Adipose stem cells control obesity-induced T cell infiltration into adipose tissue.

T cell infiltration into white adipose tissue (WAT) drives obesity-induced adipose inflammation, but the mechanisms of obesity-induced T cell infiltration into WAT remain unclear. Our single-cell RNA sequencing reveals a significant impact of adipose stem cells (ASCs) on T cells. Transplanting ASCs from obese mice into WAT enhances T cell accumulation. C-C motif chemokine ligand 5 (CCL5) is upregulated in ASCs as early as 4 weeks of high-fat diet feeding, coinciding with the onset of T cell infiltration into WAT during obesity. ASCs and bone marrow transplantation experiments demonstrate that CCL5 from ASCs plays a crucial role in T cell accumulation during obesity. The production of CCL5 in ASCs is induced by tumor necrosis factor alpha via the nuclear factor κB pathway. Overall, our findings underscore the pivotal role of ASCs in regulating T cell accumulation in WAT during the early phases of obesity, emphasizing their importance in modulating adaptive immunity in obesity-induced adipose inflammation.

OTSUCNV: an adaptive segmentation and OTSU-based anomaly classification method for CNV detection using NGS data.

Copy-number variations (CNVs), which refer to deletions and duplications of chromosomal segments, represent a significant source of variation among individuals, contributing to human evolution and being implicated in various diseases ranging from mental illness and developmental disorders to cancer. Despite the development of several methods for detecting copy number variations based on next-generation sequencing (NGS) data, achieving robust detection performance for CNVs with arbitrary coverage and amplitude remains challenging due to the inherent complexity of sequencing samples. In this paper, we propose an alternative method called OTSUCNV for CNV detection on whole genome sequencing (WGS) data. This method utilizes a newly designed adaptive sequence segmentation algorithm and an OTSU-based CNV prediction algorithm, which does not rely on any distribution assumptions or involve complex outlier factor calculations. As a result, the effective detection of CNVs is achieved with lower computational complexity. The experimental results indicate that the proposed method demonstrates outstanding performance, and hence it may be used as an effective tool for CNV detection.

DHT-Net: Dynamic Hierarchical Transformer Network for Liver and Tumor Segmentation.

Automatic segmentation of liver tumors is crucial to assist radiologists in clinical diagnosis. While various deep learningbased algorithms have been proposed, such as U-Net and its variants, the inability to explicitly model long-range dependencies in CNN limits the extraction of complex tumor features. Some researchers have applied Transformer-based 3D networks to analyze medical images. However, the previous methods focus on modeling the local information (eg. edge) or global information (eg. morphology) with fixed network weights. To learn and extract complex tumor features of varied tumor size, location, and morphology for more accurate segmentation, we propose a Dynamic Hierarchical Transformer Network, named DHT-Net. The DHT-Net mainly contains a Dynamic Hierarchical Transformer (DHTrans) structure and an Edge Aggregation Block (EAB). The DHTrans first automatically senses the tumor location by Dynamic Adaptive Convolution, which employs hierarchical operations with the different receptive field sizes to learn the features of various tumors, thus enhancing the semantic representation ability of tumor features. Then, to adequately capture the irregular morphological features in the tumor region, DHTrans aggregates global and local texture information in a complementary manner. In addition, we introduce the EAB to extract detailed edge features in the shallow fine-grained details of the network, which provides sharp boundaries of liver and tumor regions. We evaluate DHT-Net on two challenging public datasets, LiTS and 3DIRCADb. The proposed method has shown superior liver and tumor segmentation performance compared to several state-of-the-art 2D, 3D, and 2.5D hybrid models.

Long noncoding RNA colorectal neoplasia differentially expressed alleviates sepsis-induced liver injury via regulating miR-126-5p.

In this study, we intended to determine the detailed function and mechanism of long noncoding RNA (lncRNA) colorectal neoplasia differentially expressed (CRNDE) in liver injury induced by sepsis. Cecal ligation and perforation (CLP) models were adopted to induce sepsis in vivo with rats, and hepatic epithelial cells L02 were treated with lipopolysaccharide (LPS) to mimic sepsis in vitro. Enzyme-linked immunosorbent assay was conducted to detect the levels of tumor necrosis factor (TNF-α), interleukin-6 (IL-6), interleukin-10 (IL-10), and interferon-γ (IFN-γ) in the serum of rats. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to measure the expressions of CRNDE and microRNA-126-5p (miR-126-5p). Flow cytometry analysis and Cell Counting Kit-8 (CCK-8) method were carried out followed by the up- or downregulation of CRNDE and miR-126-5p to monitor the proliferation and apoptosis of L02 cells, respectively. Western blot was then applied to determine the expressions of cysteinyl aspartate specific proteinase 3 (caspase 3), poly(ADP-ribose)polymerase (PARP), cytochrome c, and BCL2-like 2 (BCL2L2). The interactions between CRNDE with miR-126-5p and miR-126-5p with BCL2L2 were determined through bioinformatics, qRT-PCR, dual luciferase reporter assay, and RNA immunoprecipitation assay. CRNDE was significantly decreased in liver tissues and hepatic cells in sepsis models. Upregulation of CRNDE promoted the viability of L02 cells and inhibited their apoptosis, while downregulation of CRNDE had opposite effects. The expression of CRNDE in liver tissues of septic rats was correlated with the expression miR-126-5p. It was also demonstrated that the transfection of miR-126-5p mimics reversed the inhibitory effect induced by CRNDE on apoptosis of L02 cells. CRNDE could specifically bind to miR-126-5p and reduce its expression, in turn promote the expression of BCL2L2. Additionally, CRNDE overexpression in rats ameliorated liver injury induced by sepsis. Downregulated CRNDE aggravates hepatic injury via regulating miR-126-5p and BCL2L2 during sepsis.

Down-regulation of LncRNA CRNDE aggravates kidney injury via increasing MiR-181a-5p in sepsis.

Long non-coding RNA (lncRNA) colorectal neoplasia differentially expressed (CRNDE) is reported to be linked to inflammation and cell apoptosis. However its role in sepsis induced kidney injury remains unclear. This study aims to explore the possible mechanism of CRNDE in kidney injury induced by sepsis. In vivo urine-derived sepsis (US) rat model and in vitro LPS-induced HK-2 and HEK293 cells were established. Kidney function was measured in rats from different groups. Relative levels of tumor necrosis factor-α (TNF-α) and interleukin-1ß(IL-1ß) in kidney tissue were detected via Enzyme-linked immune sorbent assay (ELISA). Then we up- or down-regulated CRNDE and miRNA-181a-5p expression in the cells. The biological influence of CRNDE and miR-181a-5p on cells was studied using CCK-8 assay and Annexin V assay. Interaction between CRNDE and miR-181a-5p was determined by bioinformatics analysis, RT-PCR, and dual luciferase reporter assay. Peroxisome proliferator-activated receptor-α (PPARα) and cell apoptosis related molecules were detected by western blot. We demonstrated that CRNDE was markedly down-regulated while miR-181a-5p was significantly up-regulated in sepsis models. CRNDE interacted with miR-181a-5p, and negatively regulated its expression level. CRNDE knockdown in rats increased the urea nitrogen and serum creatinine in plasma. Knockdown of CRNDE or transfection of miR-181a-5p significantly inhibited proliferation and promoted apoptosis of HK-2 and HEK293 cells, while overexpression of CRNDE and transfection of miR-181a-5p inhibitors had opposite effects. For mechanism, miR-181a-5p directly targeted the 3' untranslated region of PPARα, and depressed its protein level, and PPARα was regulated indirectly by CRNDE. We concluded that CRNDE protected renal cell from sepsis-induced injury via miR-181a-5p/PPARα pathway.

Disulfide-based PEGylated prodrugs: Reconversion kinetics, self-assembly and antitumor efficacy.

The prodrug strategy serves well in drug formulation and delivery. Two disulfide-based PEGylated prodrugs were developed and the drug reconversion upon different conditions were studied in detail. The reconversion-induced oversaturation phenomenon was firstly reported here. We found the prodrug can co-assemble with parent drug via π-π stacking into well-defined nanoparticles. The PEG layer of the self-assembled nanoparticles improved the stability of the PEGylated prodrug by reducing the contact with biological enzymes. The nanoparticles also show favorable antitumor efficacy, both in vitro and in vivo.

Water reclamation from shale gas drilling flow-back fluid using a novel forward osmosis-vacuum membrane distillation hybrid system.

This study examined the performance of a novel hybrid system of forward osmosis (FO) combined with vacuum membrane distillation (VMD) for reclaiming water from shale gas drilling flow-back fluid (SGDF). In the hybrid FO-VMD system, water permeated through the FO membrane into a draw solution reservoir, and the VMD process was used for draw solute recovery and clean water production. Using a SGDF sample obtained from a drilling site in China, the hybrid system could achieve almost 90% water recovery. Quality of the reclaimed water was comparable to that of bottled water. In the hybrid FO-VMD system, FO functions as a pre-treatment step to remove most contaminants and constituents that may foul or scale the membrane distillation (MD) membrane, whereas MD produces high quality water. It is envisioned that the FO-VMD system can recover high quality water not only from SGDF but also other wastewaters with high salinity and complex compositions.