Objective: To establish a risk prediction model for diabetic peripheral neuropathy (DPN) among patients with type 2 diabetes mellitus (T2DM), so as to provide a basis for DPN prevention and control. Methods: T2DM inpatients aged 18-65 years admitted to the department of endocrinology and metabolism at Affiliated Hospital Shandong Second Medical University from April to December 2024 were selected as study subjects. Age, T2DM duration, hypertension history, 25-hydroxyvitamin D, serum C-peptide, and high density lipoprotein cholesterol (HDL-C) were collected through electronic medical records. Risk predictors of DPN among T2DM patients were screened using multivariable logistic regression model, and a nomogram was established. The receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis were employed to evaluate the discrimination, calibration and clinical utility of the nomogram, respectively. Results: A total of 598 T2DM patients were enrolled, including 359 (60.03%) males and 239 (39.97%) females. The median age was 54.50 (interquartile range, 15.00) years, the median T2DM duration was 6.00 (interquartile range, 9.00) years. There were 262 cases of T2DM patients with DPN, accounting for 43.81%. Multivariable logistic regression identified hypertension history (OR=3.260, 95%CI: 2.220-4.790), alcohol use history (OR=2.150, 95%CI: 1.390-3.310), diabetes complications (OR=0.430, 95%CI: 0.270-0.680), T2DM duration (OR=1.040, 95%CI: 1.010-1.070), body mass index (OR=1.130, 95%CI: 1.070-1.200), 25-hydroxyvitamin D (OR=0.930, 95%CI: 0.910-0.960), and HDL-C (OR=0.400, 95%CI: 0.230-0.720) as risk predictors for DPN among T2DM patients. The area under the ROC curve of the established risk prediction model was 0.774 (95%CI: 0.737-0.812), with a sensitivity of 0.710 and a specificity of 0.723. The calibration curve after repeated sampling calibration approached the standard curve. Decision curve analysis showed that when the risk threshold probability was 0.2 to 0.4, the model demonstrates favorable clinical applicability. Conclusion The risk prediction model established in this study has favorable discrimination, calibration, and clinical utility, can effectively predict the risk of DPN among T2DM patients aged 18-65 years.

In recent decades, the prevalence of hyperuricemia and gout has increased dramatically due to lifestyle changes. The drugs currently recommended for hyperuricemia are associated with adverse reactions that limit their clinical use. In this study, we report that berberine (BBR) is an effective drug candidate for the treatment of hyperuricemia, with its mechanism potentially involving the modulation of gut microbiota and its metabolite, succinic acid. BBR has demonstrated good therapeutic effects in both acute and chronic animal models of hyperuricemia. In a clinical trial, oral administration of BBR for 6 months reduced blood uric acid levels in 22 participants by modulating the gut microbiota, which led to an increase in the abundance of Bacteroides and a decrease in Clostridium sensu stricto_1. Furthermore, Bacteroides fragilis was transplanted into ICR mice, and the results showed that Bacteroides fragilis exerted a therapeutic effect on uric acid similar to that of BBR. Notably, succinic acid, a metabolite of Bacteroides, significantly reduced uric acid levels. Subsequent cell and animal experiments revealed that the intestinal metabolite, succinic acid, regulated the upstream uric acid synthesis pathway in the liver by inhibiting adenosine monophosphate deaminase 2 (AMPD2), an enzyme responsible for converting adenosine monophosphate (AMP) to inosine monophosphate (IMP). This inhibition resulted in a decrease in IMP levels and an increase in phosphate levels. The reduction in IMP led to a decreased downstream production of hypoxanthine, xanthine, and uric acid. BBR also demonstrated excellent renoprotective effects, improving nephropathy associated with hyperuricemia. In summary, BBR has the potential to be an effective treatment for hyperuricemia through the gut-liver axis.

Alzheimer's disease (AD) is regarded as a neurodegenerative disease, and it has been proposed that AD may be a systemic disease. Studies have reported associations between non-neurological diseases and AD. The correlations between AD pathology and systemic (non-neurological) pathological changes are intricate, and the mechanisms underlying these correlations and their causality are unclear. In this article, we review the association between AD and disorders of other systems. In addition, we summarize the possible mechanisms associated with AD and disorders of other systems, mainly from the perspective of AD pathology. Regarding the relationship between AD and systemic pathological changes, we aim to provide a new outlook on the early warning signs and treatment of AD, such as establishing a diagnostic and screening system based on more accessible peripheral samples.
Alzheimer Disease/therapy* ; Humans ; Brain/pathology*

Objective:To investigate the main factors that influence ALT abnormalities in workers exposed to benzene.Methods:In June 2022, data of 613 enterprises with benzene hazards and 585 enterprises with non-benzene hazards in Tianjin in 2021 were collected, and occupational health examination data of 13018 workers with benzene exposure and 13018 workers with non-benzene exposure were collected, and the region, enterprise type, industry classification and enterprise scale of the employer were analyzed. And occupational health examination data of workers with benzene exposure and non-benzene exposure. The effects of personal general situation, occupational history, enterprise information and benzene exposure on alanine aminotransferase were evaluated by additive interaction.Results:Compared with the group of non-benzene-exposed workers, the personal general conditions, occupational history, company information were higher in the benzene-exposed workers, and the differences were statistically significant ( P<0.05). The quantitative analysis of additive interaction found that gender ( RERI=2.632, 95% CI: 1.966-3.297; AP=0.383, 95% CI: 0.311-0.456; S=1.813, 95% CI: 1.530-2.149), age ( RERI=1.142, 95% CI: 0.928-1.356; AP=0.462, 95% CI: 0.371-0.552; S=4.461, 95% CI: 1.800-11.053), length of service ( RERI=-1.199, 95% CI: -1.653--0.745; AP=-0.456, 95% CI: -0.640--0.271; S=0.576, 95% CI: 0.479-0.693), region ( RERI=0.421, 95% CI: 0.148-0.694; AP=0.161, 95% CI: 0.053-0.268; S=1.350, 95% CI: 1.057-1.726), industry classification ( RERI=0.627, 95% CI: 0.345-0.910; AP=0.232, 95% CI: 0.132-0.332; S=1.584, 95% CI: 1.233-2.035) and benzene exposure had a statistically significant additive interaction with abnormal serum ALT. Conclusion:Emphasis should be placed on male workers under the age of 40 in the petrochemical industry, oil storage and transportation, and power production, so as to protect the health of workers more specifically and reduce the risk of disability due to disease.

At present, clinical interventions for chronic kidney disease are very limited, and most patients rely on dialysis to sustain their lives for a long time. However, studies on the gut-kidney axis have shown that the gut microbiota is a potentially effective target for correcting or controlling chronic kidney disease. This study showed that berberine, a natural drug with low oral availability, significantly ameliorated chronic kidney disease by altering the composition of the gut microbiota and inhibiting the production of gut-derived uremic toxins, including p-cresol. Furthermore, berberine reduced the content of p-cresol sulfate in plasma mainly by lowering the abundance of g_Clostridium_sensu_stricto_1 and inhibiting the tyrosine-p-cresol pathway of the intestinal flora. Meanwhile, berberine increased the butyric acid producing bacteria and the butyric acid content in feces, while decreased the renal toxic trimethylamine N-oxide. These findings suggest that berberine may be a therapeutic drug with significant potential to ameliorate chronic kidney disease through the gut-kidney axis.

Specnuezhenide(SNZ)is among the main components of Fructus Ligustri Lucidi,which has anti-inflammation,anti-oxidation,and anti-tumor effect.The low bioavailability makes it difficult to explain the mechanism of pharmacological effect of SNZ.In this study,the role of the gut microbiota in the metabolism and pharmacokinetics characteristics of SNZ as well as the pharmacological meaning were explored.SNZ can be rapidly metabolized by the gut microbiome,and two intestinal bacterial metabolites of SNZ,salidroside and tyrosol,were discovered.In addition,carboxylesterase may be the main intestinal bacterial enzyme that mediates its metabolism.At the same time,no metabolism was found in the incubation system of SNZ with liver microsomes or liver homogenate,indicating that the gut microbiota is the main part involved in the metabolism of SNZ.In addition,pharmacokinetic studies showed that salidroside and tyrosol can be detected in plasma in the presence of gut microbiota.Interestingly,tumor development was inhibited in a colorectal tumor mice model administered orally with SNZ,which indicated that SNZ exhibited potential to inhibit tumor growth,and tissue distribution studies showed that salidroside and tyrosol could be distributed in tumor tissues.At the same time,SNZ modulated the structure of gut microbiota and fungal group,which may be the mechanism governing the antitumoral activity of SNZ.Furthermore,SNZ stimulates the secretion of short-chain fatty acids by intestinal flora in vitro and in vivo.In the future,targeting gut microbes and the interaction between natural products and gut microbes could lead to the discovery and development of new drugs.

Nonalcoholic fatty liver disease(NAFLD)has developed into the most common chronic liver disease and can lead to liver cancer.Our laboratory previously developed a novel prescription for NAFLD,"Eight Zhes Decoction"(EZD),which has shown good curative effects in clinical practice.However,the pharmaco-dynamic material basis and mechanism have not yet been revealed.A strategy integrating lipidomics,network pharmacology and pharmacokinetics was used to reveal the active components and mecha-nisms of EZD against NAFLD.The histopathological results showed that EZD attenuated the degrees of collagen deposition and steatosis in the livers of nonalcoholic steatofibrosis model mice.Furthermore,glycerophospholipid metabolism,arachidonic acid metabolism,glycerolipid metabolism and linoleic acid metabolism with phospholipase A2 group IVA(PLA2G4A)and cytochrome P450 as the core targets and 12,13-cis-epoxyoctadecenoic acid,12(S)-hydroxyeicosatetraenoic acid,leukotriene B4,prostaglandin E2,phosphatidylcholines(PCs)and triacylglycerols(TGs)as the main lipids were found to be involved in the treatment of NAFLD by EZD.Importantly,naringenin,artemetin,canadine,and bicuculline were iden-tified as the active ingredients of EZD against NAFLD;in particular,naringenin reduces PC consumption by inhibiting the expression of PLA2G4A and thus promotes sufficient synthesis of very-low-density lipoprotein to transport excess TGs in the liver.This research provides valuable data and theoretical support for the application of EZD against NAFLD.

Objective:To investigate the main factors that influence ALT abnormalities in workers exposed to benzene.Methods:In June 2022, data of 613 enterprises with benzene hazards and 585 enterprises with non-benzene hazards in Tianjin in 2021 were collected, and occupational health examination data of 13018 workers with benzene exposure and 13018 workers with non-benzene exposure were collected, and the region, enterprise type, industry classification and enterprise scale of the employer were analyzed. And occupational health examination data of workers with benzene exposure and non-benzene exposure. The effects of personal general situation, occupational history, enterprise information and benzene exposure on alanine aminotransferase were evaluated by additive interaction.Results:Compared with the group of non-benzene-exposed workers, the personal general conditions, occupational history, company information were higher in the benzene-exposed workers, and the differences were statistically significant ( P<0.05). The quantitative analysis of additive interaction found that gender ( RERI=2.632, 95% CI: 1.966-3.297; AP=0.383, 95% CI: 0.311-0.456; S=1.813, 95% CI: 1.530-2.149), age ( RERI=1.142, 95% CI: 0.928-1.356; AP=0.462, 95% CI: 0.371-0.552; S=4.461, 95% CI: 1.800-11.053), length of service ( RERI=-1.199, 95% CI: -1.653--0.745; AP=-0.456, 95% CI: -0.640--0.271; S=0.576, 95% CI: 0.479-0.693), region ( RERI=0.421, 95% CI: 0.148-0.694; AP=0.161, 95% CI: 0.053-0.268; S=1.350, 95% CI: 1.057-1.726), industry classification ( RERI=0.627, 95% CI: 0.345-0.910; AP=0.232, 95% CI: 0.132-0.332; S=1.584, 95% CI: 1.233-2.035) and benzene exposure had a statistically significant additive interaction with abnormal serum ALT. Conclusion:Emphasis should be placed on male workers under the age of 40 in the petrochemical industry, oil storage and transportation, and power production, so as to protect the health of workers more specifically and reduce the risk of disability due to disease.

O ⁶-carboxymethyl guanine(O ⁶-CMG) is a highly mutagenic alkylation product of DNA that causes gastrointestinal cancer in organisms. Existing studies used mutant Mycobacterium smegmatis porin A (MspA) nanopore assisted by Phi29 DNA polymerase to localize it. Recently, machine learning technology has been widely used in the analysis of nanopore sequencing data. But the machine learning always need a large number of data labels that have brought extra work burden to researchers, which greatly affects its practicability. Accordingly, this paper proposes a nano-Unsupervised-Deep-Learning method (nano-UDL) based on an unsupervised clustering algorithm to identify methylation events in nanopore data automatically. Specially, nano-UDL first uses the deep AutoEncoder to extract features from the nanopore dataset and then applies the MeanShift clustering algorithm to classify data. Besides, nano-UDL can extract the optimal features for clustering by joint optimizing the clustering loss and reconstruction loss. Experimental results demonstrate that nano-UDL has relatively accurate recognition accuracy on the O ⁶-CMG dataset and can accurately identify all sequence segments containing O ⁶-CMG. In order to further verify the robustness of nano-UDL, hyperparameter sensitivity verification and ablation experiments were carried out in this paper. Using machine learning to analyze nanopore data can effectively reduce the additional cost of manual data analysis, which is significant for many biological studies, including genome sequencing.
Deep Learning ; Guanine ; Nanopore Sequencing ; Nanopores ; Porins/genetics*

Marine fungi are important members of the marine microbiome, which have been paid growing attention by scientists in recent years. The secondary metabolites of marine fungi have been reported to contain rich and diverse compounds with novel structures (Chen et al., 2019). Aspergillus terreus, the higher level marine fungus of the Aspergillus genus (family of Trichocomaceae, order of Eurotiales, class of Eurotiomycetes, phylum of Ascomycota), is widely distributed in both sea and land. In our previous study, the coral-derived A. terreus strain C23-3 exhibited potential in producing other biologically active (with antioxidant, acetylcholinesterase inhibition, and anti-inflammatory activity) compounds like arylbutyrolactones, territrems, and isoflavones, and high sensitivity to the chemical regulation of secondary metabolism (Yang et al., 2019, 2020; Nie et al., 2020; Ma et al., 2021). Moreover, we have isolated two different benzaldehydes, including a benzaldehyde with a novel structure, from A. terreus C23-3 which was derived from Pectinia paeonia of Xuwen, Zhanjiang City, Guangdong Province, China.
Acetylcholinesterase/metabolism* ; Animals ; Anthozoa/microbiology* ; Anti-Inflammatory Agents/pharmacology* ; Aspergillus/chemistry* ; Benzaldehydes/pharmacology* ; Mice ; RAW 264.7 Cells ; Signal Transduction