Identification of Apple Flower Development-Related Gene Families and Analysis of Transcriptional Regulation.

Apple (Malus domestica Borkh.) stands out as a globally significant fruit tree with considerable economic importance. Nonetheless, the orchard production of 'Fuji' apples faces significant challenges, including delayed flowering in young trees and inconsistent annual yields in mature trees, ultimately resulting in suboptimal fruit yield due to insufficient flower bud formation. Flower development represents a pivotal process influencing plant adaptation to environmental conditions and is a crucial determinant of successful plant reproduction. The three gene or transcription factor (TF) families, C2H2, DELLA, and FKF1, have emerged as key regulators in plant flowering regulation; however, understanding their roles during apple flowering remains limited. Consequently, this study identified 24 MdC2H2, 6 MdDELLA, and 6 MdFKF1 genes in the apple genome with high confidence. Through phylogenetic analyses, the genes within each family were categorized into three distinct subgroups, with all facets of protein physicochemical properties and conserved motifs contingent upon subgroup classification. Repetitive events between these three gene families within the apple genome were elucidated via collinearity analysis. qRT-PCR analysis was conducted and revealed significant expression differences among MdC2H2-18, MdDELLA1, and MdFKF1-4 during apple bud development. Furthermore, yeast two-hybrid analysis unveiled an interaction between MdC2H2-18 and MdDELLA1. The genome-wide identification of the C2H2, DELLA, and FKF1 gene families in apples has shed light on the molecular mechanisms underlying apple flower bud development.

Occurrence and prevalence of per- and polyfluoroalkyl substances in the sediment pore water of mariculture sites: Novel findings of PFASs from the Bohai and Yellow Seas using a newly established analytical method.

A new method for the determination of 26 legacy and emerging per- and polyfluoroalkyl substances (PFASs) in marine sediment pore water was developed using online solid phase extraction coupled with liquid chromatography-tandem mass spectrometry. The proposed method requires only about 1 mL of pore water samples. Satisfactory recoveries of most target PFASs (83.55-125.30 %) were achieved, with good precision (RSD of 1.09-16.53 %), linearity (R2 ≥ 0.990), and sensitivity (MDLs: 0.05 ng/L-5.00 ng/L for most PFASs). Subsequently, the method was applied to determine PFASs in the sediment pore water of five mariculture bays in the Bohai and Yellow Seas of China for the first time. Fifteen PFASs were detected with total concentrations ranging from 150.23 ng/L to 1838.48 ng/L (mean = 636.80 ng/L). The ∑PFASs and PFOA concentrations in sediment pore water were remarkably higher than those in surface seawater (tens of ng/L), indicating that the potential toxic effect of PFASs on benthic organisms may be underestimated. PFPeA was mainly distributed in pore water, and the partition of PFHpA (50.99 %) and PFOA (49.01 %) was almost equal in the solid and liquid phases. The proportions of all other PFASs partitioned in marine sediments were significantly higher than those in pore water.

Mixed probiotics reduce the severity of stress-induced depressive-like behaviors.

In recent years, the gut microbiome has gained significant attention in the spheres of research and public health. As a result, studies have increasingly explored the potential of probiotic dietary supplements as treatment interventions for conditions such as anxiety and depression. The present study examined the effect of mixed probiotics (Lacticaseibacillus rhamnosus and Enterococcus faecium) on inflammation, microbiome composition, and depressive-like behaviors in a macaque monkey model. The mixed probiotics effectively reduced the severity of depressive-like behaviors in macaque monkeys. Further, treatment with mixed probiotics gradually increased the abundance of beneficial bacteria in the gut, improving the balance of the gut microbiota. Additionally, macaques treated with the mixed probiotics showed decreased serum levels of inflammatory factors (P < 0.05), an increased rate of L-tryptophan metabolism (P < 0.05), and the restoration of 5-HT and 5-HTP levels (P < 0.05). Correlation analysis confirmed that Lacticaseibacillus and other beneficial bacteria exhibited a negative correlation with inflammation in the body (P < 0.05), and a positive correlation with tryptophan metabolism (P < 0.05). In conclusion, the mixed probiotics effectively restored intestinal homeostasis in macaques and enhanced tryptophan metabolism, ultimately alleviating inflammation and depressive-like behaviors.

Bioaerosols in the coastal region of Qingdao: Community diversity, impact factors and synergistic effect.

Atmospheric bioaerosols are influenced by multiple factors, including physical, chemical, and biotic interactions, and pose a significant threat to the public health and the environment. The nonnegligible truth however is that the primary driver of the changes in bioaerosol community diversity remains unknown. In this study, putative biological association (PBA) was obtained by constructing an ecological network. The relationship between meteorological conditions, atmospheric pollutants, water-soluble inorganic ions, PBA and bioaerosol community diversity was analyzed using random forest regression (RFR)-An ensemble learning algorithm based on a decision tree that performs regression tasks by constructing multiple decision trees and integrating the predicted results, and the contribution of different rich species to PBA was predicted. The species richness, evenness and diversity varied significantly in different seasons, with the highest in summer, followed by autumn and spring, and was lowest in winter. The RFR suggested that the explanation rate of alpha diversity increased significantly from 73.74 % to 85.21 % after accounting for the response of the PBA to diversity. The PBA, temperature, air pollution, and marine source air masses were the most crucial factors driving community diversity. PBA, particularly putative positive association (PPA), had the highest significance in diversity. We found that under changing external conditions, abundant taxa tend to cooperate to resist external pressure, thereby promoting PPA. In contrast, rare taxa were more responsive to the putative negative association because of their sensitivity to environmental changes. The results of this research provided scientific advance in the understanding of the dynamic and temporal changes in bioaerosols, as well as support for the prevention and control of microbial contamination of the atmosphere.

All-Dielectric Integrated Meta-Antenna Operating in 6G Terahertz Communication Window.

Efficient transceivers and antennas at terahertz frequencies are leading the development of 6G terahertz communication systems. The antenna design for high-resolution terahertz spatial sensing and communication remains challenging, while emergent metallic metasurface antennas can address this issue but often suffer from low efficiency and complex manufacturing. Here, an all-dielectric integrated meta-antenna operating in 6G terahertz communication window for high-efficiency beam focusing in the sub-wavelength scale is reported. With the antenna surface functionalized by metagrating arrays with asymmetric scattering patterns, the design and optimization methods are demonstrated with a physical size constraint. The highest manipulation and diffraction efficiencies achieve 84.1% and 48.1%. The commercially accessible fabrication method with low cost and easy to implement has been demonstrated for the meta-antenna by photocuring 3D printing. A filamentous focal spot is measured as 0.86λ with a long depth of focus of 25.3λ. Its application for integrated imaging and communication has been demonstrated. The proposed technical roadmap provides a general pathway for creating high-efficiency integrated meta-antennas with great potential in high-resolution 6G terahertz spatial sensing and communication applications.

Effects of ozone on activated sludge: performance of anaerobic digestion and structure of the microbial community.

The treatment and disposal of activated sludge are currently challenging tasks in the world. As a common biological engineering technology, biological fermentation exists with disadvantages such as low efficiency and complex process. Ozone pretreatments are commonly applied to improve this problem due to their high efficiency and low cost. In this study, the significant function of ozone in anaerobic fermentation gas production was verified with excess sludge. Compared with other untreated sludge, ozone pretreatment can effectively degrade activated sludge. After ozone treatment and mixing with primary sludge, the methane production of excess sludge increased by 49.30 and 50.78%, and the methanogenic activity increased by 69.99 and 73.83%, respectively. The results indicated that the mixing of primary sludge with excess sludge possessed synergistic effects, which contributed to the anaerobic fermentation of excess sludge. The results of microbial community structure exhibited that methanogenic processes mainly involve hydrogenogens, acidogens and methanogens. The relative abundance of both bacteria and microorganisms changed significantly in the early stage of hydraulic retention time, which coincided exactly with the gas production stage. This study provided a feasible pretreatment strategy to improve sludge biodegradability and revealed the role of microorganisms during anaerobic digestion.

GABA induced by sleep deprivation promotes the proliferation and migration of colon tumors through miR-223-3p endogenous pathway and exosome pathway.

BACKGROUND: Research has indicated that long-term sleep deprivation can lead to immune dysfunction and participate in the occurance and progression of tumors. However, the relationship between sleep deprivation and colon cancer remains unclear. This study explored the specific mechanism through which sleep deprivation promotes the proliferation and migration of colon cancer, with a focus on the neurotransmitter GABA. METHODS: Chronic sleep deprivation mice model were used to investigate the effect of sleep disorder on tumors. We detected neurotransmitter levels in the peripheral blood of mice using ELISA. CCK-8 assay, colony formation assay, wound healing assay, and transwell assay were performed to investigate the effect of GABA on colon cancer cells, while immunofluorescence showed the distribution of macrophages in lung metastatic tissues. We isolated exosomes from a GABA-induced culture medium to explore the effects of GABA-induced colon cancer cells on macrophages. Gain- and loss-of-function experiments, luciferase report analysis, immunohistochemistry, and cytokine detection were performed to reveal the crosstalk between colon cancer cells and macrophages. RESULTS: Sleep deprivation promote peripheral blood GABA level and colon cancer cell proliferation and migration. Immunofluorescence analysis revealed that GABA-induced colon cancer metastasis is associated with enhanced recruitment of macrophages in the lungs. The co-culture results showed that GABA intensified M2 polarization of macrophage induced by colon cancer cells. This effect is due to the activation of the macrophage MAPK pathway by tumor-derived exosomal miR-223-3p. Furthermore, M2-like macrophages promote tumor proliferation and migration by secreting IL-17. We also identified an endogenous miR-223-3p downregulation of the E3 ligase CBLB, which enhances the stability of cMYC protein and augments colon cancer cells proliferation and migration ability. Notably, cMYC acts as a transcription factor and can also regulate the expression of miR-223-3p. CONCLUSION: Our results suggest that sleep deprivation can promote the expression of miR-223-3p in colon cancer cells through GABA, leading to downregulation of the E3 ligase CBLB and inhibition of cMYC ubiquitination. Simultaneously, extracellular miR-223-3p promotes M2-like macrophage polarization, which leads to the secretion of IL-17, further enhancing the proliferation and migration of colon cancer cells.

Temsirolimus is a promising immunomodulatory agent for enhanced transplantation outcomes.

BACKGROUND: Identifying effective immunosuppressive strategies is critical for addressing immunological rejection following organ transplantation. This study explores the potential immunosuppressive effects and mechanisms of temsirolimus, a rapamycin derivative, in organ transplantation. METHODS: A mouse cardiac allograft model was established using a cervical cannula technique with BALB/c donors and C57BL/6 recipients. Mice were administered temsirolimus intragastrically and graft survival was evaluated. Histological staining was used to assess pathological changes. The BrdU assay was used to measure splenic T cell proliferation. Flow cytometry was used to quantify regulatory T cells (Tregs), CD4+ T cells, and CD8+ T cells. ELISA and qPCR assays were used to determine Foxp3, IL-4, IFN-γ, and TGF-ß expression. RESULTS: Temsirolimus displayed potent immunosuppressive effects at 20 mg/kg/day, significantly inhibiting T cell proliferation (84.6%, P < 0.0001) and prolonging graft survival (median 49 days vs. 8.5 days in controls, P < 0.0001). However, median survival decreased to 34.5 days upon withdrawal. Temsirolimus also reduced splenic CD4+ and CD8+ T cells (2.85% and 2.92%, P < 0.001) and antibody levels (IgM, IgG1, IgG2) by 11.85-29.09% (P < 0.0001) and increased Tregs, Foxp3, IL-4 (P < 0.01), and TGF-ß (P < 0.05), while decreasing IFN-γ (P < 0.001). CONCLUSIONS: Temsirolimus exhibited potent immunosuppressive effects, emerging as a strong candidate to mitigate organ transplant rejection.

Machine learning methods for accurately predicting survival and guiding treatment in stage I and II hepatocellular carcinoma.

Accurately predicting survival in patients with early hepatocellular carcinoma (HCC) is essential for making informed decisions about treatment and prognosis. Herein, we have developed a machine learning (ML) model that can predict patient survival and guide treatment decisions. We obtained patient demographic information, tumor characteristics, and treatment details from the SEER database. To analyze the data, we employed a Cox proportional hazards (CoxPH) model as well as 3 ML algorithms: neural network multitask logistic regression (N-MLTR), DeepSurv, and random survival forest (RSF). Our evaluation relied on the concordance index (C-index) and Integrated Brier Score (IBS). Additionally, we provided personalized treatment recommendations regarding surgery and chemotherapy choices and validated models' efficacy. A total of 1136 patients with early-stage (I, II) hepatocellular carcinoma (HCC) who underwent liver resection or transplantation were randomly divided into training and validation cohorts at a ratio of 3:7. Feature selection was conducted using Cox regression analyses. The ML models (NMLTR: C-index = 0.6793; DeepSurv: C-index = 0.7028; RSF: C-index = 0.6890) showed better discrimination in predicting survival than the standard CoxPH model (C-index = 0.6696). Patients who received recommended treatments had higher survival rates than those who received unrecommended treatments. ML-based surgery treatment recommendations yielded higher hazard ratios (HRs): NMTLR HR = 0.36 (95% CI: 0.25-0.51, P < .001), DeepSurv HR = 0.34 (95% CI: 0.24-0.49, P < .001), and RSF HR = 0.37 (95% CI: 0.26-0.52, P = <.001). Chemotherapy treatment recommendations were associated with significantly improved survival for DeepSurv (HR: 0.57; 95% CI: 0.4-0.82, P = .002) and RSF (HR: 0.66; 95% CI: 0.46-0.94, P = .020). The ML survival model has the potential to benefit prognostic evaluation and treatment of HCC. This novel analytical approach could provide reliable information on individual survival and treatment recommendations.

Developing a RiskS-core Model based on Angiogenesis-related lncRNAs for Colon Adenocarcinoma Prognostic Prediction.

AIM: We screened key angiogenesis-related lncRNAs based on colon adenocarcinoma (COAD) to construct a RiskS-core model for predicting COAD prognosis and help reveal the pathogenesis of the COAD as well as optimize clinical treatment. BACKGROUND: Regulatory roles of lncRNAs in tumor progression and prognosis have been confirmed, but few studies have probed into the role of angiogenesis-related lncRNAs in COAD. OBJECTIVE: To identify key angiogenesis-related lncRNAs and build a RiskS-core model to predict the survival probability of COAD patients and help optimize clinical treatment. METHODS: Sample data were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The HALLMARK pathway score in the samples was calculated using the single sample gene set enrichment analysis (ssGSEA) method. LncRNAs associated with angiogenesis were filtered by an integrated pipeline algorithm. LncRNA-based subtypes were classified by ConsensusClusterPlus and then compared with other established subtypes. A RiskS-core model was created based on univariate Cox, least absolute shrinkage and selection operator (LASSO) regression and stepwise regression analysis. The Kaplan-Meier curve was drawn by applying R package survival. The time-dependent ROC curves were drawn by the timeROC package. Finally, immunotherapy benefits and drug sensitivity were analyzed using tumor immune dysfunction and exclusion (TIDE) software and pRRophetic package. RESULTS: Pathway analysis showed that the angiogenesis pathway was a risk factor affecting the prognosis of COAD patients. A total of 66 lncRNAs associated with angiogenesis were screened, and three molecular subtypes (S1, S2, S3) were obtained. The prognosis of S1 and S2 was better than that of S3. Compared with the existing subtypes, the S3 subtype was significantly different from the other two subtypes. Immunoassay showed that immune cell scores of the S2 subtype were lower than those of the S1 and S3 subtypes, which also had the highest TIDE scores. We recruited 8 key lncRNAs to develop a RiskS-core model. The high RiskS-core group with inferior survival and higher TIDE scores was predicted to benefit limitedly from immunotherapy, but it may be more sensitive to chemotherapeutics. A nomogram designed by RiskS-core signature and other clinicopathological characteristics shed light on rational predictive power for COAD treatment. CONCLUSION: We constructed a RiskS-core model based on angiogenesis-related lncRNAs, which could serve as potential prognostic predictors for COAD patients and may offer clues for the intervention of anti-angiogenic application. Our results may help evaluate the prognosis of COAD and provide better treatment strategies.

Rapid and noninvasive cell assay by microfluidic-integrated intracavity evanescent field absorption in a fiber ring laser.

BACKGROUND: Highly sensitive and rapid detection of cell concentration and interfacial molecular events is of great value for biological, biomedical, and chemical research. Most traditional biosensors require large sample volumes and complicated functional modifications of the surface. It is of great significance to develop label-free biosensor platforms with minimal sample consumption for studying cell concentration changes and interfacial molecular events without labor-intensive procedures. RESULTS: Here, a fiber-optic biosensor based on intracavity evanescent field absorption sensing is designed for sensitive and label-free cell assays for the first time. The interaction between the cells and the evanescent field is enhanced by introducing microfluidic-integrated intracavity absorption in a fiber ring laser. This strategy extends the range of targeted analytes to include quantification of a large number of targets on a surface and improves the detection sensitivity of the fiber-optic biosensor. The level of sensing resolution could be improved from 10-4 RIU to 10-7 RIU using this strategy. The stem cells were studied over a wide concentration range (from 500 to 1.2 × 105 cells/ml) and were measured sequentially. By measuring the output power of the intracavity absorption sensing system, the cell concentration can be directly determined in a label-free manner. The results show that dozens of stem cells can be sensitively detected with a sample consumption of 72 µL. The response was fast (15 s) with a low temperature cross-sensitivity of 0.031 cells·ml-1/°C. SIGNIFICANCE: The proposed method suggests its capacity for true label-free and noninvasive cell assays with a low limit of detection and small sample consumption. This has the potential to be used as a universal tool for quantitative and qualitative characterization of various cells and other biochemical analytes.

Occurrence and phase distribution of lipophilic marine algal toxins in the bottom boundary layer and sediment-porewater system of two mariculture sites.

To date, understanding the fate of lipophilic marine algal toxins (LMATs) in benthic environments on which cultivated shellfish depend is still limited. In this work, the occurrence, concentration levels, and phase distributions of LMATs in the benthic environments of two mariculture sites (Sishili and Rongcheng Bays) in China were investigated for the first time. Five LMATs: okadaic acid (OA), pectenotoxin-2 (PTX2), gymnodimine, 13-desmethyl spirolide C, and azaspiracid-2 (AZA2) and three derivatives: dinophysistoxin-1 isomer (DTX1-iso), pectenotoxin-2 seco acid, and 7-epi- pectenotoxin-2 seco acid were detected in different environmental samples. OA and PTX2 were the dominant LMATs in the bottom boundary layer (BBL) and sediment, whereas AZA2 was present in the sediment only. Notably, DTX1-iso was found for the first time to be widely distributed in the benthic environments of the bays. In BBL, the average proportion of LMATs in the dissolved phase (99.20%) was much higher than in the particulate phase (0.80%). Partition of LMATs was more balanced between sediment porewater (57.80% average proportion) and sediment (42.20%). The concentrations of ∑LMATs in the BBL seawater ranged from 19.09 ng/L to 41.57 ng/L (mean of 32.67 ng/L), and the spatial distribution trend was higher in offshore than nearshore. ∑LMATs concentrations in the sediment and porewater of the two bays ranged from 17.04 ng/kg to 150.13 ng/kg (mean of 53.58 ng/kg) and from 8.29 ng/L to 120.58 ng/L (mean of 46.63 ng/L), respectively. Their spatial distributions differed from those in BBL, showing a trend of high concentrations in areas with heavy land-based inputs. ∑LMATs concentrations in porewater were significantly higher than those in BBL seawaters, suggesting that the potential hazards of LMATs to benthic organisms may be underestimated.

[Distribution, Sources, and Risk Assessment of Microplastics in Surface Sediments of Yellow River Delta Wetland].

Estuarine habitats are a critical zone of the Earth with strong land-sea interactions, that are strongly influenced by human activities. Microplastics (MPs) pollution in the Yellow River Delta (YRD) wetland, a typical young warm-temperate estuarine wetland, has not been comprehensively studied. The morphology, abundance, particle size, and polymer composition of MPs in the surface sediments of the YRD wetland were determined, and the pollution status and ecological risk in the study area were evaluated using the pollution load index (PLI) and potential pollution risk index (PRI). The results showed that the abundance of MPs in the YRD wetland was 20-520 n·kg-1, with a median value of 150 n·kg-1. The MPs were primarily fibers in shape and black in color, with particle size over 1 mm. The polymer components were primarily rayon, polyethylene, polyester, and polyethylene terephthalate. The PLI and PRI values of the MPs in the area were between 0.04-0.96 and 0.00-171.60, respectively, indicating that the pollution of MPs in the YRD wetland was at a slightly polluted level with low ecological risk.

Genome-wide identification and expression analyses of phenylalanine ammonia-lyase gene family members from tomato (Solanum lycopersicum) reveal their role in root-knot nematode infection.

Phenylalanine ammonia-lyase (PAL) is a key enzyme and rate-limiting enzyme of phenylpropanoid metabolism, which is a very important pathway in plants, and the secondary products it produces play an important role in plant growth and development, disease resistance, and stress resistance responses. However, PALs still lack systematic characterization in tomato. Based on a bioinformatics methods, PAL family genes were identified and characterized from tomato. qRT-PCR was used to study the expression of PAL genes in cultivated tomato after root-knot nematode infection. In this study, 14 and 11 PAL genes were identified in cultivated and wild tomatoes, and phylogenetic analysis classified them into three subfamilies, with different subfamilies of PAL proteins evolving in different directions in monocotyledonous and dicotyledonous plants. The extensive presence of stress, growth, hormone, and light response elements in the promoter sequences of SlPAL (Solanum lycopersicum) and SpenPAL (Solanum pennellii) genes suggests that this family has a critical role in abiotic stress. Collinearity indicates that members of the tomato and Arabidopsis PAL genes family are from the same ancestor, and the SlPAL10 gene is directly homologous to monocotyledonous rice and maize, suggesting that the SlPAL10 gene was present before monocotyledonous differentiation. Two co-expressed gene modules containing PAL genes were screened by WGCNA, and the core genes in the network were mined and functionally annotated by calculating the connectivity of genes within the modules. In addition, the expression of some genes changed significantly after root-knot nematode infection, with up-regulation of 4 genes and down-regulation of 3 genes. This result provides a data reference for the study of PAL family gene functions in tomato, and also provides a potential application for the subsequent selection of PAL genes in tomato for root-knot nematode resistance.

Improved YOLOv7 Network Model for Gangue Selection Robot for Gangue and Foreign Matter Detection in Coal.

Coal production often involves a substantial presence of gangue and foreign matter, which not only impacts the thermal properties of coal and but also leads to damage to transportation equipment. Selection robots for gangue removal have garnered attention in research. However, existing methods suffer from limitations, including slow selection speed and low recognition accuracy. To address these issues, this study proposes an improved method for detecting gangue and foreign matter in coal, utilizing a gangue selection robot with an enhanced YOLOv7 network model. The proposed approach entails the collection of coal, gangue, and foreign matter images using an industrial camera, which are then utilized to create an image dataset. The method involves reducing the number of convolution layers of the backbone, adding a small size detection layer to the head to enhance the small target detection, introducing a contextual transformer networks (COTN) module, employing a distance intersection over union (DIoU) loss border regression loss function to calculate the overlap between predicted and real frames, and incorporating a dual path attention mechanism. These enhancements culminate in the development of a novel YOLOv71 + COTN network model. Subsequently, the YOLOv71 + COTN network model was trained and evaluated using the prepared dataset. Experimental results demonstrated the superior performance of the proposed method compared to the original YOLOv7 network model. Specifically, the method exhibits a 3.97% increase in precision, a 4.4% increase in recall, and a 4.5% increase in mAP0.5. Additionally, the method reduced GPU memory consumption during runtime, enabling fast and accurate detection of gangue and foreign matter.

Structure, Property, and Performance of Catalyst Layers in Proton Exchange Membrane Fuel Cells.

Catalyst layer (CL) is the core component of proton exchange membrane (PEM) fuel cells, which determines the performance, durability, and cost. However, difficulties remain for a thorough understanding of the CLs' inhomogeneous structure, and its impact on the physicochemical and electrochemical properties, operating performance, and durability. The inhomogeneous structure of the CLs is formed during the manufacturing process, which is sensitive to the associated materials, composition, fabrication methods, procedures, and conditions. The state-of-the-art visualization and characterization techniques are crucial to examine the CL structure. The structure-dependent physicochemical and electrochemical properties are then thoroughly scrutinized in terms of fundamental concepts, theories, and recent progress in advanced experimental techniques. The relation between the CL structure and the associated effective properties is also examined based on experimental and theoretical findings. Recent studies indicated that the CL inhomogeneous structure also strongly affects the performance and degradation of the whole fuel cell, and thus, the interconnection between the fuel cell performance, failure modes, and CL structure is comprehensively reviewed. An analytical model is established to understand the effect of the CL structure on the effective properties, performance, and durability of the PEM fuel cells. Finally, the challenges and prospects of the CL structure-associated studies are highlighted for the development of high-performing PEM fuel cells.

Diagnostic value of combined pelvic floor ultrasound parameters for pelvic floor dysfunction and risk factors.

OBJECTIVE: To investigate the diagnostic value of pelvic floor ultrasound parameters in combination for pelvic floor dysfunction (PFD), and to explore the risk factors. METHODS: Forty PFD patients treated from April2019to December 2020(case group) and another 40 healthy women (control group) were enrolled. Their clinical data were collected, and both groups received three-dimensional (3D) ultrasound of the pelvic floor. The diagnostic value of pelvic floor ultrasound parameters for PFD was assessed by receiver operating characteristic (ROC) curves. The risk factors of PFD were evaluated by multivariate logistic regression analysis. RESULTS: The area under the ROC curve (AUC), sensitivity, and specificity of the parameters in combination for predicting PFD were 0.851 [95% confidence interval (CI): 0.743-0.959], 0.901, and 0.812, respectively, indicating acceptable accuracy. Results of logistic regression analysis revealed that spontaneous delivery, lateral episiotomy/laceration, and large bladder neck rotation angle, posterior urethrovesical angle (PUA), bladder neck tilt angle, bladder neck distance (BND), levator hiatus area (LHA) (at anal contraction), R-LHA and V-LHA were risk factors for PFD (p < 0.05), while physical exercise was a protective factor (p < 0.05). ROC curve analysis revealed that the AUC, sensitivity, and specificity of the forest map model were 0.822 (95% CI: 0.759-0.885), 0.942, and 0.601, respectively, indicating acceptable accuracy of the model. Internal data validation of the model demonstrated consistence of the predicted occurrence of PFD with the actual one. CONCLUSIONS: Spontaneous delivery, lateral episiotomy/laceration, and large bladder neck rotation angle, PUA, bladder neck tilt angle, BND, LHA (at anal contraction), R-LHA and V-LHA were risk factors for PFD.

CBX8 Promotes Cell Proliferation and Metastasis and Leads to Radiotherapy Tolerance of Glioma Cells.

AIM: To illustrate the role of CBX8 -a protein involved in protein metabolism and chromatin regulation/acetylation- in glioma cells, especially in DNA damage repair pathways. MATERIAL AND METHODS: Detect CBX8 expression in glioma cells and clinical samples by qPCR and Western blot. Overexpression and knockdown CBX8 cell lines were constructed by lentivirus infection. CCK8, wound healing, and transwell assays were used to verify the effects of CBX8 on proliferation, migration, and invasion of glioma cells. After radiation treatment, CCK8 and colony formation assays were used to detect cell sensitivity of CBX8 expression levels to radiotherapy. Western blot detected expression levels of p-ATM, p-ATR, BRCA-1, RAD51, and P53 in various cells after radiation treatment, demonstrating CBX8?s effect on DNA damage and repair proteins. Finally, the sensitivity of tumors with different CBX8 expression levels to radiotherapy was verified in vivo. RESULTS: CBX8 expression is significantly increased in glioma. High CBX8 expression promotes proliferation, invasion, and migration of glioma cells. It also causes glioma cells to resist radiotherapy. CBX8 affects protein expression related to DNA damage repair. In vivo, tumors with low CBX8 expression are more sensitive to radiotherapy. CONCLUSION: CBX8 promotes proliferation and metastasis of glioma cells and reduces cell sensitivity to radiotherapy by affecting DNA damage repair pathways.

Identification and Analysis of the Expression of the PIP5K Gene Family in Tomatoes.

To explore the function of phosphatidylinositol 4-phosphate 5-kinase (PIP5K) in tomatoes, members of the tomato PIP5K family were identified and characterized using bioinformatic methods, and their expression patterns were also analyzed under salt stress and in different tissues. Twenty-one PIP5K members-namely, SlPIP5K1-SlPIP5K21-were identified from ten chromosomes, and these were divided into three groups according to a phylogenetic analysis. Further bioinformatic analysis showed four pairs of collinear relationships and fragment replication events among the SlPIP5K family members. To understand the possible roles of the SlPIP5Ks, a cis-acting element analysis was conducted, which indicated that tomato PIP5Ks could be associated with plant growth, hormones, and stress responses. We further validated the results of the in silico analysis by integrating RNA-seq and qRT-PCR techniques for salt- and hormone-treated tomato plants. Our results showed that SlPIP5K genes exhibited tissue- and treatment-specific patterns, and some of the SlPIP5Ks exhibited significantly altered expressions after our treatments, suggesting that they might be involved in these stresses. We selected one of the SlPIP5Ks that responded to our treatments, SlPIP5K2, to further understand its subcellular localization. Our results showed that SlPIP5K2 was located on the membrane. This study lays a foundation for the analysis of the biological functions of the tomato SlPIP5K genes and can also provide a theoretical basis for the selection and breeding of new tomato varieties and germplasm innovation, especially under salt stress.

All-Dielectric Tunable Terahertz Metagrating for Diffraction Control.

Recently, tunable metagratings have attracted substantial attention in manipulating the diffraction of electromagnetic waves with considerable flexibility, but they are usually limited to inherent ohmic loss due to the metal layers. The all-dielectric schemes can address this issue, but its design and optimization remain challenging in the terahertz regime, especially in the 6G communication window. In this work, an all-dielectric tunable terahertz metagrating is demonstrated in theoretical and experimental investigations. The metagrating operating in the 6G communication window bends the electromagnetic waves beam into the T-1 diffraction order by optimizing the unit cell. In the experiments, more than 72.46% of the transmitted energy is concentrated in the desired diffraction order for p-polarized light and more than 66.60% for s-polarized light, which agrees well with the theoretical design. The tunability by angular deflection is reported in this all-dielectric metagrating. Then, based on the all-dielectric metagrating arrays, a metalens with numerical aperture of NA = 0.39 at 0.14 THz is demonstrated. The subwavelength scale focal spot is obtained as 2.0 mm × 2.0 mm with the focusing distance of 117.8 mm. Imaging capability of the metalens is performed utilizing the transmission imaging manner. The measured and anticipated results are satisfactorily congruous with one another, which could validate our design. This work paves the way toward designing highly efficient and tunable devices with potential applications in terahertz communications, sensors, and super-resolution imaging.