Explore the vast range of titles available.

Andrographis paniculata, a medicinal plant widely found in Asia, contains andrographolide as its main active compound, known for its wide-ranging pharmacological effects, including anti-inflammatory, anti-cancer, anti-obesity, and anti-diabetic properties. Recent investigations have highlighted the anti-infective potential of andrographolide and its derivatives, with demonstrated antiviral, antibacterial, and antimalarial activities. This review summarizes progress in andrographolide’s anti-infective applications, focusing on its structure–activity relationship (SAR) and mechanisms of action. Researchers have used semi-synthetic methods, such as esterification, oxidation, Michael addition, salification, and hybrid design, to enhance andrographolide’s physicochemical properties and biological activity. These derivatives show potent antiviral activity against RNA and DNA viruses, antibacterial activity against Gram-positive and Gram-negative bacteria, antifungal effects, and antiparasitic activity against Plasmodium spp. and Leishmania spp. Nevertheless, poor solubility and limited bioavailability still hinder their clinical translation. Strategies such as nano delivery systems and β-cyclodextrin complexes are discussed to improve bioavailability. Although andrographolide itself has not received regulatory approval as a stand-alone drug, several andrographolide-containing preparations have been clinically used in certain countries. Overall, this review brings together evidence on antiviral, antibacterial, antifungal, and antiparasitic activities, linking them with structure–activity trends and pharmacokinetic insights, thereby providing a consolidated foundation for future development and clinical translation.

The efficiency and reproducibility of perovskite solar cells (PSCs) are significantly influenced by the purity of lead iodide (PbI2) in the raw materials used. Pb(OH)I has been identified as the primary impurity generated from PbI2 in water-based synthesis. Consequently, a comprehensive investigation into the impact of Pb(OH)I impurities on film and device performance is essential. In this study, PbI2, with varying stoichiometries, was synthesized to examine the effects of different Pb(OH)I levels on perovskite device performance. The characterization results revealed that even trace amounts of Pb(OH)I impede the formation of precursor prenucleation clusters. These impurities also increase the energy barrier of the α-phase and facilitate the transition of the intermediate phase to the δ-phase. These effects result in poor perovskite film morphology and sub-optimal photovoltaic device performance. To address these issues, a cost-effective method for preparing high-stoichiometry PbI2 was developed. The formation of Pb(OH)I was effectively inhibited through several strategies: adjusting solution pH and temperature, modifying material addition order, simplifying the precipitation–recrystallization process, and introducing H3PO2 as an additive. These modifications enabled the one-step synthesis of high-purity PbI2. PSCs prepared using this newly synthesized high-stoichiometry PbI2 demonstrated photovoltaic performance comparable to those fabricated with commercial PbI2 (purity ≥ 99.999%). Our novel method offers a cost-effective alternative for synthesizing high-stoichiometry PbI2, thereby providing a viable option for the production of high-performance PSCs.

HighlightsThree key processes in carbon dioxide reduction reaction (CO2RR) for ethylene generation were discussed, including CO2 adsorption/activation, *CO intermediates formation, and C-C coupling.The preferable mechanism for ethylene over C1 and other C2 products reaction pathways.Engineering strategies of Cu-based catalysts for CO2RR-ethylene.Electrochemical carbon dioxide reduction reaction (CO2RR) provides a promising way to convert CO2 to chemicals. The multicarbon (C2+) products, especially ethylene, are of great interest due to their versatile industrial applications. However, selectively reducing CO2 to ethylene is still challenging as the additional energy required for the C–C coupling step results in large overpotential and many competing products. Nonetheless, mechanistic understanding of the key steps and preferred reaction pathways/conditions, as well as rational design of novel catalysts for ethylene production have been regarded as promising approaches to achieving the highly efficient and selective CO2RR. In this review, we first illustrate the key steps for CO2RR to ethylene (e.g., CO2 adsorption/activation, formation of *CO intermediate, C–C coupling step), offering mechanistic understanding of CO2RR conversion to ethylene. Then the alternative reaction pathways and conditions for the formation of ethylene and competitive products (C1 and other C2+ products) are investigated, guiding the further design and development of preferred conditions for ethylene generation. Engineering strategies of Cu-based catalysts for CO2RR-ethylene are further summarized, and the correlations of reaction mechanism/pathways, engineering strategies and selectivity are elaborated. Finally, major challenges and perspectives in the research area of CO2RR are proposed for future development and practical applications.

Running exercise has been shown to relieve symptoms of depression, but the mechanisms underlying the antidepressant effects are unclear. Microglia and concomitant dysregulated neuroinflammation play a pivotal role in the pathogenesis of depression. However, the effects of running exercise on hippocampal neuroinflammation and the number and activation of microglia in depression have not been studied. In this study, rats were subjected to chronic unpredictable stress (CUS) for 5 weeks followed by treadmill running for 6 weeks. The depressive-like symptoms of the rats were assessed with a sucrose preference test (SPT). Immunohistochemistry and stereology were performed to quantify the total number of ionized calcium-binding adapter molecule 1 (Iba1)+ microglia, and immunofluorescence was used to quantify the density of Iba1+/cluster of differentiation 68 (CD68)+ in subregions of the hippocampus. The levels of proinflammatory cytokines in the hippocampus were measured by qRT-PCR and ELISA. The results showed that running exercise reversed the decreased sucrose preference of rats with CUS-induced depression. In addition, CUS increased the number of hippocampal microglia and microglial activation in rats, but running exercise attenuated the CUS-induced increases in the number of microglia in the hippocampus and microglial activation in the dentate gyrus (DG) of the hippocampus. Furthermore, CUS significantly increased the hippocampal levels of inflammatory factors, and the increases in inflammatory factors in the hippocampus were suppressed by running exercise. These results suggest that the antidepressant effects of exercise may be mediated by reducing the number of microglia and inhibiting microglial activation and neuroinflammation in the hippocampus.

Linguistic expressions of respectful terms are shaped by social status. Previous studies have shown respectful term usage affects online language processing. This study investigates its impact on semantic integration through three self-pace reading experiments, manipulating Respect Consistency (Respect vs. Disrespect) and Semantic Consistency (Semantic Consistent vs. Semantic Inconsistent). In Experiment 1, disrespect was manipulated by using the plain form of pronouns instead of the respectful form when addressing individuals of higher social status. The results showed longer reading times for semantically inconsistent sentences compared to consistent ones, reflecting the classic semantic integration effect. Nevertheless, this effect was only detected when respectful pronouns were employed. For Experiments 2 and 3, disrespect was operationalized by directly addressing individuals of higher social status by their personal names. A comparable interaction to that in Experiment 1 was identified solely in Experiment 3, which involved an appropriateness judgment task. In contrast, no such interaction was observed in Experiment 2, which involved a reading comprehension task. These results indicated that both disrespectful pronouns and addressing individuals by their personal names hinder semantic integration, but through different mechanisms. These findings provide important insights into the role of respectful term usage on semantic integration during discourse comprehension.

Recent studies have demonstrated that multiple early-onset diseases have shared risk genes, based on findings from de novo mutations (DNMs). Therefore, we may leverage information from one trait to improve statistical power to identify genes for another trait. However, there are few methods that can jointly analyze DNMs from multiple traits. In this study, we develop a framework called M-DATA ( M ulti-trait framework for De novo mutation A ssociation T est with A nnotations) to increase the statistical power of association analysis by integrating data from multiple correlated traits and their functional annotations. Using the number of DNMs from multiple diseases, we develop a method based on an Expectation-Maximization algorithm to both infer the degree of association between two diseases as well as to estimate the gene association probability for each disease. We apply our method to a case study of jointly analyzing data from congenital heart disease (CHD) and autism. Our method was able to identify 23 genes for CHD from joint analysis, including 12 novel genes, which is substantially more than single-trait analysis, leading to novel insights into CHD disease etiology.

Uncovering environmental factors interacting with genetic factors to influence complex traits is important in genetic epidemiology and disease etiology. We introduce BiVariate Linkage-Disequilibrium Eigenvalue Regression for Gene-Environment interactions (BV-LDER-GE), a statistical method that detects the overall contributions of G × E interactions in the genome using summary statistics of complex traits. In comparison to existing methods which either ignore correlations with additive effects or use partial information of linkage disequilibrium (LD), BV-LDER-GE harnesses correlations with additive genetic effects and full LD information to enhance the statistical power to detect genome-scale G × E interactions.

De novo variants (DNVs) with deleterious effects have proved informative in identifying risk genes for early-onset diseases such as congenital heart disease (CHD). A number of statistical methods have been proposed for family-based studies or case/control studies to identify risk genes by screening genes with more DNVs than expected by chance in Whole Exome Sequencing (WES) studies. However, the statistical power is still limited for cohorts with thousands of subjects. Under the hypothesis that connected genes in protein-protein interaction (PPI) networks are more likely to share similar disease association status, we developed a Markov Random Field model that can leverage information from publicly available PPI databases to increase power in identifying risk genes. We identified 46 candidate genes with at least 1 DNV in the CHD study cohort, including 18 known human CHD genes and 35 highly expressed genes in mouse developing heart. Our results may shed new insight on the shared protein functionality among risk genes for CHD.

Running exercise has been shown to alleviate depressive symptoms, but the mechanism of its antidepressant effect is still unclear. Astrocytes are the predominant cell type in the brain and perform key functions vital to central nervous system (CNS) physiology. Mounting evidence suggests that changes in astrocyte number in the hippocampus are closely associated with depression. However, the effects of running exercise on astrocytes in the hippocampus of depression have not been investigated. Here, adult male rats were subjected to chronic unpredictable stress (CUS) for 5 weeks followed by treadmill running for 6 weeks. The sucrose preference test (SPT) was used to assess anhedonia of rats. Then, immunohistochemistry and modern stereological methods were used to precisely quantify the total number of glial fibrillary acidic protein (GFAP)+ astrocytes in each hippocampal subregion, and immunofluorescence was used to quantify the density of bromodeoxyuridine (BrdU)+ and GFAP+ cells in each hippocampal subregion. We found that running exercise alleviated CUS-induced deficit in sucrose preference and hippocampal volume decline, and that CUS intervention significantly reduced the number of GFAP+ cells and the density of BrdU+/GFAP+ cells in the hippocampal CA1 region and dentate gyrus (DG), while 6 weeks of running exercise reversed these decreases. These results further confirmed that running exercise alleviates depressive symptoms and protects hippocampal astrocytes in depressed rats. These findings suggested that the positive effects of running exercise on astrocytes and the generation of new astrocytes in the hippocampus might be important structural bases for the antidepressant effects of running exercise.

Running exercise was shown to have a positive effect on depressive-like symptoms in many studies, but the underlying mechanism of running exercise in the treatment of depression has not been determined. Parvalbumin-positive interneurons (PV+ interneurons), a main subtype of GABA neurons, were shown to be decreased in the brain during the depression. PGC-1α, a molecule that is strongly related to running exercise, was shown to regulate PV+ interneurons. In the present study, we found that running exercise increased the expression of PGC-1α in the hippocampus of depressed mice. Adult male mice with PGC-1α gene silencing in the hippocampus ran on a treadmill for 4 weeks. Then, depression-like behavior was evaluated by the behavioral tests, and the PV+ interneurons in the hippocampus were investigated. We found that running exercise could not improve depressive-like symptoms or increase the gene expression of PV because of the lack of PGC-1α in the hippocampus. Moreover, a lack of PGC-1α in the hippocampus decreased the number and activity of PV+ interneurons in the CA3 subfield of the hippocampus, and running exercise could not reverse the pathological changes because of the lack of PGC-1α. The present study demonstrated that running exercise regulates PV+ interneurons through PGC-1α in the hippocampus of mice to reverse depressive-like behaviors. These data indicated that hippocampal PGC-1α-mediated positive effects on parvalbumin interneurons are required for the antidepressant actions of running exercise. Our results will help elucidate the antidepressant mechanism of running exercise and identify new targets for antidepressant treatment.