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Background: The vaccination status of post-stroke patients, who are at high risk of severe outcomes from Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a significant concern, yet it remains unclear. We aimed to explore the vaccination status, factors associated with vaccine hesitancy, and adverse effects after vaccination among post-stroke patients. Methods: This multi-center observational study enrolled hospitalized post-stroke patients from six Chinese hospitals (Oct 1, 2020 - Mar 31, 2021), examining vaccine uptake and self-reported reasons for vaccine hesitancy, utilizing logistic regression to investigate risk factors for vaccine hesitancy, and recording any adverse reactions post-vaccination. Results: Of the total 710 post-stroke patients included in the study, 430 (60.6%) had completed the recommended full-3 dose SARS-CoV-2 vaccination, with 176 (24.8%) remaining unvaccinated. The most common reasons for vaccine hesitancy were concerns about vaccine side effects (41.5%) and impaired mobility (33.9%). Logistic regression identified advanced age (aOR = 1.97, 95%CI: 1.36–2.85, P = 0.001), lower Barthel Index score (aOR = 0.88, 95%CI: 0.82–0.93, P = 0.018), higher Modified Rankin Scale score (aOR = 1.85, 95%CI: 1.32–2.56, P = 0.004), and poorer usual activity level of EuroQol 5-Dimension (aOR = 2.82, 95%CI: 1.51–5.28, P = 0.001) as independent risk factors for vaccine hesitancy. Approximately 14.8% reported minor adverse reactions, mainly pain at the injection site. Conclusion: We found that post-stroke patients have insufficient SARS-CoV-2 vaccination rates, with key risk factors for vaccine hesitancy including concerns about side effects, advanced age, and functional impairments. No severe adverse reactions were observed among the vaccinated population. [ABSTRACT FROM AUTHOR]

Background: Computed tomography (CT) plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease (COPD). This study aimed to explore the performance of CT-based whole lung radiomic in discriminating COPD patients and non-COPD patients. Methods: This retrospective study was performed on 2785 patients who underwent pulmonary function examination in 5 hospitals and were divided into non-COPD group and COPD group. The radiomic features of the whole lung volume were extracted. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied for feature selection and radiomic signature construction. A radiomic nomogram was established by combining the radiomic score and clinical factors. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the predictive performance of the radiomic nomogram in the training, internal validation, and independent external validation cohorts. Results: Eighteen radiomic features were collected from the whole lung volume to construct a radiomic model. The area under the curve (AUC) of the radiomic model in the training, internal, and independent external validation cohorts were 0.888 [95% confidence interval (CI) 0.869–0.906], 0.874 (95%CI 0.844–0.904) and 0.846 (95%CI 0.822–0.870), respectively. All were higher than the clinical model (AUC were 0.732, 0.714, and 0.777, respectively, P < 0.001). DCA demonstrated that the nomogram constructed by combining radiomic score, age, sex, height, and smoking status was superior to the clinical factor model. Conclusions: The intuitive nomogram constructed by CT-based whole-lung radiomic has shown good performance and high accuracy in identifying COPD in this multicenter study. [ABSTRACT FROM AUTHOR]

Background: The gut microbiota is a critical factor in the regulation of host health, but the relationship between the differential resistance of hosts to pathogens and the interaction of gut microbes is not yet clear. Herein, we investigated the potential correlation between the gut microbiota of piglets and their disease resistance using single-cell transcriptomics, 16S amplicon sequencing, metagenomics, and untargeted metabolomics. Results: Porcine epidemic diarrhea virus (PEDV) infection leads to significant changes in the gut microbiota of piglets. Notably, Landrace pigs lose their resistance quickly after being infected with PEDV, but transplanting the fecal microbiota of Min pigs to Landrace pigs alleviated the infection status. Macrogenomic and animal protection models identified Lactobacillus reuteri and Lactobacillus amylovorus in the gut microbiota as playing an anti-infective role. Moreover, metabolomic screening of the secondary bile acids' deoxycholic acid (DCA) and lithocholic acid (LCA) correlated significantly with Lactobacillus reuteri and Lactobacillus amylovorus, but only LCA exerted a protective function in the animal model. In addition, LCA supplementation altered the distribution of intestinal T-cell populations and resulted in significantly enriched CD8+ CTLs, and in vivo and in vitro experiments showed that LCA increased SLA-I expression in porcine intestinal epithelial cells via FXR receptors, thereby recruiting CD8+ CTLs to exert antiviral effects. Conclusions: Overall, our findings indicate that the diversity of gut microbiota influences the development of the disease, and manipulating Lactobacillus reuteri and Lactobacillus amylovorus, as well as LCA, represents a promising strategy to improve PEDV infection in piglets. EpMwHe2ikadzXiwzLUNV95 Video Abstract [ABSTRACT FROM AUTHOR]

The iron oxide nanoparticles (IONPs), possessing both magnetic behavior and semiconductor property, have been extensively used in multifunctional biomedical fields due to their biocompatible, biodegradable and low toxicity, such as anticancer, antibacterial, cell labelling activities. Nevertheless, there are few IONPs in clinical use at present. Some IONPs approved for clinical use have been withdrawn due to insufficient understanding of its biomedical applications. Therefore, a systematic summary of IONPs' preparation and biomedical applications is crucial for the next step of entering clinical practice from experimental stage. This review summarized the existing research in the past decade on the biological interaction of IONPs with animal/cells models, and their clinical applications in human. This review aims to provide cutting-edge knowledge involved with IONPs' biological effects in vivo and in vitro, and improve their smarter design and application in biomedical research and clinic trials. [ABSTRACT FROM AUTHOR]

This article discusses the correlation between iodine intake and thyroid diseases among naval pilots stationed at a coastal flight station in China. The study found that the urinary iodine concentrations of the pilots fell within the appropriate range, but there were significant differences among different occupational positions. The research also revealed that pilots undergoing flight training experienced higher levels of stress, which could lead to an increased demand for iodine. The study suggests that naval pilots in coastal areas should continue to consume iodized salt as a supplement and that monitoring urinary iodine concentration should be included in assessing their iodine nutritional status. [Extracted from the article]

Purpose: To develop and validate a nomogram based on 3D-PDU parameters and clinical characteristics to predict LNM and LVSI in early-stage cervical cancer preoperatively., Materials and Methods: A total of first diagnosis 138 patients with cervical cancer who had undergone 3D-PDU examination before radical hysterectomy plus lymph dissection between 2014 and 2019 were enrolled for this study. Multivariate logistic regression analyses were performed to analyze the 3D-PDU parameters and selected clinicopathologic features and develop a nomogram to predict the probability of LNM and LVSI in the early stage. ROC curve was used to evaluate model differentiation, calibration curve and Hosmer-Lemeshow test were used to evaluate calibration, and DCA was used to evaluate clinical practicability., Results: Menopause status, FIGO stage and VI were independent predictors of LNM. BMI and maximum tumor diameter were independent predictors of LVSI. The predicted AUC of the LNM and LSVI models were 0.845 (95%CI,0.765-0.926) and 0.714 (95%CI,0.615-0.813). Calibration curve and H-L test (LNM groups P = 0.478; LVSI P = 0.783) all showed that the predicted value of the model had a good fit with the actual observed value, and DCA indicated that the model had a good clinical net benefit., Conclusion: The proposed nomogram based on 3D-PDU parameters and clinical characteristics has been proposed to predict LNM and LVSI with high accuracy, demonstrating for the first time the potential of non-invasive prediction. The probability derived from this nomogram may have the potential to provide valuable guidance for physicians to develop clinical individualized treatment plans of FIGO patients with early cervical cancer., (© 2024. The Author(s).)

Background: Peutz-Jeghers syndrome (PJS) is a rare genetic disorder characterized by the development of pigmented spots, gastrointestinal polyps and increased susceptibility to cancers. Currently, most studies have investigated intestinal microbiota through fecal microbiota, and there are few reports about mucosa-associated microbiota. It remains valuable to search for the key intestinal microbiota or abnormal metabolic pathways linked to PJS., Aim: This study aimed to assess the structure and composition of mucosa-associated microbiota in patients with PJS and to explore the potential influence of intestinal microbiota disorders and metabolite changes on PJS., Methods: The bacterial composition was analyzed in 13 PJS patients and 12 controls using 16S rRNA gene sequencing (Illumina MiSeq) for bacteria. Differential analyses of the intestinal microbiota were performed from the phylum to species level. Liquid chromatography-tandem mass spectrometry (LC‒MS) was used to detect the differentially abundant metabolites of PJS patients and controls to identify different metabolites and metabolic biomarkers of small intestinal mucosa samples., Results: High-throughput sequencing confirmed the special characteristics and biodiversity of the mucosa microflora in patients with PJS. They had lower bacterial biodiversity than controls. The abundance of intestinal mucosal microflora was significantly lower than that of fecal microflora. In addition, lipid metabolism, amino acid metabolism, carbohydrate metabolism, nucleotide metabolism and other pathways were significantly different from those of controls, which were associated with the development of the enteric nervous system, intestinal inflammation and development of tumors., Conclusion: This is the first report on the mucosa-associated microbiota and metabolite profile of subjects with PJS, which may be meaningful to provide a structural basis for further research on intestinal microecology in PJS., (© 2024. The Author(s).)