Unexpected changes in source apportioned results derived from different ambient VOC metrics.

Although most source apportionments of VOCs use mixing ratios, about 23 % of published studies use mass concentrations. Thus, systematically exploring the changes in VOC source apportioned results caused by metric differences is important to assess the differences in key precursor apportionment results given the observed increases in O3 pollution situation. Different monitoring instruments measured hourly VOC volumetric concentrations in three typical Chinese cities (i.e., Qingdao, Shijiazhuang, and Zhumadian). Converting volumetric to mass concentrations under standard and/or actual temperature-pressure conditions, VOC values with different metrics were obtained. The impacts of different metrics on the source apportionments were then investigated. Compared to the positive matrix factorization of the volumetric data (VC-PMF), the VOC species concentrations with low relative molecular mass (RMM) in the factor profiles substantially decreased in mass data analyses (MC-PMF). However, those species with high RMM substantially increased. There were no substantial differences in the apportioned source contributions based on standard and actual condition mass concentrations. However, the high-low rankings of percent contributions apportioned using the volumetric and mass data produced substantial differences. Compared with the VC-PMF results, the percent contributions of sources dominated by species with low RMM (e.g., natural gas usage and mixed sources containing natural gas usage) apportioned by MC-PMF decreased, while those of sources that emitted high RMM species (e.g., solvent usage and mixed sources containing solvent usage) increased. Source apportionments based on the volumetric concentration data had more practical significance compared to the mass concentration data results for control strategy development since the mass data analyses created issues.

Crosstalk among Alternative Polyadenylation, Genetic Variants and Ubiquitin Modification Contribute to Lung Adenocarcinoma Risk.

Ubiquitin modification and alternative polyadenylation play crucial roles in the onset and progression of cancer. Hence, this study aims to comprehensively and deeply understand gene regulation and associated biological processes in lung adenocarcinoma (LUAD) by integrating both mechanisms. Alternative polyadenylation (APA)-related E3 ubiquitin ligases in LUAD were identified through multiple databases, and the association between selected genetic loci influencing gene expression (apaQTL-SNPs) and LUAD risk were evaluated through the GWAS database of the Female Lung Cancer Consortium in Asia (FLCCA). Subsequently, the interaction between RNF213 and ZBTB20, as well as their functional mechanisms in LUAD, were investigated using bioinformatics analysis, Western blot, co-immunoprecipitation, and colony formation experiments. A total of five apaQTL-SNPs (rs41301932, rs4494603, rs9890400, rs56066320, and rs41301932), located on RNF213, were significantly associated with LUAD risk (p < 0.05), and they inhibit tumor growth through ubiquitin-mediated degradation of ZBTB20.

Evaluation of ST6Gal1 expression and clinicopathological significance in human glioma.

Glioma is the most common brain tumor, accounting for a large majority of cancer-related deaths. ß-galactoside α2, 6 sialyltranferase 1 (ST6Gal1), the primary enzyme responsible for the conjugation of α2, 6 sialic acids to protein and lipid targets, is strongly associated with the occurrence and development of several brain tumor types. Still, the expression, targets, and functions of ST6Gal1 in glioma patients remain undetermined. As sialylation of the Ig-like cell adhesion family molecules have prominent roles in the latter's regulation in other biological contexts, we screened for members that have potential to be regulated by ST6Gal1 in silico and examined co-expressed protein modules using data derived from the Cancer Genome Atlas (TCGA) database, and we identified neural cell adhesion molecule (NCAM1) as a major ST6Gal1-interacting target. Bioinformatic binding analysis confirmed the interaction of ST6Gal1 and NCAM1. Immunohistochemistry was then used to evaluate post-operative samples from 156 patients with gliomas. ST6Gal1 and NCAM1 were co-expressed in gliomas, and their expression correlated significantly (p = 0.002) by univariate analysis. Our study also found that the expression levels of both ST6Gal1 and NCAM1 corresponded negatively with glioma grade, isocitrate dehydrogenase (IDH) mutation, and proliferation index (Ki67). Consistently, Kaplan-Meier survival curves showed that lower ST6Gal1 and NCAM1 protein levels are linked to unfavorable outcomes in glioma patients (p = 0.018 and p < 0.001, respectively). Our data indicate that ST6Gal1 may participate in the inhibition of oncogenesis and malignant progression via interacting with and targeting NCAM1 in glioma, thus presenting a novel strategy for intervention.

The impact of psoriasis on idiopathic pulmonary fibrosis: a two-sample Mendelian randomization study.

BACKGROUND: The association between psoriasis and pulmonary fibrosis has been reported in observational studies. However, the association is vulnerable to bias from using immunosuppressants such as methotrexate, which can cause fibrosis in multiple organs. The present study is to investigate whether psoriasis could independently increase the risk of idiopathic pulmonary fibrosis (IPF). METHODS: We conducted a two-sample Mendelian randomization (MR) study using summary statistics from genome-wide association studies. The random-effects inverse variance weighted analysis was used as the primary method. Some secondary analyses were further performed, including a sensitivity analysis using a genetic instrument that excluded extended single nucleotide polymorphisms (SNPs) in the major histocompatibility complex (MHC) gene region. RESULTS: Our study included 9267 cases and 364,071 controls for psoriasis, 2018 cases, and 373,064 controls for IPF of European ancestry, respectively. Genetically predicted psoriasis was associated with a higher risk of IPF (odds ratio (OR), 1.14; 95% confidence interval (CI), 1.08-1.22; P < 0.001). Sensitivity analyses did not uncover any statistically significant evidence of bias resulting from pleiotropy or the genetic instruments, including SNPs in the MHC gene region. CONCLUSIONS: These MR analyses support that genetically predicted psoriasis was associated with the risk of IPF, implying that pulmonary fibrosis in patients with psoriasis should not be neglected, even if they are not receiving immunosuppressant therapy.

Poly I: C Alleviated Duck Intestinal Injury Infected with Duck Viral Enteritis by Inhibiting Apoptosis.

Duck enteritis virus (DEV) may lead to vascular injury, gastrointestinal mucosal erosion, lymphoid organ injury, and Polyinosinic-polycytidylic acid (Poly I:C) has an antiviral effect by inducing low levels of interferon. The purpose of this study was to explore the pathogenesis of DEV-induced intestinal injury in ducks and to verify the therapeutic effects of different concentrations of Poly I:C. In this study, duck enteritis model was established by infecting healthy Pekin ducks with DEV. Duck intestinal tissues were extracted from normal control group, model group, and treatment group with different doses of Poly I:C. In vivo, HE and TUNEL staining were used to observe the morphological changes and apoptosis. In vitro, the proliferation and apoptosis of duck intestinal epithelial cells were evaluated by MTT assay, TUNEL staining, and flow cytometry. The results showed that Poly I:C protected ducks from DEV toxicity by improving intestinal morphology and inhibiting apoptosis. In addition, the antiviral effect of Poly I:C on DEV was found in a dose-dependent manner, with a more relatively obvious effect at a high dose of Poly I:C. All in all, these results demonstrated that Poly I:C played a vital role in the apoptosis induced by DEV in ducks and modest dose of Poly I:C treatment worked well and may provide important reference for the development of new antiviral drugs in the future.

Identification of diagnostic biomarkers of rheumatoid arthritis based on machine learning-assisted comprehensive bioinformatics and its correlation with immune cells.

Background: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by inflammatory cell infiltration, which can lead to chronic disability, joint destruction and loss of function. At present, the pathogenesis of RA is still unclear. The purpose of this study is to explore the potential biomarkers and immune molecular mechanisms of rheumatoid arthritis through machine learning-assisted bioinformatics analysis, in order to provide reference for the early diagnosis and treatment of RA disease. Methods: RA gene chips were screened from the public gene GEO database, and batch correction of different groups of RA gene chips was performed using Strawberry Perl. DEGs were obtained using the limma package of R software, and functional enrichment analysis such as gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), disease ontology (DO), and gene set (GSEA) were performed. Three machine learning methods, least absolute shrinkage and selection operator regression (LASSO), support vector machine recursive feature elimination (SVM-RFE) and random forest tree (Random Forest), were used to identify potential biomarkers of RA. The validation group data set was used to verify and further confirm its expression and diagnostic value. In addition, CIBERSORT algorithm was used to evaluate the infiltration of immune cells in RA and control samples, and the correlation between confirmed RA diagnostic biomarkers and immune cells was analyzed. Results: Through feature screening, 79 key DEGs were obtained, mainly involving virus response, Parkinson's pathway, dermatitis and cell junction components. A total of 29 hub genes were screened by LASSO regression, 34 hub genes were screened by SVM-RFE, and 39 hub genes were screened by Random Forest. Combined with the three algorithms, a total of 12 hub genes were obtained. Through the expression and diagnostic value verification in the validation group data set, 7 genes that can be used as diagnostic biomarkers for RA were preliminarily confirmed. At the same time, the correlation analysis of immune cells found that γδT cells, CD4+ memory activated T cells, activated dendritic cells and other immune cells were positively correlated with multiple RA diagnostic biomarkers, CD4+ naive T cells, regulatory T cells and other immune cells were negatively correlated with multiple RA diagnostic biomarkers. Conclusions: The results of novel characteristic gene analysis of RA showed that KYNU, EVI2A, CD52, C1QB, BATF, AIM2 and NDC80 had good diagnostic and clinical value for the diagnosis of RA, and were closely related to immune cells. Therefore, these seven DEGs may become new diagnostic markers and immunotherapy markers for RA.

Case report: Two novel compound heterozygous variant of SLC12A3 gene in a gitelman syndrome family and literature review.

A 36-year-old unmarried male chef was incidentally diagnosed with hypokalemia during an evaluation for an acute perianal abscess. Despite potassium supplementation, he developed progressive weakness in his lower limbs, culminating in an inability to stand. Investigations confirmed severe hypokalemia, metabolic alkalosis, hypomagnesemia, secondary hyperaldosteronism, and low urinary calcium excretion, with normotension. The patient's long-standing stunted growth and lean physique since childhood were noted. Biochemical assays further identified type 2 diabetes mellitus and metabolic syndrome. Genetic analysis revealed three heterozygous SLC12A3 mutations (M1: c.421G>A: p.G141R, M2: c.509T>A:p.L170Q, and M3: c.704C>A: p.T235K), compound heterozygo us and derived from both parents, with M1 and M3 reported here for the first time. Treatment with spironolactone and oral potassium chloride stabilized his potassium levels. Following the administration of SGLT2 inhibitors in patients receiving hypoglycemic therapy, we observed a mild decrease in serum sodium levels. This case highlights the criticality of vigilant metabolic surveillance in Gitelman syndrome and advises prudence with SGLT2 inhibitors in those with concurrent type 2 diabetes, given the risk of potentially aggravate sodium loss.

[Simultaneous determination of maltol and seventeen saponins in red and black ginseng by UPLC-PDA wavelength switching method].

This study developed a UPLC-PDA wavelength switching method to simultaneously determine the content of maltol and seventeen saponins in red and black ginseng and compared the quality differences of two different processed products of red and black ginseng. A Waters HSS T3 column(2. 1 mm×100 mm, 1. 8 µm) at 30 ℃ was adopted, with the mobile phase of acetonitrile(A) and water containing 0. 1% phosphoric acid(B) under gradient elution, the flow rate of 0. 3 m L·min~(-1), and the injection volume of 2 µL.The wavelength switching was set at 273 nm within 0-11 min and 203 nm within 11-60 min. The content results of multiple batches of red and black ginseng samples were analyzed by the hierarchical cluster analysis(HCA) and principal component analysis(PCA) to evaluate the quality difference. The results showed that the 18 constituents exhibited good linear relationships within certain concentration ranges, with the correlation coefficients(r) greater than 0. 999 1. The relative standard deviations(RSDs) of precision,repeatability, and stability were all less than 5. 0%. The average recoveries ranged from 95. 93% to 104. 2%, with an RSD of 1. 8%-4. 2%. The content determination results showed that the quality of red and black ginseng samples was different, and the two types of processed products were intuitively distinguished by HCA and PCA. The method is accurate, reliable, and reproducible. It can be used to determine the content of maltol and seventeen saponins in red and black ginseng and provide basic information for the quality evaluation and comprehensive utilization of red and black ginseng.

Understanding the Temporal Dynamics of Accelerated Brain Aging and Resilient Brain Aging: Insights from Discriminative Event-Based Analysis of UK Biobank Data.

The intricate dynamics of brain aging, especially the neurodegenerative mechanisms driving accelerated (ABA) and resilient brain aging (RBA), are pivotal in neuroscience. Understanding the temporal dynamics of these phenotypes is crucial for identifying vulnerabilities to cognitive decline and neurodegenerative diseases. Currently, there is a lack of comprehensive understanding of the temporal dynamics and neuroimaging biomarkers linked to ABA and RBA. This study addressed this gap by utilizing a large-scale UK Biobank (UKB) cohort, with the aim to elucidate brain aging heterogeneity and establish the foundation for targeted interventions. Employing Lasso regression on multimodal neuroimaging data, structural MRI (sMRI), diffusion MRI (dMRI), and resting-state functional MRI (rsfMRI), we predicted the brain age and classified individuals into ABA and RBA cohorts. Our findings identified 1949 subjects (6.2%) as representative of the ABA subpopulation and 3203 subjects (10.1%) as representative of the RBA subpopulation. Additionally, the Discriminative Event-Based Model (DEBM) was applied to estimate the sequence of biomarker changes across aging trajectories. Our analysis unveiled distinct central ordering patterns between the ABA and RBA cohorts, with profound implications for understanding cognitive decline and vulnerability to neurodegenerative disorders. Specifically, the ABA cohort exhibited early degeneration in four functional networks and two cognitive domains, with cortical thinning initially observed in the right hemisphere, followed by the temporal lobe. In contrast, the RBA cohort demonstrated initial degeneration in the three functional networks, with cortical thinning predominantly in the left hemisphere and white matter microstructural degeneration occurring at more advanced stages. The detailed aging progression timeline constructed through our DEBM analysis positioned subjects according to their estimated stage of aging, offering a nuanced view of the aging brain's alterations. This study holds promise for the development of targeted interventions aimed at mitigating age-related cognitive decline.

Integrating apaQTL and eQTL analysis identifies a potential causal variant associated with lung adenocarcinoma risk in the Chinese population.

Alternative polyadenylation (APA) plays a crucial role in cancer biology. Here, we used data from the 3'aQTL-atlas, GTEx, and the China Nanjing Lung Cancer GWAS database to explore the association between apaQTL/eQTL-SNPs and the risk of lung adenocarcinoma (LUAD). The variant T allele of rs277646 in NIT2 is associated with an increased risk of LUAD (OR = 1.12, P = 0.015), lower PDUI values, and higher NIT2 expression. The 3'RACE experiment showed multiple poly (A) sites in NIT2, with the rs277646-T allele causing preferential use of the proximal poly (A) site, resulting in a shorter 3'UTR transcript. This leads to the loss of the hsa-miR-650 binding site, thereby affecting LUAD malignant phenotypes by regulating the expression level of NIT2. Our findings may provide new insights into understanding and exploring APA events in LUAD carcinogenesis.

Analyzing pain patterns in the emergency department: Leveraging clinical text deep learning models for real-world insights.

OBJECTIVE: To determine the incidence of patients presenting in pain to a large Australian inner-city emergency department (ED) using a clinical text deep learning algorithm. MATERIALS AND METHODS: A fine-tuned, domain-specific, transformer-based clinical text deep learning model was used to interpret free-text nursing assessments in the electronic medical records of 235,789 adult presentations to the ED over a three-year period. The model classified presentations according to whether the patient had pain on arrival at the ED. Interrupted time series analysis was used to determine the incidence of pain in patients on arrival over time. We described the changes in the population characteristics and incidence of patients with pain on arrival occurring with the start of the Covid-19 pandemic. RESULTS: 55.16% (95%CI 54.95%-55.36%) of all patients presenting to this ED had pain on arrival. There were differences in demographics and arrival and departure patterns between patients with and without pain. The Covid-19 pandemic initially precipitated a decrease followed by a sharp, sustained rise in pain on arrival, with concurrent changes to the population arriving in pain and their treatment. DISCUSSION: Applying a clinical text deep learning model has successfully identified the incidence of pain on arrival. It represents an automated, reproducible mechanism to identify pain from routinely collected medical records. The description of this population and their treatment forms the basis of intervention to improve care for patients with pain. The combination of the clinical text deep learning models and interrupted time series analysis has reported on the effects of the Covid-19 pandemic on pain care in the ED, outlining a methodology to assess the impact of significant events or interventions on pain care in the ED. CONCLUSION: Applying a novel deep learning approach to identifying pain guides methodological approaches to evaluating pain care interventions in the ED, giving previously unavailable population-level insights.

Plasma GPI and PGD are associated with vascular normalization and may serve as novel prognostic biomarkers for lung adenocarcinoma: Multi-omics and multi-dimensional analysis.

The aim of this study was to explore potential novel plasma protein biomarkers for lung adenocarcinoma (LUAD). A plasma proteomics analysis was carried out and candidate protein biomarkers were validated in 102 LUAD cases and 102 matched healthy controls. The same LUAD tumor tissues were detected to explore the correlation between the expression of candidate proteins in tissues and plasma and vascular normalization. A LUAD active metastasis mice model was constructed to explore the role of candidate proteins for lung metastasis. GPI and PGD were verified to be upregulated in plasma from LUAD patients, and the expression of GPI in tumor tissue was positively correlated with the expression of GPI in plasma and negatively correlated with the normalization of tumor blood vessels. Meanwhile, a negative correlation between the expression of GPI and PGD in plasma and tumor vascular normalization was discovered. In the LUAD active metastasis model, the lowest levels of vascular normalization and the highest expression of GPI and PGD were found in mice with lung metastases. This study found that GPI and PGD may be potential plasma biomarkers for LUAD, and monitoring those may infer the risk of metastasis and malignancy of the tumor. SIGNIFICANT: We identified GPI and PGD as potential novel diagnostic and prognostic biomarkers for LUAD. PGD and GPI can be used as diagnostic biomarkers in combination with other available strategies to assist in the screening and diagnosis of LUAD, and as prognostic biomarkers aid in predict the risk of tumor metastasis and malignancy in patients with LUAD.

Colonization by the endophytic fungus Phyllosticta fallopiae combined with the element Si promotes the growth of Dendrobium nobile.

Endophytic fungi can promote plant growth and development, particularly of Orchidaceae species. Previously, we found that the endophytic fungus Phyllosticta fallopiae DN14, collected from Dendrobium nobile growing on rocks in a wild habitat, significantly promoted growth of its host plant D. nobile, an important herb in Chinese traditional medicine that contains the bioactive component dendrobine. Phyllosticta was positively correlated with FW and dendrobine content of D. nobile and with Si content of the epiphytic matrix. Si is also highly beneficial for the growth and productivity of many plants. Here, we co-cultured D. nobile with P. fallopiae DN14 in half-strength Murashige and Skoog medium with and without various concentrations of Si to investigate the effects of DN14 and Si on plant fresh weight and dendrobine content. We also explored the effects of DN14 infection and colonization on host plant growth, Si accumulation and transport, and expression of key genes, as well as the interaction between DN14 and Si. The combination of DN14 and Si promoted the lignification of D. nobile roots, stems, and leaves and markedly increased the thickening of xylem cell walls. Co-culture with DN14 increased transport of Si from roots to stems and from stems to leaves. Transcriptome sequencing and qRT-PCR analyses showed that enhancement of D. nobile growth by DN14 and Si may involve upregulation of plant hormone-related genes (AUX/IAA and MYC) and lignin biosynthesis genes (HCT, PAL1, and PAL2). Insoluble Si promoted the growth of DN14, perhaps through downregulation of genes (e.g., FBP, MPI, RPIAD) related to carbohydrate metabolism, and DN14 in turn promoted the transformation of insoluble Si into soluble Si for plant uptake. These findings demonstrate that endophytic fungi and Si can improve the growth of D. nobile and therefore show promise as organic amendments for commercial cultivation.

NEDD4L mediates ITGB4 ubiquitination and degradation to suppress esophageal carcinoma progression.

The ubiquitination-mediated protein degradation exerts a vital role in the progression of multiple tumors. NEDD4L, which belongs to the E3 ubiquitin ligase NEDD4 family, is related to tumor genesis, metastasis and drug resistance. However, the anti-tumor role of NEDD4L in esophageal carcinoma, and the potential specific recognition substrate remain unclear. Based on public esophageal carcinoma database and clinical sample data, it was discovered in this study that the expression of NEDD4L in esophageal carcinoma was apparently lower than that in atypical hyperplastic esophageal tissue and esophageal squamous epithelium. Besides, patients with high expression of NEDD4L in esophageal carcinoma tissue had longer progression-free survival than those with low expression. Experiments in vivo and in vitro also verified that NEDD4L suppressed the growth and metastasis of esophageal carcinoma. Based on co-immunoprecipitation and proteome analysis, the NEDD4L ubiquitination-degraded protein ITGB4 was obtained. In terms of the mechanism, the HECT domain of NEDD4L specifically bound to the Galx-ß domain of ITGB4, which modified the K915 site of ITGB4 in an ubiquitination manner, and promoted the ubiquitination degradation of ITGB4, thus suppressing the malignant phenotype of esophageal carcinoma.

Using Bulky Dodecaborane-Based Dopants to Produce Mobile Charge Carriers in Amorphous Semiconducting Polymers.

Conjugated polymers are a versatile class of electronic materials featured in a variety of next-generation electronic devices. The utility of such polymers is contingent in large part on their electrical conductivity, which depends both on the density of charge carriers (polarons) and on the carrier mobility. Carrier mobility, in turn, is largely controlled by the separation between the polarons and dopant counterions, as counterions can produce Coulombic traps. In previous work, we showed that large dopants based on dodecaborane (DDB) clusters were able to reduce Coulombic binding and thus increase carrier mobility in regioregular (RR) poly(3-hexylthiophene-2,5-diyl) (P3HT). Here, we use a DDB-based dopant to study the effects of polaron-counterion separation in chemically doped regiorandom (RRa) P3HT, which is highly amorphous. X-ray scattering shows that the DDB dopants, despite their large size, can partially order the RRa P3HT during doping and produce a doped polymer crystal structure similar to that of DDB-doped RR P3HT; Alternating Field (AC) Hall measurements also confirm a similar hole mobility. We also show that use of the large DDB dopants successfully reduces Coulombic binding of polarons and counterions in amorphous polymer regions, resulting in a 77% doping efficiency in RRa P3HT films. The DDB dopants are able to produce RRa P3HT films with a 4.92 S/cm conductivity, a value that is ∼200× higher than that achieved with 3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ), the traditional dopant molecule. These results show that tailoring dopants to produce mobile carriers in both the amorphous and semicrystalline regions of conjugated polymers is an effective strategy for increasing achievable polymer conductivities, particularly in low-cost polymers with random regiochemistry. The results also emphasize the importance of dopant size and shape for producing Coulombically unbound, mobile polarons capable of electrical conduction in less-ordered materials.

Fibroblast: A Novel Target for Autoimmune and Inflammatory Skin Diseases Therapeutics.

Fibroblasts are crucial components of the skin structure. They were traditionally believed to maintain the skin's structure by producing extracellular matrix and other elements. Recent research illuminated that fibroblasts can respond to external stimuli and exhibit diverse functions, such as the secretion of pro-inflammatory factors, adipogenesis, and antigen presentation, exhibiting remarkable heterogeneity and plasticity. This revelation positions fibroblasts as active contributors to the pathogenesis of skin diseases, challenging the traditional perspective that views fibroblasts solely as structural entities. Based on their diverse functions, fibroblasts can be categorized into six subtypes: pro-inflammatory fibroblasts, myofibroblasts, adipogenic fibroblasts, angiogenic fibroblasts, mesenchymal fibroblasts, and antigen-presenting fibroblasts. Cytokines, metabolism, and epigenetics regulate functional abnormalities in fibroblasts. The dynamic changes fibroblasts exhibit in different diseases and disease states warrant a comprehensive discussion. We focus on dermal fibroblasts' aberrant manifestations and pivotal roles in inflammatory and autoimmune skin diseases, including psoriasis, vitiligo, lupus erythematosus, scleroderma, and atopic dermatitis, and propose targeting aberrantly activated fibroblasts as a potential therapeutic strategy for inflammatory and autoimmune skin diseases.

Microporous Materials in Polymer Electrolytes: The Merit of Order.

Solid-state batteries (SSBs) have garnered significant attention in the critical field of sustainable energy storage due to their potential benefits in safety, energy density, and cycle life. The large-scale, cost-effective production of SSBs necessitates the development of high-performance solid-state electrolytes. However, the manufacturing of SSBs relies heavily on the advancement of suitable solid-state electrolytes. Composite polymer electrolytes (CPEs), which combine the advantages of ordered microporous materials (OMMs) and polymer electrolytes, meet the requirements for high ionic conductivity/transference number, stability with respect to electrodes, compatibility with established manufacturing processes, and cost-effectiveness, making them particularly well-suited for mass production of SSBs. This review delineates how structural ordering dictates the fundamental physicochemical properties of OMMs, including ion transport, thermal transfer, and mechanical stability. The applications of prominent OMMs are critically examined, such as metal-organic frameworks, covalent organic frameworks, and zeolites, in CPEs, highlighting how structural ordering facilitates the fulfillment of property requirements. Finally, an outlook on the field is provided, exploring how the properties of CPEs can be enhanced through the dimensional design of OMMs, and the importance of uncovering the underlying "feature-function" mechanisms of various CPE types is underscored.

Transcriptome Analysis Reveals the Biocontrol Mechanism of Endophytic Bacterium AM201, Rhodococcus sp., against Root Rot Disease of Atractylodes macrocephala.

Atractylodes macrocephala Koidz (AMK) is a perennial herb from the plant family Asteraceae (formerly Compositae). This herb is mainly distributed in mountainous wetlands in Zhejiang, Sichuan, Yunnan, and Hunan provinces of China. Its medicinal production and quality, however, are severely impacted by root rot disease. In our previous study, endophytic bacterium designated AM201 exerted a high biocontrol effect on the root rot disease of AMK. However, the molecular mechanisms underlying this effect remain unclear. In this study, the identity of strain AM201 as Rhodococcus sp. was determined through analysis of its morphology, physiological and biochemical characteristics, as well as 16S rDNA sequencing. Subsequently, we performed transcriptome sequencing and bioinformatics analysis to compare and analyze the transcriptome profiles of root tissues from two groups: AM201 (AMK seedlings inoculated with Fusarium solani [FS] and AM201) and FS (AMK seedlings inoculated with FS alone). We also conducted morphological, physiological, biochemical, and molecular identification analyses for the AM201 strain. We obtained 1,560 differentially expressed genes, including 187 upregulated genes and 1,373 downregulated genes. We screened six key genes (GOLS2, CIPK25, ABI2, egID, PG1, and pgxB) involved in the resistance of AM201 against AMK root rot disease. These genes play a critical role in reactive oxygen species (ROS) clearance, Ca2+ signal transduction, abscisic acid signal inhibition, plant root growth, and plant cell wall defense. The strain AM201 was identified as Rhodococcus sp. based on its morphological characteristics, physiological and biochemical properties, and 16S rDNA sequencing results. The findings of this study could enable to prevent and control root rot disease in AMK and could offer theoretical guidance for the agricultural production of other medicinal herbs.

The Analysis, Description, and Examination of the Maize LAC Gene Family's Reaction to Abiotic and Biotic Stress.

Laccase (LAC) is a diverse group of genes found throughout the plant genome essential for plant growth and the response to stress by converting monolignin into intricate lignin formations. However, a comprehensive investigation of maize laccase has not yet been documented. A bioinformatics approach was utilized in this research to conduct a thorough examination of maize (Zea mays L.), resulting in the identification and categorization of 22 laccase genes (ZmLAC) into six subfamilies. The gene structure and motifs of each subgroup were largely consistent. The distribution of the 22 LAC genes was uneven among the maize chromosomes, with the exception of chromosome 9. The differentiation of the genes was based on fragment replication, and the differentiation time was about 33.37 million years ago. ZmLAC proteins are primarily acidic proteins. There are 18 cis-acting elements in the promoter sequences of the maize LAC gene family associated with growth and development, stress, hormones, light response, and stress response. The analysis of tissue-specific expression revealed a high expression of the maize LAC gene family prior to the V9 stage, with minimal expression at post-V9. Upon reviewing the RNA-seq information from the publicly available transcriptome, it was discovered that ZmLAC5, ZmLAC10, and ZmLAC17 exhibited significant expression levels when exposed to various biotic and abiotic stress factors, suggesting their crucial involvement in stress responses and potential value for further research. This study offers an understanding of the functions of the LAC genes in maize's response to biotic and abiotic stress, along with a theoretical basis for comprehending the molecular processes at play.

Ultrahigh Bipolar Photoresponse in a Self-Powered Ultraviolet Photodetector Based on GaN and In/Sn-Doped Ga2O3 Nanowires pn junction.

Self-powered ultraviolet photodetectors with bipolar photoresponse have great potential in the fields of ultraviolet optical communication, all-optical controlled artificial synapses, high-resolution ultraviolet imaging equipment, and multiband photoelectric detection. However, the current low optoelectronic performance limits the development of such polar switching devices. Here, we construct a self-powered ultraviolet photodetector based on GaN and In/Sn-doped Ga2O3 (IGTO) nanowires (NWs) pn junction structure. This unique nanowire/thin film structure allows GaN and IGTO to dominate the absorption of light at different wavelengths, resulting in a highly bipolar photoresponse. The device has a responsivity of 2.04 A/W and a normalized detectivity of 7.18 × 1013 Jones at 254 nm and a responsivity of -2.09 A/W and a normalized detectivity of -7 × 1013 Jones at 365 nm, both at zero bias. In addition, it has an extremely high Ilight/Idark ratio of 1.05 × 105 and ultrafast response times of 2.4/1.9 ms (at 254 nm) and 5.7/5.2 ms (at 365 nm). These excellent properties are attributed to the high specific surface area of the one-dimensional nanowire structure and the abundant voids generated by the nanowire network to enhance the absorption of light, and the p-n junction structure enables the rapid separation and transfer of photogenerated electron-hole pairs. Our findings provide a feasible strategy for high-performance wavelength-controlled polarity switching devices.