Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality.

Sleep is essential to life. Accurate measurement and classification of sleep/wake and sleep stages is important in clinical studies for sleep disorder diagnoses and in the interpretation of data from consumer devices for monitoring physical and mental well-being. Existing non-polysomnography sleep classification techniques mainly rely on heuristic methods developed in relatively small cohorts. Thus, we aimed to establish the accuracy of wrist-worn accelerometers for sleep stage classification and subsequently describe the association between sleep duration and efficiency (proportion of total time asleep when in bed) with mortality outcomes. We developed a self-supervised deep neural network for sleep stage classification using concurrent laboratory-based polysomnography and accelerometry. After exclusion, 1448 participant nights of data were used for training. The difference between polysomnography and the model classifications on the external validation was 34.7 min (95% limits of agreement (LoA): -37.8-107.2 min) for total sleep duration, 2.6 min for REM duration (95% LoA: -68.4-73.4 min) and 32.1 min (95% LoA: -54.4-118.5 min) for NREM duration. The sleep classifier was deployed in the UK Biobank with 100,000 participants to study the association of sleep duration and sleep efficiency with all-cause mortality. Among 66,214 UK Biobank participants, 1642 mortality events were observed. Short sleepers (<6 h) had a higher risk of mortality compared to participants with normal sleep duration of 6-7.9 h, regardless of whether they had low sleep efficiency (Hazard ratios (HRs): 1.58; 95% confidence intervals (CIs): 1.19-2.11) or high sleep efficiency (HRs: 1.45; 95% CIs: 1.16-1.81). Deep-learning-based sleep classification using accelerometers has a fair to moderate agreement with polysomnography. Our findings suggest that having short overnight sleep confers mortality risk irrespective of sleep continuity.

An antifouling epoxy coated metal surface containing silica-immobilized carbonic anhydrase supraparticles for CO2 capture through microalgae.

Carbonic anhydrase (CA) has a promising application as a green and efficient biocatalyst for CO2 capture, and many successful cases of immobilizing CA have been reported. However, CA antifouling coatings on metal for CO2 sequestration have rarely been reported. Herein, dimeric CA from Sulfurihydrogenibium azorense (SazCA) with a ferritin tag, which was prepared by low-speed centrifugation with high yield, was adopted as a free enzyme and encapsulated in the sol-gel silica. The silica-immobilized CAs were dispersed into the commercialized metal-antifouling epoxy resin paint to obtain CA coated nickel foams, which had excellent stability, with 90 % and 67 % residual activity after 28 days of incubation at 30 °C and 60 °C, respectively. The CA coated nickel foams remained 60 % original activity after 6 cycles of use within 28 days. Then, a CA-microalgae carbon capture device was constructed using the CA coated nickel foams and Chlorella. The growth rate of Chlorella was significantly increased and the biomass of Chlorella increased by 29 % compared with control after 7 days of incubation. Due to the simple and cost-effective preparation process, sustainable and efficient CO2 absorption, this easy-to-scale up CA coated nickel foam has great potential in CA assisted microalgae-based CO2 capture and carbon neutrality.

Comparative efficacy and safety of ginkgo-based Chinese patent medicines in patients with hypertension: A systematic review and network meta-analysis of randomized clinical trials.

BACKGROUND: The efficacy and safety of different oral ginkgo-based Chinese patent medicines (CPMs) regimens for hypertension patients were analyzed based on the network meta-analysis of the frequency framework. METHODS: We conducted a comprehensive search of PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure, Wanfang, China Science and Technology Journal Database, and Chinese Biomedical Literature Database to gather data on randomized controlled trials (RCTs) evaluating the efficacy of 8 ginkgo biloba oral preparations for the treatment of hypertension. The trials included in the analysis were conducted from the inception of the databases up to September 2023. Methodological quality and risk of bias were assessed using the RoB 2.0 evaluation tool, and a reticulated meta-analysis was conducted using STATA MP 14 software. The RCTs included in this study were published studies and therefore did not require ethics committee review or patient consent. RESULTS: We ultimately included 46 RCTs covering 8 CPMs including ginkgo biloba tablet (GBT), GB capsule (GBC), ginkgo biloba drop (GBD), ginkgo biloba ketone ester drop, Fufangyinxing capsule, fufangyinxingtongmai oral liquid, Yinxingmihuan oral liquid, Yindanxinanotong softgel capsule (YDXNT). GBD + CT demonstrated the highest effectiveness in reducing systolic blood pressure (surface under the cumulative ranking [SUCRA] = 78.7%) and improving total effective rate (SUCRA = 86.7%). GBC + CT exhibited the greatest efficacy in reducing diastolic blood pressure (SUCRA = 92.6%). GBT + CT was identified as the most effective in lowering total cholesterol (TC) (SUCRA = 100%). Additionally, YDXNT + CT demonstrated notable improvements in triglyceride levels (SUCRA = 92.2%), Nitric oxide (NO) (SUCRA = 93.9%), and ET-1 (SUCRA = 67.5%). In terms of safety, 14 studies reported the occurrence of adverse reactions with a high degree of clinical heterogeneity, which was only qualitatively analyzed in this study. CONCLUSION SUBSECTIONS: We found that a combination of 8 ginkgo-based CPMs + CT was effective in hypertension compared with CT. The evidence showed that GBD + CT were the best in improving systolic blood pressure and total effective rate, GBC + CT improved diastolic blood pressure, GBT + CT were the most effective in improving TC, and YDXNT + CT was the most effective in improving TG, NO, and ET-1. Adverse effects were only analyzed qualitatively, and the number of adverse effects of CPMs treatment was relatively low compared to CT. In addition, the quality of the literature included in the study was low, and further validation through RCTs with larger sample sizes, higher quality, and more rigorously designed is needed.

DDX39B protects against sorafenib-induced ferroptosis by facilitating the splicing and cytoplasmic export of GPX4 pre-mRNA in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the main histological subtype of primary liver cancer and remains one of the most common solid malignancies globally. Ferroptosis was recently defined as an iron-catalyzed form of regulated necrosis. Because cancer cells exhibit higher iron requirements than noncancer cells, treatment with ferroptosis-inducing compounds may be a feasible strategy for cancer therapy. However, cancer cells develop acquired resistance to evade ferroptosis, and the mechanisms responsible for ferroptosis resistance are not fully clarified. In the current study, we reported that DDX39B was downregulated during sorafenib-induced ferroptosis in a dose- and time-dependent manner. Exogenous introduction of DDX39B ensured the survival of HCC cells upon exposure to sorafenib, while the opposite phenomenon was observed in DDX39B-silenced HCC cells. Mechanistically, we demonstrated that DDX39B increased GPX4 levels by promoting the splicing and cytoplasmic translocation of GPX4 pre-mRNA, which was sufficient to detoxify sorafenib-triggered excess lipid ROS production, lipid peroxidation accumulation, ferrous iron levels, and mitochondrial damage. Inhibition of DDX39B ATPase activity by CCT018159 repressed the splicing and cytoplasmic export of GPX4 pre-mRNA and synergistically assisted sorafenib-induced ferroptotic cell death in HCC cells. Taken together, our data uncover a novel role for DDX39B in ferroptosis resistance by modulating the maturation of GPX4 mRNA via a posttranscriptional approach and suggest that DDX39B inhibition may be a promising therapeutic strategy to enhance the sensitivity and vulnerability of HCC cells to sorafenib.

Metal-Organic Frameworks/Heterojunction Structures for Surface-Enhanced Raman Scattering with Enhanced Sensitivity and Tailorability.

Metal-organic frameworks (MOFs), which are composed of crystalline microporous materials with metal ions, have gained considerable interest as promising substrate materials for surface-enhanced Raman scattering (SERS) detection via charge transfer. Research on MOF-based SERS substrates has advanced rapidly because of the MOFs' excellent structural tunability, functionalizable pore interiors, and ultrahigh surface-to-volume ratios. Compared with traditional noble metal SERS plasmons, MOFs exhibit better biocompatibility, ease of operation, and tailorability. However, MOFs cannot produce a sufficient limit of detection (LOD) for ultrasensitive detection, and therefore, developing an ultrasensitive MOF-based SERS substrate is imperative. To the best of our knowledge, this is the first study to develop an MOFs/heterojunction structure as an SERS enhancing material. We report an in situ ZIF-67/Co(OH)2 heterojunction-based nanocellulose paper (nanopaper) plate (in situ ZIF-67 nanoplate) as a device with an LOD of 0.98 nmol/L for Rhodamine 6G and a Raman enhancement of 1.43 × 107, which is 100 times better than that of the pure ZIF-67-based SERS substrate. Further, we extend this structure to other types of MOFs and develop an in situ HKUST-1 nanoplate (with HKUST-1/Cu(OH)2). In addition, we demonstrate that the formation of heterojunctions facilitates efficient photoinduced charge transfer for SERS detection by applying the Mx(OH)y-assisted (where M = Co, Cu, or other metals) MOFs/heterojunction structure. Finally, we successfully demonstrate the application of medicine screening on our nanoplates, specifically for omeprazole. The nanoplates we developed still maintain the tailorability of MOFs and perform high anti-interference ability. Our approach provides customizing options for MOF-based SERS detection, catering to diverse possibilities in future research and applications.

PPARγ regulates osteoarthritis chondrocytes apoptosis through caspase-3 dependent mitochondrial pathway.

Osteoarthritis (OA) is the most prevalent form of arthritis, characterized by a complex pathogenesis. One of the key factors contributing to its development is the apoptosis of chondrocytes triggered by oxidative stress. Involvement of peroxisome proliferator-activated receptor gamma (PPARγ) has been reported in the regulation of oxidative stress. However, there remains unclear mechanisms that through which PPARγ influences the pathogenesis of OA. The present study aims to delve into the role of PPARγ in chondrocytes apoptosis induced by oxidative stress in the context of OA. Primary human chondrocytes, both relatively normal and OA, were isolated and cultured for the following study. Various assessments were performed, including measurements of cell proliferation, viability and cytotoxicity. Additionally, we examined cell apoptosis, levels of reactive oxygen species (ROS), nitric oxide (NO), mitochondrial membrane potential (MMP) and cytochrome C release. We also evaluated the expression of related genes and proteins, such as collagen type II (Col2a1), aggrecan, inducible nitric oxide synthase (iNOS), caspase-9, caspase-3 and PPARγ. Compared with relatively normal cartilage, the expression of PPARγ in OA cartilage was down-regulated. The proliferation of OA chondrocytes decreased, accompanied by an increase in the apoptosis rate. Down-regulation of PPARγ expression in OA chondrocytes coincided with an up-regulation of iNOS expression, leading to increased secretion of NO, endogenous ROS production, and decrease of MMP levels. Furthermore, we observed the release of cytochrome C, elevated caspase-9 and caspase-3 activities, and reduction of the components of extracellular matrix (ECM) Col2a1 and aggrecan. Accordingly, utilization of GW1929 (PPARγ Agonists) or Z-DEVD-FMK (caspase-3 inhibitor) can protect chondrocytes from mitochondrial-related apoptosis and alleviate the progression of OA. During the progression of OA, excessive oxidative stress in chondrocytes leads to apoptosis and ECM degradation. Activation of PPARγ can postpone OA by down-regulating caspase-3-dependent mitochondrial apoptosis pathway.

Automatic offline-capable smartphone paper-based microfluidic device for efficient biomarker detection of Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative disease with no effective treatment. Efficient and rapid detection plays a crucial role in mitigating and managing AD progression. Deep learning-assisted smartphone-based microfluidic paper analysis devices (µPADs) offer the advantages of low cost, good sensitivity, and rapid detection, providing a strategic pathway to address large-scale disease screening in resource-limited areas. However, existing smartphone-based detection platforms usually rely on large devices or cloud servers for data transfer and processing. Additionally, the implementation of automated colorimetric enzyme-linked immunoassay (c-ELISA) on µPADs can further facilitate the realization of smartphone µPADs platforms for efficient disease detection. RESULTS: This paper introduces a new deep learning-assisted offline smartphone platform for early AD screening, offering rapid disease detection in low-resource areas. The proposed platform features a simple mechanical rotating structure controlled by a smartphone, enabling fully automated c-ELISA on µPADs. Our platform successfully applied sandwich c-ELISA for detecting the ß-amyloid peptide 1-42 (Aß 1-42, a crucial AD biomarker) and demonstrated its efficacy in 38 artificial plasma samples (healthy: 19, unhealthy: 19, N = 6). Moreover, we employed the YOLOv5 deep learning model and achieved an impressive 97 % accuracy on a dataset of 1824 images, which is 10.16 % higher than the traditional method of curve-fitting results. The trained YOLOv5 model was seamlessly integrated into the smartphone using the NCNN (Tencent's Neural Network Inference Framework), enabling deep learning-assisted offline detection. A user-friendly smartphone application was developed to control the entire process, realizing a streamlined "samples in, answers out" approach. SIGNIFICANCE: This deep learning-assisted, low-cost, user-friendly, highly stable, and rapid-response automated offline smartphone-based detection platform represents a good advancement in point-of-care testing (POCT). Moreover, our platform provides a feasible approach for efficient AD detection by examining the level of Aß 1-42, particularly in areas with low resources and limited communication infrastructure.

Bioinspired Colorimetric Double Inverse Opal Photonic Crystal Indicators for Ethanol Concentration Sensing in Fermentation Engineering.

Photonic crystal-based ethanol concentration indicators with rapid response and brilliant structural color output definitely take a place in colorimetric sensors. Here, based on the H-bond-regulated swelling of acrylate shape memory polymers (SMPs) and the solvent-induced structural color change of the double inverse opal photonic crystals (DIOPCs), new-type photonic crystals (PCs) colorimetric indicators were constructed, exhibiting a span of maximum reflection wavelength (λmax) up to ∼166 nm in response to alcohols with concentrations from 0 to 100 vol %. DIOPC indicators (DIOPCIs) show a rapid response to alcohols (<1.5 s) and output different structural colors (covering from blue to red). The colorimetric sensing mechanism includes the solvent-triggered recovery of the inverse opal skeleton, the cosolvency effect and H-bonds induced swelling/shrinkage of the polymer, the phase separation between polystyrene (PS) microsphere and polymer skeleton, and the light diffraction of DIOPCs. While ensuring a larger λmax span by regulating the H-bond interactions in polymer chains through acrylamide (AAm), AAm-modified DIOPCIs are sensitive to some specific ethanol concentrations. The real-time sensing of ethanol concentration during fermentation verified the practicability of DIOPCIs, thus establishing a visual model between structural color and corresponding fermentation kinetics. We envisage that the DIOPCIs will contribute to the intelligentization of the alcoholic fermentation and distillation industry.

Localization of Chiral Edge States by the Non-Hermitian Skin Effect.

Quantum Hall systems host chiral edge states extending along the one-dimensional boundary of any two-dimensional sample. In solid state materials, the edge states serve as perfectly robust transport channels that produce a quantized Hall conductance; due to their chirality, and the topological protection by the Chern number of the bulk band structure, they cannot be spatially localized by defects or disorder. Here, we show experimentally that the chiral edge states of a lossy quantum Hall system can be localized. In a gyromagnetic photonic crystal exhibiting the quantum Hall topological phase, an appropriately structured loss configuration imparts the edge states' complex energy spectrum with a feature known as point-gap winding. This intrinsically non-Hermitian topological invariant is distinct from the Chern number invariant of the bulk (which remains intact) and induces mode localization via the "non-Hermitian skin effect." The interplay of the two topological phenomena-the Chern number and point-gap winding-gives rise to a non-Hermitian generalization of the paradigmatic Chern-type bulk-boundary correspondence principle. Compared to previous realizations of the non-Hermitian skin effect, the skin modes in this system have superior robustness against local defects and disorders.

Self-supervised learning for human activity recognition using 700,000 person-days of wearable data.

Accurate physical activity monitoring is essential to understand the impact of physical activity on one's physical health and overall well-being. However, advances in human activity recognition algorithms have been constrained by the limited availability of large labelled datasets. This study aims to leverage recent advances in self-supervised learning to exploit the large-scale UK Biobank accelerometer dataset-a 700,000 person-days unlabelled dataset-in order to build models with vastly improved generalisability and accuracy. Our resulting models consistently outperform strong baselines across eight benchmark datasets, with an F1 relative improvement of 2.5-130.9% (median 24.4%). More importantly, in contrast to previous reports, our results generalise across external datasets, cohorts, living environments, and sensor devices. Our open-sourced pre-trained models will be valuable in domains with limited labelled data or where good sampling coverage (across devices, populations, and activities) is hard to achieve.

A universal plasma metabolites-derived signature predicts cardiovascular disease risk in MAFLD.

BACKGROUND: Metabolic associated fatty liver disease (MAFLD) is a novel concept proposed in 2020, which is more practical for identifying patients with fatty liver disease with high risk of disease progression. Fatty liver is a driver for extrahepatic complications, particularly cardiovascular diseases (CVD). Although the risk of CVD in MAFLD could be predicted by carotid ultrasound test, a very early stage prediction method before the formation of pathological damage is still lacking. METHODS: Stool microbiomes and plasma metabolites were compared across 196 well-characterized participants encompassing normal controls, simple MAFLD patients, MAFLD patients with carotid artery pathological changes, and MAFLD patients with diagnosed coronary artery disease (CAD). 16S rDNA sequencing data and untargeted metabolomic profiles were interrogatively analyzed using differential abundance analysis and random forest (RF) machine learning algorithm to identify discriminatory gut microbiomes and metabolomic. RESULTS: Characteristic microbial changes in MAFLD patients with CVD risk were represented by the increase of Clostridia and Firmicutes-to-Bacteroidetes ratios. Faecalibacterium was negatively correlated with mean-intima-media thickness (IMT), TC, and TG. Megamonas, Bacteroides, Parabacteroides, and Escherichia were positively correlated with the exacerbation of pathological indexes. MAFLD patients with CVD risk were characterized by the decrease of lithocholic acid taurine conjugate, and the increase of ethylvanillin propylene glycol acetal, both of which had close relationship with Ruminococcus and Gemmiger. Biotin l-sulfoxide had positive correlation with mean-IMT, TG, and weight. The general auxin pesticide beta-naphthoxyacetic acid and the food additive glucosyl steviol were both positively correlated with the increase of mean-IMT. The model combining the metabolite signatures with 9 clinical parameters accurately distinguished MAFLD with CVD risk in the proband and validation cohort. It was found that citral was the most important discriminative metabolite marker, which was validated by both in vitro and in vivo experiments. CONCLUSIONS: Simple MAFLD patients and MAFLD patients with CVD risk had divergent gut microbes and plasma metabolites. The predictive model based on metabolites and 9 clinical parameters could effectively discriminate MAFLD patients with CVD risk at a very early stage.

No evidence of difference in mortality with amoxicillin versus co-amoxiclav for hospital treatment of community-acquired pneumonia.

OBJECTIVES: Current guidelines recommend broad-spectrum antibiotics for high-severity community-acquired pneumonia (CAP), potentially contributing to antimicrobial resistance (AMR). We aim to compare outcomes in CAP patients treated with amoxicillin (narrow-spectrum) versus co-amoxiclav (broad-spectrum), to understand if narrow-spectrum antibiotics could be used more widely. METHODS: We analysed electronic health records from adults (≥16 y) admitted to hospital with a primary diagnosis of pneumonia between 01-January-2016 and 30-September-2023 in Oxfordshire, United Kingdom. Patients receiving baseline ([-12 h,+24 h] from admission) amoxicillin or co-amoxiclav were included. The association between 30-day all-cause mortality and baseline antibiotic was examined using propensity score (PS) matching and inverse probability treatment weighting (IPTW) to address confounding by baseline characteristics and disease severity. Subgroup analyses by disease severity and sensitivity analyses with missing covariates imputed were also conducted. RESULTS: Among 16,072 admissions with a primary diagnosis of pneumonia, 9685 received either baseline amoxicillin or co-amoxiclav. There was no evidence of a difference in 30-day mortality between patients receiving initial co-amoxiclav vs. amoxicillin (PS matching: marginal odds ratio 0.97 [0.76-1.27], p = 0.61; IPTW: 1.02 [0.78-1.33], p = 0.87). Results remained similar across stratified analyses of mild, moderate, and severe pneumonia. Results were also similar with missing data imputed. There was also no evidence of an association between 30-day mortality and use of additional macrolides or additional doxycycline. CONCLUSIONS: There was no evidence of co-amoxiclav being advantageous over amoxicillin for treatment of CAP in 30-day mortality at a population-level, regardless of disease severity. Wider use of narrow-spectrum empirical treatment of moderate/severe CAP should be considered to curb potential for AMR.

EEPD1 is identified as a predictor of prognosis and immune microenvironment through pan-cancer analysis and related to progression of colorectal cancer.

Background: EEPD1 is vital in homologous recombination, while its role in cancer remains unclear. Methods: We performed multiple pan-cancer analyses of EEPD1 with bioinformatics methods, such as gene expression, gene alterations, Prognosis and enrichment analysis, tumor microenvironment, immune cell infiltration, TMB, MSI, immunotherapy, co-expression of genes, and drug resistance. Finally, RT-qPCR, EdU, and transwell assays helped investigate the impact of EEPD1 on CRC cells. Results: EEPD1 was dysregulated and correlated with bad prognosis in several cancers. GSVA and GSEA revealed that EEPD1 was primarily associated with the "WNT_BETA_CATENIN_SIGNALING," "ribonucleoprotein complex biogenesis," "Ribosome," and "rRNA processing." The infiltration of CD8+ T cells, MAIT cells, iTreg cells, NK cells, Tc cells, Tex cells, Tfh cells, and Th1 cells were negatively correlated with EEPD1 expression. Additionally, EEPD1 is significantly associated with TMB and MSI in COAD, while enhanced CRC cell proliferation and migration. Conclusions: EEPD1 was dysregulated in human cancers and correlated with various cancer patient prognoses. The dysregulated EEPD1 expression can affect tumor-infiltrating immune cells and immunotherapy response. Therefore, EEPD1 could act as an oncogene associated with immune cell infiltration in CRC.

Mechanical Characterization of Multifunctional Metal-Coated Polymer Lattice Structures.

Metal-coated lattice structures hold significant promise for customizing mechanical properties in diverse industrial applications, including the mechanical arms of unmanned aerial vehicles. However, their intricate geometries pose computational challenges, resulting in time-intensive and costly numerical evaluations. This study introduces a parameterization-based multiscale method to analyze body-centered cubic lattice structures with metal coatings. We establish the validity and precision of our proposed method with a comparative analysis of numerical results at the Representative Volume Element (RVE) scale and experimental findings, specifically addressing both elastic tensile and bending stiffness. Furthermore, we showcase the method's accuracy in interpreting the bending stiffness of coated lattice structures using a homogenized material-based solid model, underscoring its effectiveness in predicting the elastic properties of such structures. In exploring the mechanical characterization of coated lattice structures, we unveil positive correlations between elastic tensile stiffness and both coating thickness and strut diameter. Additionally, the metal coating significantly enhances the structural elastic bending stiffness multiple times over. The diverse failure patterns observed in coated lattices under tensile and bending loads primarily stem from varied loading-induced stress states rather than external factors. This work not only mitigates computational challenges but also successfully bridges the gap between mesoscale RVE mechanical properties and those at the global structural scale.

Developing a novel strategy for fabricating matrix film to assess the distribution of potassium perfluorooctanic sulfonate by matrix-assisted laser desorption/ionization mass spectrometry imaging.

Matrix deposition plays a critical role in image quality of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). To improve the ionization efficiency and overcome the limitation of traditional matrix deposition methods in the face of difficult-to-sublimate or difficult-to-dissolve matrix, covalent organic frameworks (COFs) named COF-DhaTab was successfully synthesized and firstly used as matrix film. It was fabricated by imprinting of sieved COF-DhaTab powder on the surface of a double-sided adhesive tape. Outstanding reproducibility and uniformity of COF-DhaTab film were demonstrated by relative standard deviation (RSD) within 8.37% and 7.71% from dot-to-dot and plate-to-plate, respectively. With the introduction of double-sided adhesive tape, water contact angle (WCA) of COF-DhaTab film increased from 55° to 141°, resulting in significant suppression of analyte diffusion. Moreover, the intensity of potassium perfluorooctanic sulfonate (PFOS, C8F17SO3-, m/z 498.93) was 9.3 × 105, more than six hundred times higher than that using DHB matrix. This enhancement was attributed to the rough surface and multiple branches of the synthesized COF-DhaTab. To verify the ability of COF-DhaTab film as substrate, the spatial distribution of PFOS in zebrafish, rat liver and kidney tissues was explored. Superior imaging capability was displayed with high-spatial resolution and reliable location distribution. These results not only demonstrate the outstanding ability of COF-DhaTab as matrix for MALDI-MS and MALDI-MSI, but also provide a facile approach for fabrication of novel matrix films for MALDI-MSI.

A SERS nanocellulose-paper-based analytical device for ultrasensitive detection of Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD), one of the most prevalent neurodegenerative diseases, results in severe cognitive decline and irreversible memory loss. Early detection of AD is significant to patients for personalized intervention since effective cure and treatment methods for AD are still lacking. Despite the severity of the disease, existing highly sensitive AD detection methods, including neuroimaging and brain deposit-positive lesion tests, are not suitable for screening purposes due to their high cost and complicated operation. Therefore, these methods are unsuitable for early detection, especially in low-resource settings. Although regular paper-based microfluidics are cost-efficient for AD detection, they are restricted by a poor limit of detection (LOD). RESULTS: To address the above limitations, we report the ultrasensitive and low-cost nanocellulose paper (nanopaper)-based analytical microfluidic devices (NanoPADs) for detecting one of the promising AD blood biomarkers (glial fibrillary acidic protein, GFAP) using Surface-enhanced Raman scattering (SERS) immunoassay. Nanopaper offers advantages as a SERS substrate, such as an ultrasmooth surface, high optical transparency, and tunable chemical properties. We detected the target GFAP in artificial serum, achieving a LOD of 150 fg mL-1. SIGNIFICANCE: The developed NanoPADs are distinguished by their cost-efficiency and ease of implementation, presenting a promising avenue for effective early detection of AD's GFAP biomarker with ultrahigh sensitivity. More importantly, our work provides the experimental routes for SERS-based immunoassay of biomarkers on NanoPADs for various diseases in the future.

Sesamin alleviates lipid accumulation induced by oleic acid via PINK1/Parkin-mediated mitophagy in HepG2 cells.

Sesamin, a special compound present in sesame and sesame oil, has been reported a role in regulating lipid metabolism, while the underlying mechanisms remain unclear. Autophagy has been reported associated with lipid metabolism and regarded as a key modulator in liver steatosis. The present work aimed to investigate whether sesamin could exert its protective effects against lipid accumulation via modulating autophagy in HepG2 cells stimulated with oleic acid (OA). Cell viability was evaluated using the CCK-8 method, and triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein, cholesterol (LDL-C), alanine aminotransferase (ALT), along with aspartate aminotransferase (AST) were assessed by oil red O staining, transmission electron microscopy (TEM), and biochemical kits to investigate the lipid-lowering effects of sesamin. Differentially expressed genes were screened by RNA sequencing and validated using real-time quantitative PCR and Western blot. Autophagy and mitophagy related molecules were analyzed employing TEM, Western blot, and immunofluorescence. The data shows that in HepG2 cells stimulated by OA, sesamin reduces levels of TG, TC, LDL-C, ALT, and AST while elevating HDL-C, alleviates the lipid accumulation and improves fatty acid metabolism through modulating the levels of fat metabolism related genes including PCSK9, FABP1, CD36, and SOX4. Sesamin restores the suppressed autophagy in HepG2 cells caused by OA, which could be blocked by autophagy inhibitors. This indicates that sesamin improves fatty acid metabolism by enhancing autophagy levels, thereby mitigating the intracellular lipid accumulation. Furthermore, sesamin significantly enhances the mitophagy and improves mitochondrial homeostasis via activating the PINK/Parkin pathway. These data suggest that sesamin alleviates the excessive lipid accumulation in HepG2 caused by OA by restoring the impaired mitophagy via the PINK1/Parkin pathway, probably playing a preventive or therapeutic role in hepatic steatosis.

Neuroprotective effects of cordycepin on MPTP-induced Parkinson's disease mice via suppressing PI3K/AKT/mTOR and MAPK-mediated neuroinflammation.

Parkinson's disease (PD) is a prevalent progressive and multifactorial neurodegenerative disorder. Cordycepin is known to exhibit antitumor, anti-inflammatory, antioxidative stress, and neuroprotective effects; however, few studies have explored the neuroprotective mechanism of cordycepin in PD. Using a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mouse model, we investigated the impact of cordycepin on PD and its underlying molecular mechanisms. The findings indicated that cordycepin significantly mitigated MPTP-induced behavior disorder and neuroapoptosis, diminished the loss of dopaminergic neurons in the striatum-substantia nigra pathway, elevated striatal monoamine levels and its metabolites, and inhibited the polarization of microglia and the expression of pro-inflammatory factors. Subsequent proteomic and phosphoproteomic analyses revealed the involvement of the MAPK, mTOR, and PI3K/AKT signaling pathways in the protective mechanism of cordycepin. Cordycepin treatment inhibited the activation of the PI3K/AKT/mTOR signaling pathway and enhanced the expression of autophagy proteins in the striatum and substantia nigra. We also demonstrated the in vivo inhibition of the ERK/JNK signaling pathway by cordycepin treatment. In summary, our investigation reveals that cordycepin exerts neuroprotective effects against PD by promoting autophagy and suppressing neuroinflammation and neuronal apoptosis by inhibiting the PI3K/AKT/mTOR and ERK/JNK signaling pathways. This finding highlights the favorable characteristics of cordycepin in neuroprotection and provides novel molecular insights into the neuroprotective role of natural products in PD.

The potential role of hydrogen sulfide in cancer cell apoptosis.

For a long time, hydrogen sulfide (H2S) has been considered a toxic compound, but recent studies have found that H2S is the third gaseous signaling molecule which plays a vital role in physiological and pathological conditions. Currently, a large number of studies have shown that H2S mediates apoptosis through multiple signaling pathways to participate in cancer occurrence and development, for example, PI3K/Akt/mTOR and MAPK signaling pathways. Therefore, the regulation of the production and metabolism of H2S to mediate the apoptotic process of cancer cells may improve the effectiveness of cancer treatment. In this review, the role and mechanism of H2S in cancer cell apoptosis in mammals are summarized.