Assessment of bioenergy plant locations using a GIS-MCDA approach based on spatio-temporal stability maps of agricultural and livestock byproducts: A case study.

Addressing the global challenge of energy sustainability and global directives on farming emissions, the United Nations, the European Union, and China have led with strict targets for clean energy, renewable share growth, and carbon neutrality, highlighting a commitment to collective sustainability. This work is situated within the ambit of the Sustainable Development Goals (SDGs), advocating for a transition towards renewable energy sources. With substantial and accessible bioenergy resources, notably in Hubei Province, China, biogas technology has emerged as an emission-cutting solution. This research, focused on the Jianghan Plain, employs an integrated approach combining spatial analyses with machine learning tools to evaluate crop yield stability over two decades, with the aim of maximising the biogas yield from agricultural byproducts, i.e., crop straw and livestock manure. Using Multi-Criteria Decision Analysis (MCDA), which is informed by grey-based DEMATEL, 9 constraints and 13 environmental, social, and economic criteria were assessed to identify optimal sites for biogas facilities. The findings underscore the significant bioenergy potential of agricultural byproducts from the plain of 6.3 × 1012 kJ/year at an 11.4 kJ/m2 density. Stability analyses revealed consistent biomass availability, with rice in Gongan and Shayang and wheat in Jiangling being the primary contributors. Through the MCDA, 45-66 optimal biogas plants were identified across 4 critical counties (Zhongxiang, Shangyang, Jingshan, and Yichen), balancing the energy supply and demand under various stable scenarios. Furthermore, this study demonstrated the criticality of moderate biomass stability for stakeholder consensus and identified areas of high stability essential for energy demand fulfilment. Theoretically, this study offers a practical model for bioenergy resource exploitation that aligns with global sustainability and carbon neutrality goals to address the urgent need for renewable energy solutions amidst the global energy crisis. Practically, this study sets a precedent for policy and planning in environmental, agricultural, and renewable sectors, signifying a step forwards in achieving environmental sustainability and an energy-efficient future.

Triboelectric Nanogenerators: State of the Art.

The triboelectric nanogenerator (TENG), as a novel energy harvesting technology, has garnered widespread attention. As a relatively young field in nanogenerator research, investigations into various aspects of the TENG are still ongoing. This review summarizes the development and dissemination of the fundamental principles of triboelectricity generation. It outlines the evolution of triboelectricity principles, ranging from the fabrication of the first TENG to the selection of triboelectric materials and the confirmation of the electron cloud overlapping model. Furthermore, recent advancements in TENG application scenarios are discussed from four perspectives, along with the research progress in performance optimization through three primary approaches, highlighting their respective strengths and limitations. Finally, the paper addresses the major challenges hindering the practical application and widespread adoption of TENGs, while also providing insights into future developments. With continued research on the TENG, it is expected that these challenges can be overcome, paving the way for its extensive utilization in various real-world scenarios.

In-droplet multiplex immunoassays for hypoxia-induced single-cell cytokines.

Cytokine expression is an important biomarker in understanding hypoxia microenvironments in tumor growth and metastasis. In-droplet-based immunoassays performed above the target cell membrane were employed to track the cytokines of single cells with the aid of three types of immuno-nanoprobes (one capture nanoprobe and two reporter nanoprobes). Single cells and nanoprobes were co-packaged in water-in-oil microdroplets (about 100 µm in diameter) using a cross-shaped microfluidic chip. In each droplet, capture nanoprobes would be first fixed to the cell surface by linking to membrane proteins that have been streptavidinized. Then, the capture nanoprobes can collect cell-secreted cytokines (VEGF and IL-8) by the antibodies, followed by two reporter nanoprobes that emit distinguishable fluorescence. Fluorescence imaging was utilized to record the signal outputs of two reporter probes, which reflect cytokine expressions secreted by a single tumor cell. The cytokine levels at different degrees of hypoxia induction were assessed. Multiple chemometric methods were adopted to distinguish differences in the secretion of two cytokines and the results demonstrated a positive correlation. This study developed an in-droplet, dual-target, simultaneous biosensing strategy for a single cell, which is helpful for understanding the impacts of hypoxia microenvironments on cell cytokines that are vital for assessing early cancer diagnosis and prognosis.

Non B Cell-Derived Immunoglobulins in Intestinal Tract.

Intestinal epithelium constitutes a barrier to the unrestricted movement of pathogens, and other detrimental substances from the external world (gut lumen) into the interstitial environment. Intestinal epithelial cells obstruct harmful substances passing through the epithelium as a physical and chemical barrier; Moreover, the epithelial cells can express Toll-like receptors (TLRs) and cytokines to exert innate immune function. In addition, high levels of immunoglobulin A (IgA) and other antibodies exist in the intestinal mucosa, maintaining intestinal immune homeostasis in conjunction with intestinal probiotics. Traditionally, these antibodies have been deemed to be secreted by submucosal plasma cells. Nonetheless, in recent years, it has been demonstrated that intestinal epithelial cells produce a substantial amount of Igs, especially IgA or free Ig light chains, which are involved in intestinal immune homeostasis and the survival of normal epithelial cells. Furthermore, mounting evidence affirms that many human carcinoma cells, including colorectal cancer (CRC), can overexpress Igs, particularly IgG. Cancer-derived Igs exhibit a unique V(D)J rearrangement pattern distinct from B cell-derived Ig; moreover, this cancer cell-derived IgG also has a unique sialic acid modification on the 162 site of CH1 domain (SIA-IgG). The SIA-IgG plays a crucial role in promoting cancer initiation, progression, metastasis, and tumour immune escape. Simultaneously, CRC cells can also express free Ig light chains, which promote colitis, colitis-associated colon carcinogenesis, and CRC progression. Therefore, Igs expressed by CRC cells could be a potential target for diagnosing and preventing the transformation of inflammation into cancer, as well as treating CRC.

Single-Atom 3d Transition Metals on SnO2 as Model Cell for Conversion Mechanism: Revealing Thermodynamic Catalytic Effects on Enhanced Na Storage of Heterostructures.

Since the discovery in 2000, conversion-type materials have emerged as a promising negative-electrode candidate for next-generation batteries with high capacity and tunable voltage, limited by low reversibility and severe voltage hysteresis. Heterogeneous construction stands out as a cost-effective and efficient approach to reducing reaction barriers and enhancing energy density. However, the second term introduced by conventional heterostructure inevitably complicates the electrochemical analysis and poses great challenges to harvesting systematic insights and theoretical guidance. A model cell is designed and established herein for the conversion reactions between Na and TMSA-SnO2, where TMSA-SnO2 represents single atom modification of eight different 3d transition elements (V, Cr, Mn, Fe, Co, Ni, Cu or Zn). Such a model unit fundamentally eliminates the interference from the second phase and thus enables independent exploration of activation manifestations of the heterogeneous architecture. For the first time, a thermodynamically dependent catalytic effect is proposed and verified through statistical data analysis. The mechanism behind the unveiled catalytic effect is further elucidated by which the active d orbitals of transition metals weaken the surface covalent bonds and lower the reaction barriers. This research provides both theoretical insights and practical demonstrations of the advanced heterogeneous electrodes.

[Treatment strategy of carotid blowout syndrome after radiotherapy for nasopharyngeal carcinoma].

Objective:To investigate the treatment of internal carotid artery rupture after radiotherapy for nasopharyngeal carcinoma. Methods:The clinical data of 7 patients with internal carotid artery rupture after radiotherapy for nasopharyngeal carcinoma from March 2020 to March 2023 were retrospectively analyzed. Results:Skull base osteonecrosis with infection occurred in 4 cases, and tumor recurrence with infection in 3 cases. DSA showed that internal carotid artery rupture was located in the internal carotid artery petrosal segment in 6 cases, and in the paravicular segment in 1 case. Balloon occlusion test（BOT） was performed in 6 patients, of which 3 passed and 3 failed. Vascular treatment included internal carotid artery embolization（4 cases）, false aneurysm embolization 1 case（rebleeding）, coated stent 1 case（rebleeding）, muscle compression during operation（1 case）. Patients with rebleeding received high-flow bypass. Three cases developed cerebral infarction after embolization without severe sequelae after treatment, and no death occurred within 90 days. After bleeding control, all 3 patients with cranial base necrosis received surgical treatment to remove the necrotic bone and tissue flap repair, and 1 patient with recurrence received gamma knife and targeted therapy, 1 patient received immune and surgical therapy, and 1 patient received immune and targeted therapy. Conclusion:Rupture and hemorrhage of internal carotid artery after radiotherapy is related to tumor invasion, tissue injury and local infection after radiotherapy. For those caused by tumor invasion, it is recommended to sacrifice the responsible vessels. For those caused by infection, emergency surgery is recommended and blood vessels preserved. Emergency vascular occlusion remains a life-saving option.

A spatiotemporal graph transformer approach for Alzheimer's disease diagnosis with rs-fMRI.

Alzheimer's disease (AD) is a neurodegenerative disease accompanied by cognitive impairment. Early diagnosis is crucial for the timely treatment and intervention of AD. Resting-state functional magnetic resonance imaging (rs-fMRI) records the temporal dynamics and spatial dependency in the brain, which have been utilized for automatically diagnosis of AD in the community. Existing approaches of AD diagnosis using rs-fMRI only assess functional connectivity, ignoring the spatiotemporal dependency mining of rs-fMRI. In addition, it is difficult to increase diagnosis accuracy due to the shortage of rs-fMRI sample and the poor anti-noise ability of model. To deal with these problems, this paper proposes a novel approach for the automatic diagnosis of AD, namely spatiotemporal graph transformer network (STGTN). The proposed STGTN can effectively extract spatiotemporal features of rs-fMRI. Furthermore, to solve the sample-limited problem and to improve the anti-noise ability of the proposed model, an adversarial training strategy is adopted for the proposed STGTN to generate adversarial examples (AEs) and augment training samples with AEs. Experimental results indicate that the proposed model achieves the classification accuracy of 92.58%, and 85.27% with the adversarial training strategy for AD vs. normal control (NC), early mild cognitive impairment (eMCI) vs. late mild cognitive impairment (lMCI) respectively, outperforming the state-of-the-art methods. Besides, the spatial attention coefficients reflected from the designed model reveal the importance of brain connections under different classification tasks.

Machine learning-based model development for predicting risk factors of prolonged intra-aortic balloon pump therapy in patients with coronary artery bypass grafting.

Machine learning algorithms are frequently used to clinical risk prediction. Our study was designed to predict risk factors of prolonged intra-aortic balloon pump (IABP) use in patients with coronary artery bypass grafting (CABG) through developing machine learning-based models. Patients who received perioperative IABP therapy were divided into two groups based on their length of IABP implantation longer than the 75th percentile for the whole cohort: normal (≤ 10 days) and prolonged (> 10 days) groups. Seven machine learning-based models were created and evaluated, and then the Shapley Additive exPlanations (SHAP) method was employed to further illustrate the influence of the features on model. In our study, a total of 143 patients were included, comprising 56 cases (38.16%) in the prolonged group. The logistic regression model was considered the final prediction model according to its most excellent performance. Furthermore, feature important analysis identified left ventricular end-systolic or diastolic diameter, preoperative IABP use, diabetes, and cardiac troponin T as the top five risk variables for prolonged IABP implantation in patients. The SHAP analysis further explained the features attributed to the model. Machine learning models were successfully developed and used to predict risk variables of prolonged IABP implantation in patients with CABG. This may help early identification for prolonged IABP use and initiate clinical interventions.

Pd/C-Catalyzed Stereoselective Arene Hydrogenation of Benzocyclobutenes Enabled by π-Bond Localization.

We developed here a Pd/C-catalyzed diastereoselective cis-hydrogenation of benzocyclobutene derivatives under mild conditions to deliver an array of bicyclo[4.2.0]octane scaffolds with up to five stereocenters. The π-bond localization enabled hydrogenation of the arene moiety to occur even at room temperature under 1 atm of a H2 atmosphere.

Deep transcranial magnetic stimulation for schizophrenia: a systematic review.

Background: The efficacy and safety of deep transcranial magnetic stimulation (dTMS) as an intervention for schizophrenia remain unclear. This systematic review examined the efficacy and safety of dTMS for schizophrenia. Methods: A systematic search of Chinese (WanFang and Chinese Journal Net) and English databases (PubMed, EMBASE, PsycINFO, and Cochrane Library) were conducted. Results: Three randomized clinical trials (RCTs) comprising 80 patients were included in the analyses. Active dTMS was comparable to the sham treatment in improving total psychopathology, positive symptoms, negative symptoms, and auditory hallucinations measured by the Positive and Negative Syndrome Scale (PANSS), the Scale for the Assessment of Positive Symptoms (SAPS), the Scale for the Assessment of Negative Symptoms (SANS), and the Auditory Hallucinations Rating Scale (AHRS), respectively. Only one RCT reported the effects on neurocognitive function measured by the Cambridge Neuropsychological Test Automated Battery (CANTAB), suggesting that dTMS may only improve one Stockings of Cambridge measure (i.e., subsequent times for five move problems). All three studies reported overall discontinuation rates, which ranged from 16.7% to 44.4%. Adverse events were reported in only one RCT, the most common being tingling/twitching (30.0%, 3/10), head/facial discomfort (30.0%, 3/10), and back pain (20.0%, 2/10). Conclusion: This systematic review suggests that dTMS does not reduce psychotic symptoms in schizophrenia, but it shows potential for improving executive functions. Future RCTs with larger sample sizes focusing on the effects of dTMS on psychotic symptoms and neurocognitive function in schizophrenia are warranted to further explore these findings.

Association of longitudinal trajectories of fasting plasma glucose with all-cause and cardiovascular mortality among a Chinese older population: a retrospective cohort study.

The association between fasting plasma glucose (FPG), an important indicator of overall glycemic status, and the risk of cardiovascular mortality has been well investigated. The longitudinal study can repeatedly collect measured results for the variables to be studied and then consider the potential effects of intraindividual changes in measurement. This study aimed to identify long-term FPG trajectories and investigate the association between trajectory groups and cardiovascular and all-cause mortality. A latent class growth mixture modeling (LCGMM) was used to identify FPG trajectories. Cox proportional hazard models were used to estimate associations between FPG trajectories and the risk of all-cause and cardiovascular mortality. A U-shaped relationship between FPG and all-cause and cardiovascular mortality was observed in the restricted cubic spline regression models. Two FPG longitudinal trajectories of low-level (mean FPG = 5.12mmol/L) and high-level (mean FPG = 6.74mmol/L) were identified by LCGMM. After being adjusted for potential confounders, compared with the low-level category, the hazard ratios (HRs) for all-cause and cardiovascular mortality were 1.23(1.16-1.30) and 1.25(1.16-1.35), respectively, for the high-level group. Long-term FPG trajectories are significantly associated with and potentially impact the risk of all-cause and cardiovascular mortality.

CRISPR/Cas9-Based Functional Characterization of SfUGT50A15 Reveals Its Roles in the Resistance of Spodoptera frugiperda to Chlorantraniliprole, Emamectin Benzoate, and Benzoxazinoids.

UDP-glycosyltransferases (UGTs) are a diverse superfamily of enzymes. Insects utilize uridine diphosphate-glucose (UDP-glucose) as a glycosyl donor for glycosylation in vivo, involved in the glycosylation of lipophilic endosymbionts and xenobiotics, including phytotoxins. UGTs act as second-stage detoxification metabolizing enzymes, which are essential for the detoxification metabolism of insecticides and benzoxazine compounds. However, the UGT genes responsible for specific glycosylation functions in S. frugiperda are unclear at present. In this study, we utilized CRISPR/Cas9 to produce a SfUGT50A15-KO strain to explore its possible function in governing sensitivity to chemical insecticides or benzoxazinoids. The bioassay results suggested that the SfUGT50A15-KO strain was significantly more sensitive to chlorantraniliprole, emamectin benzoate, and benzoxazinoids than the wild-type strains. This finding suggests that the overexpression of the SfUGT50A15 gene may be linked to S. frugiperda resistance to pesticides (chlorantraniliprole and emamectin benzoate) as well as benzoxazinoids (BXDs).

All-Inorganic Halide Perovskites Boost High-Ranged Figure-of-Merit in Bi0.4Sb1.6Te3 for Thermoelectric Cooling and Low-Grade Heat Recovery.

The all-inorganic halide perovskite CsPbX3 (X = Cl, Br, or I) offers various advantages, such as tunable electronic structure and high carrier mobility. However, its potential application in thermoelectric materials remains underexplored. In this study, we propose a simple yet effective method to synthesize a CsPbX3/Bi0.4Sb1.6Te3 (BST) nanocomposite by sintering a uniformly mixed raw powder. The intrinsic excitation of the BST system is suppressed by exploiting the rich phase structure and tunable electrical transport properties of CsPbX3, and the thermoelectric properties were synergistically optimized. Notably, for CsPbI3, its phase-transition-induced dislocation arrays together with low group velocities drastically reduce thermal conductivity. As a result, the composite achieves an ultrahigh average figure-of-merit (ZT) of 1.4 from 298 to 523 K. The two-pair TE module demonstrates a superior conversion efficiency of 7.3%. This study expands the potential applications of inorganic halide perovskites, into thermoelectrics.

Engineering Co3O4@3DOM LaCoO3 multistage-pore nanoreactor with superior SO2 resistance for toluene catalytic combustion.

Sulfur dioxide poisoning is a significant factor in catalyst deactivation during the catalytic combustion of volatile organic compounds. In this study, we prepared the LaCoO3 and Co3O4 composite catalysts using both the Ship-in-Bottle and Building-Bottle-Around-Ship approaches. Three-dimensionally ordered macropores (3DOM LaCoO3) were utilized as nanoreactors to protect the active sites during the catalytic combustion of toluene, preventing SO2 poisoning. Additionally, we grew ZIF-67 confined in the nanoreactor to create a multistage-pore structure. The Co3O4@3DOM LaCoO3 catalysts exhibited excellent activity in the complete catalytic oxidation of toluene. Various characterization studies confirmed the presence of a significant number of Co3+ species and an abundance of surface weak acid sites in the Co3O4@3DOM LaCoO3 catalysts, which synergistically enhanced the conversion of VOCs at low temperatures. Notably, the multistage pore structure provided a favorable reaction environment, accelerating the adsorption and diffusion of toluene and intermediates, resulting in excellent sulfur resistance of the catalysts. Moreover, XPS analysis confirmed a strong interaction between Co3O4 and LaCoO3, promoting rapid electron transfer and increasing the activation of O2-. In situ DRIFTS experiments verified that toluene mainly follows the MvK mechanism over Co3O4@3DOM LaCoO3 catalysts, indicating the following reaction pathway: toluene adsorption → benzyl alcohol → benzaldehyde → benzoate → anhydride → CO2 and H2O.

Metal-organic frameworks as candidates for tumor sonodynamic therapy: Designable structures for targeted multifunctional transformation.

Sonodynamic therapy (SDT), utilizing ultrasound (US) as the trigger, has gained popularity recently as a therapeutic approach with significant potential for treating various diseases. Metal-organic frameworks (MOFs), characterized by structural flexibility, are prominently emerging in the SDT realm as an innovative type of sonosensitizer, offering functional tunability and biocompatibility. However, due to the inherent limitations of MOFs, such as low reactivity to reactive oxygen species and challenges posed by the complex tumor microenvironment, MOF-based sonosensitizers with singular functions are unable to demonstrate the desired therapeutic efficacy and may pose risks of toxicity, limiting their biological applications to superficial tissues. MOFs generally possess distinctive crystalline structures and properties, and their controlled coordination environments provide a flexible platform for exploring structure-effect relationships and guiding the design and development of MOF-based nanomaterials to unlock their broader potential in biological fields. The primary focus of this paper is to summarize cases involving the modification of different MOF materials and the innovative strategies developed for various complex conditions. The paper outlines the diverse application areas of functionalized MOF-based sonosensitizers in tumor synergistic therapies, highlighting the extensive prospects of SDT. Additionally, challenges confronting SDT are briefly summarized to stimulate increased scientific interest in the practical application of MOFs and the successful clinical translation of SDT. Through these discussions, we strive to foster advancements that lead to early-stage clinical benefits for patients. STATEMENT OF SIGNIFICANCE: 1. An overview for the progresses in SDT explored from a novel and fundamental perspective. 2. Different modification strategies to improve the MOFs-mediated SDT efficacy are provided. 3. Guidelines for the design of multifunctional MOFs-based sonosensitizers are offered. 4. Powerful tumor ablation potential is reflected in SDT-led synergistic therapies. 5. Future challenges in the field of MOFs-based SDT in clinical translation are suggested.

Polyphyllin I ameliorates gefitinib resistance and inhibits the VEGF/VEGFR2/p38 pathway by targeting HIF-1a in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have been administered as the first-line therapy for patients with EGFR mutations in LUAD, but it is almost inevitable that resistance to EGFR-TKIs therapy eventually arises. Polyphyllin I (PPI), derived from Paris polyphylla rhizomes, has been shown to have potent anti-cancer properties in a range of human cancer types including LUAD. However, the role of PPI in gefitinib resistance and the underlying mechanism remain elusive. PURPOSE: To evaluate the antitumor impacts of PPI on gefitinib resistance cells and investigate its molecular mechanism. METHODS: CCK-8, wound healing, transwell assay, and xenograft model were performed to determine the anti-cancer effects of PPI as well as its ability to overcome gefitinib resistance. Immunoblotting, co-immunoprecipitation, phospho-RTK antibody array, qRT-PCR, and immunofluorescence were utilized to explore the mechanism by which PPI overrides gefitinib resistance. RESULTS: PPI inhibited cell survival, growth, and migration/invasion in both gefitinib-sensitive (PC9) and -resistant (PC9/GR) LUAD cells (IC50 at 2.0 µM). Significantly, treatment with PPI at 1.0 µM resensitized the resistant cells to gefitinib. Moreover, cell-derived xenograft experiments revealed that the combination of PPI and gefitinib overcame gefitinib resistance. The phospho-RTK array and immunoblotting analyses showed PPI significant inhibition of the VEGFR2/p38 pathway. In addition, molecular docking suggested the interaction between PPI and HIF-1α. Mechanistically, PPI reduced the protein expression of HIF-1α in both normoxia and hypoxia conditions by triggering HIF-1α degradation. Moreover, HIF-1α protein but not mRNA level was elevated in gefitinib-resistant LUAD. We further demonstrated that PPI considerably facilitated the binding of HIF-1α to VHL. CONCLUSIONS: We present a novel discovery demonstrating that PPI effectively counteracts gefitinib resistance in LUAD by modulating the VEGF/VEGFR2/p38 pathway. Mechanistic investigations unveil that PPI facilitates the formation of the HIF-1α /VHL complex, leading to the degradation of HIF-1α and subsequent inhibition of angiogenesis. These findings uncover a previously unidentified mechanism governing HIF-1α expression in reaction to PPI, providing a promising method for therapeutic interventions targeting EGFR-TKI resistance in LUAD.

Association of the CUN-BAE body adiposity estimator and other obesity indicators with cardiometabolic multimorbidity: a cross-sectional study.

Cardiometabolic multimorbidity (CM), defined as the coexistence of two or three cardiometabolic disorders, is one of the most common and deleterious multimorbidities. This study aimed to investigate the association of Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) with the prevalence of CM. The data were obtained from the 2021 health checkup database for residents of the Electronic Health Management Center in Xinzheng, Henan Province, China. 81,532 participants aged ≥ 60 years were included in this study. Logistic regression models were used to estimate the odd ratios (ORs) and 95% confidence intervals (CIs) for CUN-BAE, BMI, WC, and WHtR in CM. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory ability of different anthropometric indicators for CM. The multivariable-adjusted ORs (95% CIs) (per 1 SD increase) of CM were 1.799 (1.710-1.893) for CUN-BAE, 1.329 (1.295-1.364) for BMI, 1.343 (1.308-1.378) for WC, and 1.314 (1.280-1.349) for WHtR, respectively. Compared with BMI, WC and WHtR, CUN-BAE had the highest AUC in both males and females (AUC: 0.642; 95% CI 0.630-0.653 for males, AUC: 0.614; 95% CI 0.630-0.653 for females). CUN-BAE may be a better measure of the adverse effect of adiposity on the prevalence of CM than BMI, WC, and WHtR.

Endoplasmic reticulum-resident selenoproteins and their roles in glucose and lipid metabolic disorders.

Glucose and lipid metabolic disorders (GLMDs), such as diabetes, dyslipidemia, metabolic syndrome, nonalcoholic fatty liver disease, and obesity, are significant public health issues that negatively impact human health. The endoplasmic reticulum (ER) plays a crucial role at the cellular level for lipid and sterol biosynthesis, intracellular calcium storage, and protein post-translational modifications. Imbalance and dysfunction of the ER can affect glucose and lipid metabolism. As an essential trace element, selenium contributes to various human physiological functions mainly through 25 types of selenoproteins (SELENOs). At least 10 SELENOs, with experimental and/or computational evidence, are predominantly found on the ER membrane or within its lumen. Two iodothyronine deiodinases (DIOs), DIO1 and DIO2, regulate the thyroid hormone deiodination in the thyroid and some external thyroid tissues, influencing glucose and lipid metabolism. Most of the other eight members maintain redox homeostasis in the ER. Especially, SELENOF, SELENOM, and SELENOS are involved in unfolded protein responses; SELENOI catalyzes phosphatidylethanolamine synthesis; SELENOK, SELENON, and SELENOT participate in calcium homeostasis regulation; and the biological significance of thioredoxin reductase 3 in the ER remains unexplored despite its established function in the thioredoxin system. This review examines recent research advances regarding ER SELENOs in GLMDs and aims to provide insights on ER-related pathology through SELENOs regulation.

Design and Synthesis of Electrocatalysts Base on Catalysis-Unit Engineering.

It is a pressing need to develop new energy materials to address the existing energy crisis. However, screening optimal targets out of thousands of material candidates remains a great challenge. Herein, an alternative concept for highly effective materials screening based on dual-atom salphen catalysis units, is proposed and validated. Such an approach simplifies the design of catalytic materials and reforms the trial-and-error experimental model into a building-blocks-assembly like process. First, density functional theory (DFT) calculations are performed on a series of potential catalysis units that are possible to synthesize. Then, machine learning (ML) is employed to define the structure-performance relationship and acquire chemical insights. Afterward, the projected catalysis units are integrated into covalent organic frameworks (COFs) to validate the concept Electrochemical tests confirming that Ni-SalphenCOF and Co-SalphenCOF are promising conductive agent-free oxygen evolution reaction (OER) catalysts. This work provides a fast-tracked strategy for the design and development of functional materials, which serves as a potentially workable framework for seamlessly integrating DFT calculations, ML, and experimental approaches.