Body mass index and weight loss as risk factors for poor outcomes in patients with idiopathic pulmonary fibrosis: a systematic review and meta-analysis.

OBJECTIVE: The association between nutritional status and prognosis of idiopathic pulmonary fibrosis (IPF) remains unclear. This systematic review and meta-analysis aimed to explore the effect of body mass index (BMI) and weight loss on the prognosis of IPF patients. METHODS: We accumulated studies on IPF, BMI, and weight loss from databases including PubMed, Embase, Web of science, Scopus, Ovid and Cochrane Library up to 4 August 2023. Using Cox proportional hazard regression model for subgroup analysis, hazard ratio (HR) and 95% confidence intervals (CI) for BMI in relation to mortality, acute exacerbation (AE), and hospitalization in IPF patients were calculated, and HR, odds ratio (OR), and 95% CI for weight loss corresponding to IPF patient mortality were assessed. Sensitivity analysis was peformed by eliminating every study one by one, and publication bias was judged by Egger's test and trim-and-fill method. RESULTS: A total of 34 eligible studies involving 18,343 IPF patients were included in the meta-analysis. The pooled results by univariate Cox regression analysis showed that baseline BMI was a predictive factor for IPF mortality (HR = 0.93, 95%CI = [0.91, 0.94]). Furthermore, the results by the multivariable regression model indicated that baseline BMI was an independent risk factor for predicting IPF mortality (HR = 0.94, 95%CI = [0.91, 0.98]). Weight loss was identified as a risk factor for IPF mortality (HR = 2.74, 95% CI = [2.12, 3.54]; OR = 4.51, 95% CI = [1.72, 11.82]) and there was no predictive value of BMI for acute exacerbation (HR = 1.00, 95% CI= [0.93, 1.07]) or hospitalization (HR = 0.95, 95% CI = [0.89, 1.02]). CONCLUSION: Low baseline BMI and weight loss in the course of IPF may indicate a high risk of mortality in patients with IPF, so it is meaningful to monitor and manage the nutritional status of IPF patients, and early intervention should be conducted for low BMI and weight loss.

Speciation, leachability, and phytoaccessibility of heavy metals during thermochemical liquefaction of contaminated peanut straw.

In this study, the speciation, leachability, phytoaccessibility, and environmental risks of heavy metals (Cd, Zn, and Cu) during liquefaction of contaminated peanut straw in ethanol at different temperatures (220, 260, 300, 340, and 380 °C) were comprehensively investigated. The results showed that elevated temperatures facilitated heavy metal accumulation in the biochar. The acid-soluble/exchangeable and reducible fraction percentages of heavy metals were substantially reduced in the biochar after liquefaction as the temperature increased, and the oxidizable fraction became the dominant heavy metal fraction, accounting for 44.14-78.67%. Furthermore, although an excessively high liquefaction temperature (380 °C) increased the residual fraction percentages of Zn and Cu, it was detrimental to Cd immobilization. The acid-soluble/exchangeable Cd in the contaminated peanut straw readily migrates to the bio-oil during liquefaction, with the highest concentration of 1.60 mg/kg at 260 °C liquefaction temperature, whereas Zn and Cu are predominantly bound to the unexchangeable fraction in the bio-oil. Liquefaction inhibited heavy metal leachability and phytoaccessibility in biochar, the lowest extraction rates of Cd, Zn, and Cu were 0.71%, 1.66% and 0.95% by diethylenetriamine pentaacetic acid, respectively. However, the leaching and extraction concentrations increased when the temperature was raised to 380 °C. Additionally, heavy metal risk was reduced from medium and high risk to no and low risk. In summary, liquefaction reduces heavy metal toxicity and the risks associated with contaminated peanut straw, and a temperature range of 300-340 °C for ethanol liquefaction can be considered optimal for stabilizing heavy metals.

Ultra-Thin Hydrogen-Organic-Framework (HOF) Nanosheets for Ultra-Stable Alkali Ions Battery Storage.

Organic frameworks-based batteries with excellent physicochemical stability and long-term high capacity will definitely reduce the cost, carbon emissions, and metal consumption and contamination. Here, an ultra-stable and ultra-thin perylene-dicyandiamide-based hydrogen organic framework (HOF) nanosheet (P-DCD) of ≈3.5 nm in thickness is developed. When applied in the cathode, the P-DCD exhibits exceptional long-term capacity retention for alkali-ion batteries (AIBs). Strikingly, for lithium-ion batteries (LIBs), at current of 2 A g-1, the large reversible capacity of 108 mA h g-1 shows no attenuation within 5 000 cycles. For sodium-ion batteries (SIBs), the related capacity retains 91.7% within 10 000 cycles compared to the initial state, significantly much more stable than conventional organic materials reported previously. Mechanism studies through ex situ and in situ experiments and theoretical density functional theory (DFT) calculations reveal that the impressive long-term performance retention originates from the large electron delocalization, fast ion diffusion, and physicochemical stability within the ultra-thin 2D P-DCD, featuring π-π and hydrogen bonding stacking, nitrogen-rich units, and low impedance. The advantageous features demonstrate that rationally designed stable and effective organic frameworks pave the way to utilizing complete organic materials for developing next-generation low-cost and highly stable energy storage batteries.

Decentralized Primal-Dual Proximal Operator Algorithm for Constrained Nonsmooth Composite Optimization Problems over Networks.

In this paper, we focus on the nonsmooth composite optimization problems over networks, which consist of a smooth term and a nonsmooth term. Both equality constraints and box constraints for the decision variables are also considered. Based on the multi-agent networks, the objective problems are split into a series of agents on which the problems can be solved in a decentralized manner. By establishing the Lagrange function of the problems, the first-order optimal condition is obtained in the primal-dual domain. Then, we propose a decentralized algorithm with the proximal operators. The proposed algorithm has uncoordinated stepsizes with respect to agents or edges, where no global parameters are involved. By constructing the compact form of the algorithm with operators, we complete the convergence analysis with the fixed-point theory. With the constrained quadratic programming problem, simulations verify the effectiveness of the proposed algorithm.

Protective effect of Astragalus membranaceus and Astragaloside IV in sepsis-induced acute kidney injury.

BACKGROUND: Acute kidney injury (AKI) is the most common target organ damage in sepsis. Sepsis-associated AKI (SA-AKI) may be characterized by damage to the renal tubular epithelium. In this study, the pharmacological mechanisms of Astragalus membranaceus and its active monomer Astragaloside IV (AS-IV) were predicted based on a network pharmacology approach and validated both in vitro and in vivo using the SA-AKI model. METHOD: We constructed an in vivo sepsis model using a mouse cecum ligation puncture (CLP) and HK-2 cells were treated with lipopolysaccharide (LPS) to mimic Gram (-) induced sepsis to assess the renal-protective efficacy of Astragalus membranaceus and AS-IV. RESULTS: The findings demonstrated that Astragalus membranaceus and AS-IV attenuate renal tubular injury in mice with polymicrobial sepsis, including vacuolization, loss of brush border, mitochondrial ultrastructural changes, and increased staining of kidney injury molecule-1 (KIM-1). AS-IV protected human proximal tubular epithelial (HK-2) cells against LPS induced cell viability loss. Both Astragalus membranaceus and AS-IV activated the PI3K/AKT pathway both in vitro and in vivo, as shown by Western blot and immunohistochemistry analysis. CONCLUSION: The findings demonstrate that Astragalus membranaceus and AS-IV protect against sepsis-induced kidney tubular injury by activating the PI3K/AKT pathway.

Design of a rapid diagnostic model for bladder compliance based on real-time intravesical pressure monitoring system.

OBJECTIVE: The diagnosis of bladder dysfunction for children depends on the confirmation of abnormal bladder shape and bladder compliance. The existing gold standard needs to conduct voiding cystourethrogram (VCUG) examination and urodynamic studies (UDS) examination on patients separately. To reduce the time and injury of children's inspection, we propose a novel method to judge the bladder compliance by measuring the intravesical pressure during the VCUG examination without extra UDS. METHODS: Our method consisted of four steps. We firstly developed a single-tube device that can measure, display, store, and transmit real-time pressure data. Secondly, we conducted clinical trials with the equipment on a cohort of 52 patients (including 32 negative and 20 positive cases). Thirdly, we preprocessed the data to eliminate noise and extracted features, then we used the least absolute shrinkage and selection operator (LASSO) to screen out important features. Finally, several machine learning methods were applied to classify and predict the bladder compliance level, including support vector machine (SVM), Random Forest, XGBoost, perceptron, logistic regression, and Naive Bayes, and the classification performance was evaluated. RESULTS: 73 features were extracted, including first-order and second-order time-domain features, wavelet features, and frequency domain features. 15 key features were selected and the model showed promising classification performance. The highest AUC value was 0.873 by the SVM algorithm, and the corresponding accuracy was 84%. CONCLUSION: We designed a system to quickly obtain the intravesical pressure during the VCUG test, and our classification model is competitive in judging patients' bladder compliance. SIGNIFICANCE: This could facilitate rapid auxiliary diagnosis of bladder disease based on real-time data. The promising result of classification is expected to provide doctors with a reliable basis in the auxiliary diagnosis of some bladder diseases prior to UDS.

Clemastine improves hypomyelination in rats with hypoxic-ischemic brain injury by reducing microglia-derived IL-1ß via P38 signaling pathway.

BACKGROUND: Microglia activation is associated with the development of hypoxic-ischemic brain injury (HIBI). Neuroinflammation suppression might be a suitable therapeutic target in hypoxic oligodendrocyte injury. This study aims to determine whether clemastine can improve hypomyelination by suppressing the activated microglia and promoting the maturation of oligodendrocyte progenitor cells (OPCs) in HIBI. METHODS: A bilateral common carotid artery occlusion (BCCAO) rat model that received continuous intraperitoneal injection (1 mg/kg) for 14 days was employed to elaborate the neuroprotection effects of clemastine. Interleukin-1ß (IL-1ß), nod-like receptor protein 3 (NLRP3), histamine H1 receptor, and OPC differentiation levels in the corpus callosum were measured. Primary cultured OPCs and co-culture of microglia and OPCs were used to explore the link between microglia activation and hypomyelination. Data were evaluated by one-way ANOVA with Fisher's protected least significant difference test. RESULTS: Clemastine treatment could reverse hypomyelination and restrain the upregulation of IL-1ß and NLRP3 in the corpus callosum of BCCAO rats. Primary cultured OPCs treated with IL-1ß showed failed maturation. However, clemastine could also reverse the OPC maturation arrest by activating the extracellular signal-regulated kinase (ERK) signaling pathway. Co-culture of microglia and OPCs with oxygen glucose deprivation treatment exhibited IL-1ß and NLRP3 upregulation. Clemastine could downregulate NLRP3 and IL-1ß and reverse hypomyelination by inhibiting the p38 signaling pathway. CONCLUSIONS: Clemastine could restrain microglia activation, improve axonal hypomyelination in BCCAO rats, and thus might be a viable strategy to inhibit hypomyelination in the corpus callosum of patients with HIBI.