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BACKGROUND: The prevalence of obesity is escalating. Previous research has concentrated on the link between frailty and obesity; however, the association between prefrailty and obesity has been less studied. Prefrailty screening and intervention may prevent or postpone frailty in older persons. OBJECTIVE: The study was to investigate into the relationship between prefrailty and several obesity indicators in Chinese community-dwelling older individuals. METHODS: This research employed the Frailty Screening Index to investigate the frailty phenotype of people living in Shanghai. Bioelectrical impedance analysis was used for evaluating body composition. RESULTS: There were 510 participants (39.0%) with high visceral adipose areas. Participants with a high visceral adipose area showed a higher risk of prefrailty (adjusted OR, 1.53; 95% CI, 1.19-1.96), according to multivariate models. When body mass index (BMI) and visceral fat area (VFA) were combined, it was discovered that having an overweight BMI with normal VFA was a protective factor for prefrailty (corrected OR, 0.62; 95% CI, 0.43-0.90), but having a normal weight but excess VFA increased the risk of prefrailty (corrected OR, 1.87; 95% CI, 1.15-3.03). CONCLUSION: Visceral fat obesity is an independent risk factor for prefrailty in Chinese older adults. Implementing targeted interventions, such as dietary modifications, increased physical activity, and other lifestyle changes, could play a crucial role in reducing the risk of prefrailty and improving overall health outcomes in this population.
Subject(s)
Body Mass Index , Frailty , Intra-Abdominal Fat , Humans , Male , Female , Aged , Cross-Sectional Studies , China/epidemiology , Frailty/epidemiology , Frailty/etiology , Obesity/epidemiology , Obesity/complications , Aged, 80 and over , Obesity, Abdominal/epidemiology , Obesity, Abdominal/complications , Frail Elderly/statistics & numerical data , Risk Factors , Body Composition , Prognosis , Middle Aged , East Asian PeopleABSTRACT
In this study, a mouse model of premature ovarian failure(POF) was constructed by injecting D-galactose(200 mg·kg~(-1)) into the back of the neck for 6 weeks. The mice were randomly divided into a normal group(group N), a model group(group M), and a Qiwei Guibao Granules group(group A, 12.87 g·kg~(-1)). Starting from the 11th day of modeling, group A was treated with Qiwei Guibao Granules by gavage for 32 days, while group M and group N were given equal volume of saline. Metabolomics analysis was used to explore the mechanism of action of Qiwei Guibao Granules in the treatment of POF. The results showed that compared with group N, the group M exhibited decreased wet weight of bilateral ovaries, increased levels of LH and FSH in serum, and significantly decreased levels of E_2 and PROG. After treatment with Qiwei Guibao Granules, compared with the group M, the group A showed a significant increase in the wet weight of bilateral ovaries, a significant decrease in the levels of FSH and LH in serum, and a significant increase in the level of E_2. Metabolomics analysis revealed 55 differential metabolites identified between group N and group M(14 upregulated and 41 downregulated compared with group N) and 82 differential metabolites identified between group M and group A(56 upregulated and 26 downregulated compared with group M), with 5 metabolites showing consistent changes between the group N vs group M. After excluding these 5 metabolites, 77 metabolites that changed after intervention with Qiwei Guibao Granules were focused on. These mainly involved histidine metabolism, glycine, serine, and threonine metabolism, and glycerophospholipid metabolism. Among them, carnosine, 1-methyl-L-histidine, imidazoleacetic acid, choline, L-threonine, beta-hydroxypyruvic acid, phosphatidylcholine, and glycerol-3-phosphate were the major differential metabolites in these three metabolic pathways. Therefore, Qiwei Guibao Granules may exert therapeutic effects on POF mice by regulating amino acid metabolism and lipid metabolism in the mouse body.
Subject(s)
Drugs, Chinese Herbal , Metabolomics , Primary Ovarian Insufficiency , Animals , Female , Primary Ovarian Insufficiency/drug therapy , Primary Ovarian Insufficiency/metabolism , Drugs, Chinese Herbal/administration & dosage , Drugs, Chinese Herbal/pharmacology , Mice , Humans , Ovary/drug effects , Ovary/metabolism , Disease Models, AnimalABSTRACT
OBJECTIVE: This study aimed to examine the relationship between different dimensions of depressive symptoms and the presence of diabetes mellitus in hemodialysis patients. Additionally, the study sought to elucidate the mediating effect of physical performance on this association. METHODS: This was a cross-sectional multicenter study conducted between July 2020 and March 2023, involving 1024 patients from eight hemodialysis centers in Shanghai. Diabetes mellitus was based on a documented physician diagnosis and blood glucose tests. Physical performance and depressive symptoms were assessed using short-physical performance battery (SPPB) and the patient health questionnaire-9, respectively. Regression and mediation analysis were applied to statistical analysis. RESULTS: Among the 1024 participants, 39.26% (n = 402) were found to have coexisting diabetes mellitus. Diminished SPPB scores (OR = 0.843, 95% CI = 0.792-0.897) and cognitive depressive symptoms (OR = 1.068, 95% CI = 1.011-1.129) exhibited significant associations with diabetes mellitus, while somatic depressive symptoms did not show a significant correlation. Notably, SPPB emerged as a complete mediator in the relationship between cognitive depressive symptoms and diabetes mellitus. The observed indirect effect of SPPB on this relationship was estimated at 0.038 (95% CI: 0.021-0.057). CONCLUSION: This study showed an association between diabetes mellitus and cognitive depressive symptoms in patients undergoing hemodialysis, with physical performance appearing to mediate the relationship between diabetes mellitus and depressive symptoms.
Subject(s)
Depression , Diabetes Mellitus , Renal Dialysis , Humans , Male , Cross-Sectional Studies , Female , Middle Aged , Renal Dialysis/psychology , Depression/epidemiology , Depression/psychology , China/epidemiology , Diabetes Mellitus/psychology , Aged , Adult , Physical Functional PerformanceABSTRACT
BACKGROUND: National treatment guidelines of China evolving necessitates population-level surveillance of transmitted drug resistance (TDR) to inform or update HIV treatment strategies. METHODS: We analyzed the demographic, clinical, and virologic data obtained from people with HIV (PWH) residing in 31 provinces of China who were newly diagnosed between 2018 and 2023. Evidence of TDR was defined by the World Health Organization list for surveillance of drug resistance mutations. RESULTS: Among the 22 124 PWH with protease and reverse transcriptase sequences, 965 (4.36%; 95% CI, 4.1-4.63) had at least 1 TDR mutation. The most frequent TDR mutations were nonnucleoside reverse transcriptase inhibitor (NNRTI) mutations (2.39%; 95% CI, 2.19%-2.59%), followed by nucleoside reverse transcriptase inhibitor mutations(1.35%; 95% CI, 1.2%-1.5%) and protease inhibitor mutations (1.12%; 95% CI, .98%-1.26%). The overall protease and reverse transcriptase TDR increased significantly from 4.05% (95% CI, 3.61%-4.52%) in 2018 to 5.39% (95% CI, 4.33%-6.57%) in 2023. A low level of integrase strand transfer inhibitor TDR was detected in 9 (0.21%; 95% CI, .1%-.38%) of 4205 PWH. CONCLUSIONS: Presently, the continued use of NNRTI-based first-line antiretroviral therapy regimen for HIV treatment has been justified.
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Single-atom nanozymes have garnered significant attention due to their exceptional atom utilization and ability to establish well-defined structure-activity relationships. However, conventional pyrolytic synthesis methods pose challenges such as high energy consumption and random local environments at the active sites, while achieving non-pyrolytic synthesis of single-atom nanozymes remains a formidable technical hurdle. The present study focuses on the synthesis of laccase-like iron-based single-atom nanozymes (Fe-SAzymes) using a non-pyrolysis method facilitated by microwave irradiation. Under low iron loading conditions, Fe-SAzymes exhibited significantly enhanced laccase activity (12.1 U/mg), surpassing that of laccase by 24-fold. Moreover, Fe-SAzymes demonstrated efficient catalytic oxidation of epinephrine (EP), enabling its colorimetric detection. Owing to the remarkable laccase activity of Fe-SAzymes, the conventional nanozymes EP detection time was reduced from 60 min to 20 min, with an impressive low detection limit as low as 2.95 µM. In addition, an ultra-sensitive fluorescence method for EP detection was developed using the internal filter effect of EP oxidation products and CDs combined with carbon dots probe. The detection limit of fluorescence method was only 0.39 µM. Therefore, an visual, fast, and highly sensitive dual-mode EP detection strategy has great potential in the clinical diagnostic industry.
Subject(s)
Colorimetry , Epinephrine , Iron , Laccase , Laccase/chemistry , Laccase/metabolism , Colorimetry/methods , Epinephrine/analysis , Iron/chemistry , Spectrometry, Fluorescence , Limit of Detection , Nanostructures/chemistry , Oxidation-Reduction , Fluorescence , MicrowavesABSTRACT
Flavonoids, a significant group of natural polyphenolic compounds, possess a broad spectrum of pharmacological effects. Recent advances in the systematic metabolic engineering of yeast cell factories (YCFs) provide new opportunities for enhanced flavonoid production. Herein, we outline the latest research progress on typical flavonoid products in YCFs. Advanced engineering strategies involved in flavonoid biosynthesis are discussed in detail, including enhancing precursor supply, cofactor engineering, optimizing core pathways, eliminating competitive pathways, relieving transport limitations, and dynamic regulation. Additionally, we highlight the existing problems in the biosynthesis of flavonoid glucosides in yeast, such as endogenous degradation of flavonoid glycosides, substrate promiscuity of UDP-glycosyltransferases, and an insufficient supply of UDP-sugars, with summaries on the corresponding solutions. Discussions also cover other typical postmodifications like prenylation and methylation, and the recent biosynthesis of complex flavonoid compounds in yeast. Finally, a series of advanced technologies are envisioned, i.e., semirational enzyme engineering, ML/DL algorithn, and systems biology, with the aspiration of achieving large-scale industrial production of flavonoid compounds in the future.
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Surface wrinkling structures based on a bilayer system are widely employed in storing and encrypting specific optical information. However, constructing a stable wrinkling structure with high-level security remains an extensive challenge due to the delamination issue between the skin layer and the substrate. Herein, a double cross-linking strategy is introduced between a hydrogel layer doped with fluorescent molecules and polydimethylsiloxane to establish a stable interfacial wrinkling structure with dual-mode functionality, in which the light reflection of the wrinkles and fluorescence intensity of fluorescent molecules can be simultaneously regulated by the modulus ratio between the two layers. The spontaneous wrinkling structures with a physically unclonable function can enhance the photoluminescence emission intensity of the wrinkling area under ultraviolet radiation. Meanwhile, the skin layer constructed of acrylamide and acrylic acid copolymer protects the interfacial wrinkling patterns from the loss of a detailed structure for authentication due to external damage. The stable interfacial wrinkling structures with fluorescence can find potential applications in the fields of information storage and encryption.
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BACKGROUND: Atopic dermatitis (AD) is a common chronic skin disorder in children. We aimed to investigate trends and regional disparities of burden in paediatric AD at global, regional and national levels, and to explore potential associated factors. METHODS: Based on data from Global Burden of Disease study 2019, we assessed trends in burden of AD aged <19 years from 1990 to 2019, including prevalent and incident cases, age-standardised prevalence and age-standardised incidence. For potential associated factors, correlations of above trends and indexes of socio-economic status (sociodemographic index, SDI) and health service coverage (universal health coverage index, UHCI) were evaluated. We conducted decomposition analysis to understand the net contribution of population-level factors and their contribution proportions on changes of prevalent and incident cases, including age structure, population change and epidemiological change. RESULTS: Global prevalent and incident cases of paediatric AD increased by about 5.7 and 0.7 million between 1990 and 2019, respectively. Global age-standardised prevalence and incidence decreased by -0.17% (-0.19% to -0.16%) and -0.12% (-0.13% to -0.11%) per year from 1990 to 2019, respectively. Regionally, the highest increase of prevalent and incident cases was in low SDI region (by 96.77% and 84.85%); the highest decrease of age-standardised prevalence and incidence was in high SDI regions (by -0.20% and -0.27% per year). The correlation analyses identified significant negative correlations between trends and SDI and UHCI. Population change was a major driver of case rise; epidemiological change and age structure showed negative impact of case rise. Regional disparities in contribution of three population-level factors were seen, including net contribution direction (positive or negative) and contribution proportion levels. CONCLUSION: Global paediatric AD case numbers increased, primarily due to population growth. Prevalence and incidence decreased slightly. Geographic inequalities were seen. Developing region-specific strategies targeting potential factors is essential to reduce paediatric AD burden.
ABSTRACT
Physical performance in hemodialysis patients declines and serves as a cardiovascular disease (CVD) incidence and mortality predictor. However, lower extremity function's role remains unclear. This study aimed to quantify the association between lower extremity function and CVD risk in hemodialysis patients. This was a multicenter cross-sectional study enrolling 868 participants (532 males, 336 females) from seven hemodialysis centers in Shanghai, China. Patients were divided into three groups per lower extremity function, evaluated by short physical performance battery (SPPB) scores: 0-6, 7-9, and 10-12. Upper extremity function was quantified through grip strength assessment. CVD risk was assessed using the Framingham Risk Score. Approximately 35% of hemodialysis patients had impaired lower extremity function (SPPB score < 10). Participants with high SPPB scores had stronger handgrip and lower Framingham CVD risk scores than those with low and moderate SPPB scores (p < 0.05). After adjusting clinical confounders, SPPB was independently associated with CVD risk, as a categorized variable (odds ratio: 0.577, 95% confidence interval [CI]: 0.388-0.857, p = 0.006) and as a continuous variable (odds ratio: 0.858, 95% CI: 0.772-0.953, p = 0.004). An SPPB score < 10 predicted an increased CVD risk (area under curve: 0.649, 95% CI: 0.599-0.699, p < 0.001). Causality between physical performance and CVD risk was not considered. Some upper limb results may not be generalizable to peritoneal dialysis and kidney transplant patients. Lower extremity function was significantly associated with CVD risk in hemodialysis patients. Further studies are needed to explore the long-term relationship between lower extremity function and CVD risk.
Subject(s)
Cardiovascular Diseases , Lower Extremity , Renal Dialysis , Humans , Male , Female , Renal Dialysis/adverse effects , Middle Aged , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/etiology , Cardiovascular Diseases/physiopathology , Cross-Sectional Studies , Aged , Hand Strength , Adult , Heart Disease Risk Factors , Risk Factors , China/epidemiology , Kidney Failure, Chronic/therapy , Kidney Failure, Chronic/physiopathology , Kidney Failure, Chronic/epidemiologyABSTRACT
BACKGROUND: In 2016, China has implemented the World Health Organization's "treat all" policy. We aimed to assess the impact of significant improvements in the 95-95-95 targets on population-level human immunodeficiency virus (HIV) transmission dynamics and incidence. METHODS: We focused on 3 steps of the HIV care continuum: diagnosed, on antiretroviral therapy, and achieving viral suppression. The molecular transmission clusters were inferred using HIV-TRACE. New HIV infections were estimated using the incidence method in the European Centre for Disease Prevention and Control HIV Modelling Tool. RESULTS: Between 2004 and 2023, the national HIV epidemiology database recorded 2.99 billion person-times of HIV tests and identified 1 976 878 new diagnoses. We noted a roughly "inverted-V" curve in the clustering frequency, with the peak recorded in 2014 (67.1% [95% confidence interval, 63.7%-70.5%]), concurrent with a significant improvement in the 95-95-95 targets from 10-13-<71 in 2005 to 84-93-97 in 2022. Furthermore, we observed a parabolic curve for a new infection with the vertex occurring in 2010. CONCLUSIONS: In general, it was suggested that the improvements in the 95-95-95 targets were accompanied by a reduction in both the population-level HIV transmission rate and incidence. Thus, China should allocate more effort to the first "95" target to achieve a balanced 95-95-95 target.
ABSTRACT
Even though catalytic asymmetric bifunctionalization of allenes has been extensively studied, almost all of the reported examples have been achieved in a two-component manner. In this study, we report a highly efficient asymmetric bifunctionalization of allenes with iodohydrocarbons and NH2-unprotected amino acid esters. The adopted chiral aldehyde/palladium combined catalytic system precisely governs the chemoselectivity, regioselectivity, and stereoselectivity of this three-component reaction. A wide range of substituted aryl iodides, allenes and amino acid esters can well participate in this reaction and deliver structurally diverse α,α-disubstituted α-amino acid esters with excellent experimental outcomes. One of the resulting products is utilized for the total synthesis of the molecule (S,R)-VPC01091.
ABSTRACT
Objective: Depression is a common comorbidity in hypertensive older adults, yet depression is more difficult to diagnose correctly. Our goal is to find predictive models of depression in hypertensive patients using a combination of various machine learning (ML) methods and metabolomics. Methods: Methods We recruited 379 elderly people aged ≥65 years from the Chinese community. Plasma samples were collected and assayed by gas chromatography/liquid chromatography-mass spectrometry (GC/LC-MS). Orthogonal partial least squares discriminant analysis (OPLS-DA), volcano diagrams and thermograms were used to distinguish metabolites. The attribute discriminators CfsSubsetEval combined with search method BestFirst in WEKA software was used to find the best predicted metabolite combinations, and then 24 classification methods with 10-fold cross-validation were used for prediction. Results: 34 individuals were considered hypertensive combined with depression according to our criteria, and 34 subjects with hypertension only were matched according to age and sex. 19 metabolites by GC-MS and 65 metabolites by LC-MS contributed significantly to the differentiation between the depressed and non-depressed cohorts, with a VIP value of more than 1 and a P value of less than 0.05. There were multiple metabolic pathway alterations. The metabolite combinations screened with WEKA for optimal diagnostic value included 12 metabolites. The machine learning methods with AUC values greater than 0.9 were bayesNet and random forests, and their other evaluation measures are also better. Conclusion: Altered metabolites and metabolic pathways are present in older adults with hypertension combined with depression. Methods using metabolomics and machine learning performed quite well in predicting depression in hypertensive older adults, contributing to further clinical research.
ABSTRACT
Iron-anchored nitrogen/doped carbon single-atom nanozymes (Fe-N/C), which possess homogeneous active sites and adjustable catalytic environment, represent an exemplary model for investigating the structure-function relationship and catalytic activity. However, the development of pyrolysis-free synthesis technique for Fe-N/C with adjustable enzyme-mimicking activity still presents a significant challenge. Herein, Fe-N/C anchored three carrier morphologies were created via a pyrolysis-free approach by covalent organic polymers. The peroxidase-like activity of these Fe-N/C nanozymes was regulated via the pores of the anchored carrier, resulting in varying electron transfer efficiency due to disparities in contact efficacy between substrates and catalytic sites within diverse microenvironments. Additionally, a colorimetric sensor array for identifying antioxidants was developed: (1) the Fe-N/C catalytically oxidized two substrates TMB and ABTS, respectively; (2) the development of a colorimetric sensor array utilizing oxTMB and oxABTS as sensing channels enabled accurate discrimination of antioxidants such as ascorbic acid (AsA), glutathione (GSH), cysteine (Cys), gallic acid (GA), and caffeic acid (CA). Subsequently, the sensor array underwent rigorous testing to validate its performance, including assessment of antioxidant mixtures and individual antioxidants at varying concentrations, as well as target antioxidants and interfering substances. In general, the present study offered valuable insights into the active origin and rational design of nanozyme materials, and highlighting their potential applications in food analysis.
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This study identified phenolic compounds in five flaxseed varieties and evaluated their antioxidant activities. Results showed significant variations in phenolic acids and flavonoids among the varieties. Longya 16 had the lowest flavonoid content, Longya 13 had the lowest phenolic acid content, while Longya 10 exhibited the highest content and diversity of polyphenols, including six flavonoids (vitexin, quercitrin, quercetin, apigenin, kaempfero1, (+)-dihydroquercetin) and five phenolic acids (gallic acid, vanillic acid, ferulic acid, sinapic acid, and 4-hydroxybenzoic acid). Antioxidant activity was assessed using DPPH and ABTS radical scavenging assays, and cell-based assays under tBHP-induced oxidative stress. Flaxseed polyphenol extracts significantly reduced ROS, MDA, and GSSG levels and increased SOD and CAT activities, preserving cell vitality and morphology. These findings confirmed the significant antioxidant activity of flaxseed polyphenols, providing a theoretical basis for their application in antioxidative functional areas.
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Lysophospholipids (LPLs) represent a major class of polar lipids crucial for rice's nutritional and functional properties. This study investigates the impact of varying storage temperatures (20, 30, and 40 °C) and humidity (50 and 95%) on the nonstarch and starch LPLs of paddy and milled rice. The findings revealed that the average nonstarch LPL content in paddy rice aged at 20 °C (82.6 µg/g) and 40 °C (83.6 µg/g) was significantly lower than that at 30 °C (95.0 µg/g). The nonstarch LPL content of milled rice aged at 20 °C (78.0 µg/g) was significantly higher than that at 30 and 40 °C. High storage temperature (40 °C) and humidity (95%) resulted in a significant reduction in rice total starch LPC and LPE content when compared to low humidity (50%). The ratio of rice starch/nonstarch LPL components such as LPC16:0 and LPC18:2 remarkably increased with increased storage temperature and humidity.
Subject(s)
Lysophospholipids , Oryza , Temperature , Oryza/chemistry , Lysophospholipids/chemistry , Food Storage , Starch/chemistry , Humidity , Seeds/chemistry , Seeds/growth & developmentABSTRACT
BACKGROUND: Diabetes mellitus is generally accompanied by dyslipidaemia, but inconsistent relationships between lipid profiles and diabetes are noted. Moreover, genetic variations in insertion/deletion (I/D) polymorphisms at angiotensin-converting enzyme gene (ACE) and T/C polymorphisms in the angiotensin type 1 receptor gene (AGTR1) are related to diabetes and lipid levels, but the associations are controversial. Thus, the current research aimed to explore the effects of ACE I/D, AGTR1 rs5182 and diabetes mellitus on serum lipid profiles in 385 Chinese participants with an average age of 75.01 years. METHODS: The ACE I/D variant was identified using the polymerase chain reaction (PCR) method, whereas the AGTR1 rs5182 polymorphism was identified using the PCR-based restriction fragment length polymorphism (PCR-RFLP) method and verified with DNA sequencing. Total cholesterol (TC), triglyceride (TG), apolipoprotein A (ApoA), apolipoprotein B (ApoB), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels were measured using routine methods, and the lipid ratios were calculated. RESULTS: ACE I/D, but not AGTR1 rs5182, was a predictor of TG/HDL-C for the whole study population. Both ACE I/D and AGTR1 rs5182 were predictors of HDL-C and LDL-C levels in females but not in males. Moreover, in females, diabetes mellitus and ACE I/D were identified as predictors of TG and TG/HDL-C, whereas AGTR1 rs5182 and diabetes mellitus were predictors of TG/HDL-C. Moreover, diabetes mellitus and the combination of ACE I/D and AGTR1 rs5182 variations were predictors of TG and TG/HDL-C exclusively in females. CONCLUSIONS: The results demonstrated the potential for gender-dependent interactions of ACE I/D, AGTR1 rs5182, and diabetes on lipid profiles. These findings may serve as an additional explanation for the inconsistent changes of blood lipids in individuals with diabetes mellitus, thereby offering a novel perspective for the clinical management of blood lipid levels in diabetic patients.
Subject(s)
Peptidyl-Dipeptidase A , Receptor, Angiotensin, Type 1 , Humans , Male , Female , Aged , Receptor, Angiotensin, Type 1/genetics , Peptidyl-Dipeptidase A/genetics , Peptidyl-Dipeptidase A/blood , Polymorphism, Single Nucleotide , Lipids/blood , Lipids/genetics , Asian People/genetics , Triglycerides/blood , Aged, 80 and over , Cholesterol, HDL/blood , Cholesterol, HDL/genetics , Diabetes Mellitus/genetics , Diabetes Mellitus/blood , INDEL Mutation , Cholesterol, LDL/blood , Cholesterol, LDL/genetics , Genetic Association Studies , China/epidemiology , Genetic Predisposition to Disease , East Asian PeopleABSTRACT
Deciphering the intricate relationships between transcription factors (TFs), enhancers, and genes through the inference of enhancer-driven gene regulatory networks (eGRNs) is crucial in understanding gene regulatory programs in a complex biological system. This study introduces STREAM, a novel method that leverages a Steiner forest problem model, a hybrid biclustering pipeline, and submodular optimization to infer eGRNs from jointly profiled single-cell transcriptome and chromatin accessibility data. Compared to existing methods, STREAM demonstrates enhanced performance in terms of TF recovery, TF-enhancer linkage prediction, and enhancer-gene relation discovery. Application of STREAM to an Alzheimer's disease dataset and a diffuse small lymphocytic lymphoma dataset reveals its ability to identify TF-enhancer-gene relations associated with pseudotime, as well as key TF-enhancer-gene relations and TF cooperation underlying tumor cells.
Subject(s)
Enhancer Elements, Genetic , Gene Regulatory Networks , RNA-Seq , Single-Cell Analysis , Single-Cell Analysis/methods , Humans , Transcription Factors/metabolism , Transcription Factors/genetics , Chromatin Immunoprecipitation Sequencing , Algorithms , Computational Biology/methods , Alzheimer Disease/genetics , Alzheimer Disease/metabolism , Single-Cell Gene Expression AnalysisABSTRACT
Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represents a complex ailment that results in prolonged hyperglycemia and severe complications. Patients endure severe ramifications such as kidney disease, vision impairment, cardiovascular disorders, and susceptibility to infections, leading to significant physical suffering and imposing substantial socio-economic burdens. This condition has evolved into an increasingly severe health crisis. There is an urgent need to develop new treatments with improved efficacy and fewer adverse effects to meet clinical demands. However, novel drug development is costly, time-consuming, and often associated with side effects and suboptimal efficacy, making it a major challenge. Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized drug development across its comprehensive lifecycle, spanning drug discovery, preclinical studies, clinical trials, and post-market surveillance. These technologies have significantly accelerated the identification of promising therapeutic candidates, optimized trial designs, and enhanced post-approval safety monitoring. Recent advances in AI, including data augmentation, interpretable AI, and integration of AI with traditional experimental methods, offer promising strategies for overcoming the challenges inherent in AI-based drug discovery. Despite these advancements, there exists a notable gap in comprehensive reviews detailing AI and ML applications throughout the entirety of developing medications for diabetes mellitus. This review aims to fill this gap by evaluating the impact and potential of AI and ML technologies at various stages of diabetes mellitus drug development. It does that by synthesizing current research findings and technological advances so as to effectively control diabetes mellitus and mitigate its far-reaching social and economic impacts. The integration of AI and ML promises to revolutionize diabetes mellitus treatment strategies, offering hope for improved patient outcomes and reduced healthcare burdens worldwide.
ABSTRACT
Six new phenylpropanoid glycosides (1-6), two new phenylethanol glycosides (7 and 8), one new phenylmethanol glycoside (9), three new phenylpropanoid dimers (10-12), two new phenylpropanoid-flavan-3-ol heterodimers (13 and 14), and six known relevant compounds (15-20) were isolated and identified from the well-liked edible and medicinal substance (the bark of Cinnamomum cassia (L.) J.Presl). The structures of these isolates were determined by using spectroscopic analyses, chemical methods, and quantum chemical calculations. Notably, compounds 4-9 were rare apiuronyl-containing glycosides, and compounds 13 and 14 were heterodimers of phenylpropanoids and flavan-3-ols linked through C-9â³-C-8 bonds. The antioxidant and α-glucosidase inhibitory activities of all isolates were evaluated. Compounds 10 and 12 exhibited DPPH radical scavenging capacities with IC50 values of 20.1 and 13.0 µM, respectively (vitamin C IC50 value of 14.3 µM). In the ORAC experiment, all these compounds exhibited different levels of capacity for scavenging free radicals, and compound 10 displayed extraordinary free radical scavenging capacity with the ORAC value of 6.42 ± 0.01 µM TE/µM (EGCG ORAC value of 1.54 ± 0.02 µM TE/µM). Compound 12 also showed significant α-glucosidase inhibitory activity with an IC50 of 56.3 µM (acarbose IC50 of 519.4 µM).
Subject(s)
Antioxidants , Cinnamomum aromaticum , Glycoside Hydrolase Inhibitors , Glycosides , Plant Bark , Plant Extracts , Plant Bark/chemistry , Glycosides/chemistry , Glycosides/pharmacology , Cinnamomum aromaticum/chemistry , Glycoside Hydrolase Inhibitors/chemistry , Glycoside Hydrolase Inhibitors/pharmacology , Antioxidants/chemistry , Antioxidants/pharmacology , Molecular Structure , Plant Extracts/chemistry , Plant Extracts/pharmacology , alpha-Glucosidases/chemistry , alpha-Glucosidases/metabolism , DimerizationABSTRACT
Background: Untargeted metabonomics has provided new insight into the pathogenesis of sarcopenia. In this study, we explored plasma metabolic signatures linked to a heightened risk of sarcopenia in a cohort study by LC-MS-based untargeted metabonomics. Methods: In this nested case-control study from the Adult Physical Fitness and Health Cohort Study (APFHCS), we collected blood plasma samples from 30 new-onset sarcopenia subjects (mean age 73.2 ± 5.6 years) and 30 healthy controls (mean age 74.2 ± 4.6 years) matched by age, sex, BMI, lifestyle, and comorbidities. An untargeted metabolomics methodology was employed to discern the metabolomic profile alterations present in individuals exhibiting newly diagnosed sarcopenia. Results: In comparing individuals with new-onset sarcopenia to normal controls, a comprehensive analysis using liquid chromatography-mass spectrometry (LC-MS) identified a total of 62 metabolites, predominantly comprising lipids, lipid-like molecules, organic acids, and derivatives. Receiver operating characteristic (ROC) curve analysis indicated that the three metabolites hypoxanthine (AUC=0.819, 95% CI=0.711-0.927), L-2-amino-3-oxobutanoic acid (AUC=0.733, 95% CI=0.598-0.868) and PC(14:0/20:2(11Z,14Z)) (AUC= 0.717, 95% CI=0.587-0.846) had the highest areas under the curve. Then, these significant metabolites were observed to be notably enriched in four distinct metabolic pathways, namely, "purine metabolism"; "parathyroid hormone synthesis, secretion and action"; "choline metabolism in cancer"; and "tuberculosis". Conclusion: The current investigation elucidates the metabolic perturbations observed in individuals diagnosed with sarcopenia. The identified metabolites hold promise as potential biomarkers, offering avenues for exploring the underlying pathological mechanisms associated with sarcopenia.