Nutritional status in patients with active pulmonary tuberculosis and new nutritional risk screening model for active tuberculosis: a national, multicenter, cross-sectional study in China.

Background: Tuberculosis (TB) remains a significant challenge for public health and is closely associated with malnutrition; however, few studies have attempted to screen malnutrition among TB patients. The study aimed to evaluate the nutrition status and build a new nutritional screening model for active TB. Methods: A retrospective, multicenter, large cross-sectional study was conducted in China from 1 January 2020 to 31 December 2021. All included patients diagnosed with active pulmonary TB (PTB) were evaluated both by Nutrition Risk Screening 2002 (NRS 2002) and Global Leadership Initiative on Malnutrition (GLIM) criteria. Univariate and multivariate analyses were conducted to screen the risk factors associated with malnutrition, and a new screening risk model, mainly for TB patients, was constructed. Results: A total of 14,941 cases meeting the inclusion criteria were entered into the final analysis. The malnutrition risk rate among PTB patients in China was 55.86% and 42.70%, according to the NRS 2002 and GLIM, respectively. The inconsistency rate between the two methods was 24.77%. A total of 11 clinical factors, including elderly, low body mass index (BMI), decreased lymphocyte cells, taking immunosuppressive agents, co-pleural TB, diabetes mellitus (DM), human immunodeficiency virus (HIV), severe pneumonia, decreased food intake within a week, weight loss and dialysis were identified as independent risk factors of malnutrition based on multivariate analyses. A new nutritional risk screening model was constructed for TB patients with a diagnostic sensitivity of 97.6% and specificity of 93.1%. Conclusions: Active TB patients have severe malnutrition status according to screening by the NRS 2002 and GLIM criteria. The new screening model is recommended for PTB patients as it is more closely tailored to the characteristics of TB.

Determination of in vivo biological activities of Dodonaea viscosa flowers against CCL4 toxicity in albino mice with bioactive compound detection.

Dodonaea viscosa L.Jacq. is an evergreen shrub and native to Asia, Africa, and Australia. It has been used as traditional medicine in different countries. The foremost objective of the current study was to discover the protective potential of D. viscosa flowers Methanol (DVM) and Chloroform (DVC) extracts against CCL4 induced toxicity in mice. This study was intended to identify phytochemicals through HPLC, GCMS, and FT-IR, as well as in vitro antioxidant and in vitro anti-tuberculosis activity. Our comprehensive findings indicate that Dodonaea viscosa is valuable and widespread herbal medicine through therapeutic potentials for curing various ailments. Dodonaeaviscosa flowersare found to have a protective effect against oxidative stress produced by CCL4 in the liver, kidney, and spleen. The intake of DV extracts restored the level of hepatic enzymes (ALP, AST ALT, and Direct bilirubin), hematological parameters (RBCs, WBCs, and Platelets), total protein, and liver antioxidant enzymes (SOD, GPx, and CAT) after a decline in levels by CCL4. Histopathological results discovered the defensive effect of 300 mg/kg of DVM extract against CCL4 induced damage, thus having an improved protective effect compared to DVC and control. As a result of metabolite screening, the total flavonoids and total phenolics were present in abundance. A phytochemical investigation by HPLC identified gallic acid, epicatechin, cumeric acid, flavonoids, while GCMS estimated oleic acid (Octadecenoic acid) (C18H34O2), Stearic acid (C18H36O2), Ricinoleic acid (C18H34O3), and Cedrol (C15H26O). DVM extract exhibited resistance against in vitro Mycobacterium tuberculosis strains. So this study proposed that the protective effect of DV against oxidative damage induced in the liver, kidney, and spleen can be correlated to the antioxidant compounds.

Global transmission dynamic of SIR model in the time of SARS-CoV-2.

This current work studies a new mathematical model for SARS-CoV-2. We show how immigration, protection, death rate, exposure, cure rate and interaction of infected people with healthy people affect the population. Our model is SIR model, which has three classes including susceptible, infected and recovered respectively. Here, we find the basic reproduction number and local stability through jacobean matrix. Lyapunvo function theory is used to calculate the global stability for the problem under investigation. Also a nonstandard finite difference sachem (NSFDS) is used to simulate the results.