Structural elucidation, binding sites exploration and biological activities of bound phenolics from Radix Puerariae Thomsonii.

Radix puerariae thomsonii (RPT) contains many phenolics and exhibits various health benefits. Although the free phenolics in RPT have been identified, the composition and content of bound phenolics, which account for approximately 20% of the total phenolic content, remain unknown. In this study, 12 compounds were isolated and identified from RPT-bound phenolic extracts, of which 2 were novel and 6 were reported first in RPT. ORAC and PSC antioxidant activities of 12 compounds, as well as their effects on alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), α-glucosidase, and α-amylase were evaluated. Genistein exhibited the highest ORAC activity, while daidzin demonstrated superior PSC activity. Five compounds, including two new compounds, exhibited the ability to activate both ADH and ALDH. All the compounds except 4-hydroxyphenylacetic acid methyl ester and 2,4,4'-trihydroxydeoxybenzoin demonstrated inhibitory effects on α-glucosidase and α-amylase. Alkaline hydrolysis and stepwise enzymatic hydrolysis revealed that bound phenolics in RPT mainly exist within starch.

Redox-Sensitive NiOx Stabilizing Perovskite Films for High-Performance Photovoltaics.

Metal halide perovskite materials inherently possess imperfections, particularly under nonequilibrium conditions, such as exposure to light or heat. To tackle this challenge, we introduced stearate ligand-capped nickel oxide (NiOx), a redox-sensitive metal oxide with variable valence, into perovskite intermediate films. The integration of NiOx improved the efficiency and stability of perovskite solar cells (PSCs) by offering multifunctional roles: (1) chemical passivation for ongoing defect repair, (2) energetic passivation to bolster defect tolerance, and (3) field-effect passivation to mitigate charge accumulation. Employing a synergistic approach that tailored these three passivation mechanisms led to a substantial increase in the devices' efficiencies. The target cell (0.12 cm2) and module (18 cm2) exhibited efficiencies of 24.0 and 22.9%, respectively. Notably, the encapsulated modules maintained almost 100 and 87% of the initial efficiencies after operating for 1100 h at the maximum power point (60 °C, 50% RH) and 2000 h of damp-heat testing (85 °C, 85% RH), respectively. Outdoor real-time tests further validated the commercial viability of the NiOx-assisted PSMs. The proposed passivation strategy provides a practical and uncomplicated approach for fabricating high-efficiency and stable photovoltaics.

Annexin A1 conveys neuroprotective function via inhibiting oxidative stress in diffuse axonal injury of rats.

Diffuse axonal injury (DAI) is a critical pathological facet of traumatic brain injury (TBI). Oxidative stress plays a significant role in the progress of DAI. Annexin A1 (AnxA1) has been demonstrated to benefit from recovery of neurofunctional outcomes after TBI. However, whether AnxA1 exhibits neuronal protective function by modulating oxidative stress in DAI remains unknown. Expression of AnxA1 was evaluated via real-time PCR and western blotting in rat brainstem after DAI. The neurological effect of AnxA1 following DAI through quantification of modified neurologic severity score (mNSS) was compared between wild-type and AnxA1-knockout rats. Brain edema and neuronal apoptosis, as well as expression of oxidative factors and inflammatory cytokines, were analyzed between wild-type and AnxA1 deficiency rats after DAI. Furthermore, mNSS, oxidative and inflammatory cytokines were assayed after timely administration of recombinant AnxA1 for DAI rats. In the brainstem of DAI, the expression of AnxA1 remarkably increased. Ablation of AnxA1 increased the mNSS score and brain water content of rats after DAI. Neuron apoptosis in the brainstem after DAI was exaggerated by AnxA1 deficiency. In addition, AnxA1 deficiency significantly upregulated the level of oxidative and inflammatory factors in the brainstem of DAI rats. Moreover, mNSS decreased by AnxA1 treatment in rats following DAI. Expression of oxidative and inflammatory molecules in rat brainstem subjected to DAI inhibited by AnxA1 administration. AnxA1 exhibited neuronal protective function in the progression of DAI mainly dependent on suppressing oxidative stress and inflammation.

Elaboration and validation of a novelty nomogram for the prognostication of anxiety susceptibility in individuals suffering from low back pain.

Low back pain (LBP) constitutes a distressing emotional ordeal and serves as a potent catalyst for adverse emotional states, notably anxiety. We dedicated to discerning methodologies for identifying patients who are predisposed to heightened levels of anxiety and pain. A self-assessment questionnaire was administered to patients afflicted with LBP. The pain scores were subjected to analysis in conjunction with anxiety scores, and a clustering procedure was executed using the scientific k-means methodology. Subsequently, six machine learning algorithms, including Logistics Regression (LR), K-Nearest Neighbor (KNN), Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGB), were employed. Next, five pertinent variables were identified, namely Age, Course, Body Mass Index (BMI), Education, and Marital status. Furthermore, a LR model was utilized to construct a nomogram, which was subsequently subjected to assessment for discrimination, calibration, and evaluation of its clinical utility. As a result, 599 questionnaires were valid (effective rate: 99 %). The correlation analysis revealed a significant association between anxiety and pain scores (r = 0.31, P < 0.001). LBP patients could be divided into two clusters, Cluster1 had higher pain scores (P < 0.05) and SAS scores (P < 0.001). The proposed nomogram demonstrated an area under the receiver operating characteristics curve (ROC) of 0.841 (95 %CI: 0.804-0.878) and 0.800 (95 %CI: 0.733-0.867) in the training and test groups, respectively. Briefly, the established nomogram has demonstrated remarkable proficiency in discerning individuals afflicted with LBP who are at a heightened risk of experiencing anxiety.

Contact-Electro-Catalysis for Direct Oxidation of Methane under Ambient Conditions.

The conversion of methane under ambient conditions has attracted significant attention. Although advancements have been made using active oxygen species from photo- and electro- chemical processes, challenges such as complex catalyst design, costly oxidants, and unwanted byproducts remain. This study exploits the concept of contact-electro-catalysis, initiating chemical reactions through charge exchange at a solid-liquid interface, to report a novel process for directly converting methane under ambient conditions. Utilizing the electrification of commercially available Fluorinated Ethylene Propylene (FEP) with water under ultrasound, we demonstrate how this interaction promote the activation of methane and oxygen molecules. Our results show that the yield of HCHO and CH3OH can reach 467.5 and 151.2 µmol ⋅ gcat -1, respectively. We utilized electron paramagnetic resonance (EPR) to confirm the evolution of hydroxyl radicals (⋅OH) and superoxide radicals (⋅OOH). Isotope mass spectrometry (MS) was employed to analyze the elemental origin of CH3OH, which can be further oxidized to HCHO. Additionally, we conducted density functional theory (DFT) simulations to assess the reaction energies of FEP with H2O, O2, and CH4 under these conditions. The implications of this methodology, with its potential applicability to a wider array of gas-phase catalytic reactions, underscore a significant advance in catalysis.

Identification of genetic features that are associated with amplitude of low-frequency fluctuation changes in schizophrenia using omics analysis.

Genetic risk for schizophrenia is thought to trigger variation in clinical features of schizophrenia, but biological processes associated with neuronal activity in brain regions remain elusive. In this study, gene expression features were mapped to various sub-regions of the brain by integrating low-frequency amplitude features and gene expression data from the schizophrenia brain and using gene co-expression network analysis of the Allen Transcriptome Atlas of the human brain from six donors to identify genetic features of brain regions and important associations with neuronal features. The results indicate that changes in the dynamic amplitude of low-frequency fluctuation (dALFF) are mainly associated with transcriptome signature factors such as cortical layer synthesis, immune response, and expanded membrane transport. Further modular disease enrichment analysis revealed that the same set of signature genes associated with dALFF levels was enriched for multiple neurological biological processes. Finally, genetic profiling of individual modules identified multiple core genes closely related to schizophrenia, also potentially associated with neuronal activity. Thus, this paper explores genetic features of brain regions in the schizophrenia closely related to low-frequency amplitude ratio levels based on imaging genetics, which suggests structural endophenotypes associated with schizophrenia.

Comprehensive analysis of flavor formation mechanisms in the mechanized preparation Cantonese soy sauce koji using absolute quantitative metabolomics and microbiomics approaches.

Based on the widespread application and under-research of mechanized preparation Cantonese soy sauce koji (MP), absolute quantitative approaches were utilized to systematically analyze the flavor formation mechanism in MP. The results indicated that the enzyme activities increased greatly during MP fermentation, and 4 organic acids, 15 amino acids, and 2 volatiles were identified as significantly different flavor actives. The flavor parameters of MP4 were basically identical to those of MP5. Furthermore, microorganisms were dominated by Staphylococcus, Weissella, and Aspergillus in MP, and their biomass demonstrated an increasing trend. A precise enumeration of microorganisms exposed the inaccuracy of relative quantitative data. Concurrently, Staphylococcus and Aspergillus were positively correlated with numerous enzymes and flavor compounds, and targeted strains for enhancing MP quality. The flavor formation network comprises pathways including carbohydrate metabolism, lipid metabolism and oxidation, and protein degradation and amino acid metabolism. In summary, the fermentation period of MP can be substantially shortened without compromising the product quality. These findings lay the groundwork for refining parameters in modern production processes.

A novel strategy by combining foam fractionation with high-speed countercurrent chromatography for the rapid and efficient isolation of antioxidants and cytostatics from Camellia oleifera cake.

Camellia oleifera cake is a by-product, which is rich in functional chemical components. However, it is typically used as animal feed with no commercial value. The purpose of this study was to isolate and identify compounds from Camellia oleifera cake using a combination of foam fractionation and high-speed countercurrent chromatography (HSCCC) and to investigate their biological activities. Foam fractionation with enhanced drainage through a hollow regular decahedron (HRD) was first established for simultaneously enriching flavonoid glycosides and saponins for further separation of target compounds. Under suitable operating conditions, the introduction of HRD resulted in a threefold increase in enrichment ratio with no negative effect on recovery. A novel elution-extrusion countercurrent chromatography (EECCC) coupled with the consecutive injection mode was established for the successful simultaneous isolation of flavonoid glycosides and saponins. As a result, 38.7 mg of kaemferol-3-O-[2-O-D-glucopyranosyl-6-O-α-L-rhamnopyranosyl]-ß-D-glucopyranoside (purity of 98.17%, FI), 70.8 mg of kaemferol-3-O-[2-O-ß-D-xylopyranosyl-6-O-α-L-rhamnopyranosyl]-ß-D-glucopyranoside (purity of 97.52%, FII), and 560 mg of an oleanane-type saponin (purity of 92.32%, FIII) were separated from the sample (900 mg). The present study clearly showed that FI and II were natural antioxidants (IC50 < 35 µg/mL) without hemolytic effect. FIII displayed the effect of inhibiting Hela cell proliferation (IC50 < 30 µg/mL). Further erythrocyte experiments showed that this correlated with the extremely strong hemolytic effect of FIII. Overall, this study offers a potential strategy for efficient and green isolation of natural products, and is beneficial to further expanding the application of by-products (Camellia oleifera cake) in food, cosmetics, and pharmacy.

Impacts of Aspergillus oryzae 3.042 on the flavor formation pathway in Cantonese soy sauce koji.

To investigate the mechanism of flavor formation during the traditional preparation Cantonese soy sauce koji (TP), the changes of microorganisms, physicochemical properties, and flavor compounds in TP were comprehensively and dynamically monitored by absolute quantitative methods. Results demonstrated that inoculating Aspergillus oryzae 3.042 in TP was crucial role in enhancing enzyme activity properties. Absolute quantification of flavor combined with multivariate statistical analysis yielded 5 organic acids, 15 amino acids, and 2 volatiles as significantly different flavors of TP. Amplicon sequencing and RT-qPCR revealed that the dominant genera were Staphylococcus, Weissella, Enterobacter, Lactic streptococci, Lactobacillus, and Aspergillus, which exhibited a increasing trend in TP. Correlation analysis exhibited that Staphylococcus and Aspergillus were the pivotal genera contributing to the enzyme activities and flavor of TP. The flavor formation network involved lipid and protein degradation, carbohydrate metabolism and other pathways. Simultaneously, TP can appropriately increase the fermentation time to improve product quality.

Long-term abuse of caffeine sodium benzoate induces endothelial cells injury and leads to coagulation dysfunction.

Our hospital admitted a patient who had difficulty in coagulation even after blood replacement, and the patient had abused caffeine sodium benzoate (CSB) for more than 20 years. Hence, we aimed to explore whether CSB may cause dysfunction in vascular endothelial cells and its possible mechanism. Low, medium, and high concentrations of serum of long-term CSB intake patients were used to treat HUVECs, with LPS as the positive control. MTT and CCK8 were performed to verify CSB's damaging effect on HUVECs. The expression of ET-1, ICAM-1, VCAM-1, and E-selectin were measured by ELISA. TUNEL assay and Matrigel tube formation assay were carried out to detect apoptosis and angiogenesis of HUVECs. Flow cytometry was applied to analyze cell cycles and expression of CD11b, PDGF, and ICAM-1. Expression of PDGF-BB and PCNA were examined by western blot. The activation of MAPK signaling pathway was detected by qRT-PCR and western blot. Intracellular Ca2+ density was detected by fluorescent probes. CCK8 assay showed high concentration of CSB inhibited cell viability. Cell proliferation and angiogenesis were inhibited by CSB. ET-1, ICAM-1, VCAM-1, and E-selectin upregulated in CSB groups. CSB enhanced apoptosis of HUVECs. CD11b, ICAM-1 increased and PDGF reduced in CSB groups. The expression level and phosphorylation level of MEK, ERK, JUN, and p38 in MAPK pathway elevated in CSB groups. The expression of PCNA and PDGF-BB was suppressed by CSB. Intracellular Ca2+ intensity was increased by CSB. Abuse of CSB injured HUVECs and caused coagulation disorders.

Effects and plasma proteomic analysis of GLP-1RA versus CPA/EE, in combination with metformin, on overweight PCOS women: a randomized controlled trial.

PURPOSE: Polycystic ovary syndrome (PCOS) is characterized by reproductive dysfunctions and metabolic disorders. This study aims to compare the therapeutic effectiveness of glucagon-like peptide-1 receptor agonist (GLP-1RA) + Metformin (Met) versus cyproterone acetate/ethinylestradiol (CPA/EE) + Met in overweight PCOS women and identify potential proteomic biomarkers of disease risk in women with PCOS. METHODS: In this prospective, open-label randomized controlled trial, we recruited 60 overweight PCOS women into two groups at a 1:1 ratio to receive CPA/EE (2 mg/day: 2 mg cyproterone acetate and 35-µg ethinylestradiol,) +Met (1500 mg/day) or GLP-1 RA (liraglutide, 1.2-1.8 mg/day) +Met (1500 mg/day) for 12 weeks. The clinical effectiveness and adverse effects were evaluated, followed by plasma proteomic analysis and verification of critical biomarkers by ELISA. RESULTS: Eighty(80%) patients completed the study. Both interventions improved menstrual cycle, polycystic ovaries, LH(luteinizing hormone) and HbA1c(hemoglobin A1c) levels after the 12-week treatment. GLP-1RA + Met was more effective than CPA/EE + Met in reducing body weight, BMI (Body Mass Index), and waist circumference, FBG(fasting blood glucose), AUCI(area under curve of insulin),TC (Total Cholesterol), IL-6(Interleukin-6) and improving insulin sensitivity, and ovulation in overweight women with PCOS, with acceptable short-term side effects. CPA/EE + Met was more effective in improving hyperandrogenemia, including T(total testosterone), LH, LH/FSH(Luteinizing hormone/follicle-stimulating hormone), SHBG(sex hormone-binding globulin) and FAI (free androgen index). By contract, GLP-1RA+Met group only improved LH. Plasma proteomic analysis revealed that the interventions altered proteins involved in reactive oxygen species detoxification (PRDX6, GSTO1, GSTP1, GSTM2), platelet degranulation (FN1), and the immune response (SERPINB9). CONCLUSIONS: Both CPA/EE+Met and GLP-1RA + Met treatment improved reproductive functions in overweight PCOS women. GLP-1RA + Met was more effective than CPA/EE + Met in reducing body weight, BMI, and waist, and improving metabolism, and ovulation in overweight women with PCOS, with acceptable short-term side effects. CPA/EE + Met was more effective in reducing hyperandrogenemia. The novel plasma biomarkers PRDX6, FN1, and SERPINB9, might be indicators and targets for PCOS treatment. TRIAL REGISTRATION CLINICALTIALS. GOV TRIAL NO: NCT03151005. Registered 12 May, 2017, https://clinicaltrials.gov/ct2/show/NCT03151005 .

Instability in a carbon pool driven by multiple dissolved organic matter sources in a eutrophic lake basin: Potential factors for increased greenhouse gas emissions.

Lakes serve as vital reservoirs of dissolved organic matter (DOM) and play pivotal roles in biogeochemical carbon cycles. However, the sources and compositions of DOM in freshwater lakes and their potential effects on lake sediment carbon pools remain unclear. In this study, seven inflowing rivers in the Lake Taihu basin were selected to explore the potential effects of multi-source DOM inputs on the stability of the lake sediment carbon pool. The results showed the high concentrations of dissolved organic carbon in the Lake Taihu basin, accompanied by a high complexity level. Lignins constituted the majority of DOM compounds, surpassing 40% of the total, while the organic carbon content was predominantly composed of humic acids (1.02-3.01 g kg-1). The high amounts of lignin oxidative cleavage led to CHO being the main molecular structure in the DOM of the seven rivers. The carbon constituents within the sediment carbon reservoir exhibited a positive correlation with dissolved CH4 and CO2, with a notable emphasis on humic acid and dissolved CH4 (R2 = 0.86). The elevated concentration of DOM, coupled with its intricate composition, contributed to the increases in dissolved greenhouse gases (GHGs). Experiments showed that the mixing of multi-source DOM can accelerate the organic carbon mineralization processes. The unit carbon emission efficiency was highest in the mixed group, reaching reached 160.9 µmol∙Cg-1, which also exhibited a significantly different carbon pool. The mixed decomposition of DOM from different sources influenced the roles of the lake carbon pool as source and sink, indicating that the multi-source DOM of this lake basin was a potential driving factor for increased carbon emissions. These findings have improved our understanding of the sources and compositions of DOM in lake basins and revealed their impacts on carbon emissions, thereby providing a theoretical basis for improving assessments of lake carbon emissions.

Foam and fluid properties of purified saponins and non-purified water extracts from Camellia oleifera cake (by-product).

The physicochemical and foam properties of non-purified water extracts (WE) and purified tea saponins (TS) from Camellia oleifera cake (byproduct) were compared. WE showed different fluid properties at equal saponin concentrations (1.0 wt%) compared to TS. Particularly, it exhibited limited micelle size (average 434.1 nm), effective viscosity (0.15 Pa·s), and surface tension (43.9 mN/m) independently of pH. Moreover, the foam properties of WE were comparable to TS and better than sodium caseinate, especially foam stability. WE foam was more stable than TS foam under pH (3-7) and heating (40-80 °C). In the presence of NaCl, sucrose, and ethanol (5-20 wt%), WE and TS were effective and had similar foam behavior. Low concentrations of sucrose (<10 wt%)/ethanol (<20 wt%) significantly increased the foam capacity, while ethanol over 30 wt% was unfavorable. WE/TS foam contributes significantly to the desired physicochemical and sensory attributes (taste, texture, and appearance) of foods.

Construction of a clinical prediction model for the impact of acupuncture on pregnancy outcomes in poor ovarian response (POR) patients based on a patient registry research platform. / åŸºäºŽç— ä¾‹æ³¨å†Œç™»è®°ç ”ç©¶å¹³å°æž„å»ºé’ˆç¸å¯¹åµå·¢ä½Žååº”æ‚£è€ å¦Šå¨ ç»“å±€çš„ä¸´åºŠé¢„æµ‹æ¨¡åž‹.

OBJECTIVES: To construct a clinical prediction model for the impact of acupuncture on pregnancy outcomes in poor ovarian response (POR) patients, providing insights and methods for predicting pregnancy outcomes in POR patients undergoing acupuncture treatment. METHODS: Clinical data of 268 POR patients (2 cases were eliminated) primarily treated with "thirteen needle acupuncture for Tiaojing Cuyun (regulating menstruation and promoting pregnancy)" was collected from the international patient registry platform of acupuncture moxibustion (IPRPAM) from September 19, 2017 to April 30, 2023, involving 24 clinical centers including Acupuncture-Moxibustion Hospital of China Academy of Chinese Medical Sciences. LASSO and univariate Cox regression were used to screen factors influencing pregnancy outcomes, and a multivariate Cox regression model was established based on the screening results. The best model was selected using the Akaike information criterion (AIC), and a nomogram for clinical pregnancy prediction was constructed. The prediction model was evaluated using receiver operating characteristic (ROC) curves and calibration curves, and internal validation was performed using the Bootstrap method. RESULTS: (1) Age, level of anti-Müllerian hormone (AMH), and total treatment numbers of acupuncture were independent predictors of pregnancy outcomes in POR patients receiving acupuncture (P<0.05). (2) The AIC value of the best subset-Cox multivariate model (560.6) was the smallest, indicating it as the optimal model. (3) The areas under curve (AUCs) of the clinical prediction model after 6, 12, 24, and 36 months treatment were 0.627, 0.719, 0.770, and 0.766, respectively, and in the validation group, they were 0.620, 0.704, 0.759, and 0.765, indicating good discrimination and repeatability of the prediction model. (4) The calibration curve showed that the prediction curve of the clinical prediction model was close to the ideal model's prediction curve, indicating good calibration of the prediction model. CONCLUSIONS: The clinical prediction model for the impact of acupuncture on pregnancy outcomes in POR patients based on the IPRPAM platform has good clinical application value and provides insights into predicting pregnancy outcomes in POR patients undergoing acupuncture treatment.

Dissecting the mediating and moderating effects of depression on the associations between traits and coronary artery disease: A two-step Mendelian randomization and phenome-wide interaction study

Background: Depression is often present concurrently with coronary artery disease (CAD), a disease with which it shares many risk factors. However, the manner in which depression mediates and moderates the association between traits (including biomarkers, anthropometric indicators, lifestyle behaviors, etc.) and CAD is largely unknown. Methods: In our causal mediation analyses using two-step Mendelian randomization (MR), univariable MR was first used to investigate the causal effects of 108 traits on liability to depression and CAD. The traits with significant causal effects on both depression and CAD, but not causally modulated by depression, were selected for the second-step analyses. Multivariable MR was used to estimate the direct effects (independent of liability to depression) of these traits on CAD, and the indirect effects (mediated via liability to depression) were calculated. To investigate the moderating effect of depression on the association between 364 traits and CAD, a cross-sectional phenome-wide interaction study (PheWIS) was conducted in a study population from UK Biobank (UKBB) (N=275,257). Additionally, if the relationship between traits and CAD was moderated by both phenotypic and genetically predicted depression at a suggestive level of significance (Pinteraction≤0.05) in the PheWIS, the results were further verified by a cohort study using Cox proportional hazards regression. Results: Univariable MR indicated that 10 of 108 traits under investigation were significantly associated with both depression and CAD, which showed a similar direct effect compared to the total effect for most traits. However, the traits “drive faster than speed limit” and “past tobacco smoking” were both exceptions, with the proportions mediated by depression at 24.6% and 7.2%, respectively. (AU)

Spatiotemporal Patterns of Hospitalizations Among Older Adults With Co-Presence of Cancer and Dementia in US Counties: 2013-2018.

We assessed the spatiotemporal patterns of hospitalization with comorbid cancer and dementia. Using the 2013-2018 inpatient claims data for Medicare fee-for-service (FFS) beneficiaries, we calculated hospitalization rates by dividing the total admissions from individuals with the co-presence of a major cancer (breast, prostate, lung, and colorectal) and dementia diagnoses with the total counts of FFS beneficiaries aged 65 or older. We identified 22 hotspots with high hospitalization rates that showed heterogeneous spatial and temporal utilization patterns. The odds of a county being a hotspot increased significantly with the county-level percentage of dual Medicare-Medicaid beneficiaries (aOR 1.05; 95% CI: 1.04-1.07) and the prevalence of cancer (aOR 1.73; 95% CI: 1.59-1.89), while decreased significantly with increasing degree of rurality (aOR .82; 95% CI: .79-.85) and decreased yearly over time (aOR .72; 95% CI: .68-.75). The identified hotspots and factors at the county-level may help understand healthcare utilization patterns and assess resource allocation for this unique patient group.

Multi-View Graph Contrastive Learning via Adaptive Channel Optimization for Depression Detection in EEG Signals.

Automated detection of depression using Electroencephalogram (EEG) signals has become a promising application in advanced bioinformatics technology. Although current methods have achieved high detection performance, several challenges still need to be addressed: (1) Previous studies do not consider data redundancy when modeling multi-channel EEG signals, resulting in some unrecognized noise channels remaining. (2) Most works focus on the functional connection of EEG signals, ignoring their spatial proximity. The spatial topological structure of EEG signals has not been fully utilized to capture more fine-grained features. (3) Prior depression detection models fail to provide interpretability. To address these challenges, this paper proposes a new model, Multi-view Graph Contrastive Learning via Adaptive Channel Optimization (MGCL-ACO) for depression detection in EEG signals. Specifically, the proposed model first selects the critical channels by maximizing the mutual information between tracks and labels of EEG signals to eliminate data redundancy. Then, the MGCL-ACO model builds two similarity metric views based on functional connectivity and spatial proximity. MGCL-ACO constructs the feature extraction module by graph convolutions and contrastive learning to capture more fine-grained features of different perspectives. Finally, our model provides interpretability by visualizing a brain map related to the significance scores of the selected channels. Extensive experiments have been performed on public datasets, and the results show that our proposed model outperforms the most advanced baselines. Our proposed model not only provides a promising approach for automated depression detection using optimal EEG signals but also has the potential to improve the accuracy and interpretability of depression diagnosis in clinical practice.

Cost-effectiveness of physical activity interventions for prevention and management of cognitive decline and dementia-a systematic review.

BACKGROUND: Although increasing physical activity (PA) has been suggested to prevent and manage cognitive decline and dementia, its economic impact on healthcare systems and society is largely unknown. This study aimed to summarize evidence on the cost-effectiveness of PA interventions to prevent and manage cognitive decline and dementia. METHODS: Electronic databases, including PubMed/MEDLINE, Embase, and ScienceDirect, were searched from January 2000 to July 2023. The search strategy was driven by a combination of subject-heading terms related to physical activity, cognitive function, dementia, and cost-effectiveness. Selected studies were included in narrative synthesis, and extracted data were presented in narrative and tabular forms. The risk of bias in each study was assessed using the Consolidated Health Economic Evaluation Reporting Standards and Consensus on Health Economic Criteria list. RESULTS: Five of the 11 identified studies focused on individuals with existing dementia. Six of the 11 identified studies focused on individuals with no existing dementia, including 3 on those with mild cognitive impairment (MCI), and 3 on those with no existing MCI or dementia. PA interventions focused on individuals with no existing dementia were found to be cost-effective compared to the control group. Findings were mixed for PA interventions implemented in individuals with existing dementia. CONCLUSIONS: PA interventions implemented before or during the early stage of cognitive impairment may be cost-effective in reducing the burden of dementia. More research is needed to investigate the cost-effectiveness of PA interventions in managing dementia. Most existing studies used short-term outcomes in evaluating the cost-effectiveness of PA interventions in the prevention and management of dementia; future research should consider adding long-term outcomes to strengthen the study design.

Actionable insights into hazard mitigation of typical 3D printing waste via pyrolysis.

3D printing waste (3DPW) contains hazardous substances, such as photosensitizers and pigments, and may cause environmental pollution when improperly disposed of. Pyrolysis treatment can reduce hazards and turn waste into useful resources. This study coupled thermogravimetric (TG), TG-Fourier transform infrared spectroscopy-gas chromatography/mass spectrometry, and rapid pyrolysis gas chromatography/mass spectrometry analysis to evaluate the pyrolytic reaction mechanisms, products, and possible decomposition pathways of the three typical 3DPW of photosensitive resin waste (PRW), polyamide waste (PAW), and polycaprolactone waste (PCLW). The main degradation stages of the typical 3DPW occurred at 320-580 °C. The most appropriate reaction mechanisms of PRW, PAW and PCLW were D1, A1.2 and A1.5, respectively. The main pyrolysis processes were the decomposition of the complex organic polymers of PRW, the breaking of the NH-CH2 bond and dehydration of -CO-NH- of PAW, and the breaking and reorganization of the molecular chains of PCLW, mainly resulting in toluene (C7H8), undecylenitrile (C11H21N), tetrahydrofuran (C4H8O), respectively. Unlike the slow pyrolysis, the rapid pyrolysis produced volatiles consisting mainly of phenol, 4,4'-(1-methylethylidene)bis- (C15H16O2) for PRW; 1,10-dicyanodecane (C12H20N2) for PAW; and ɛ-caprolactone (C6H10O2) for PCLW. These pyrolysis products hold great potential for applications. The findings of the study offer actionable insights into the hazard reduction and resource recovery of 3D printing waste.

Dissecting the mediating and moderating effects of depression on the associations between traits and coronary artery disease: A two-step Mendelian randomization and phenome-wide interaction study.

Background: Depression is often present concurrently with coronary artery disease (CAD), a disease with which it shares many risk factors. However, the manner in which depression mediates and moderates the association between traits (including biomarkers, anthropometric indicators, lifestyle behaviors, etc.) and CAD is largely unknown. Methods: In our causal mediation analyses using two-step Mendelian randomization (MR), univariable MR was first used to investigate the causal effects of 108 traits on liability to depression and CAD. The traits with significant causal effects on both depression and CAD, but not causally modulated by depression, were selected for the second-step analyses. Multivariable MR was used to estimate the direct effects (independent of liability to depression) of these traits on CAD, and the indirect effects (mediated via liability to depression) were calculated. To investigate the moderating effect of depression on the association between 364 traits and CAD, a cross-sectional phenome-wide interaction study (PheWIS) was conducted in a study population from UK Biobank (UKBB) (N=275,257). Additionally, if the relationship between traits and CAD was moderated by both phenotypic and genetically predicted depression at a suggestive level of significance (Pinteraction≤0.05) in the PheWIS, the results were further verified by a cohort study using Cox proportional hazards regression. Results: Univariable MR indicated that 10 of 108 traits under investigation were significantly associated with both depression and CAD, which showed a similar direct effect compared to the total effect for most traits. However, the traits "drive faster than speed limit" and "past tobacco smoking" were both exceptions, with the proportions mediated by depression at 24.6% and 7.2%, respectively. In the moderation analyses, suggestive evidence of several traits was found for moderating effects of phenotypic depression or susceptibility to depression, as estimated by polygenic risk score, including chest pain when hurrying, reason of smoking quitting and weight change. Consistent results were observed in survival analyses and Cox regression. Conclusion: The independent role of traits in CAD pathogenesis regardless of depression was highlighted in our mediation analyses, and the moderating effects of depression observed in our study may be helpful for CAD risk stratification and optimized allocation of scarce medical resources.