Forensic toxicological studies of acute glufosinate poisoning: A case series.

Glufosinate is a widely and increasingly used non-selective, broad-spectrum herbicide. Although cases of glufosinate poisoning are frequently reported, they are rarely documented in forensic case reports, particularly in fatal instances. The present study examined six cases of glufosinate poisoning, including a fatal case involving a 25-year-old female found deceased by the roadside, with an empty 1000 mL bottle labeled "glufosinate" by her side. Biological specimens such as plasma or cardiac blood, gastric contents, and liver tissues were collected for quantitative analysis of glufosinate levels using LC-MS/MS. In five cases of acute glufosinate poisoning, glufosinate plasma concentrations ranged from 0.62 to 3.92 µg/mL. In the fatal case, the concentrations of glufosinate in cardiac blood, gastric contents, and liver tissues were 8.41 µg/mL, 31.25 µg/mL, and 66.1 µg/g, respectively. The pathological autopsy concluded that the cause of death was acute cardio-respiratory failure due to glufosinate poisoning, characterized by multi-organ congestion without specific pathological findings. The toxicological data provided in this study aim to serve as a critical reference for future clinical treatment and forensic validation of glufosinate poisoning-related deaths.

RemixFormer++: A Multi-modal Transformer Model for Precision Skin Tumor Differential Diagnosis with Memory-efficient Attention.

Diagnosing malignant skin tumors accurately at an early stage can be challenging due to ambiguous and even confusing visual characteristics displayed by various categories of skin tumors. To improve diagnosis precision, all available clinical data from multiple sources, particularly clinical images, dermoscopy images, and medical history, could be considered. Aligning with clinical practice, we propose a novel Transformer model, named Remix-Former++ that consists of a clinical image branch, a dermoscopy image branch, and a metadata branch. Given the unique characteristics inherent in clinical and dermoscopy images, specialized attention strategies are adopted for each type. Clinical images are processed through a top-down architecture, capturing both localized lesion details and global contextual information. Conversely, dermoscopy images undergo a bottom-up processing with two-level hierarchical encoders, designed to pinpoint fine-grained structural and textural features. A dedicated metadata branch seamlessly integrates non-visual information by encoding relevant patient data. Fusing features from three branches substantially boosts disease classification accuracy. RemixFormer++ demonstrates exceptional performance on four single-modality datasets (PAD-UFES-20, ISIC 2017/2018/2019). Compared with the previous best method using a public multi-modal Derm7pt dataset, we achieved an absolute 5.3% increase in averaged F1 and 1.2% in accuracy for the classification of five skin tumors. Furthermore, using a large-scale in-house dataset of 10,351 patients with the twelve most common skin tumors, our method obtained an overall classification accuracy of 92.6%. These promising results, on par or better with the performance of 191 dermatologists through a comprehensive reader study, evidently imply the potential clinical usability of our method.

Comparative Evaluation of LLMs in Clinical Oncology.

BACKGROUND: As artificial intelligence (AI) tools become widely accessible, more patients and medical professionals will turn to them for medical information. Large language models (LLMs), a subset of AI, excel in natural language processing tasks and hold considerable promise for clinical use. Fields such as oncology, in which clinical decisions are highly dependent on a continuous influx of new clinical trial data and evolving guidelines, stand to gain immensely from such advancements. It is therefore of critical importance to benchmark these models and describe their performance characteristics to guide their safe application to clinical oncology. Accordingly, the primary objectives of this work were to conduct comprehensive evaluations of LLMs in the field of oncology and to identify and characterize strategies that medical professionals can use to bolster their confidence in a model's response. METHODS: This study tested five publicly available LLMs (LLaMA 1, PaLM 2, Claude-v1, generative pretrained transformer 3.5 [GPT-3.5], and GPT-4) on a comprehensive battery of 2044 oncology questions, including topics from medical oncology, surgical oncology, radiation oncology, medical statistics, medical physics, and cancer biology. Model prompts were presented independently of each other, and each prompt was repeated three times to assess output consistency. For each response, models were instructed to provide a self-appraised confidence score (from 1 to 4). Model performance was also evaluated against a novel validation set comprising 50 oncology questions curated to eliminate any risk of overlap with the data used to train the LLMs. RESULTS: There was significant heterogeneity in performance between models (analysis of variance, P<0.001). Relative to a human benchmark (2013 and 2014 examination results), GPT-4 was the only model to perform above the 50th percentile. Overall, model performance varied as a function of subject area across all models, with worse performance observed in clinical oncology subcategories compared with foundational topics (medical statistics, medical physics, and cancer biology). Within the clinical oncology subdomain, worse performance was observed in female-predominant malignancies. A combination of model selection, prompt repetition, and confidence self-appraisal allowed for the identification of high-performing subgroups of questions with observed accuracies of 81.7 and 81.1% in the Claude-v1 and GPT-4 models, respectively. Evaluation of the novel validation question set produced similar trends in model performance while also highlighting improved performance in newer, centrally hosted models (GPT-4 Turbo and Gemini 1.0 Ultra) and local models (Mixtral 8×7B and LLaMA 2). CONCLUSIONS: Of the models tested on a standardized set of oncology questions, GPT-4 was observed to have the highest performance. Although this performance is impressive, all LLMs continue to have clinically significant error rates, including examples of overconfidence and consistent inaccuracies. Given the enthusiasm to integrate these new implementations of AI into clinical practice, continued standardized evaluations of the strengths and limitations of these products will be critical to guide both patients and medical professionals. (Funded by the National Institutes of Health Clinical Center for Research and the Intramural Research Program of the National Institutes of Health; Z99 CA999999.).

Hyaluronic acid-coated porphyrin nanoplatform with oxygen sustained supplying and glutathione depletion for enhancing photodynamic/ion/chemo synergistic cancer treatment.

Hypoxia and high concentration of glutathione (GSH) in tumor seriously hinder the role of reactive oxygen species (ROS) and oxygen-dependence strategy in tumor treatment. In this work, a self-generating oxygen and self-consuming GSH hyaluronic acid (HA)-coated porphyrin nanoplatform (TAPPP@CaO2/Pt(IV)/HA) is established for enhancing photodynamic/ion/chemo targeting synergistic therapy of tumor. During the efforts of ROS production by nanosystems, a GSH consuming strategy is implemented for augmenting ROS-induced oxidative damage for synergetic cancer therapy. CaO2 in the nanosystems is decomposed into O2 and H2O2 in an acidic environment, which alleviates hypoxia and enhances the photodynamic therapy (PDT) effect. Calcium overload causes mitochondria dysfunction and induces apoptosis. Pt (IV) reacts with GSH to produce Pt (II) for chemotherapy and reduce the concentration of GSH, protecting ROS from scavenging for augmenting ROS-induced oxidative damage. In vitro and in vivo results demonstrated the self-generating oxygen and self-consuming GSH strategy can enhance ROS-dependent PDT coupled with ion/chemo synergistic therapy. The proposed strategy not only solves the long-term problem that hypoxia limits therapeutic effect of PDT, but also ameliorates the highly reducing environment of tumors. Thus the preparation of TAPPP@CaO2/Pt(IV)/HA provided a novel strategy for the effective combined therapy of cancers.

Gut microbiota causally affects drug-induced liver injury via plasma metabolites: a Mendelian randomization study.

Background: The gut microbiota and plasma metabolites play important roles in the progression of drug-induced liver injury (DILI). We investigated the causal associations between the gut microbiota, plasma metabolome, and DILI. Methods: The summary data for gut microbiota (n = 18,340), plasma metabolome (n = 8,299), and DILI (n = 366,838) were obtained from the large genome-wide association studies. A two-sample Mendelian randomization was performed to explore the associations between the gut microbiota, plasma metabolome, and DILI. Additionally, a two-step Mendelian randomization was performed to explore the potential metabolites. Results: Five taxa were causally associated with DILI, including Oscillospira [odds ratio (OR) = 2.257, 95% confidence interval (CI) = 1.110-4.590], Blautia (OR = 2.311, 95% CI = 1.010-5.288), Roseburia (OR = 2.869, 95% CI = 1.429-5.761), Fusicatenibacter (OR = 1.995, 95% CI = 1.024-3.890), and Prevotella 7 (OR = 1.549, 95% CI = 1.065-2.253). Moreover, 53 metabolites were causally associated with DILI. After mediation analysis, four taxa were found to affect DILI through five mediation metabolites. N6-carbamoylthreonyladenosine mediated the effect of Blautia on DILI. Acetylcarnitine mediated the effect of Fusicatenibacter on DILI. In addition, 4-cholesten-3-one mediated the effect of Prevotella 7 on DILI. Furthermore, 5,6-dihydrothymine levels and the salicylate-to-citrate ratio mediated the effect of Oscillospira on DILI. Conclusion: We found that the gut microbiota could affect DILI through plasma metabolites, which could serve as potential biomarkers for risk stratification and elucidate underlying mechanisms for further investigation of DILI.

High-frequency ultrasound-assisted Mohs micrographic surgery for the treatment of dermatofibrosarcoma protuberans.

BACKGROUND: Dermatofibrosarcoma protuberans (DFSP) is a superficial sarcoma characterized by infiltrative growth with tentacle-like borders. Mohs micrographic surgery (MMS) is the preferred treatment option for DFSP. However, the imprecise boundary localization in MMS leads to an increased number of Mohs layers required and a longer surgery time. High-frequency ultrasound has excellent tissue recognition capability for DFSP, allowing for precise boundary marking. MATERIALS AND METHODS: In this study, we retrospectively analyzed 14 cases of DFSP treated with MMS using preoperative ultrasound localization and three-dimensional reconstruction at Xiangya Hospital over the past 5 years. We also reviewed previous studies on MMS for DFSP treatment. RESULTS: It was found that the average number of Mohs layers for patients after preoperative ultrasound localization was 1.57, ranging from 1 to 3, which was less than the previously reported 1.86 layers, ranging from 1 to 12. This effectively reduced the number of Mohs layers required. CONCLUSIONS: By utilizing preoperative high-frequency ultrasound to determine the boundaries and depth of DFSP, the number of Mohs layers can be effectively reduced, leading to less workload for pathological examination, shorter operation time, and reduced surgical risks for patients. Ultrasound imaging data can be used for three-dimensional reconstruction, enabling less experienced Mohs surgeons to have a visual understanding of the morphology and extent of infiltration of the lesions. This aids in developing optimal surgical plans, smoothing the learning curve, and promoting the wider adoption of MMS.

The biological impact of deuterium and therapeutic potential of deuterium-depleted water.

Since its discovery by Harold Urey in 1932, deuterium has attracted increased amounts of attention from the scientific community, with many previous works aimed to uncover its biological effects on living organisms. Existing studies indicate that deuterium, as a relatively rare isotope, is indispensable for maintaining normal cellular function, while its enrichment and depletion can affect living systems at multiple levels, including but not limited to molecules, organelles, cells, organs, and organisms. As an important compound of deuterium, deuterium-depleted water (DDW) possess various special effects, including but not limited to altering cellular metabolism and potentially inhibiting the growth of cancer cells, demonstrating anxiolytic-like behavior, enhancing long-term memory in rats, reducing free radical oxidation, regulating lipid metabolism, harmonizing indices related to diabetes and metabolic syndrome, and alleviating toxic effects caused by cadmium, manganese, and other harmful substances, implying its tremendous potential in anticancer, neuroprotective, antiaging, antioxidant, obesity alleviation, diabetes and metabolic syndrome treatment, anti-inflammatory, and detoxification, thereby drawing extensive attention from researchers. This review comprehensively summarizes the latest progress in deuterium acting on living organisms. We start by providing a snapshot of the distribution of deuterium in nature and the tolerance of various organisms to it. Then, we discussed the impact of deuterium excess and deprivation, in the form of deuterium-enriched water (DEW) and deuterium-depleted water (DDW), on living organisms at different levels. Finally, we focused on the potential of DDW as an adjuvant therapeutic agent for various diseases and disorders.

Design, synthesis and biological evaluation of naphthyl amide derivatives as reversible monoacylglycerol lipase (MAGL) inhibitors.

Monoacylglycerol lipase (MAGL) is a key enzyme responsible for the metabolism of the endocannabinoid 2-arachidonoylglycerol (2-AG), and has attracted great interest due to its involvement in various physiological and pathological processes, such as cancer progression. In the past, a number of covalent irreversible inhibitors have been reported for MAGL, however, experimental evidence highlighted some drawbacks associated with the use of these irreversible agents. Therefore, efforts were mainly focused on the development of reversible MAGL inhibitor in recent years. Here, we designed and synthesized a series of naphthyl amide derivatives (12-39) as another type of reversible MAGL inhibitors, exemplified by ± 34, which displayed good MAGL inhibition with a pIC50 of 7.1, and the potency and selectivity against endogenous MAGL were further demonstrated by competitive ABPP. Moreover, the compound showed appreciable antiproliferative activities against several cancer cells, including H460, HT29, CT-26, Huh7 and HCCLM-3. The investigations culminated in the discovery of the naphthyl amide derivative ± 34, and it may represent as a new scaffold for MAGL inhibitor development, particularly for the reversible ones.

Identification of phosphodiesterase-7A (PDE7A) as a novel target for reducing ethanol consumption in mice.

BACKGROUND: Ethanol elicits a rapid stimulatory effect and a subsequent, prolonged sedative response, which are potential predictors of EtOH consumption by decreasing adenosine signaling; this phenomenon also reflects the obvious sex difference. cAMP-PKA signaling pathway modulation can influence the stimulatory and sedative effects induced by EtOH in mice. This study's objective is to clarify the role of phosphodiesterase (PDE) in mediating the observed sex differences in ethanol responsiveness between male and female animals. METHODS: EtOH was administered intraperitoneally (i.p.) for 7 days to identify the changes in PDE isoforms in response to EtOH treatment. Additionally, EtOH consumption and preference of male and female C57BL/6J mice were assessed using the drinking-in-the-dark (DID) and two-bottle choice (2BC) tests. Further, pharmacological inhibition of PDE7A heterozygote knockout mice was performed to investigate its effects on ethanol-induced stimulation and sedation in both male and female mice. Finally, Western blotting analysis was performed to evaluate the alterations in cAMP-PKA/Epac2 pathways. RESULTS: Ethanol administration resulted in an immediate upregulation in PDE7A expression in female mice, indicating a strong association between PDE7A and ethanol stimulation. Through the pharmacological inhibition of PDE7A KD mice, we have demonstrated, for the first time, that PDE7A selectively attenuates ethanol responsiveness and consumption exclusively in female mice may be associated with the cAMP-PKA/Epac2 pathway and downstream phosphorylation of CREB and ERK1/2. CONCLUSIONS: PDE7A inhibition or knockdown attenuates EtOH responsiveness and consumption exclusively in female mice associated the change of cAMP-PKA/Epac2 signaling pathways, thereby highlighting its potential as a novel therapeutic target for alcohol use disorder.

Liposomes Loaded with 5-Fluorouracil Can Improve the Efficacy in Pathological Scars.

Introduction: Pathological scars, such as hypertrophic scars and keloids, are characterized by the proliferation of fibroblasts and the deposition of collagen that often cause pruritus, pain, and disfigurement. Due to their high incidence and deformity, pathological scars have resulted in severe physical and psychological trauma for patients. Intralesional injection of 5-fluorouracil (5-Fu) is a recommended option for treating pathological scars. However, the efficacy of 5-Fu injection was limited and unstable due to limited drug penetration and short retention time. Methods: Liposomes are promising carriers that have advantages, such as high biocompatibility, controlled release property, and enhanced clinical efficacy. Here, we constructed a transdermal 5-Fu-loaded liposome (5-Fu-Lip) to provide a more effective and safer modality to scar treatment. Results: Compared to 5-Fu, 5-Fu-Lip showed superior ability in inhibiting primary keloid fibroblasts proliferation, migration, and collagen deposition, and also significantly inhibited human umbilical vein endothelial cells (HUVECs) proliferation and microvessel construction. In vivo experiments demonstrated that 5-Fu-Lip can significantly reduce the severity of hypertrophic scars in a rabbit ear wounding model. Discussion: 5-Fu-Lip provides a promising strategy to improve drug efficacy, which has great potential in the treatment of pathological scars.

Pretreatment Sarcopenia and MRI-Based Radiomics to Predict the Response of Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer.

The association between sarcopenia and the effectiveness of neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) remains uncertain. This study aims to examine the potential of sarcopenia as a predictive factor for the response to NAC in TNBC, and to assess whether its combination with MRI radiomic signatures can improve the predictive accuracy. We collected clinical and pathological information, as well as pretreatment breast MRI and abdominal CT images, of 121 patients with TNBC who underwent NAC at our hospital between January 2012 and September 2021. The presence of pretreatment sarcopenia was assessed using the L3 skeletal muscle index. Clinical models were constructed based on independent risk factors identified by univariate regression analysis. Radiomics data were extracted on breast MRI images and the radiomics prediction models were constructed. We integrated independent risk factors and radiomic features to build the combined models. The results of this study demonstrated that sarcopenia is an independent predictive factor for NAC efficacy in TNBC. The combination of sarcopenia and MRI radiomic signatures can further improve predictive performance.

Analysis of Bending Deformation and Stress of 6063-T5 Aluminum Alloy Multi-Cavity Tube Filled with Liquid.

The production of aluminum alloy multi-lumen tubes primarily involves hot bending formation, a process where controlling thermal deformation quality is difficult. Specifically, the inner cavity wall of the tube is prone to bending instability defects under the bending stress field. To address these challenges in the bending deformation of aluminum alloy multi-lumen tubes, a multi-lumen liquid-filled bypass forming method is proposed in this paper. This study focuses on the 6063-T5 aluminum alloy double-lumen tube as the research object. The liquid-filled bending deformation behavior of the aluminum alloy double-lumen tube was investigated, and the deformation theory of the aluminum alloy double-lumen tube was studied. Through experimental and numerical simulation methods, the influence of support internal pressure, bending radius, and tube wall thickness on the liquid-filled bending deformation behavior of the double-lumen tube was examined. The results indicate that when the value of internal pressure was 7.5 MPa, the straightening of the outer wall was improved by 2.51%, the thinning rate of wall thickness was minimized, and the internal concave defect was effectively suppressed. The liquid-filled bending method provides a promising new approach for the integrated bending and forming of multi-lumen tubes.

Advancements in Nanomaterial Dispersion and Stability and Thermophysical Properties of Nano-Enhanced Phase Change Materials for Biomedical Applications.

Phase change materials (PCMs) are materials that exhibit thermal response characteristics, allowing them to be utilized in the biological field for precise and controllable temperature regulation. Due to considerations of biosafety and the spatial limitations within human tissue, the amount of PCMs used in medical applications is relatively small. Therefore, researchers often augment PCMs with various materials to enhance their performance and increase their practical value. The dispersion of nanoparticles to modify the thermophysical properties of PCMs has emerged as a mature concept. This paper aims to elucidate the role of nanomaterials in addressing deficiencies and enhancing the performance of PCMs. Specifically, it discusses the dispersion methods and stabilization mechanisms of nanoparticles within PCMs, as well as their effects on thermophysical properties such as thermal conductivity, latent heat, and specific heat capacity. Furthermore, it explores how various nano-additives contribute to improved thermal conductivity and the mechanisms underlying enhanced latent heat and specific heat. Additionally, the potential applications of PCMs in biomedical fields are proposed. Finally, this paper provides a comprehensive analysis and offers suggestions for future research to maximize the utilization of nanomaterials in enhancing the thermophysical properties of PCMs for biomedical applications.

Machine learning-based prediction of clinical outcomes after traumatic brain injury: Hidden information of early physiological time series.

AIMS: To assess the predictive value of early-stage physiological time-series (PTS) data and non-interrogative electronic health record (EHR) signals, collected within 24 h of ICU admission, for traumatic brain injury (TBI) patient outcomes. METHODS: Using data from TBI patients in the multi-center eICU database, we focused on in-hospital mortality, neurological status based on the Glasgow Coma Score (mGCS) motor subscore at discharge, and prolonged ICU stay (PLOS). Three machine learning (ML) models were developed, utilizing EHR features, PTS signals collected 24 h after ICU admission, and their combination. External validation was performed using the MIMIC III dataset, and interpretability was enhanced using the Shapley Additive Explanations (SHAP) algorithm. RESULTS: The analysis included 1085 TBI patients. Compared to individual models and existing scoring systems, the combination of EHR and PTS features demonstrated comparable or even superior performance in predicting in-hospital mortality (AUROC = 0.878), neurological outcomes (AUROC = 0.877), and PLOS (AUROC = 0.835). The model's performance was validated in the MIMIC III dataset, and SHAP algorithms identified six key intervention points for EHR features related to prognostic outcomes. Moreover, the EHR results (All AUROC >0.8) were translated into online tools for clinical use. CONCLUSION: Our study highlights the importance of early-stage PTS signals in predicting TBI patient outcomes. The integration of interpretable algorithms and simplified prediction tools can support treatment decision-making, contributing to the development of accurate prediction models and timely clinical intervention.

Coordination Site Selective Occupation Strategy for Tuning the Photosalient Effects of Photoactive Cd Complexes.

The application of photo responsive crystals to useful actuation demands a rational design to elicit controllable movement. The [2+2] photocycloaddition reaction triggers mechanical motion  using associated photosalient (PS) effects. We herein report a coordination site selective occupation strategy to modulate the arrangement of C=C bonds and thereby tune the PS effect. Replacing or repositioning the donor atom at one end of the linear ligand allowed for a greater level of molecular structural flexibility, facilitating [2+2] photocycloaddition. The distance between photoreactive centres and coordination sites was adjusted by ligand design to regulate PS behavior. This work suggests new avenues for modulating PS movement to achieve useful motion.

Sulfadiazine degradation by Bjerkandera adusta DH0817 at low temperatures and its cold-adaptation mechanisms.

The prolonged period of low temperatures in northern China poses a significant challenge to the bioremediation of antibiotic pollution. This study reports that a white-rot fungus Bjerkandera adusta DH0817, isolated from a poultry farm in Liaoning Province, can remove 60 % of SDZ within 20 days at 10°C and reduce the biotoxicity of SDZ. Six degradation pathways were proposed. SDZ biodegradation was primarily driven by cytochrome P450. Transcriptome analysis revealed that DH0817 upregulated genes associated with cell membrane, transcription factors and soluble sugars in response to low temperatures. Subsequently, genes associated with fatty acid, proteins and enzymes were upregulated to remove SDZ at low temperatures. This study provides valuable microbial resources and serves as a theoretical reference for addressing antibiotic pollution in livestock and poultry farms under low temperature conditions.

Integrated analyses highlight interactions between the three-dimensional genome and DNA, RNA and epigenomic alterations in metastatic prostate cancer.

The impact of variations in the three-dimensional structure of the genome has been recognized, but solid cancer tissue studies are limited. Here, we performed integrated deep Hi-C sequencing with matched whole-genome sequencing, whole-genome bisulfite sequencing, 5-hydroxymethylcytosine (5hmC) sequencing and RNA sequencing across a cohort of 80 biopsy samples from patients with metastatic castration-resistant prostate cancer. Dramatic differences were present in gene expression, 5-methylcytosine/5hmC methylation and in structural variation versus mutation rate between A and B (open and closed) chromatin compartments. A subset of tumors exhibited depleted regional chromatin contacts at the AR locus, linked to extrachromosomal circular DNA (ecDNA) and worse response to AR signaling inhibitors. We also identified topological subtypes associated with stark differences in methylation structure, gene expression and prognosis. Our data suggested that DNA interactions may predispose to structural variant formation, exemplified by the recurrent TMPRSS2-ERG fusion. This comprehensive integrated sequencing effort represents a unique clinical tumor resource.

Cascade Synthesis of Fe-N2-Fe Dual-Atom Catalysts for Superior Oxygen Catalysis.

Dual-atom catalysts (DACs) have been proposed to break the limitation of single-atom catalysts (SACs) in the synergistic activation of multiple molecules and intermediates, offering an additional degree of freedom for catalytic regulation. However, it remains a challenge to synthesize DACs with high uniformity, atomic accuracy, and satisfactory loadings. Herein, we report a facile cascade synthetic strategy for DAC via precise electrostatic interaction control and neighboring vacancy construction. We synthesized well-defined, uniformly dispersed dual Fe sites which were connected by two nitrogen bonds (denoted as Fe-N2-Fe). The as-synthesized DAC exhibited superior catalytic performances towards oxygen reduction reaction, including good half-wave potential (0.91 V), high kinetic current density (21.66 mA cm-2), and perfect durability. Theoretical calculation revealed that the DAC structure effectively tunes the oxygen adsorption configuration and decreases the cleavage barrier, thereby improving the catalytic kinetics. The DAC-based zinc-air batteries exhibited impressive power densities of 169.8 and 52.18 mW cm-2 at 25 oC and -40 oC, which is 1.7 and 2.0 times higher than those based on Pt/C+Ir/C, respectively. We also demonstrated the universality of our strategy in synthesizing other M-N2-M DACs (M= Co, Cu, Ru, Pd, Pt, and Au), facilitating the construction of a DAC library for different catalytic applications.

Mechanisms of regulation of glycolipid metabolism by natural compounds in plants: effects on short-chain fatty acids.

BACKGROUND: Natural compounds can positively impact health, and various studies suggest that they regulate glucose‒lipid metabolism by influencing short-chain fatty acids (SCFAs). This metabolism is key to maintaining energy balance and normal physiological functions in the body. This review explores how SCFAs regulate glucose and lipid metabolism and the natural compounds that can modulate these processes through SCFAs. This provides a healthier approach to treating glucose and lipid metabolism disorders in the future. METHODS: This article reviews relevant literature on SCFAs and glycolipid metabolism from PubMed and the Web of Science Core Collection (WoSCC). It also highlights a range of natural compounds, including polysaccharides, anthocyanins, quercetins, resveratrols, carotenoids, and betaines, that can regulate glycolipid metabolism through modulation of the SCFA pathway. RESULTS: Natural compounds enrich SCFA-producing bacteria, inhibit harmful bacteria, and regulate operational taxonomic unit (OTU) abundance and the intestinal transport rate in the gut microbiota to affect SCFA content in the intestine. However, most studies have been conducted in animals, lack clinical trials, and involve fewer natural compounds that target SCFAs. More research is needed to support the conclusions and to develop healthier interventions. CONCLUSIONS: SCFAs are crucial for human health and are produced mainly by the gut microbiota via dietary fiber fermentation. Eating foods rich in natural compounds, including fruits, vegetables, tea, and coarse fiber foods, can hinder harmful intestinal bacterial growth and promote beneficial bacterial proliferation, thus increasing SCFA levels and regulating glucose and lipid metabolism. By investigating how these compounds impact glycolipid metabolism via the SCFA pathway, novel insights and directions for treating glucolipid metabolism disorders can be provided.