effectiveness threshold in Hong Kong. Results comparing pembrolizumab to TMZ and to PC were similar to that when compared to DTIC. Probability sensitivity analyses showed that 99% of the simulated ICERs were below three times the Gross Domestic Product (GDP) per capita for Hong Kong (currently at $119,274//QALY threshold). In a scenario analysis comparing pembrolizumab with ipilimumab, the estimated ICER was USD8,904. CONCLUSIONS: Pembrolizumab is cost-effective relative to chemotherapy (DTIC, TMZ and PC), and highly-cost-effective compared to ipilimumab, for the first-line treatment of advanced melanoma in Hong Kong.

Integrin alpha x stimulates cancer angiogenesis through PI3K/Akt signaling-mediated VEGFR2/VEGF-A overexpression in blood vessel endothelial cells.

Integrin alpha x (ITGAX), a member of the integrin family, usually serves as a receptor of the extracellular matrix. Recently, accumulating evidence suggests that ITGAX may be involved in angiogenesis in dendritic cells. Herein, we report a direct role of ITGAX in angiogenesis during tumor development. Overexpression of ITGAX in human umbilical vein endothelial cells (HUVECs) enhanced their proliferation, migration, and tube formation and promoted xenograft ovarian tumor angiogenesis and growth. Further study showed that overexpression of ITGAX activated the PI3k/Akt pathway, leading to the enhanced expression of c-Myc, vascular endothelial growth factor-A (VEGF-A), and VEGF receptor 2 (VEGFR2), whereas, the treatment of cells with PI3K inhibitor diminished these effects. Besides, c-Myc was observed to bind to the VEGF-A promoter. By Co-Immunoprecipitation (Co-IP) assay, we manifested the interaction between ITGAX and VEGFR2 or the phosphorylated VEGFR2. Immunostaining of human ovarian cancer specimens suggested that endothelial cells of micro-blood vessels displayed strong expression of VEGF-A, c-Myc, VEGFR2, and the PI3K signaling molecules. Also, overexpression of ITGAX in HUVECs could stimulate the spheroid formation of ovarian cancer cells. Our study uncovered that ITGAX stimulates angiogenesis through the PI3K/Akt signaling-mediated VEGFR2/VEGF-A overexpression during cancer development.