Soil colloids can significantly enhance spreading of polybromodiphenyl ethers in groundwater by serving as an effective carrier.

Polybromodiphenyl ethers (PBDEs), the widely used flame retardants, are common contaminants in surface soils at e-waste recycling sites. The association of PBDEs with soil colloids has been observed, indicating the potential risk to groundwater due to colloid-facilitated transport. However, the extent to which soil colloids may enhance the spreading of PBDEs in groundwater is largely unknown. Herein, we report the co-transport of decabromodiphenyl ester (BDE-209) and soil colloids in saturated porous media. The colloids released from a soil sample collected at an e-waste recycling site in Tianjin, China, contain high concentration of PBDEs, with BDE-209 being the most abundant conger (320 ± 30 mg/kg). The colloids exhibit relatively high mobility in saturated sand columns, under conditions commonly observed in groundwater environments. Notably, under all the tested conditions (i.e., varying flow velocity, pH, ionic species and ionic strength), the mass of eluted BDE-209 correlates linearly with that of eluted soil colloids, even though the mobility of the colloids varies markedly depending on the specific hydrodynamic and solution chemistry conditions involved. Additionally, the mass of BDE-209 retained in the columns also correlates strongly with the mass of retained colloids. Apparently, the PBDEs remain bound to soil colloids during transport in porous media. Findings in this study indicate that soil colloids may significantly promote the transport of PBDEs in groundwater by serving as an effective carrier. This might be the reason why the highly insoluble and adsorptive PBDEs are found in groundwater at some PBDE-contaminated sites.

Gut microbiota characteristics of colorectal cancer patients in Hubei, China, and differences with cohorts from other Chinese regions.

The research on the correlation or causality between gut microbiota and the occurrence, development, and treatment of colorectal cancer (CRC) is receiving increasing emphasis. At the same time, the incidence and mortality of colorectal cancer vary among individuals and regions, as does the gut microbiota. In order to gain a better understanding of the characteristics of the gut microbiota in CRC patients and the differences between different regions, we initially compared the gut microbiota of 25 CRC patients and 26 healthy controls in the central region of China (Hubei Province) using 16S rRNA high-throughput sequencing technology. The results showed that Corynebacterium, Enterococcus, Lactobacillus, and Escherichia-Shigella were significantly enriched in CRC patients. In addition, we also compared the potential differences in functional pathways between the CRC group and the healthy control group using PICRUSt's functional prediction analysis. We then analyzed and compared it with five cohort studies from various regions of China, including Central, East, and Northeast China. We found that geographical factors may affect the composition of intestinal microbiota in CRC patients. The composition of intestinal microbiota is crucial information that influences colorectal cancer screening, early detection, and the prediction of CRC treatment outcomes. This emphasizes the importance of conducting research on CRC-related gut microbiota in various regions of China.

Activation of non-classical Wnt signaling pathway effectively enhances HLA-A presentation in acute myeloid leukemia.

Objective: The escape from T cell-mediated immune surveillance is an important cause of death for patients with acute myeloid leukemia (AML). This study aims to identify clonal heterogeneity in leukemia progenitor cells and explore molecular or signaling pathways associated with AML immune escape. Methods: Single-cell RNA sequencing (scRNA-seq) was performed to identified AML-related cellular subsets, and intercellular communication was analyzed to investigate molecular mechanisms associated with AML immune escape. Bulk RNA sequencing (RNA-seq) was performed to screen differentially expressed genes (DEGs) related to hematopoietic stem cell progenitors (HSC-Prog) in AML, and critical ore signaling pathways and hub genes were found by Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The mRNA level of the hub gene was verified using quantitative real-time PCR (qRT-PCR) and the protein level of human leukocyte antigen A (HLA-A) using enzyme-linked immuno sorbent assay (ELISA). Results: scRNA-seq analysis revealed a large heterogeneity of HSC-Prog across samples, and the intercellular communication analysis indicated a strong association between HSC-Prog and CD8+-T cells, and HSC-Prog also had an association with HLA-A. Transcriptome analysis identified 1748 DEGs, enrichment analysis results showed that non-classical wnt signaling pathway was associated with AML, and 4 pathway-related genes (RHOA, RYK, CSNK1D, NLK) were obtained. After qRT-PCR and ELISA validation, hub genes and HLA-A were found to be down-regulated in AML and up-regulated after activation of the non-classical Wnt signaling pathway. Conclusion: In this study, clonal heterogeneity of HSC-Prog cells in AML was identified, non-classical wnt signaling pathways associated with AML were identified, and it was verified that HLA-A could be upregulated by activation of non-classical wnt signaling, thereby increasing antigen presentation.

Functional modification of gut bacteria for disease diagnosis and treatment.

Intestinal bacteria help keep humans healthy by regulating lipid and glucose metabolism as well as the immunological and neurological systems. Oral treatment using intestinal bacteria is limited by the high acidity of stomach fluids and the immune system's attack on foreign bacteria. Scientists have created coatings and workarounds to overcome these limitations and improve bacterial therapy. These preparations have demonstrated promising outcomes, with advances in synthetic biology and optogenetics improving their focused colonization and controlled release. Engineering bacteria preparations have become a revolutionary therapeutic approach that converts intestinal bacteria into cellular factories for medicinal chemical synthesis. The present paper discusses various aspects of engineering bacteria preparations, including wrapping materials, biomedical uses, and future developments.

The impact of 25-hydroxyvitamin D and calcium on the risk of age-related macular degeneration: A Mendelian randomization study.

BACKGROUND: The relationships between 25-hydroxyvitamin D (25(OH)D) and calcium and age-related macular degeneration (AMD) are unclear. OBJECTIVE: This study aimed to investigate the causal role of 25(OH)D concentrations, calcium concentrations, and dietary supplements use of vitamin D and calcium on the risk of AMD and its subtypes. METHODS: Independent genetic variants associated with 25(OH)D and calcium concentrations were used as instrumental variables in published genome-wide association studies (GWASs) of European ancestry. The bidirectional two-sample Mendelian randomization (MR) analyses were performed using summary-level data from the UK Biobank and FinnGen datasets. Sensitivity analyses were conducted to ensure the robustness of the MR results. The meta-analyses were conducted using both fixed-effect and random-effect models to provide comprehensive and reliable estimates. RESULTS: A standard deviation increase in calcium concentrations was linked to a 14%, 17%, and 13% reduction in the likelihood of developing AMD (95% confidence interval [CI] = 0.77, 0.97), wet AMD (95% CI = 0.73, 0.95), and dry AMD (95% CI = 0.75, 1.00), respectively. No significant causal relationships were detected between genetically predicted 25(OH)D concentrations and AMD and its subtypes (all P > 0.05). The combined analyses showed that higher calcium concentrations were associated with a reduced risk of overall AMD, with an OR of 0.89 (95% CI = 0.81, 0.98). CONCLUSIONS: This study provides evidence supporting the causal relationship between calcium concentrations and the risk of AMD and its subtypes, which may have important implications for the prevention, monitoring, and treatment of AMD.

Optimize individualized energy delivery for septic patients using predictive deep learning models.

BACKGROUND AND OBJECTIVES: We aim to establish deep learning models to optimize the individualized energy delivery for septic patients. METHODS AND STUDY DESIGN: We conducted a study of adult septic patients in ICU, collecting 47 indicators for 14 days. We filtered out nutrition-related features and divided the data into datasets according to the three metabolic phases proposed by ESPEN: acute early, acute late, and rehabilitation. We then established optimal energy target models for each phase using deep learning and conducted external validation. RESULTS: A total of 179 patients in training dataset and 98 patients in external validation dataset were included in this study, and total data size was 3115 elements. The age, weight and BMI of the patients were 63.05 (95%CI 60.42-65.68), 61.31(95%CI 59.62-63.00) and 22.70 (95%CI 22.21-23.19), respectively. And 26.0% (72) of the patients were female. The models indicated that the optimal energy targets in the three phases were 900kcal/d, 2300kcal/d, and 2000kcal/d, respectively. Excessive energy intake increased mortality rapidly in the early period of the acute phase. Insufficient energy in the late period of the acute phase significantly raised the mortality as well. For the rehabilitation phase, too much or too little energy delivery were both associated with elevated death risk. CONCLUSIONS: Our study established time-series prediction models for septic patients to optimize energy delivery in the ICU. We recommended permissive underfeeding only in the early acute phase. Later, increased energy intake may improve survival and settle energy debts caused by underfeeding.

Designing a highly efficient type III polyketide whole-cell catalyst with minimized byproduct formation.

BACKGROUND: Polyketide synthases (PKSs) are classified into three types based on their enzyme structures. Among them, type III PKSs, catalyzing the iterative condensation of malonyl-coenzyme A (CoA) with a CoA-linked starter molecule, are important synthases of valuable natural products. However, low efficiency and byproducts formation often limit their applications in recombinant overproduction. RESULTS: Herein, a rapid growth selection system is designed based on the accumulation and derepression of toxic acyl-CoA starter molecule intermediate products, which could be potentially applicable to most type III polyketides biosynthesis. This approach is validated by engineering both chalcone synthases (CHS) and host cell genome, to improve naringenin productions in Escherichia coli. From directed evolution of key enzyme CHS, beneficial mutant with ~ threefold improvement in capability of naringenin biosynthesis was selected and characterized. From directed genome evolution, effect of thioesterases on CHS catalysis is first discovered, expanding our understanding of byproduct formation mechanism in type III PKSs. Taken together, a whole-cell catalyst producing 1082 mg L-1 naringenin in flask with E value (evaluating product specificity) improved from 50.1% to 96.7% is obtained. CONCLUSIONS: The growth selection system has greatly contributed to both enhanced activity and discovery of byproduct formation mechanism in CHS. This research provides new insights in the catalytic mechanisms of CHS and sheds light on engineering highly efficient heterologous bio-factories to produce naringenin, and potentially more high-value type III polyketides, with minimized byproducts formation.

YOLO SSPD: a small target cotton boll detection model during the boll-spitting period based on space-to-depth convolution.

Introduction: Cotton yield estimation is crucial in the agricultural process, where the accuracy of boll detection during the flocculation period significantly influences yield estimations in cotton fields. Unmanned Aerial Vehicles (UAVs) are frequently employed for plant detection and counting due to their cost-effectiveness and adaptability. Methods: Addressing the challenges of small target cotton bolls and low resolution of UAVs, this paper introduces a method based on the YOLO v8 framework for transfer learning, named YOLO small-scale pyramid depth-aware detection (SSPD). The method combines space-to-depth and non-strided convolution (SPD-Conv) and a small target detector head, and also integrates a simple, parameter-free attentional mechanism (SimAM) that significantly improves target boll detection accuracy. Results: The YOLO SSPD achieved a boll detection accuracy of 0.874 on UAV-scale imagery. It also recorded a coefficient of determination (R2) of 0.86, with a root mean square error (RMSE) of 12.38 and a relative root mean square error (RRMSE) of 11.19% for boll counts. Discussion: The findings indicate that YOLO SSPD can significantly improve the accuracy of cotton boll detection on UAV imagery, thereby supporting the cotton production process. This method offers a robust solution for high-precision cotton monitoring, enhancing the reliability of cotton yield estimates.

Activin A as a potential biomarker for preserved ratio impaired spirometry (PRISm) and clinical outcomes in community-dwelling adults.

INTRODUCTION: This study endeavors to decipher the association between Activin A and PRISm, thereby addressing the potential of Activin A as a serum biomarker for early detection and long-term clinical outcome prediction of PRISm and subsequent all-cause mortality. METHODS: The study sample comprised middle-aged and older adults from the I-Lan Longitudinal Aging Study. Pulmonary function including forced vital capacity (FVC) and forced expiratory volume in one second (FEV1) were measured. Demographic data and laboratory data (including serum Activin A levels) were also collected. Multivariate logistic regression and Cox proportional hazards models were used to identify independent predictors of PRISm and all-cause mortality, respectively. RESULTS: Among 711 eligible participants, 34 % had PRISm. The risk of PRISm elevated with Activin A levels in group quartiles (adjusted odds ratio (aOR), Q2: 1.606 [95 % CI 0.972-2.652], p = 0.064, Q3: 2.666 [1.635-4.348], p < 0.001, Q4: 3.225 [1.965-5.293], p < 0.001). On the other hand, lower hemoglobin (aOR: 1.122, p = 0.041) and higher blood urea nitrogen (BUN) levels (aOR: 1.033, p = 0.048) were associated with increased risk of PRISm. In addition, the PRISm group had a higher all-cause mortality rate (non-PRISm 4.5% vs. PRISm 8.3 %, p = 0.038). Multivariate Cox models also identify a higher level of Activin A as a risk factor of all-cause mortality (aHR: 1.001 [1.000-1.003], p = 0.042). CONCLUSIONS: Higher Activin A quartiles were linked to increased risk of PRISm, along with lower hemoglobin and higher BUN levels. Additonally, elevated Activin A was a significant risk factor of all-cause mortality.

Irisin attenuates acute glaucoma-induced neuroinflammation by activating microglia-integrin αVß5/AMPK and promoting autophagy.

Neuroinflammation, characterized by microglial activation and the release of multiple inflammatory mediators, is a key factor in acute glaucomatous injury leading to retinal ganglion cell (RGC) death and ultimately irreversible vision loss. Irisin, a novel exercise-induced myokine, has demonstrated anti-inflammatory activity in ischemia/reperfusion injuries across multiple organs and has displayed a significant neuroprotective role in experimental stroke disease models. This study examined the protective impact of irisin and investigated its potential mechanism involved in this process utilizing an acute ocular hypertension (AOH)-induced retinal injury model in mice and a microglia inflammation model induced by lipopolysaccharide (LPS). There was a transient downregulation of irisin in the retina after AOH injury, with parallel emergence of retinal neuroinflammation and RGC death. Irisin attenuated retinal and optic nerve damage and promotes the phenotypic conversion of microglia from M1 to M2. Mechanistically, irisin significantly upregulated the expression of integrin αVß5, p-AMPK, and autophagy-related markers. Integrin αVß5 was highly expressed on microglia but hardly expressed on RGC. The integrin αVß5 inhibitor cilengitide, the AMPK inhibitor dorsomorphin, and the autophagy inhibitor 3-Methyladenine (3-MA) blocked the neuroprotective effects of irisin. Our results suggest irisin attenuates acute glaucoma-induced neuroinflammation and RGC death by activating integrin αVß5/AMPK in microglia and promoting autophagy. It should be considered a potential neuroprotective therapy for acute glaucoma.

DeepSAP: A Novel Brain Image-Based Deep Learning Model for Predicting Stroke-Associated Pneumonia From Spontaneous Intracerebral Hemorrhage.

RATIONALE AND OBJECTIVE: Stroke-associated pneumonia (SAP) often appears as a complication following intracerebral hemorrhage (ICH), leading to poor prognosis and increased mortality rates. Previous studies have typically developed prediction models based on clinical data alone, without considering that ICH patients often undergo CT scans immediately upon admission. As a result, these models are subjective and lack real-time applicability, with low accuracy that does not meet clinical needs. Therefore, there is an urgent need for a quick and reliable model to timely predict SAP. METHODS: In this retrospective study, we developed an image-based model (DeepSAP) using brain CT scans from 244 ICH patients to classify the presence and severity of SAP. First, DeepSAP employs MRI-template-based image registration technology to eliminate structural differences between samples, achieving statistical quantification and spatial standardization of cerebral hemorrhage. Subsequently, the processed images and filtered clinical data were simultaneously input into a deep-learning neural network for training and analysis. The model was tested on a test set to evaluate diagnostic performance, including accuracy, specificity, and sensitivity. RESULTS: Brain CT scans from 244 ICH patients (mean age, 60.24; 66 female) were divided into a training set (n = 170) and a test set (n = 74). The cohort included 143 SAP patients, accounting for 58.6% of the total, with 66 cases classified as moderate or above, representing 27% of the total. Experimental results showed an AUC of 0.93, an accuracy of 0.84, a sensitivity of 0.79, and a precision of 0.95 for classifying the presence of SAP. In comparison, the model relying solely on clinical data showed an AUC of only 0.76, while the radiomics method had an AUC of 0.74. Additionally, DeepSAP achieved an optimal AUC of 0.84 for the SAP grading task. CONCLUSION: DeepSAP's accuracy in predicting SAP stems from its spatial normalization and statistical quantification of the ICH region. DeepSAP is expected to be an effective tool for predicting and grading SAP in clinic.

Targeting Ferroptosis as an Advance Strategy in Cancer Therapy.

Ferroptosis, triggered by the buildup of lipid peroxidation and reliance on iron, is crucial in maintaining cellular balance. Research related to ferroptosis has surged due to its distinct characteristics compared to other forms of controlled cell death, both in terms of mechanisms and appearance. Scientists believe that directing efforts towards targeting ferroptosis could pave the way for innovative precision cancer treatments, addressing challenges such as cancer recurrence and resistance. This review systematically outlines the molecular mechanisms behind ferroptosis, the substances that induce ferroptosis, and how different cancers respond to ferroptotic inducers. Also, the study further looks into the molecular basis of ferroptosis in tumor biology. It provides a conceptual framework illustrating its interaction with the tumor immune microenvironment, guiding treatment choices, predicting efficacy, exploring combination therapies, and identifying new therapeutic targets to overcome cancer resistance to standard treatments. Finally, it highlights key issues and obstacles in future research and clinical translation of ferroptosis as a potential strategy in cancer therapy.

Vitamin D3 attenuates autoimmune thyroiditis by regulating Th17/Treg cell differentiation via YAP/JAK1/STAT1 axis.

BACKGROUND: Autoimmune thyroiditis (AITD) is an organ-specific autoimmune disease. Substantial evidence suggests that Vitamin D (VitD) deficiency is closely associated with an increased risk of AITD. However, the effects of VitD3 on immune cells, especially Th17/Treg cell subsets, and the underlying molecular mechanism in AITD have not yet been investigated. METHODS: An experimental autoimmune thyroiditis (EAT) mouse model was established with a high-iodine diet. After 8 weeks, thyroid injury was assessed using hematoxylin and eosin (H&E) staining. ELISA was employed to measure serum levels of thyroxine (T3 and T4), thyroid autoimmune antibodies (Tg-Ab and TPO-Ab), and inflammatory cytokines. Flow cytometry and multiplex fluorescence immunohistochemical (mIHC) assays were used to analyze Th17/Treg cell subsets. The CCK-8 and flow cytometry assays were used to determine cell viability and apoptosis. RESULTS: Administration of VitD3 reduced thyroid follicle destruction, decreased lymphocyte infiltration, and lowered T3, T4, Tg-Ab, and TPO-Ab serum levels in EAT mice. VitD3 treatment also reduced the frequency of Th17 cells while promoting the Treg cell subset both in the thyroid tissue and in the splenocytes cultured in vitro. Furthermore, VitD3 administration suppressed the production of inflammatory cytokines in EAT mice. VitD3 was also found to regulate Treg cells' differentiation, viability, and apoptosis. Mechanistically, we discovered that VitD3 treatment upregulated YAP expression and activated the JAK/STAT pathway. Rescue assays confirmed that depletion of YAP counteracted the effects of VitD3 on Treg cell differentiation and function. CONCLUSION: Vitamin D3 attenuates AITD by modulating Th17/Treg cell balance via regulating the YAP/JAK1/STAT1 axis.

KAT7 Suppresses Tumorigenesis in Clear Cell Renal Cell Carcinoma (ccRCC) by Regulating Cell Cycle and Ferroptosis Sensitivity.

Clear cell renal cell carcinoma (ccRCC) is one of the most aggressive malignancies in the urological system, known for its high immunogenicity. However, its pathogenesis remains unclear. This study utilized bioinformatics algorithms and in vitro experiments to investigate the role of KAT7 in ccRCC. The results indicate that KAT7 is significantly downregulated in ccRCC tissues and cell lines, which is linked to distant metastasis and unfavorable outcomes in ccRCC patients. Overexpression of KAT7 in vitro notably decreased the proliferation, migration, and invasion of renal cancer cells and inhibited Epithelial-Mesenchymal Transition (EMT). Additionally, Gene Set Enrichment Analysis (GSEA) demonstrated that KAT7-related gene functions are associated with cell cycle and ferroptosis transcription factors. Treatment with a KAT7 acetylation inhibitor in ccRCC cell lines reversed the S phase arrest caused by KAT7 overexpression. Similarly, ferroptosis inhibitors alleviated ferroptosis induced by overexpressed KAT7. In conclusion, the findings suggest that KAT7 acts as a tumor suppressor in ccRCC by modulating the cell cycle and ferroptosis sensitivity, underscoring its potential as a therapeutic target and prognostic biomarker for renal cell carcinoma patients.

NBS1 lactylation is required for efficient DNA repair and chemotherapy resistance.

The Warburg effect is a hallmark of cancer that refers to the preference of cancer cells to metabolize glucose anaerobically rather than aerobically1,2. This results in substantial accumulation of lacate, the end product of anaerobic glycolysis, in cancer cells3. However, how cancer metabolism affects chemotherapy response and DNA repair in general remains incompletely understood. Here we report that lactate-driven lactylation of NBS1 promotes homologous recombination (HR)-mediated DNA repair. Lactylation of NBS1 at lysine 388 (K388) is essential for MRE11-RAD50-NBS1 (MRN) complex formation and the accumulation of HR repair proteins at the sites of DNA double-strand breaks. Furthermore, we identify TIP60 as the NBS1 lysine lactyltransferase and the 'writer' of NBS1 K388 lactylation, and HDAC3 as the NBS1 de-lactylase. High levels of NBS1 K388 lactylation predict poor patient outcome of neoadjuvant chemotherapy, and lactate reduction using either genetic depletion of lactate dehydrogenase A (LDHA) or stiripentol, a lactate dehydrogenase A inhibitor used clinically for anti-epileptic treatment, inhibited NBS1 K388 lactylation, decreased DNA repair efficacy and overcame resistance to chemotherapy. In summary, our work identifies NBS1 lactylation as a critical mechanism for genome stability that contributes to chemotherapy resistance and identifies inhibition of lactate production as a promising therapeutic cancer strategy.

3D magnetic flower-spherical Fe2O3-NiO derived from NiFe-layered double hydroxides for the efficient removal of Bensulfuron methyl: Morphological control and bimetallic synergy.

Three-dimensional (3D) magnetic flower-spherical Fe2O3-NiO derived from NiFe-layered double hydroxides (NiFe-LDHs) was fabricated through urea hydrothermal and calcination methods. The as-prepared materials were applied to activate PMS to degrade one of herbicide named Bensulfuron methyl (BSM). Fe2O3-NiO-1 demonstrated the highest catalytic activity and the lowest ions leaching by comparing the performance of LDHs and derivative bimetallic oxide synthesized by co-precipitation method, urea hydrothermal method and direct calcination method. Based on the results of SEM, BET and CV, the high catalytic activity of Fe2O3-NiO-1 originated from 3D morphology, lager specific area and pore size and faster electron transfer capability. The factors influencing the degradation performance were investigated and 0.1 g·L-1 Fe2O3-NiO could effectively activate PMS (1 mmol·L-1) to completely remove 10 mg·L-1 BSM within 30 min at pH 7.0. In Fe2O3-NiO/PMS system, OH, SO4- and 1O2 were produced and contributed to the BSM removal according to the results of EPR and quenching experiments. In order to expand its application range, Fe2O3-NiO/PMS system was used to degrade aniline (AN), sulfamethoxazole (SMZ), phenacetin (PNT), bisphenol A (BPA) and 2,4,6-triclofen (2,4,6-TCP) and the results showed the degradation efficiency could reach 90 % or more. Additionally, the application of catalysts in different actual water samples and the ability of reuse were tested. Based on the strategies of bimetallic synergy and morphology control, Fe-based bimetallic oxides with 3D morphology were developed in this study, which could effectively enhance the catalytic activity and inhibit the dissolution of metal ions, providing the design ideas for the construction of efficient catalysts and the removal of complex organic pollutants.

A unified model-based framework for doublet or multiplet detection in single-cell multiomics data.

Droplet-based single-cell sequencing techniques rely on the fundamental assumption that each droplet encapsulates a single cell, enabling individual cell omics profiling. However, the inevitable issue of multiplets, where two or more cells are encapsulated within a single droplet, can lead to spurious cell type annotations and obscure true biological findings. The issue of multiplets is exacerbated in single-cell multiomics settings, where integrating cross-modality information for clustering can inadvertently promote the aggregation of multiplet clusters and increase the risk of erroneous cell type annotations. Here, we propose a compound Poisson model-based framework for multiplet detection in single-cell multiomics data. Leveraging experimental cell hashing results as the ground truth for multiplet status, we conducted trimodal DOGMA-seq experiments and generated 17 benchmarking datasets from two tissues, involving a total of 280,123 droplets. We demonstrated that the proposed method is an essential tool for integrating cross-modality multiplet signals, effectively eliminating multiplet clusters in single-cell multiomics data-a task at which the benchmarked single-omics methods proved inadequate.

Cell signaling and transcriptional regulation of osteoblast lineage commitment, differentiation, bone formation, and homeostasis.

The initiation of osteogenesis primarily occurs as mesenchymal stem cells undergo differentiation into osteoblasts. This differentiation process plays a crucial role in bone formation and homeostasis and is regulated by two intricate processes: cell signal transduction and transcriptional gene expression. Various essential cell signaling pathways, including Wnt, BMP, TGF-ß, Hedgehog, PTH, FGF, Ephrin, Notch, Hippo, and Piezo1/2, play a critical role in facilitating osteoblast differentiation, bone formation, and bone homeostasis. Key transcriptional factors in this differentiation process include Runx2, Cbfß, Runx1, Osterix, ATF4, SATB2, and TAZ/YAP. Furthermore, a diverse array of epigenetic factors also plays critical roles in osteoblast differentiation, bone formation, and homeostasis at the transcriptional level. This review provides an overview of the latest developments and current comprehension concerning the pathways of cell signaling, regulation of hormones, and transcriptional regulation of genes involved in the commitment and differentiation of osteoblast lineage, as well as in bone formation and maintenance of homeostasis. The paper also reviews epigenetic regulation of osteoblast differentiation via mechanisms, such as histone and DNA modifications. Additionally, we summarize the latest developments in osteoblast biology spurred by recent advancements in various modern technologies and bioinformatics. By synthesizing these insights into a comprehensive understanding of osteoblast differentiation, this review provides further clarification of the mechanisms underlying osteoblast lineage commitment, differentiation, and bone formation, and highlights potential new therapeutic applications for the treatment of bone diseases.

VirRep: a hybrid language representation learning framework for identifying viruses from human gut metagenomes.

Identifying viruses from metagenomes is a common step to explore the virus composition in the human gut. Here, we introduce VirRep, a hybrid language representation learning framework, for identifying viruses from human gut metagenomes. VirRep combines a context-aware encoder and an evolution-aware encoder to improve sequence representation by incorporating k-mer patterns and sequence homologies. Benchmarking on both simulated and real datasets with varying viral proportions demonstrates that VirRep outperforms state-of-the-art methods. When applied to fecal metagenomes from a colorectal cancer cohort, VirRep identifies 39 high-quality viral species associated with the disease, many of which cannot be detected by existing methods.

Implementation factors of tuberculosis control program in primary healthcare settings in China: a mixed-methods using the Consolidated Framework for Implementation Research framework.

BACKGROUND: Tuberculosis (TB) is a major cause of death worldwide, and Chinese TB burden ranked the second globally. Chinese primary healthcare (PHC) sectors implement the TB Control Program (TCP) to improve active case finding, referral, treatment adherence, and health education. This study aimed to identify barriers and enablers of TCP implementation in high TB burden regions of West China. METHODS: We conducted a representative study using mixed-methods in 28 counties or districts in Chongqing Municipality and Guizhou Province of West China from October 2021 to May 2022. Questionnaire surveys and semi-structured in-depth interviews were conducted with 2720 TB healthcare workers (HCWs) and 20 interviewees in PHC sectors. Descriptive statistical analysis was used to investigate TB HCWs' characteristics, and path analysis model was utilized to analyze the impact of associated factors on TCP implementation. Thematic framework analysis was developed with the guide of the adapted Consolidated Framework for Implementation Research (CFIR) on factors of TCP implementation. RESULTS: This study found that 84.6% and 94.1% of community and village HCWs had low professional titles. Based on the results of multiple regression analysis and correlation analysis, lower TB core knowledge scores (-0.09) were identified as barriers for TCP implementation in community PHC sectors, and low working satisfaction (-0.17) and low working willingness (-0.10) are barriers for TPC implementation in village PHC sectors. The results of in-depth interviews reported barriers in all domains and enablers in four domains of CFIR. There were identified 19 CFIR constructs associated with TCP implementation, including 22 barriers such as HCWs' heavy workload, and 12 enablers such as HCWs' passion towards TCP planning. CONCLUSIONS: With the guide of the CFIR framework, complex factors (barriers and enablers) of TCP implementation in PHC sectors of West China were explored, which provided important evidences to promote TB program in high TB burden regions. Further implementation studies to translate those factors into implementation strategies are urgent needed.