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Cisplatin is a particularly potent antineoplastic drug. However, its usefulness is restricted due to the induction of nephrotoxicity. More recent research has indicated that β-hydroxybutyrate (β-HB) protects against acute or chronic organ damage as an efficient healing agent. Nonetheless, the therapeutic mechanisms of β-HB in acute kidney damage caused by chemotherapeutic drugs remain unclear. Our study developed a model of cisplatin-induced acute kidney injury (AKI), which involved the administration of a ketogenic diet or β-HB. We analyzed blood urea nitrogen (BUN) and creatinine (Cr) levels in serum, and used western blotting and immunohistochemical staining to assess ferroptosis and the calcium/calmodulin-dependent kinase kinase 2 (Camkk2)/AMPK pathway. The mitochondrial morphology and function were examined. Additionally, we conducted in vivo and in vitro experiments using selective Camkk2 inhibitor or activator to investigate the protective mechanism of β-HB on cisplatin-induced AKI. Exogenous or endogenous β-HB effectively alleviated cisplatin-induced abnormally elevated levels of BUN and Cr and renal tubular necrosis in vivo. Additionally, β-HB reduced ferroptosis biomarkers and increased the levels of anti-ferroptosis biomarkers in the kidney. β-HB also improved mitochondrial morphology and function. Moreover, β-HB significantly attenuated cisplatin-induced cell ferroptosis and damage in vitro. Furthermore, western blotting and immunohistochemical staining indicated that β-HB may prevent kidney injury by regulating the Camkk2-AMPK pathway. The use of the Camkk2 inhibitor or activator verified the involvement of Camkk2 in the renal protection by β-HB. This study provided evidence of the protective effects of β-HB against cisplatin-induced nephrotoxicity and identified inhibited ferroptosis and Camkk2 as potential molecular mechanisms.

BackgroundTriphala, is a composite of three individual botanical drugs: Terminalia chebula, Terminalia bellirica, and Emblica officinalis. It exhibits properties such as heatclearing, anti-inflammatory, anti-fatigue, antioxidant, and antibacterial effects,making it extensively utilized in India and Tibet. It has been found to exhibitinhibitory effects on Helicobacter pylori (H. pylori); however, further comprehensive research is still needed to elucidate its specific antibacterial mechanism. The present study investigates the in vitro antibacterial activity and antibacterial mechanism of Triphala against H. pylori.MethodsOurs research investigates the in vitro inhibitory activity of Triphala on multiple standard and clinical strains using microdilution broth method, time-kill curve, time-bactericidal curve and scanning electron microscopy (SEM). Furthermore, the antibacterial mechanism of Triphala is further explored through experiments on urease activity, biofilm formation, anti-adhesion properties, virulence actor assays using RT-qPCR and Western Blotting techniques.ResultsThe research findings indicate that Triphala exhibits a minimum inhibitory concentration of 80–320 μg/mL against both standard and clinical strains of H. pylori. Triphala exerts its anti-H. pylori effect by perturbing the microstructure of H. pylori, downregulating adhesion-associated genes (alpA, alpB, babA), urease-related genes (ureA, ureB, ureE, ureF), and flagellar genes (flaA, flaB); inhibiting bacterial adhesion, biofilm formation, urease activity as well as CagA protein expression.DiscussionThese findings suggest that Triphala exerts inhibitory effects on H. pylori activity through multiple mechanisms, underscoring its potential as a new drug for the prevention and treatment of H. pylori infection.

BackgroundTerminalia chebula Retz, known as the King of Tibet, is considered a functional food in China, celebrated for its antioxidant, immune-modulating, antibacterial, and anti-inflammatory properties. Chebulinic acid, derived from aqueous extracts of Terminalia chebula Retz, is known for its anti-inflammatory properties. However, its potential as an anti-Helicobacter pylori (HP) agent has not been fully explored.MethodsHerein, we extracted the main compound from Terminalia chebula Retz using a semi-preparative liquid chromatography (LC) system and identified compound 5 as chebulinic acid through Ultra-high performance liquid chromatography-MS/MS (UPLC–MS/MS) and Nuclear Magnetic Resonance (NMR). To evaluate its role, we conducted minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assays, scanning electron microscope (SEM) imaging, inhibiting kinetics curves, urea fast test, cell counting kit-8 (CCK-8) assay, western blot analysis, griess reagent system, and molecular docking.ResultsOur results showed that chebulinic acid effectively inhibited the growth of the HP strain ATCC 700392, damaged the HP structure, and exhibited selective antimicrobial activity without affecting normal epithelial cells GES-1. Importantly, it suppressed the expression of Cytotoxin-associated gene A (Cag A) protein, a crucial factor in HP infection. Molecular docking analysis predicted a strong affinity (−9.7 kcal/mol) between chebulinic acid and Cag A protein.ConclusionOverall, our findings suggest that chebulinic acid acts as an anti-adhesive agent, disrupting the adhesion of HP to host cells, which is a critical step in HP infection. It also suppresses the Cag A protein. These results highlight the potential of chebulinic acid against HP infections.

Abstract The AI-based small molecule drug discovery has become a significant trend at the intersection of computer science and life sciences. In the pursuit of novel compounds, fragment-based drug discovery has emerged as a novel approach. The Generative Pre-trained Transformers (GPT) model has showcased remarkable prowess across various domains, rooted in its pre-training and representation learning of fundamental linguistic units. Analogous to natural language, molecular encoding, as a form of chemical language, necessitates fragmentation aligned with specific chemical logic for accurate molecular encoding. This review provides a comprehensive overview of the current state of the art in molecular fragmentation. We systematically summarize the approaches and applications of various molecular fragmentation techniques, with special emphasis on the characteristics and scope of applicability of each technique, and discuss their applications. We also provide an outlook on the current development trends of molecular fragmentation techniques, including some potential research directions and challenges.

BackgroundHelicobacter pylori (H. pylori) is thought to primarily colonize the human stomach and lead to various gastrointestinal disorders, such as gastritis and gastric cancer. Currently, main eradication treatment is triple or quadruple therapy centered on antibiotics. Due to antibiotic resistance, the eradication rate of H. pylori is decreasing gradually. Therefore, searching for anti-H. pylori drugs from herbal sources has become a strategy for the treatment. Our team proposed a Hezi Qingyou Formula (HZQYF), composed of Chebulae Fructus, Ficus hirta Vahl and Cloves, and studied its anti-H. pylori activity and mechanism.MethodsChemical components of HZQYF were studied using UHPLC–MS/MS and HPLC. Broth microdilution method and agar dilution method were used to evaluate HZQYF’s antibacterial activity. The effects of HZQYF on expression of adhesion genes (alpA, alpB, babA), urease genes (ureE, ureF), and flagellar genes (flaA, flaB) were explored using Reverse Transcription-quantitative Polymerase Chain Reaction (RT-qPCR) technology. Effects on morphology and permeability of the extracellular membrane were studied using scanning electron microscopy (SEM) and N-phenylnaphthalen-1-amine (NPN) uptake. Effect on urease activity was studied using a urease kinetics analysis in vitro. Immunofluorescence staining method was used to examine the effect on adhesion. Western blot was used to examine the effect on cagA protein.ResultsMinimum inhibitory concentration (MIC) values of the formula against H. pylori clinical strains and standard strains were 80–160 μg/mL, and minimum bactericidal concentration (MBC) values were 160–320 μg/mL. The formula could down-regulate the expression of adhesion genes (alpA, alpB, babA), urease genes (ureE, ureF) and flagellar genes (flaA, flaB), change the morphology of H. pylori, increase its extracellular membrane permeability, and decrease its urease activity.ConclusionPresent studies confirmed that HZQYF had promising in vitro anti-H. pylori activities and demonstrated its possible mechanism of action by down-regulating the bacterial adhesion, urease, and flagellar gene expression, which provided scientific bases for further clinical investigations.

Summary: Compound-protein interaction (CPI) affinity prediction plays an important role in reducing the cost and time of drug discovery. However, the interpretability of how fragments function in CPI is impacted by the fact that current methods ignore the affinity relationships between fragments of compounds and fragments of proteins in CPI modeling. This article introduces an improved Transformer called FOTF-CPI (a Fusion of Optimal Transport Fragments compound-protein interaction prediction model). We use an optimal transport-based fragmentation approach to improve the model’s understanding of compound and protein sequences. Additionally, a fused attention mechanism is employed, which combines the features of fragments to capture full affinity information. This fused attention redistributes higher attention scores to fragments with higher affinity. Experimental results show FOTF-CPI achieves an average 2% higher performance than other models on all three datasets. Furthermore, the visualization confirms the potential of FOTF-CPI for drug discovery applications.

Rosuvastatin calcium is a widely used 3-hydroxy-3-methylglutaryl coenzyme A-reductase inhibitor developed for the treatment of dyslipidemia. To establish a control strategy for the elemental impurities, a new digestion method combined with an inductively coupled plasma-mass spectrometer (ICP-MS) was developed and validated by our team to determine elements Cd, Pb, As, Hg, Co, V, and Ni in rosuvastatin calcium tablets, which digest the sample perfectly even in the presence of a large number of excipients, especially titanium dioxide. The measurement mode was collision cell mode with kinetic energy discrimination (KED). 209Bi+, 115In+, and 89Y+ were chosen as internal standard elements. The recoveries of the limit of quantitation (LOQ) ranged from 90.5% to 106.4%, concentrations of the abovementioned elements in LOQ were 0.25 µg·L−1, 0.25 µg·L−1, 0.75 µg·L−1, 1.5 µg·L−1, 2.5 µg·L−1, 5 µg·L−1, and 8 µg·L−1 , respectively, linear correlation coefficients were above 0.9997, the recoveries in accuracy item ranged from 91.8% to 103.6%, and relative standard deviations (RSDs) of recovery in precision were not more than 1.8%, reflecting a reliable method of high sensitivity, strong anti-interference capacity, and good precision, and that it was suitable for the determination of elemental impurities in drugs.

Acute kidney injury (AKI) induces significant energy metabolic reprogramming in renal tubular epithelial cells (TECs), thereby altering lipid, glucose, and amino acid metabolism. The changes in lipid metabolism encompass not only the downregulation of fatty acid oxidation (FAO) but also changes in cell membrane lipids and triglycerides metabolism. Regarding glucose metabolism, AKI leads to increased glycolysis, activation of the pentose phosphate pathway (PPP), inhibition of gluconeogenesis, and upregulation of the polyol pathway. Research indicates that inhibiting glycolysis, promoting the PPP, and blocking the polyol pathway exhibit a protective effect on AKI-affected kidneys. Additionally, changes in amino acid metabolism, including branched-chain amino acids, glutamine, arginine, and tryptophan, play an important role in AKI progression. These metabolic changes are closely related to the programmed cell death of renal TECs, involving autophagy, apoptosis, necroptosis, pyroptosis, and ferroptosis. Notably, abnormal intracellular lipid accumulation can impede autophagic clearance, further exacerbating lipid accumulation and compromising autophagic function, forming a vicious cycle. Recent studies have demonstrated the potential of ameliorating AKI-induced kidney damage through calorie and dietary restriction. Consequently, modifying the energy metabolism of renal TECs and dietary patterns may be an effective strategy for AKI treatment.

Acute Kidney Injury (AKI), a critical clinical syndrome, has been strongly linked to mitochondrial malfunction. Mitochondria, vital cellular organelles, play a key role in regulating cellular energy metabolism and ensuring cell survival. Impaired mitochondrial function in AKI leads to decreased energy generation, elevated oxidative stress, and the initiation of inflammatory cascades, resulting in renal tissue damage and functional impairment. Therefore, mitochondria have gained significant research attention as a potential therapeutic target for AKI. Mitochondrial dynamics, which encompass the adaptive shifts of mitochondria within cellular environments, exert significant influence on mitochondrial function. Modulating these dynamics, such as promoting mitochondrial fusion and inhibiting mitochondrial division, offers opportunities to mitigate renal injury in AKI. Consequently, elucidating the mechanisms underlying mitochondrial dynamics has gained considerable importance, providing valuable insights into mitochondrial regulation and facilitating the development of innovative therapeutic approaches for AKI. This comprehensive review aims to highlight the latest advancements in mitochondrial dynamics research, provide an exhaustive analysis of existing studies investigating the relationship between mitochondrial dynamics and acute injury, and shed light on their implications for AKI. The ultimate goal is to advance the development of more effective therapeutic interventions for managing AKI.

1,3,6-Trigalloylglucose is a natural compound that can be extracted from the aqueous extracts of ripe fruit of Terminalia chebula Retz, commonly known as “Haritaki”. The potential anti-Helicobacter pylori (HP) activity of this compound has not been extensively studied or confirmed in scientific research. This compound was isolated using a semi-preparative liquid chromatography (LC) system and identified through Ultra-high-performance liquid chromatography–MS/MS (UPLC-MS/MS) and Nuclear Magnetic Resonance (NMR). Its role was evaluated using Minimum inhibitory concentration (MIC) assay and minimum bactericidal concentration (MBC) assay, scanning electron microscope (SEM), inhibiting kinetics curves, urea fast test, Cell Counting Kit-8 (CCK-8) assay, Western blot, and Griess Reagent System. Results showed that this compound effectively inhibits the growth of HP strain ATCC 700392, damages the HP structure, and suppresses the Cytotoxin-associated gene A (Cag A) protein, a crucial factor in HP infection. Importantly, it exhibits selective antimicrobial activity without impacting normal epithelial cells GES-1. In vitro studies have revealed that 1,3,6-Trigalloylglucose acts as an anti-adhesive agent, disrupting the adhesion of HP to host cells, a critical step in HP infection. These findings underscore the potential of 1,3,6-Trigalloylglucose as a targeted therapeutic agent against HP infections.

Existing formats based on the simplified molecular input line entry system (SMILES) encoding and molecular graph structure are designed to encode the complete semantic and structural information of molecules. However, the physicochemical properties of molecules are complex, and a single encoding of molecular features from SMILES sequences or molecular graph structures cannot adequately represent molecular information. Aiming to address this problem, this study proposes a sequence graph cross-attention (SG-ATT) representation architecture for a molecular property prediction model to efficiently use domain knowledge to enhance molecular graph feature encoding and combine the features of molecular SMILES sequences. The SG-ATT fuses the two-dimensional molecular features so that the current model input molecular information contains molecular structure information and semantic information. The SG-ATT was tested on nine molecular property prediction tasks. Among them, the biggest SG-ATT model performance improvement was 4.5% on the BACE dataset, and the average model performance improvement was 1.83% on the full dataset. Additionally, specific model interpretability studies were conducted to showcase the performance of the SG-ATT model on different datasets. In-depth analysis was provided through case studies of in vitro validation. Finally, network tools for molecular property prediction were developed for the use of researchers.

Parecoxib sodium is a widely used parenteral cyclooxygenase 2 selective inhibitor to relieve acute postoperative pain following gynecologic laparotomy surgery. To ensure the quality of the drug, a detailed quality specification is indispensable. Nevertheless, it is unavoidable to introduce inorganic impurities during the drug preparation process and how to assess and control them matters. This study proposed an analytical procedure for the determination of elemental impurities (Cd, Pb, As, Hg, Co, V, Ni, Li, Sb, and Cu) in parecoxib sodium, where an easier and safer digestion protocol, graphite digestion, combined with an inductively coupled plasma-mass spectrometer (ICP-MS) was adopted when compared with microwave digestion. Moreover, the study also discussed whether should they be listed in specification to comply with ICH Q3D guidelines after test of process validation batches. Limit of quantitation (LOQ) of the above elemental impurities reached to 0.05, 0.125, 0.375, 0.075, 0.125, 0.25, 0.5, 6.25, 2.25 and 7.5 ppm, respectively, and recovery in accuracy item ranged from 90.2% to 129.9%, reflecting a sensitive and accurate method.

Sentiment analysis based on social media text is found to be essential for multiple applications such as project design, measuring customer satisfaction, and monitoring brand reputation. Deep learning models that automatically learn semantic and syntactic information have recently proved effective in sentiment analysis. Despite earlier studies’ good performance, these methods lack syntactic information to guide feature development for contextual semantic linkages in social media text. In this paper, we introduce an enhanced LSTM-based on dependency parsing and a graph convolutional network (DPG-LSTM) for sentiment analysis. Our research aims to investigate the importance of syntactic information in the task of social media emotional processing. To fully utilize the semantic information of social media, we adopt a hybrid attention mechanism that combines dependency parsing to capture semantic contextual information. The hybrid attention mechanism redistributes higher attention scores to words with higher dependencies generated by dependency parsing. To validate the performance of the DPG-LSTM from different perspectives, experiments have been conducted on three tweet sentiment classification datasets, sentiment140, airline reviews, and self-driving car reviews with 1,604,510 tweets. The experimental results show that the proposed DPG-LSTM model outperforms the state-of-the-art model by 2.1% recall scores, 1.4% precision scores, and 1.8% F1 scores on sentiment140.

Copper is a vital cofactor in various enzymes, plays a pivotal role in maintaining cell homeostasis. When copper metabolism is disordered and mitochondrial dysfunction is impaired, programmed cell death such as apoptosis, paraptosis, pyroptosis, ferroptosis, cuproptosis, autophagy and necroptosis can be induced. In this review, we focus on the metabolic mechanisms of copper. In addition, we discuss the mechanism by which copper induces various programmed cell deaths. Finally, this review examines copper’s involvement in prevalent kidney diseases such as acute kidney injury and chronic kidney disease. The findings indicate that the use of copper chelators or plant extracts can mitigate kidney damage by reducing copper accumulation, offering novel insights into the pathogenesis and treatment strategies for kidney diseases.

Objective: To investigate whether the combination of repetitive transcranial magnetic stimulation (rTMS) and auricular point pressure bean could effectively ameliorate postoperative affective disorder in elderly patients suffering from cerebral hemorrhage. Methods: From June 2020 to September 2023, 116 elderly patients with depression after cerebral hemorrhage, who underwent surgical procedures were divided into the exposure group and the control group. The division was determined based on whether received rTMS and traditional Chinese medicine auricular point pressure bean therapy. Hamilton anxiety scale (HAMA), Hamilton Depression scale (HAMD), National Institutes of Health Stroke scale (NIHSS), Montreal Cognitive Assessment scale (MoCA) and Mini Mental State examination scale (MMSE) were collected and compared between before intervention and after intervention. Results: In accordance with a 1 : 1 matching ratio, the patients in the study were paired using propensity score matching (PSM), with 53 patients in both the exposure group and the control group. There were no notable differences in baseline characteristics between the 2 groups (P > .05). Following the intervention, the HAMA score and the NIHSS score of the exposure group were markedly lower than those of the control group (P < .001). Additionally, theMoCA scores (P = .001) and MMSE scores (P < .001) in the exposure group were significantlyhigher. The difference score have a significant difference in HAMA score (P = .001), NIHSS score (P < .001), MoCA (P < .001) and MMSE scores (P < .001). Conclusion: The combination of rTMS therapy and auricular point pressure bean therapy in traditional Chinese medicine demonstrates can effectively relieve the anxiety level, postoperative emotional and cognitive disorders of elderly patients after intracerebral hemorrhage, and provide certain ideas and support for clinical treatment. [ABSTRACT FROM AUTHOR]

China has the largest elderly population in the world, while its overall population has been unprecedentedly growing for quite some time now. The aging population is particularly concerning in China where the 'family is traditionally responsible for taking care of their elders as there is no established, sustainable social security system' especially in rural areas. Worse still, the one child policy and the rapid urbanisation processes resulting in younger adults leaving rural areas for better jobs and lifestyles since the 1990s have put greater pressures on rural families who have fewer younger people to depend on for taking care of their elderlies. Against this background, there is an urgent need to build ground work for future research which can shed more light on social organisations for the rural elderly in China, giving particular attention to indigenous features in the Chinese context - a contribution this paper offers to make. [ABSTRACT FROM AUTHOR]

Although sustainable agriculture and food systems have appeared to start generating increasing scholarly and policy-maker interest since the 1950s (Pretty, 2008), the very idea creating some level of sustainability in agriculture can be traced back to ancient writings in China (Li, 2001). Despite scholarly and policy efforts, the growing population which in turn results in increasing demands for food and other agricultural products while minimising potentially negative impacts on earth and the environment has remained as a major challenge for this century (Godfray et al., 2010; Sanaullah et al. 2020). With the growing literature on agricultural ecosystems and sustainability in farming, and despite practitioners being an important of the community, there has been insufficient discussion on the practitioners' views grounded in experiences. Accordingly, this paper provides an account of case-based practitioner's experiences in China. [ABSTRACT FROM AUTHOR]