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Radiation-induced pulmonary fibrosis (RIPF) is a common consequence of radiation for thoracic tumors, and is accompanied by gradual and irreversible organ failure. This severely reduces the survival rate of cancer patients, due to the serious side effects and lack of clinically effective drugs and methods. Radiation-induced pulmonary fibrosis is a dynamic process involving many complicated and varied mechanisms, of which alveolar type II epithelial (AT2) cells are one of the primary target cells, and the epithelial–mesenchymal transition (EMT) of AT2 cells is very relevant in the clinical search for effective targets. Therefore, this review summarizes several important signaling pathways that can induce EMT in AT2 cells, and searches for molecular targets with potential effects on RIPF among them, in order to provide effective therapeutic tools for the clinical prevention and treatment of RIPF.

Microplastic (MP) pollution in aquatic ecosystems poses significant ecological and public health risks. A comprehensive understanding of estuarine MP pollution, influenced by multiple anthropogenic and environmental factors, remains elusive in current research. This study investigated the spatial distribution patterns and dominant factors influencing MP abundance (MPA) and physicochemical diversity in the river water and sediments of the Pearl River Estuary (PRE), while also assessing the associated ecological risks. The dominant MP categories in river water and sediments were fibers, clear in color, <1 mm in length, and composed of polyethylene terephthalate and polypropylene. Whereas inland regions showed higher MPA, nearshore regions exhibited marginally greater physicochemical diversity. Multivariate statistical analysis identified population density as the primary driver of both MPA in river water and MP physicochemical diversity in sediments. MP physicochemical diversity in river water was predominantly governed by the synergistic effect of salinity and the vegetation land. MPA in sediments depended on the synergistic effect of flow rate and watershed area. Ecological risk assessment identified elevated risks in the eastern study area driven by the presence of polymethyl methacrylate. This study establishes a scientific basis for PRE region MP management and provides global comparative data for estuarine MP research.

Understanding miRNAs regulatory roles in epithelial-mesenchymal transition (EMT) would help establish new avenues for further uncovering the mechanisms underlying radiation-induced pulmonary fibrosis (RIPF) and identifying preventative and therapeutic targets. Here, we demonstrated that miR-541-5p repression by Myeloid Zinc Finger 1 (MZF1) promotes radiation-induced EMT and RIPF. Irradiation could decrease miR-541-5p expression in vitro and in vivo and inversely correlated to RIPF development. Ectopic miR-541-5p expression suppressed radiation-induced-EMT in vitro and in vivo. Knockdown of Slug, the functional target of miR-541-5p, inhibited EMT induction by irradiation. The upregulation of transcription factor MZF1 upon irradiation inhibited the expression of endogenous miR-541-5p and its primary precursor (pri-miR-541-5p), which regulated the effect of the Slug on the EMT process. Our finding showed that ectopic miR-541-5p expression mitigated RIPF in mice by targeting Slug. Thus, irradiation activates MZF1 to downregulate miR-541-5p in alveolar epithelial cells, promoting EMT and contributing to RIPF by targeting Slug. Our observation provides further understanding of the development of RIPF and determines potential preventative and therapeutic targets.

The coffee industry is developing rapidly in the world, and the use of coffee filtration nonwovens (CFNs) is becoming more and more extensive; however, there is a lack of standards and research for its production and trade, and the quality of related products on the market is uneven at present. Here, eight double-layer composite coffee filtration nonwovens (D-LCCFNs) were prepared by using 5 g/m2 and 10 g/m2 polypropylene (PP) melt-blown nonwovens (MNs), 20 g/m2 PP spunbonded nonwovens and 20 g/m2 viscose/ES fiber chemically bonded nonwovens, and the physical properties, morphology and the filtration effect of coffee and purified water for the prepared samples were tested. It was found that the surface density of the microfiber layer (MNs) in the D-LCCFNs was negatively correlated with the coffee filtration rate; when the microfiber layer in the D-LCCFNs was in direct contact with the coffee, the liquid started to drip later, and the filtration rate of the coffee was slower; the filtration rate of the samples with the viscose/ES chemically bonded nonwovens was very fast. However, the samples without viscose/ES fibers basically did not filter pure water much, but they could filter out the coffee liquid normally, and the samples’ hydrophilicity increased significantly after filtering coffee.

Dual-target drug design addresses complex diseases and drug resistance, yet existing computational approaches struggle with simultaneous multi-protein optimization. This study presents SFG-Drug, a novel dual-target molecular generation model combining Monte Carlo tree search with gated recurrent unit neural networks for simultaneous MEK1 and mTOR targeting. The methodology employed DigFrag digital fragmentation on ZINC-250k dataset, integrated low-frequency masking techniques for enhanced diversity, and utilized molecular docking scores as reward functions. Comprehensive evaluation on MOSES benchmark demonstrated superior performance compared to state-of-the-art methods, achieving perfect validity (1.000), uniqueness (1.000), and novelty (1.000) scores with highest internal diversity indices (0.878 for IntDiv1, 0.860 for IntDiv2). Over 90% of generated molecules exhibited favorable binding affinity with both targets, showing optimal drug-like properties including QED values in [0.2, 0.7] range and high synthetic accessibility scores. Generated compounds demonstrated structural novelty with Tanimoto coefficients below 0.25 compared to known inhibitors while maintaining dual-target binding capability. The SFG-Drug model successfully bridges the gap between computational prediction and practical drug discovery, offering significant potential for developing new dual-target therapeutic agents and advancing AI-driven pharmaceutical research methodologies.

In recent years, flows of many rivers and lakes have become reduced in arid and semi-arid regions around the world. The most typical examples of this phenomenon occur in Central Asia, and the reduction of the Aral Sea area is closely related to agricultural water use. However, due to a lack of continuous data in Central Asia spanning many years, “virtual water” is used to evaluate changes in agricultural water use. Based on virtual water theory, 325 kinds of agricultural products in eight categories are selected as the research object, and changes in virtual water are calculated for Central Asia from 1992 to 2016. Results indicate that: (1) The average annual net export of agricultural virtual water (TVWNE) in Central Asia is about 9 billion m 3 , concentrated in Kazakhstan, whose annual TVWNE reaches 8.1 billion m 3 . (2) Since 2007, the TVWNE in Central Asia has dropped significantly, with a drop rate of 86%, while the total volume of agricultural virtual water has gradually increased since 1998. (3) The upstream and downstream countries in Central Asia have different characteristics in the change of virtual water quantity.

Radon (Rn) exposure has a strong association with lung cancer risk and is influenced by epigenetic modifications. To investigate the characterization of DNA methylation (DNAm) episignatures for radon-induced lung cancer, we detected the specific changes in DNAm in blood and lung tissues using reduced representation bisulfite sequencing (RRBS). We identified the differentially methylated regions (DMRs) induced by radon exposure. The bioinformatics analysis of the DMR-mapped genes revealed that pathways in cancer were affected by radon exposure. Among them, the DNAm episignatures of MAPK10, PLCG1, PLCβ3 and PIK3R2 were repeated between lung tissue and blood, and validated by the MassArray. In addition, radon exposure promoted lung cancer development in the genetic engineering mouse model (GEMM), accompanied by decreased MAPK10 and increased PLCG1, PLCβ3, and PIK3R2 with mRNA and protein levels. Conclusively, radon exposure significantly changes the genomic DNAm patterns in lung tissue and blood. The DNAm episignatures of MAPK10, PLCG1, PLCβ3 and PIK3R2 have a significant influence on radon-induced lung cancer. This brings a new perspective to understanding the pathways involved in radon-induced lung cancer and offers potential targets for developing blood-based biomarkers and epigenetic therapeutics.

Incidence of delayed graft function (DGF) increases due to the decline in donor kidney quality and the increased use of marginal allografts, while the promising biomarkers for early DGF prediction are lacking. Previous analyses showed that Tenascin-C (TNC) was associated with acute kidney injury; however, its correlation with DGF is unclear. This study aimed to evaluate the ability of TNC to predict DGF. This prospective study included 36 perioperative kidney transplant recipients. Serum and urine samples were collected at regular intervals before and during the 10 days after transplantation to measure TNC and other conventional biomarkers. Pre-implantation graft renal biopsies were analyzed using Remuzzi and TNC staining scores. These data were then combined with clinical risk factors to construct a DGF prediction model. In recipients with DGF, sTNC levels peaked on postoperative day 4, and were associated with increased risk of composite events (DGF and rehospitalization). uTNC levels were significantly higher in recipients without DGF, peaking at 8 hours postoperatively. sTNC levels at postoperative day 4 and TNC immunohistochemical scores were identified as independent risk factors for DGF. Incorporating the above two factors into a model comprising recipient age, cholesterol levels, donor cold ischemia time, and surgery duration significantly improved its ability to predict DGF, with the area under the curve increasing from 0.6790 to 0.9321. This study highlights the TNC levels in perioperative kidney transplant recipients and their correlation with DGF. sTNC levels and TNC immunohistochemical staining scores may serve as potential biomarker predicting DGF.

Background Retaining the native bilateral kidneys after transplantation is a common treatment for patients with end-stage autosomal dominant polycystic kidney disease. However, this strategy poses the risks of potential complications from polycystic kidney infection. The efficiency of antibiotic therapy and the optimal time for native nephrectomy in managing these infections remain uncertain. Case presentation We report a case of a kidney transplant recipient with retained bilateral polycystic kidneys who experienced recurrent cyst and bloodstream infections, accompanied by antibiotic-driven pathogen replacement. After multiple failed attempts at antibiotic therapy, the patient subsequently underwent unilateral polycystic kidney resection. Subsequently, a new infection episode occurred, leading to the other native nephrectomy. Cystic tissue and fluid samples were collected from both shallow and deep layers of the polycystic kidneys, along with peripheral blood and urine samples. These samples were analyzed using microbial culture, metagenome sequencing, and digital polymerase chain reaction to identify infectious pathogens. Pathogen replacement occurred across different infection episodes, with the dominant bacterial species being Escherichia coli , Klebsiella aerogenes , and Enterococcus faecium , in succession. Conclusions This case highlights the replacement of dominant pathogens under antibiotic selection pressure in polycystic kidney infections, primarily involving gram-negative bacilli. When initial and subsequent antibiotic therapy fail, re-evaluation of the cyst infection definition is necessary, and preemptive native nephrectomy should be considered.