Computed tomography-based radiomics to predict early recurrence of hepatocellular carcinoma post-hepatectomy in patients background on cirrhosis.

BACKGROUND: The prognosis for hepatocellular carcinoma (HCC) in the presence of cirrhosis is unfavourable, primarily attributable to the high incidence of recurrence. AIM: To develop a machine learning model for predicting early recurrence (ER) of post-hepatectomy HCC in patients with cirrhosis and to stratify patients' overall survival (OS) based on the predicted risk of recurrence. METHODS: In this retrospective study, 214 HCC patients with cirrhosis who underwent curative hepatectomy were examined. Radiomics feature selection was conducted using the least absolute shrinkage and selection operator and recursive feature elimination methods. Clinical-radiologic features were selected through univariate and multivariate logistic regression analyses. Five machine learning methods were used for model comparison, aiming to identify the optimal model. The model's performance was evaluated using the receiver operating characteristic curve [area under the curve (AUC)], calibration, and decision curve analysis. Additionally, the Kaplan-Meier (K-M) curve was used to evaluate the stratification effect of the model on patient OS. RESULTS: Within this study, the most effective predictive performance for ER of post-hepatectomy HCC in the background of cirrhosis was demonstrated by a model that integrated radiomics features and clinical-radiologic features. In the training cohort, this model attained an AUC of 0.844, while in the validation cohort, it achieved a value of 0.790. The K-M curves illustrated that the combined model not only facilitated risk stratification but also exhibited significant discriminatory ability concerning patients' OS. CONCLUSION: The combined model, integrating both radiomics and clinical-radiologic characteristics, exhibited excellent performance in HCC with cirrhosis. The K-M curves assessing OS revealed statistically significant differences.

DCENet-based low-light image enhancement improved by spiking encoding and convLSTM.

The direct utilization of low-light images hinders downstream visual tasks. Traditional low-light image enhancement (LLIE) methods, such as Retinex-based networks, require image pairs. A spiking-coding methodology called intensity-to-latency has been used to gradually acquire the structural characteristics of an image. convLSTM has been used to connect the features. This study introduces a simplified DCENet to achieve unsupervised LLIE as well as the spiking coding mode of a spiking neural network. It also applies the comprehensive coding features of convLSTM to improve the subjective and objective effects of LLIE. In the ablation experiment for the proposed structure, the convLSTM structure was replaced by a convolutional neural network, and the classical CBAM attention was introduced for comparison. Five objective evaluation metrics were compared with nine LLIE methods that currently exhibit strong comprehensive performance, with PSNR, SSIM, MSE, UQI, and VIFP exceeding the second place at 4.4% (0.8%), 3.9% (17.2%), 0% (15%), 0.1% (0.2%), and 4.3% (0.9%) on the LOL and SCIE datasets. Further experiments of the user study in five non-reference datasets were conducted to subjectively evaluate the effects depicted in the images. These experiments verified the remarkable performance of the proposed method.

Rethinking Biosynthesis of Aclacinomycin A.

Aclacinomycin A (ACM-A) is an anthracycline antitumor agent widely used in clinical practice. The current industrial production of ACM-A relies primarily on chemical synthesis and microbial fermentation. However, chemical synthesis involves multiple reactions which give rise to high production costs and environmental pollution. Microbial fermentation is a sustainable strategy, yet the current fermentation yield is too low to satisfy market demand. Hence, strain improvement is highly desirable, and tremendous endeavors have been made to decipher biosynthesis pathways and modify key enzymes. In this review, we comprehensively describe the reported biosynthesis pathways, key enzymes, and, especially, catalytic mechanisms. In addition, we come up with strategies to uncover unknown enzymes and improve the activities of rate-limiting enzymes. Overall, this review aims to provide valuable insights for complete biosynthesis of ACM-A.

Transcriptomics Analysis of the Toxicological Impact of Enrofloxacin in an Aquatic Environment on the Chinese Mitten Crab (Eriocheir sinensis).

Enrofloxacin is an important antimicrobial drug that is widely used in aquaculture. Enrofloxacin residues can have negative effects on aquatic environments and animals. The toxicological effects of different concentrations of enrofloxacin residues in cultured water on Chinese mitten crabs (Eriocheir sinensis) were compared. A histological analysis of the E. sinensis hepatopancreas demonstrated that the hepatopancreas was damaged by the different enrofloxacin residue concentrations. The hepatopancreas transcriptome results revealed that 1245 genes were upregulated and that 1298 genes were downregulated in the low-concentration enrofloxacin residue group. In the high-concentration enrofloxacin residue group, 380 genes were upregulated, and 529 genes were downregulated. The enrofloxacin residues led to differentially expressed genes related to the immune system and metabolic processes in the hepatopancreas of the Chinese mitten crab, such as the genes for alkaline phosphatase, NF-kappa B inhibitor alpha, alpha-amylase, and beta-galactosidase-like. The gene ontology terms "biological process" and "molecular function" were enriched in the carboxylic acid metabolic process, DNA replication, the synthesis of RNA primers, the transmembrane transporter activity, the hydrolase activity, and the oxidoreductase activity. A Kyoto Encyclopedia of Genes and Genomes pathway analysis determined that the immune and metabolic signal transduction pathways were significantly enriched. Furthermore, the nonspecific immune enzyme (alkaline phosphatase) and the metabolic enzyme system played a role in the enrofloxacin metabolism in the E. sinensis hepatopancreas. These findings helped us to further understand the basis of the toxicological effects of enrofloxacin residues on river crabs and provided valuable information for the better utilization of enrofloxacin in aquatic water environments.

Traditional Chinese medicine for the treatment of diabetic kidney disease: A study-level pooled analysis of 44 randomized controlled trials.

Background: Accumulating evidence suggests that traditional Chinese medicine (TCM) has significant effects on reducing 24-h urinary protein (24-h UPRO) and improves renal function indices. The current level of evidence-based medicine is still not enough due to the limitation of clinical center size and sample size. Objective: We aimed to update the current evidence on the efficacy of TCM in the treatment of diabetic kidney disease (DKD). Methods: PubMed, Embase, the Cochrane Library, and SinoMed were searched to identify randomized controlled trials (RCTs) comparing the clinical efficacy of TCM combined with Western medicine with that of Western medicine alone for the treatment of DKD. The main outcome measure was 24-h UPRO. The secondary outcomes were serum creatinine (Scr), blood urea nitrogen (BUN), glycosylated hemoglobin (HbA1c), fasting blood glucose (FBG), total cholesterol (TC), and triglyceride (TG). Meta-analyses were performed using random-effects models. The revised Cochrane risk-of-bias tool was used to assess the risk of bias. Results: A total of 44 RCTs with 3,730 participants were included. The summary estimates showed that compared with Western medicine alone, TCM combined with Western medicine significantly improved 24-h UPRO [standardized mean difference (SMD) -1.10, 95% confidence interval (CI) -1.45 to -0.74]. Moreover, TCM combined with Western medicine significantly reduced the levels of other renal function indices, including Scr (SMD -1.25, 95% CI: -1.69 to -0.81) and BUN (SMD -0.75, 95% CI: -1.10 to -0.40). TCM combined with Western medicine also showed greater benefits in reducing the levels of FBG (SMD -0.31, 95% CI: -0.47 to -0.15) and HbA1c (SMD -0.62, 95% CI: -0.89 to -0.36) in patients with DKD. In addition, superior effects on the lipid profile were noted in the TCM combined with Western medicine group in terms of TG (SMD -1.17, 95% CI: -1.76 to -0.59) and TC (SMD -0.95, 95% CI: -1.43 to -0.47). The risk of bias could have resulted from selective reports, unclear randomization methods, unblinded assignments, and some missing data. Conclusion: The results of this meta-analysis suggest that TCM combined with Western medicine has significant effects on reducing 24-h UPRO and improves renal function indices and lipid profiles compared with Western medicine alone for DKD. However, the results should be interpreted with caution due to the risk of bias of the included trials. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=213199], identifier [CRD: 42020213199].

Study of SPRC Impact Resistance Based on the Weibull Distribution and the Response Surface Method.

Silica-fume-polyvinyl-alcohol-fiber-reinforced concrete (SPRC) is a green and environmentally friendly composite material incorporating silica fume and polyvinyl alcohol fiber into concrete. To study the impact resistance of SPRC, compressive-strength and drop hammer impact tests were conducted on SPRC with different silica-fume and polyvinyl-alcohol-fiber contents. The mechanical and impact resistance properties of the SPRC were comprehensively analyzed in terms of the compressive strength, ductility ratio and impact-energy-dissipation variation. Based on the impact resistance of the SPRC, the impact life of SPRC with different failure probabilities was predicted by incorporating the Weibull distribution model, and an impact damage evolution equation for SPRC was established. The impact life of SPRC under the action of silica-fume content, polyvinyl-alcohol-fiber content and failure probability was analyzed in depth by the response surface method (RSM). The research results show that, when the content of silica fume is 10% and the content of polyvinyl alcohol fiber is 1%, the compressive strength and impact resistance of SPRC are the best. The RSM response model can effectively predict and describe the impact life of SPRC specimens under the action of three factors.

Decreased angiotensin receptor 1 expression in ± AT1 Knockout mice testis results in male infertility and GnRH reduction.

BACKGROUND: This study aimed to detect the effect of angiotensin receptor 1 (AT1) knock out (KO) on spermatogenesis and hypothalamic-pituitary-gonadal (HPG) axis hormone expression. METHODS: Normal C57BL/6 male mice were used as control group or treated with angiotensin receptor blocker, in addition heterozygous ± AT1KO mice were generated. After caged at a ratio of 2 to 1 with females, pregnancy rates of female mice were determined by detection of vaginal plugs. Deformity rate of spermatozoa was evaluated by eosin staining and morphology evaluation. The AT1 mRNA expression in the testes of male ± AT1KO mice was detected by quantitative real-time polymerase chain reaction (QRT-PCR). Serum GnRH level was determined by ELISA. RESULTS: Compared to control, ± AT1KO mice showed reduced expression of AT1 in testes, pituitary and hypothalamus. In addition, decreased level of GnRH, but not follicle stimulating hormone (FSH) or luteinizing hormone (LH), in ± AT1KO mice was detected. Treatment with angiotensin receptor blocker (ARB) did not have significant effects on HPG hormones. ± AT1KO mice exhibited male infertility and significant abnormality of sperm morphology. CONCLUSION: Reduced AT1 knockout resulted in male infertility, potentially by inducing abnormal spermatogenesis. Both testis and HPG axis signaling may be involved.

Polydopamine Nanocluster Embedded Nanofibrous Membrane via Blow Spinning for Separation of Oil/Water Emulsions.

Developing a porous separation membrane that can efficiently separate oil-water emulsions still represents a challenge. In this study, nanofiber membranes with polydopamine clusters polymerized and embedded on the surface were successfully constructed using a solution blow-spinning process. The hierarchical surface structure enhanced the selective wettability, superhydrophilicity in air (≈0°), and underwater oleophobicity (≈160.2°) of the membrane. This membrane can effectively separate oil-water emulsions, achieving an excellent permeation flux (1552 Lm-2 h-1) and high separation efficiency (~99.86%) while operating only under the force of gravity. When the external driving pressure was increased to 20 kPa, the separation efficiency hardly changed (99.81%). However, the permeation flux significantly increased to 5894 Lm-2 h-1. These results show that the as-prepared polydopamine nanocluster-embedded nanofiber membrane has an excellent potential for oily wastewater treatment applications.