Unraveling the underlying pathogenic factors driving nonalcoholic steatohepatitis and hepatocellular carcinoma: an in-depth analysis of prognostically relevant gene signatures in hepatocellular carcinoma.

BACKGROUND: Nonalcoholic steatohepatitis (NASH) is a progressive manifestation of nonalcoholic fatty liver disease (NAFLD) that can lead to fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Despite the growing knowledge of NASH and HCC, the association between the two conditions remains to be fully explored. Bioinformatics has emerged as a valuable approach for identifying disease-specific feature genes, enabling advancements in disease prediction, prevention, and personalized treatment strategies. MATERIALS AND METHODS: In this study, we utilized CellChat, copy number karyotyping of aneuploid tumors (CopyKAT), consensus Non-negative Matrix factorization (cNMF), Gene set enrichment analysis (GSEA), Gene set variation analysis (GSVA), Monocle, spatial co-localization, single sample gene set enrichment analysis (ssGSEA), Slingshot, and the Scissor algorithm to analyze the cellular and immune landscape of NASH and HCC. Through the Scissor algorithm, we identified three cell types correlating with disease phenotypic features and subsequently developed a novel clinical prediction model using univariate, LASSO, and multifactor Cox regression. RESULTS: Our results revealed that macrophages are a significant pathological factor in the development of NASH and HCC and that the macrophage migration inhibitory factor (MIF) signaling pathway plays a crucial role in cellular crosstalk at the molecular level. We deduced three prognostic genes (YBX1, MED8, and KPNA2), demonstrating a strong diagnostic capability in both NASH and HCC. CONCLUSION: These findings shed light on the pathological mechanisms shared between NASH and HCC, providing valuable insights for the development of novel clinical strategies.

Ocular biomarkers of cognitive decline based on deep-learning retinal vessel segmentation.

BACKGROUND: The current literature shows a strong relationship between retinal neuronal and vascular alterations in dementia. The purpose of the study was to use NFN+ deep learning models to analyze retinal vessel characteristics for cognitive impairment (CI) recognition. METHODS: We included 908 participants from a community-based cohort followed for over 15 years (the prospective KaiLuan Study) who underwent brain magnetic resonance imaging (MRI) and fundus photography between 2021 and 2022. The cohort consisted of both cognitively healthy individuals (N = 417) and those with cognitive impairment (N = 491). We employed the NFN+ deep learning framework for retinal vessel segmentation and measurement. Associations between Retinal microvascular parameters (RMPs: central retinal arteriolar / venular equivalents, arteriole to venular ratio, fractal dimension) and CI were assessed by Pearson correlation. P < 0.05 was considered statistically significant. The correlation between the CI and RMPs were explored, then the correlation coefficients between CI and RMPs were analyzed. Random Forest nonlinear classification model was used to predict whether one having cognitive decline or not. The assessment criterion was the AUC value derived from the working characteristic curve. RESULTS: The fractal dimension (FD) and global vein width were significantly correlated with the CI (P < 0.05). Age (0.193), BMI (0.154), global vein width (0.106), retinal vessel FD (0.099), and CRAE (0.098) were the variables in this model that were ranked in order of feature importance. The AUC values of the model were 0.799. CONCLUSIONS: Establishment of a predictive model based on the extraction of vascular features from fundus images has a high recognizability and predictive power for cognitive function and can be used as a screening method for CI.

Comparison of Changes in Retinal Vascular Parameters and Density in Patients with Moyamoya Disease: A Retrospective Study.

INTRODUCTION: This study aimed to compare retinal vascular parameters and density in patients with moyamoya disease using the optical coherence tomography angiography. METHODS: This clinical trial totally enrolls 78 eyes from 39 participants, and all these patients with moyamoya disease (N = 13) are set as experimental group and participants with health who matched with age and gender are considered as the control group (N = 26). Then all these participants receive optical coherence tomography angiography detection. Participants' general data are collected and analyzed. Skeleton density (SD) value, vessel density (VD) value, fractal dimension (FD) value, vessel diameter index (VDI) value, foveal avascular zone (FAZ) value are analyzed. RESULTS: A total of 39 participants are included in this study. The SD value in the experimental group was significantly lower than that in control group (0.175 [0.166, 0.181] vs. 0.184 [0.175, 0.188], p = 0.017). Similarly, the VD value in the experimental group was significantly lower than that in the control group (0.333 [0.320, 0.350] vs. 0.354 [0.337, 0.364], p = 0.024). Additionally, the FD value in the experimental group was significantly lower than that in the control group (2.088 [2.083, 2.094] vs. 2.096 [2.090, 2.101], p = 0.022). As for the VDI and FAZ, VDI and FAZ values in the experimental group were lower than those in the control group, there was no significant difference in VDI and FAZ values between the two groups. CONCLUSIONS: Our study, using non-invasive and rapid OCTA imaging, confirmed decreased retinal vascular parameters and density in patients with moyamoya disease.

Advancing the application of the analytical renal pathology system in allograft IgA nephropathy patients.

BACKGROUND: The analytical renal pathology system (ARPS) based on convolutional neural networks has been used successfully in native IgA nephropathy (IgAN) patients. Considering the similarity of pathologic features, we aim to evaluate the performance of the ARPS in allograft IgAN patients and broaden its implementation. METHODS: Biopsy-proven allograft IgAN patients from two different centers were enrolled for internal and external validation. We implemented the ARPS to identify glomerular lesions and intrinsic glomerular cells, and then evaluated its performance. Consistency between the ARPS and pathologists was assessed using intraclass correlation coefficients. The association of digital pathological features with clinical and pathological data was measured. Kaplan-Meier survival curve and cox proportional hazards model were applied to investigate prognosis prediction. RESULTS: A total of 56 biopsy-proven allograft IgAN patients from the internal center and 17 biopsy-proven allograft IgAN patients from the external center were enrolled in this study. The ARPS was successfully applied to identify the glomerular lesions (F1-score, 0.696-0.959) and quantify intrinsic glomerular cells (F1-score, 0.888-0.968) in allograft IgAN patients rapidly and precisely. Furthermore, the mesangial hypercellularity score was positively correlated with all mesangial metrics provided by ARPS [Spearman's correlation coefficient (r), 0.439-0.472, and all p values < 0.001]. Besides, a higher allograft survival was noticed among patients in the high-level groups of the maximum and ratio of endothelial cells, as well as the maximum and density of podocytes. CONCLUSION: We propose that the ARPS could be implemented in future clinical practice with outstanding capability.

Surgical methods influence on the risk of anastomotic fistula after pancreaticoduodenectomy: a systematic review and network meta-analysis.

BACKGROUND: Pancreaticoduodenectomy is the first choice surgical intervention for the radical treatment of pancreatic tumors. However, an anastomotic fistula is a common complication after pancreaticoduodenectomy with a high mortality rate. With the development of minimally invasive surgery, open pancreaticoduodenectomy (OPD), laparoscopic pancreaticoduodenectomy (LPD), and robotic pancreaticoduodenectomy (RPD) are gaining interest. But the impact of these surgical methods on the risk of anastomosis has not been confirmed. Therefore, we aimed to integrate relevant clinical studies and explore the effects of these three surgical methods on the occurrence of anastomotic fistula after pancreaticoduodenectomy. METHODS: A systematic literature search was conducted for studies reporting the RPD, LPD, and OPD. Network meta-analysis of postoperative anastomotic fistula (Pancreatic fistula, biliary leakage, gastrointestinal fistula) was performed. RESULTS: Sixty-five studies including 10,026 patients were included in the network meta-analysis. The rank of risk probability of pancreatic fistula for RPD (0.00) was better than LPD (0.37) and OPD (0.62). Thus, the analysis suggests the rank of risk of the postoperative pancreatic fistula for RPD, LPD, and OPD. The rank of risk probability for biliary leakage was similar for RPD (0.15) and LPD (0.15), and both were better than OPD (0.68). CONCLUSIONS: This network meta-analysis provided ranking for three different types of pancreaticoduodenectomy. The RPD and LPD can effectively improve the quality of surgery and are safe as well as feasible for OPD.

A Lysosome-Targeting Self-Condensation Prodrug-Nanoplatform System for Addressing Drug Resistance of Cancer.

Lysosome-targeting self-assembling prodrugs had emerged as an attractive approach to overcome the acquisition of resistance to chemotherapeutics by inhibiting lysosomal sequestration. Taking advantage of lysosomal acidification induced intracellular hydrolytic condensation, we developed a lysosomal-targeting self-condensation prodrug-nanoplatform (LTSPN) system for overcoming lysosome-mediated drug resistance. Briefly, the designed hydroxycamptothecine (HCPT)-silane conjugates self-assembled into silane-based nanoparticles, which were taken up into lysosomes by tumor cells. Subsequently, the integrity of the lysosomal membrane was destructed because of the acid-triggered release of alcohol, wherein the nanoparticles self-condensed into silicon particles outside the lysosome through intracellular hydrolytic condensation. Significantly, the LTSPN system reduced the half-maximal inhibitory concentration (IC50) of HCPT by approximately 4 times. Furthermore, the LTSPN system realized improved control of large established tumors and reduced regrowth of residual tumors in several drug-resistant tumor models. Our findings suggested that target destructing the integrity of the lysosomal membrane may improve the therapeutic effects of chemotherapeutics, providing a potent treatment strategy for malignancies.

Nano Proteolysis Targeting Chimeras (PROTACs) with Anti-Hook Effect for Tumor Therapy.

Proteolysis targeting chimera (PROTAC) is an emerging pharmacological modality with innovated post-translational protein degradation capabilities. However, off-target induced unintended tissue effects and intrinsic "hook effect" hinder PROTAC biotechnology to be maturely developed. Herein, an intracellular fabricated nano proteolysis targeting chimeras (Nano-PROTACs) modality with a center-spoke degradation network for achieving efficient dose-dependent protein degradation in tumor is reported. The PROTAC precursors are triggered by higher GSH concentrations inside tumor cells, which subsequently in situ self-assemble into Nano-PROTACs through intermolecular hydrogen bond interactions. The fibrous Nano-PROTACs can form effective polynary complexes and E3 ligases degradation network with multi-binding sites, achieving dose-dependent protein degradation with "anti-hook effect". The generality and efficacy of Nano-PROTACs are validated by degrading variable protein of interest (POI) such as epidermal growth factor receptor (EGFR) and androgen receptor (AR) in a wide-range dose-dependent manner with a 95 % degradation rate and long-lasting potency up to 72 h in vitro. Significantly, Nano-PROTACs achieve in vivo dose-dependent protein degradation up to 79 % and tumor growth inhibition in A549 and LNCap xenograft mice models, respectively. Taking advantages of in situ self-assembly strategy, the Nano-PROTACs provide a generalizable platform to promote precise clinical translational application of PROTAC.

Optimized plasmonic performances and derivate applications of Au nanobipyramids.

Gold nanobipyramids (AuBPs) with narrow size distribution and high monodispersity have driven intensive attention because they display more advantageous plasmonic properties than gold nanorods (AuNRs). Applications of AuBPs based on tunable plasmonic properties and enhanced electromagnetic fields are being widely investigated in recent years. In this article, we focused on the preparation of well-defined AuBPs using the seed-mediated method, the plasmonic properties, and the exploration of AuBP-supported derivatives. The synergetic contributions of penta-twinned and appropriate growth environment could produce high-purity AuBPs. Systematic comparisons of plasmonic properties between AuBPs and AuNRs are illustrated. In addition, the well-defined AuBPs can be used as a template to synthesize multi-metallic nanostructures. The development of the epitaxial growth based on the AuBPs and corresponding applications are introduced. This study will provide a guide for the fabrication of composite nanostructures and advance their plasmonic applications.

Comparison of clinical effects between early follicular prolonged GnRH agonist protocol and GnRH antagonist protocol in 3310 cycles: a retrospective study.

BACKGROUND: It is the duty of doctors to choose a safe, simple, economic and effective controlled ovulation stimulation (COS) protocol for the patients. This study aims to compare the clinical effects of the early follicular prolonged GnRH agonist (EFPL) and GnRH antagonist (GnRH-Ant) protocols, hoping to provide some reference for clinicians when choosing COS program. METHODS: A retrospective study included 3310 ovum pick up cycles undergoing assisted reproductive technology during January 2019 to May 2022 in Renmin Hospital of Wuhan University. Propensity Score Matching (PSM) and multivariable logistic regression analysis were used to improve the comparability between the two protocols. Subgroups were divided according to age, body mass index (BMI) and anti-Mullerian hormone (AMH). The live birth rate (LBR) and clinical pregnancy rate (CPR) were the primary outcomes. RESULTS: After PSM, the endometrial thickness, fresh embryo transplantation rate, chemical pregnancy rate, CPR were significantly higher in EFPL group than that in GnRH-Ant group (P < 0.001). The E2, LH, P values on trigger day were significantly lower in EFPL group (P < 0.001). The cycle cancellation rate was significantly reduced in EFPL group (P < 0.001). However, the total amount of Gn and duration of Gn were significantly increased in the EFPL group (P < 0.001). Multivariable logistic regression analysis showed that the LBR was significantly higher in EFPL group after matching [OR (95%CI), 1.86 (1.13, 3.05), P = 0.02], especially for those with age < 35 years [OR (95%CI), 1.95 (1.14, 3.34), P = 0.02], BMI < 24 kg/m2 [OR (95%CI), 2.08 (1.14, 3.80), P = 0.02], AMH levels ≥ 4.5 ng/ml [OR (95%CI), 4.19 (1.53, 11.43), P < 0.01]. CONCLUSION: EFPL regimen is more suitable to elicit live birth for those young patients with BMI < 24 kg/m2 and AMH ≥ 4.5 ng/ml. However, for patients with decreased ovarian reserve or advanced age, EFPL regimen has no advantage over the GnRH-Ant regimen.

In Situ Self-Assembly of Bispecific Peptide for Cancer Immunotherapy.

Precise and effective manipulation of protein functions still faces tremendous challenges. Herein we report a programmable peptide molecule, consisted of targeting and self-assembly modules, that enables specific and highly efficient assembly governed by targeting receptor proteins. Upon binding to the cell membrane receptor, peptide conformation is somewhat stabilized along with decreased self-assembly activation energy, promoting peptide-protein complex oligomerization. We first design a GNNQQNY-RGD peptide (G7-RGD) to recognize integrin αV ß3 receptor for proof-of-concept study. In the presence of αV ß3 protein, the critical assembly concentration of free G7-RGD decreases from 525 to 33 µM and the resultant G7-RGD cluster drives integrin receptor oligomerization. Finally, a bispecific assembling peptide antiCD3-G7-RGD is rationally designed for cancer immunotherapy, which validates CD3 oligomerization and concomitant T cell activation, leading to T cell-mediated cancer cell cytolysis.

In Situ Constructed Nano-Drug Depots through Intracellular Hydrolytic Condensation for Chemotherapy of Bladder Cancer.

Intravesical administration of first-line drugs has shown failure in the treatment of bladder cancer owing to the poor tumor retention time of chemotherapeutics. Herein, we report an intracellular hydrolytic condensation (IHC) system to construct long-term retentive nano-drug depots in situ, wherein sustained drug release results in highly efficient suppression of bladder cancer. Briefly, the designed doxorubicin (Dox)-silane conjugates self-assemble into silane-based prodrug nanoparticles, which condense into silicon particle-based nano-drug depots inside tumor cells. Significantly, we demonstrate that the IHC system possesses highly potent antitumor efficacy, which leads to the regression and eradication of large established tumors and simultaneously extends the overall survival of air pouch bladder cancer mice compared with that of mice treated with Dox. The concept of intracellular hydrolytic condensation can be extended via conjugating other chemotherapeutic drugs, which may facilitate rational design of novel nanomedicines for augmentation of chemotherapy.

ATP-Dependent Protease ClpP and Its Subunits ClpA, ClpB, and ClpX Involved in the Field Bismerthiazol Resistance in Xanthomonas oryzae pv. oryzae.

Resistance of Xanthomonas oryzae pv. oryzae, which causes rice bacterial leaf blight, to bismerthiazol has been detected in China since the 1990s. The strains resistant to bismerthiazol on rice plants were more sensitive to bismerthiazol than wild-type (WT) strains in vitro. Here, quantitative PCR was applied to detect the fold expression of adenosine triphosphate-dependent proteases, ClpP and its subunits, which withstand stresses including bactericides in bismerthiazol-resistant strains and their parental susceptible WT strain (ZJ173). Results showed that the expression of ClpP and its subunits was higher in bismerthiazol-resistant strains than in ZJ173. They were upregulated during the early growth phase and downregulated during the middle growth phase in ZJ173 treated with bismerthiazol but did not change in the resistant strains. ClpP and its subunits were overexpressed in X. oryzae pv. oryzae in this study; the higher expression of these genes increased sensitivity in vitro and increased resistance in vivo to bismerthiazol. Bismerthiazol inhibition of exopolysaccharide (EPS) production, biofilm production, and motility was also lower in ClpP and its subunits' overexpression mutants of X. oryzae pv. oryzae. The deletion mutants of ClpP and its subunits in ZJ173 decreased pathogenicity, biofilm production, swimming ability, EPS production, and growth in low-nutrient environments. Moreover, ClpP and its subunits may act downstream of the histidine utilization pathway, which could be inhibited by bismerthiazol in X. oryzae pv. oryzae. Taken together, our results indicated that ClpP and its subunits of X. oryzae pv. oryzae influenced resistance to bismerthiazol.

CapsTM: capsule network for Chinese medical text matching.

BACKGROUND: Text Matching (TM) is a fundamental task of natural language processing widely used in many application systems such as information retrieval, automatic question answering, machine translation, dialogue system, reading comprehension, etc. In recent years, a large number of deep learning neural networks have been applied to TM, and have refreshed benchmarks of TM repeatedly. Among the deep learning neural networks, convolutional neural network (CNN) is one of the most popular networks, which suffers from difficulties in dealing with small samples and keeping relative structures of features. In this paper, we propose a novel deep learning architecture based on capsule network for TM, called CapsTM, where capsule network is a new type of neural network architecture proposed to address some of the short comings of CNN and shows great potential in many tasks. METHODS: CapsTM is a five-layer neural network, including an input layer, a representation layer, an aggregation layer, a capsule layer and a prediction layer. In CapsTM, two pieces of text are first individually converted into sequences of embeddings and are further transformed by a highway network in the input layer. Then, Bidirectional Long Short-Term Memory (BiLSTM) is used to represent each piece of text and attention-based interaction matrix is used to represent interactive information of the two pieces of text in the representation layer. Subsequently, the two kinds of representations are fused together by BiLSTM in the aggregation layer, and are further represented with capsules (vectors) in the capsule layer. Finally, the prediction layer is a connected network used for classification. CapsTM is an extension of ESIM by adding a capsule layer before the prediction layer. RESULTS: We construct a corpus of Chinese medical question matching, which contains 36,360 question pairs. This corpus is randomly split into three parts: a training set of 32,360 question pairs, a development set of 2000 question pairs and a test set of 2000 question pairs. On this corpus, we conduct a series of experiments to evaluate the proposed CapsTM and compare it with other state-of-the-art methods. CapsTM achieves the highest F-score of 0.8666. CONCLUSION: The experimental results demonstrate that CapsTM is effective for Chinese medical question matching and outperforms other state-of-the-art methods for comparison.

The ontogenesis of catabolic abilities and energy metabolism during endogenous nutritional periods of tongue sole, Cynoglossus semilaevis.

The ontogenesis of catabolic abilities and energy metabolism during endogenous nutritional periods of tongue sole was investigated. In this work, trypsin-like proteases (TRY) and triglyceride lipase (LIP) activities were measured to assess the capacities to catabolize proteins and lipids, respectively. Meanwhile, specific enzymes including pyruvate kinase (PK), glutamic oxalo acetic transaminase (GOT) and glutamate dehydrogenase (GDH), and hydroxyacyl CoA dehydrogenase (HOAD) as well as their ratios were assayed to evaluate the abilities to use energy substrates of carbohydrates, amino acids and fatty acids, respectively, for energy production. In addition, activities of citrate synthase (CS) and lactate dehydrogenase (LDH) and LDH/CS ratio were calculated to analyse the evolution of aerobic and anaerobic pathways. The study found that hatching occurred at 38.8 h after fertilization (HAF), mouth-opening day of eleuteroembryo appeared at 3 days after hatching (DAH), and the most rapid embryonic growth was observed in blastula stage before hatching. Enzymatic assay revealed that except for PK which appeared in cleavage stage onwards, all the other enzymes functioned after fertilization, preparing well for the coming embryogenesis of tongue sole. By comparing the average specific activity of enzyme in each period, it can be found that the highest value occurred at 3 DAH (for TRY, LIP, PK and LDH), 2 DAH (for GDH), fertilized egg (for GOT) and segmentation stage (for HOAD and CS), and the lowest value occurred at fertilized egg (for HOAD, CS and GDH), cleavage stage (for TRY, PK and LDH), gastrula stage (for GOT) and hatching day (for LIP). Based on the changeable patterns of metabolic enzymatic activities and ratios, it is concluded that metabolic capacities on three energy substrates displayed stage-specific traits, and the dominant energy substrate was fatty acids before segmentation stage, amino acids until hatching day and carbohydrate during eleuteroembryo period. As for energy production mode, aerobic pathway appeared to increase greater in fertilized egg and gastrula stage, whereas anaerobic pathway played a predominant role during cleavage stage, blastula stage, segmentation stage and eleuteroembryo stage. These results are valuable to elucidate the nutritional requirements of embryonic stages in tongue sole and to further understand their energy metabolic mechanisms.

Methodological implementation of mixed linear models in multi-locus genome-wide association studies.

The mixed linear model has been widely used in genome-wide association studies (GWAS), but its application to multi-locus GWAS analysis has not been explored and assessed. Here, we implemented a fast multi-locus random-SNP-effect EMMA (FASTmrEMMA) model for GWAS. The model is built on random single nucleotide polymorphism (SNP) effects and a new algorithm. This algorithm whitens the covariance matrix of the polygenic matrix K and environmental noise, and specifies the number of nonzero eigenvalues as one. The model first chooses all putative quantitative trait nucleotides (QTNs) with ≤ 0.005 P-values and then includes them in a multi-locus model for true QTN detection. Owing to the multi-locus feature, the Bonferroni correction is replaced by a less stringent selection criterion. Results from analyses of both simulated and real data showed that FASTmrEMMA is more powerful in QTN detection and model fit, has less bias in QTN effect estimation and requires a less running time than existing single- and multi-locus methods, such as empirical Bayes, settlement of mixed linear model under progressively exclusive relationship (SUPER), efficient mixed model association (EMMA), compressed MLM (CMLM) and enriched CMLM (ECMLM). FASTmrEMMA provides an alternative for multi-locus GWAS.

Dielectric function modelling and sensitivity forecast for Au-Ag alloy nanostructures.

Plasmonic metal nanostructures are promising for chemical and biological sensor applications due to their high spectral sensitivity, defined as the relative shift in resonance wavelength with respect to the refractive index changes of the surroundings. In this work, the refractive index sensitivity (RI sensitivity) of one kind of core-shell nanostructure was studied, in which the gold nanobipyramid (AuBP) core was sheltered by the Au-Ag alloy shell. We investigated the dependence of the RI sensitivity and the figure of merit (FOM) of the localized surface plasmon resonance (LSPR) on the geometry and the composition of the nanostructures. Theoretical consideration on the LSPR revealed that the RI sensitivity of the nanostructures is determined by the bulk plasma wavelength, dielectric properties of the alloy and the geometrical parameters. To quantitatively explore the dependence of the RI sensitivity on the metal compositions and the aspect ratios of the nanostructures, the frequency-related dielectric properties of the alloy were calculated using the Drude-critical points model (DCPM). Then the calculated dielectric data were applied in the finite difference time domain (FDTD) solutions to simulate the optical spectra of the alloy nanostructures with various Ag concentrations. Experimentally, a series of fabrication processes were also carried out for the growth of a homogeneous Au-Ag alloy nanoshell on the surface of AuBPs using a wet-chemical method. The measured RI sensitivities agree well with the values predicted from FDTD simulations, indicating the availability, credibility and feasibility of the modelled dielectric data of the alloy. The DCPM and FDTD simulations can be combined to calculate the dielectric properties and forecast the sensitivity properties of the Au-Ag alloyed nanostructures with varying concentrations.

Health information needs regarding diabetes mellitus in China: an internet-based analysis.

BACKGROUND: Today,. most people use the Internet to seek online health-related information from general public health-related websites and discussion groups. However, there are no Internet-based analyses of health information needs pertaining to diabetes in China until now. With the development of artificial intelligence,we can analyzed these online health-related information and provide references for health providers to improve their health service. METHODS: We have done a study of statistically analyzing the questions about diabetes collected from 39 health website, the number of which is 151,589. We have divided these questions into 9 categories using a convolutional neural network. RESULTS: The diabetes problems of consumer are presented as follows, diagnosis: 34.95%, treatment: 25.17%, lifestyle: 21.09%, complication: 8.00%, maternity-related:5.00%, prognosis: 2.59%, health provider choosing: 1.40%, prevention: 1.23%, others: 0.58%, The elderly are more concerned about the treatment and complications of diabetes, while the young are more concerned about the maternity-related and prognosis of diabetes. The diabetes drugs most frequently mentioned by consumers are insulin, metformin and Xiaoke pills, The most concerned complication is caidiovascular disease and diabetic eye disease. CONCLUSION: Diabetes health education should focus on how to prevent diabetes and the contents of health education should be different for differernt age groups;on diabetes treatment, the use of insulin and oral hypoglycemic drugs education should be strengthened.

Effective Fungal Spore Inactivation with an Environmentally Friendly Approach Based on Atmospheric Pressure Air Plasma.

Fungal contamination of surfaces is a global burden, posing a major environmental and public health challenge. A wide variety of antifungal chemical agents are available; however, the side effects of the use of these disinfectants often result in the generation of toxic residues raising major environmental concerns. Herein, atmospheric pressure air plasma generated by a surface barrier discharge (SBD) is presented as an innovative green chemical method for fungal inactivation, with the potential to become an effective replacement for conventional chemical disinfection agents, such as Virkon. Using Aspergillus flavus spores as a target organism, a comparison of plasma based decontamination techniques is reported, highlighting their respective efficiencies and uncovering their underpining inactivation pathways. Tests were performed using both direct gaseous plasma treatment and an indirect treatment using a plasma activated aqueous broth solution (PAB). Concentrations of gaseous ozone and nitrogen oxides were determined with Fourier-transform infrared spectroscopy (FTIR) and Optical emission spectroscopy (OES), whereas hydrogen peroxides, nitrites, nitrates, and pH were measured in PAB. It is demonstrated that direct exposure to the gaseous plasma effluent exhibited superior decontamination efficiency and eliminated spores more effectively than Virkon, a finding attributed to the production of a wide variety of reactive oxygen and nitrogen species within the plasma.