Monitoring the leaf damage by the rice leafroller with deep learning and ultra-light UAV.

BACKGROUND: Rice leafroller is a serious threat to the production of rice. Monitoring the damage caused by rice leafroller is essential for effective pest management. Owing to limitations in collecting decent quality images and high-performing identification methods to recognize the damage, studies recommending fast and accurate identification of rice leafroller damage are rare. In this study, we employed an ultra-lightweight unmanned aerial vehicle (UAV) to eliminate the influence of the downwash flow field and obtain very high-resolution images of the damaged areas of the rice leafroller. We used deep learning technology and the segmentation model, Attention U-Net, to recognize the damaged area by the rice leafroller. Further, a method is presented to count the damaged patches from the segmented area. RESULTS: The result shows that Attention U-Net achieves high performance, with an F1 score of 0.908. Further analysis indicates that the deep learning model performs better than the traditional image classification method, Random Forest (RF). The traditional method of RF causes a lot of false alarms around the edge of leaves, and is sensitive to the changes in brightness. Validation based on the ground survey indicates that the UAV and deep learning-based method achieve a reasonable accuracy in identifying damage patches, with a coefficient of determination of 0.879. The spatial distribution of the damage is uneven, and the UAV-based image collecting method provides a dense and accurate method to recognize the damaged area. CONCLUSION: Overall, this study presents a vision to monitor the damage caused by the rice leafroller with ultra-light UAV efficiently. It would also contribute to effectively controlling and managing the hazardous rice leafroller. © 2024 Society of Chemical Industry.

Integrated genomics provides insights into the evolution of the polyphosphate accumulation trait of Ca. Accumulibacter.

Candidatus Accumulibacter, a prominent polyphosphate-accumulating organism (PAO) in wastewater treatment, plays a crucial role in enhanced biological phosphorus removal (EBPR). The genetic underpinnings of its polyphosphate accumulation capabilities, however, remain largely unknown. Here, we conducted a comprehensive genomic analysis of Ca. Accumulibacter-PAOs and their relatives within the Rhodocyclaceae family, identifying 124 core genes acquired via horizontal gene transfer (HGT) at its least common ancestor. Metatranscriptomic analysis of an enrichment culture of Ca. Accumulibacter revealed active transcription of 44 of these genes during an EBPR cycle, notably including the polyphosphate kinase 2 (PPK2) gene instead of the commonly recognized polyphosphate kinase 1 (PPK1) gene. Intriguingly, the phosphate regulon (Pho) genes showed minimal transcriptions, pointing to a distinctive fact of Pho dysregulation, where PhoU, the phosphate signaling complex protein, was not regulating the high-affinity phosphate transport (Pst) system, resulting in continuous phosphate uptake. To prevent phosphate toxicity, Ca. Accumulibacter utilized the laterally acquired PPK2 to condense phosphate into polyphosphate, resulting in the polyphosphate-accumulating feature. This study provides novel insights into the evolutionary emergence of the polyphosphate-accumulating trait in Ca. Accumulibacter, offering potential advancements in understanding the PAO phenotype in the EBPR process.

Associations between sleep-related disorders and cardiovascular disease risk in hypertensive patients: Insights from the National Health and Nutrition Examination Survey (NHANES): A cross-sectional study.

Both sleep-related disorders (SRD) and hypertension (HTN) are closely related to the occurrence of cardiovascular disease (CVD); however, few studies have explored their combined effect. Based on the National Health and Nutrition Examination Survey (NHANES) database, we comprehensively analyzed the combined effect of SRD and HTN on the occurrence of CVD. The weighted multivariate logistic regression analysis was adopted to explore how SRD and HTN can affect the occurrence of CVD. Specifically, the additive interaction was evaluated by the relative excess risk due to interaction (RERI), attributable proportion (AP), and the synergy index (SI), and the multiplicative interaction was evaluated by the odds ratio (OR) along with 95% confidence interval (CI) from the product term. All the 33,383 participants from the NHANES database were divided into 2 groups, i.e., the CVD (n = 3712) and non-CVD (n = 29,671) groups. The results indicated that SRD (Model 3: OR = 1.90, 95% CI: 1.60-2.25) and HTN (Model 3: OR = 2.28, 95% CI: 1.87-2.79) were both significantly associated with an increased risk of CVD. Additionally, we observed a significant additive interaction (RERI = 0.88, 95% CI: 0.03-0.65; AP = 0.22, 95% CI: 0.01-0.21; SI = 1.15, 95% CI: 1.07-1.33) and a significant multiplicative interaction (OR = 1.07, 95% CI: 1.03-1.10) between SRD and HTN on the occurrence of CVD. While both SRD and HTN are associated with CVD occurrence, their interaction can also contribute to the development of CVD.

Spatial regulation of NMN supplementation on brain lipid metabolism upon subacute and sub-chronic PM exposure in C57BL/6 mice.

BACKGROUND: Atmospheric particulate matter (PM) exposure-induced neuroinflammation is critical in mediating nervous system impairment. However, effective intervention is yet to be developed. RESULTS: In this study, we examine the effect of ß-nicotinamide mononucleotide (NMN) supplementation on nervous system damage upon PM exposure and the mechanism of spatial regulation of lipid metabolism. 120 C57BL/6 male mice were exposed to real ambient PM for 11 days (subacute) or 16 weeks (sub-chronic). NMN supplementation boosted the level of nicotinamide adenine dinucleotide (NAD+) in the mouse brain by 2.04 times. This augmentation effectively reduced neuroinflammation, as evidenced by a marked decrease in activated microglia levels across various brain regions, ranging from 29.29 to 85.96%. Whole brain lipidomics analysis revealed that NMN intervention resulted in an less increased levels of ceramide (Cer) and lysophospholipid in the brain following subacute PM exposure, and reversed triglyceride (TG) and glycerophospholipids (GP) following sub-chronic PM exposure, which conferred mice with anti-neuroinflammation response, improved immune function, and enhanced membrane stability. In addition, we demonstrated that the hippocampus and hypothalamus might be the most sensitive brain regions in response to PM exposure and NMN supplementation. Particularly, the alteration of TG (60:10, 56:2, 60:7), diacylglycerol (DG, 42:6), and lysophosphatidylcholine (LPC, 18:3) are the most profound, which correlated with the changes in functional annotation and perturbation of pathways including oxidative stress, inflammation, and membrane instability unveiled by spatial transcriptomic analysis. CONCLUSIONS: This study demonstrates that NMN intervention effectively reduces neuroinflammation in the hippocampus and hypothalamus after PM exposure by modulating spatial lipid metabolism. Strategies targeting the improvement of lipid homeostasis may provide significant protection against brain injury associated with air pollutant exposure.

Nondestructive detection of saline-alkali stress in wheat (Triticum aestivum L.) seedlings via fusion technology.

BACKGROUND: Wheat (Triticum aestivum L.) is an important grain crops in the world, and its growth and development in different stages is seriously affected by saline-alkali stress, especially in seedling stage. Therefore, nondestructive detection of wheat seedlings under saline-alkali stress can provide more comprehensive technical support for wheat breeding, cultivation and management. RESULTS: This research focused on moisture signal prediction and classification of saline-alkali stress in wheat seedlings using fusion techniques. After collecting and analyzing transverse relaxation time and Multispectral imaging (MSI) information of wheat seedlings, four regression models were used to predict the moisture signal. K-Nearest Neighbor (KNN) and Gaussian-Naïve Bayes (GNB) models were combined with fivefold cross validation to classify the prediction of wheat seedling stress. The results showed that wheat seedlings would increase the bound water content through a certain mechanism to enhance their saline-alkali stress. Under the same Na concentration, the effect of alkali stress on moisture, growth and spectrum of wheat seedlings is stronger than salt stress. The Gradient Boosting Decision Regression Tree model performs the best in predicting wheat moisture signals, with a coefficient of determination (R2P) of 0.98 and a root mean square error of 109.60. It also had a short training time (1.48 s) and an efficient prediction speed (1300 obs/s). The KNN and GNB demonstrated significantly enhanced predictive performance when classifying the fused dataset, compared to using single datasets individually. In particular, the GNB model performing best on the fused dataset, with Precision, Recall, Accuracy, and F1-score of 90.30, 88.89%, 88.90%, and 0.90, respectively. CONCLUSIONS: Under the same Na concentration, the effects of alkali stress on water content, spectrum, and growth of wheat were stronger than that of salt stress, which was more unfavorable to the growth of wheat. The fusion of low-field nuclear magnetic resonance and MSI technology can improve the classification of wheat stress, and provide an effective technical method for rapid and accurate monitoring of wheat seedlings under saline-alkali stress.

A patent review of SCF E3 ligases inhibitors for cancer：Structural design, pharmacological activities and structure-activity relationship.

Currently, as the largest family of E3 ubiquitin ligases, Skp1-Cullin 1-F-box (SCF) E3 ligase complexes have attracted extensive attention. Among SCF complexes, Skp2, ß-TrCP, and FBXW7 have undergone extensive research on their structures and functions. Previous studies suggest Skp2, ß-TrCP, and FBXW7 are overexpressed in numerous cancers. Thus, the SCF E3 ligase complex has become a significant target for the development of anti-cancer drugs. Over the past few decades, a variety of anti-tumor inhibitors targeting the SCF E3 ligase complex have been attempted. However, since almost none of the SCF E3 ligase inhibitors passed clinical trials, the design and synthesis of the new inhibitors are needed. Here, we will introduce the structure and function of Skp2, ß-TrCP, and FBXW7, their connections with cancer development, the relevant in vitro and in vivo activities, selectivity, structure-activity relationships, and the therapeutic or preventive application of small molecule inhibitors targeting these three F-box proteins reported in the patent (2010-present). This information will help develop drugs targeting the SCF E3 ubiquitin ligase, providing new strategies for future cancer treatments.

Improving UASS pesticide application: optimizing and validating drift and deposition simulations.

BACKGROUND: As unmanned aerial spraying systems (UASS) usage grows rapidly worldwide, a critical research study was conducted to optimize the simulation of UASS applications, aiming to enhance pesticide delivery efficiency and reduce environmental impact. The study examined several key aspects for accurate simulation of UASS application with lattice Boltzmann method (LBM). Based on these discussions, the most suitable grid size and simulation parameters were selected to create a robust model for optimizing UASS performance in various pest management scenarios, potentially leading to more targeted and sustainable pest control practices. RESULTS: The effect of stability parameter, grid size around the rotor and near ground, and parameters at wake flow were carefully analyzed to improve the precision of pesticide drift predictions and deposition patterns. Optimal grid sizes were identified as 0.2 m generally, 0.025 m near rotors, and a 0.1 + 0.2 m scheme for ground proximity, with finer grids improving accuracy but increasing computation time. Wake resolution and threshold significantly influenced simulation results, while wake distance had minimal impact beyond a certain point. The LBM's accuracy was validated by comparing simulated downwash flow and droplet deposition with field test data. CONCLUSION: This study optimized UASS simulation parameters, balancing computational efficiency with accuracy. The validated model enhances our ability to design more effective UASS for pest management, potentially leading to more precise and targeted pesticide applications. These advancements contribute to the development of sustainable pest control strategies, aiming to reduce pesticide usage and environmental impact while maintaining crop protection efficacy. © 2024 Society of Chemical Industry.

Nursing students' work readiness and its influencing factors before participating in a nurse residency program: a multicenter cross-sectional study.

Background: Studies have shown that work readiness is closely related to nurses' role adaptation, career development, and patient safety. However, we know little about the nursing students' work readiness and its influencing factors before participating in a nurse residency program, and whether factors have changed from before. Aim: (1) To investigate the work readiness of nursing students ready to engage in a nurse residency program; (2) to identify the factors affecting the nursing students' work readiness and the associations between emotional intelligence and work readiness; and (3) to discuss the changes of factors affecting nursing students' work readiness. Design: An online, multicenter cross-sectional study. Methods: 878 nursing students from eight tertiary hospitals in Chongqing, China were recruited. The online investigation used the General Information Questionnaire, the Nursing Students' Work Readiness Scale, and the Emotional Intelligence scale. The data were analyzed using IBM SPSS V23.0. Results: 768 valid questionnaires were included in this study. The nurses obtained a work readiness score of 277.08 ± 44.39 and an emotional intelligence score of 89.57 ± 13.89. Univariate analysis revealed that the following factors affected work readiness: age, sex, family support for becoming a nurse, voluntary choice of nursing major, previous experience as a student cadre, scholarship recipient status, willingness to engage in nursing work during the COVID-19 pandemic and confidence in clinical nursing practice. Frequent incidents of violence, poor salary for nurses for the nurse residency program, and low social acceptance were the top three reasons for decreased confidence in clinical nursing among nursing students. Furthermore, multiple linear regression analysis indicated that age, voluntary choice of nursing major, student leadership experience, confidence in clinical nursing work, self-emotion, and emotional application significantly influenced nurses' work readiness. Conclusion: Clinical instructors and administrators should dynamically assess nurses' work readiness, prioritize individuals aged ≤23, who have chosen the nursing profession involuntarily, lack prior experience as student cadres, and exhibit low confidence in clinical nursing work. This focus will enhance their emotional self-management skills and ability to apply emotions effectively, improving their work readiness and training efficacy.

The relationship between intracranial atherosclerosis and white matter hyperintensity in ischemic stroke patients: a retrospective cross-sectional study using high-resolution magnetic resonance vessel wall imaging.

Background: Both intracranial atherosclerosis and white matter hyperintensity (WMH) are prevalent among the stroke population. However, the relationship between intracranial atherosclerosis and WMH has not been fully elucidated. Therefore, the aim of this study was to investigate the relationship between the characteristics of intracranial atherosclerotic plaques and the severity of WMH in patients with ischemic stroke using high-resolution magnetic resonance vessel wall imaging. Methods: Patients hospitalized with ischemic stroke and concurrent intracranial atherosclerosis at Beijing Tsinghua Changgung Hospital, a tertiary comprehensive stroke center, who underwent high-resolution magnetic resonance vessel wall imaging and conventional brain magnetic resonance imaging were continuously recruited from January 2018 to December 2018. Both intracranial plaque characteristics (plaque number, maximum wall thickness, luminal stenosis, T1 hyperintensity, and plaque length) and WMH severity (Fazekas score and volume) were evaluated. Spearman correlation or point-biserial correlation analysis was used to determine the association between clinical characteristics and WMH volume. The independent association between intracranial plaque characteristics and the severity as well as WMH score was analyzed using logistic regression. The associations of intracranial plaque characteristics with total white matter hyperintensity (TWMH) volume, periventricular white matter hyperintensity (PWMH) volume and deep white matter hyperintensity (DWMH) volume were determined using multilevel mixed-effects linear regression. Results: A total of 159 subjects (mean age: 64.0±12.5 years; 103 males) were included into analysis. Spearman correlation analysis indicated that age was associated with TWMH volume (r=0.529, P<0.001), PWMH volume (r=0.523, P<0.001) and DWMH volume (r=0.515, P<0.001). Point-biserial correlation analysis indicated that smoking (r=-0.183, P=0.021) and hypertension (r=0.159, P=0.045) were associated with DWMH volume. After adjusting for confounding factors, logistic regression analysis showed plaque number was significantly associated with the presence of severe WMH [odds ratio (OR), 1.590; 95% CI, 1.241-2.035, P<0.001], PWMH score of 3 (OR, 1.726; 95% CI, 1.074-2.775, P=0.024), and DWMH score of 2 (OR, 1.561; 95% CI, 1.150-2.118, P=0.004). Intracranial artery luminal stenosis was associated with presence of severe WMH (OR, 1.032; 95% CI, 1.002-1.064, P=0.039) and PWMH score of 2 (OR, 1.057; 95% CI, 1.008-1.109, P=0.023). Multilevel mixed-effects linear regression analysis showed that plaque number was associated with DWMH volume (ß=0.128; 95% CI, 0.016-0.240; P=0.026) after adjusted for age and sex. Conclusions: In ischemic stroke patients, intracranial atherosclerotic plaque characteristics as measured by plaque number and luminal stenosis were associated with WMH burden.

Botulinum toxin type A-targeted SPP1 contributes to neuropathic pain by the activation of microglia pyroptosis.

BACKGROUND: Neuropathic pain (NP) is the primary symptom of various neurological conditions. Patients with NP often experience mood disorders, particularly depression and anxiety, that can severely affect their normal lives. Microglial cells are associated with NP. Excessive inflammatory responses, especially the secretion of large amounts of pro-inflammatory cytokines, ultimately lead to neuroinflammation. Microglial pyroptosis is a newly discovered form of inflammatory cell death associated with immune responses and inflammation-related diseases of the central nervous system. AIM: To investigate the effects of botulinum toxin type A (BTX-A) on microglial pyroptosis in terms of NP and associated mechanisms. METHODS: Two models, an in vitro lipopolysaccharide (LPS)-stimulated microglial cell model and a selective nerve injury model using BTX-A and SPP1 knockdown treatments, were used. Key proteins in the pyroptosis signaling pathway, NLRP3-GSDMD, were assessed using western blotting, real-time quantitative polymerase chain reaction, and immunofluorescence. Inflammatory factors [interleukin (IL)-6, IL-1ß, and tumor necrosis factor (TNF)-α] were assessed using enzyme-linked immunosorbent assay. We also evaluated microglial cell proliferation and apoptosis. Furthermore, we measured pain sensation by assessing the delayed hind paw withdrawal latency using thermal stimulation. RESULTS: The expression levels of ACS and GSDMD-N and the mRNA expression of TNF-α, IL-6, and IL-1ß were enhanced in LPS-treated microglia. Furthermore, SPP1 expression was also induced in LPS-treated microglia. Notably, BTX-A inhibited SPP1 mRNA and protein expression in the LPS-treated microglia. Additionally, depletion of SPP1 or BTX-A inhibited cell viability and induced apoptosis in LPS-treated microglia, whereas co-treatment with BTX-A enhanced the effect of SPP1 short hairpin (sh)RNA in LPS-treated microglia. Finally, SPP1 depletion or BTX-A treatment reduced the levels of GSDMD-N, NLPRP3, and ASC and suppressed the production of inflammatory factors. CONCLUSION: Notably, BTX-A therapy and SPP1 shRNA enhance microglial proliferation and apoptosis and inhibit microglial death. It improves pain perception and inhibits microglial activation in rats with selective nerve pain.

Spliceosomal GTPase Eftud2 deficiency-triggered ferroptosis leads to Purkinje cell degeneration.

Spliceosomal GTPase elongation factor Tu GTP binding domain containing 2 (EFTUD2) is a causative gene for mandibulofacial dysostosis with microcephaly (MFDM) syndrome comprising cerebellar hypoplasia and motor dysfunction. How EFTUD2 deficiency contributes to these symptoms remains elusive. Here, we demonstrate that specific ablation of Eftud2 in cerebellar Purkinje cells (PCs) in mice results in severe ferroptosis, PC degeneration, dyskinesia, and cerebellar atrophy, which recapitulates phenotypes observed in patients with MFDM. Mechanistically, Eftud2 promotes Scd1 and Gch1 expression, upregulates monounsaturated fatty acid phospholipids, and enhances antioxidant activity, thereby suppressing PC ferroptosis. Importantly, we identified transcription factor Atf4 as a downstream target to regulate anti-ferroptosis effects in PCs in a p53-independent manner. Inhibiting ferroptosis efficiently rescued cerebellar deficits in Eftud2 cKO mice. Our data reveal an important role of Eftud2 in maintaining PC survival, showing that pharmacologically or genetically inhibiting ferroptosis may be a promising therapeutic strategy for EFTUD2 deficiency-induced disorders.

Identification of sanguinarine as a novel antagonist for perfluorooctanoate/perfluorooctane sulfonate-induced senescence of hepatocytes: An integrated computational and experimental analysis.

Perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS), two prominent per- and polyfluoroalkyl substances (PFASs), are potentially harmful to many human organs. However, there only exist limited methods to mitigate their health hazards. The aim of this study is to combine a bioinformatics analysis with in vitro experiments to discover small molecules that can alleviate liver damage caused by PFOA/PFOS. We identified 192 and 82 key genes related to hepatocytes exposed to PFOA and PFOS, respectively. The functional enrichment analysis of key genes suggested cellular senescence may be important in PFOA/PFOS-induced hepatotoxicity. The in vitro models revealed that PFOA/PFOS led to hepatocyte senescence by increasing the activity of SA-ß-gal, inducing mitochondrial dysfunction, impacting cell cycle arrest, and elevating the expressions of p21, p53, IL-1ß, and SASP-related cytokines. The drug-target gene set enrichment analysis method was employed to compare the transcriptome data from the Gene Expression Omnibus database (GEO), Comparative Toxicogenomics Database (CTD), and the high-throughput experiment- and reference-guided database (HERB), and 21 traditional Chinese medicines (TCMs) were identified that may alleviate PFOA/PFOS-induced liver aging. The experimental results of co-exposure to PFOA/PFOS and TCMs showed that sanguinarine has particular promise in alleviating cellular senescence caused by PFOA/PFOS. Further investigations revealed that the mTOR-p53 signaling pathway was involved in PFOA/PFOS-mediated hepatic senescence and can be blocked using sanguinarine.

Suppressing Surface Oxidation of Pyrite FeS2 by Cobalt Doping in Lithium Sulfur Batteries.

Lithium-sulfur batteries have emerged as a promising energy storage device due to ultra-high theoretical capacity, but the slow kinetics of sulfur and polysulfide shuttle hinder the batteries' further development. Here, the 10% cobalt-doped pyrite iron disulfide electrocatalyst deposited on acetylene black as a separator coating in lithium-sulfur batteries is reported. The adsorption rate to the intermediate Li2S6 is significantly improved while surface oxidation of FeS2 is inhibited: iron oxide and sulfate, thus avoiding FeS2 electrocatalyst deactivation. The electrocatalytic activity has been evaluated in terms of electronic resistivity, lithium-ion diffusion, liquid-liquid, and liquid-solid conversion kinetics. The coin batteries exhibit ultra-long cycle life at 1 C with an initial capacity of 854.7 mAh g-1 and maintained at 440.8 mAh g-1 after 920 cycles. Furthermore, the separator is applied to a laminated pouch battery with a sulfur mass of 326 mg (3.7 mg cm-2) and retained the capacity of 590 mAh g-1 at 0.1 C after 50 cycles. This work demonstrates that FeS2 electrocatalytic activity can be improved when Co-doped FeS2 suppresses surface oxidation and provides a reference for low-cost separator coating design in pouch batteries.

Astragali radix (Huangqi): a time-honored nourishing herbal medicine.

Astragali radix (AR, namded Huangqi in Chinese) is the dried root of Astragalus membranaceus (Fisch.) Bge. var. mongholicus (Bge.) Hsiao or Astragalus membranaceus (Fisch.) Bge. As a widely used ethnomedicine, the biological activities of AR include immunomodulatory, anti-hyperglycemic, anti-oxidant, anti-aging, anti-inflammatory, anti-viral, anti-tumor, cardioprotective, and anti-diabetic effects, with minimum side effects. Currently, it is known that polysaccharides, saponins, and flavonoids are the indispensable components of AR. In this review, we will elaborate the research advancements of AR on ethnobotany, ethnopharmacological practices, phytochemicals, pharmacological activities, clinical uses, quality control, production developments, and toxicology. The information is expected to assist clinicians and scientists in developing useful therapeutic medicines with minimal systemic side effects.

Manipulating Orbital Hybridization of CoSe2 by S Doping for the Highly Active Catalytic Effect of Lithium-Sulfur Batteries.

In recent years, various transition metal compounds have been extensively studied to deal with the problems of slow reaction kinetics and the shuttle effect of lithium-sulfur (Li-S) batteries. Nevertheless, their catalytic performance still needs to be further improved by enhancing intrinsic catalytic activity and enriching active sites. Doping is an effective means to boost the catalytic performance through adjusting the electron structure of the catalysts. Herein, the electron structure of CoSe2 is adjusted by doping P, S with different p electron numbers and electronegativity. After S doping (S-CoSe2), the content of Co2+ increases, and charge is redistributed. Furthermore, more electrons are transferred between Li2S4/Li2S and S-CoSe2, and optimal Co-S bonds are formed between them with optimized d-p orbital hybridization, making the bonds of Li2S4/Li2S the longest and easy to break and decompose. Consequently, the Li-S batteries with the S-CoSe2-modified separator achieve improved rate performance and cycling performance, benefiting from the better bidirectional catalytic activity. This work will provide reference for the selection of the anion doping element to enhance the catalytic effect of transition metal compounds.

Urolithin A attenuates hexavalent chromium-induced small intestinal injury by modulating PP2A/Hippo/YAP1 pathway.

Hexavalent chromium (Cr(VI)) exposure has been linked with gastrointestinal toxicity, whereas the molecular pathways and key targets remain elusive. Computational toxicology analysis predicted the correlation between protein phosphatase 2A (PP2A) and genes regarding Cr(VI)-induced intestinal injury. Here, we generated a mouse model with intestinal epithelium-specific knock out of Ppp2r1a (encoding PP2A Aα subunit) to investigate the mechanisms underlying Cr(VI)-induced small intestinal toxicity. Heterozygous (HE) mice and matched WT littermates were administrated with Cr(VI) at 0, 5, 20, and 80 mg/l for 28 successive days. Cr(VI) treatment led to crypt hyperplasia, epithelial cell apoptosis, and intestinal barrier dysfunction, accompanied by the decline of goblet cell counts and Occludin expression in WT mice. Notably, these effects were aggravated in HE mice, indicating that PP2A Aα deficiency conferred mice with susceptibility to Cr(VI)-induced intestinal injury. The combination of data analysis and biological experiments revealed Cr(VI) exposure could decrease YAP1 phosphorylation at Ser127 but increase protein expression and activity, together with elevated transcriptional coactivator with PDZ-binding motif protein driving epithelial crypt cells proliferation following damage, suggesting the involvement of Hippo/YAP1 signaling pathway in Cr(VI)-induced intestinal toxicity. Nevertheless, the enhanced phosphorylation of YAP1 in HE mice resulted in proliferation/repair defects in intestinal epithelium, thereby exacerbating Cr(VI)-induced gut barrier dysfunction. Notably, by molecular docking and further studies, we identified urolithin A, a microbial metabolite, attenuated Cr(VI)-induced disruption of intestinal barrier function, partly by modulating YAP1 expression and activity. Our findings reveal the novel molecular pathways participated in Cr(VI)-caused small intestinal injury and urolithin A could potentially protect against environmental hazards-induced intestinal diseases.

Unmasking the silent killer: The hidden aggressiveness of signet-ring cell carcinoma in gallbladder cancer.

The prognostic significance of the signet-ring cell component in gallbladder carcinoma (GBC) has not been systematically evaluated. The aim of this study was to assess the similarities and differences between gallbladder signet-ring cell carcinoma (GBSRCA) and gallbladder adenocarcinoma (GBAC) in terms of clinicopathological features and long-term survival. Using the Surveillance, Epidemiology, and End Results (SEER) database, we analyzed 6,612 patients diagnosed with gallbladder cancer between 2000 and 2021. The cohort included 147 patients with GBSRCA and 6,465 with GBAC. Patients with GBSRCA were significantly younger, with 33.3% being age 60 or younger compared to 23.9% of patients with GBAC (p = 0.009). There was a higher proportion of females in the GBSRCA group (77.6%) compared to the GBAC group (70.1%, p = 0.049). GBSRCA was associated with a more advanced tumor stage (T3-T4: 56.5% vs. 44.4%, P = 0.004), higher rates of lymph node metastasis (43.5% vs. 28.0%, P < 0.001), and poorer differentiation status (poorly to undifferentiated: 80.3% vs. 29.7%, P < 0.001). Survival analysis revealed that patients with GBSRCA had significantly worse overall survival (OS) and cancer-specific survival (CSS) compared to patients with GBAC (p < 0.001). GBSRCA was an independent prognostic factor for OS (P = 0.001) in the entire cohort, while the T stage and N stage were independent prognostic factors for OS and CSS in patients with GBSRCA. Even after propensity score matching, patients with GBSRCA still had a poorer prognosis.

Prediction of Femtosecond Laser Etching Parameters Based on a Backpropagation Neural Network with Grey Wolf Optimization Algorithm.

Investigating the optimal laser processing parameters for industrial purposes can be time-consuming. Moreover, an exact analytic model for this purpose has not yet been developed due to the complex mechanisms of laser processing. The main goal of this study was the development of a backpropagation neural network (BPNN) with a grey wolf optimization (GWO) algorithm for the quick and accurate prediction of multi-input laser etching parameters (energy, scanning velocity, and number of exposures) and multioutput surface characteristics (depth and width), as well as to assist engineers by reducing the time and energy require for the optimization process. The Keras application programming interface (API) Python library was used to develop a GWO-BPNN model for predictions of laser etching parameters. The experimental data were obtained by adopting a 30 W laser source. The GWO-BPNN model was trained and validated on experimental data including the laser processing parameters and the etching characterization results. The R2 score, mean absolute error (MAE), and mean squared error (MSE) were examined to evaluate the prediction precision of the model. The results showed that the GWO-BPNN model exhibited excellent accuracy in predicting all properties, with an R2 value higher than 0.90.

Triphase Enzyme Electrode Based on ZIF-8 with Enhanced Oxidase Catalytic Kinetics and Bioassay Performance.

Oxidase enzyme-based electrochemical bioassays have garnered considerable interest due to their specificity and high efficiency. However, in traditional solid-liquid diphase enzyme electrode systems, the low solubility of oxygen and its slow mass transfer rate limit the oxidase catalytic reaction kinetics, thereby affecting the bioassay performance, including the detection accuracy, sensitivity, and linear dynamic range. ZIF-8 nanoparticles (NPs) possess hydrophobic and high-porosity characteristics, enabling them to serve as oxygen nanocarriers. In this work, we constructed a solid-liquid-air triphase enzyme electrode by encapsulating ZIF-8 NPs within an oxidase network. Hydrophobic ZIF-8 NPs can provide a rapid and sufficient supply of oxygen for the oxidase-catalyzed reactions, which enhances and stabilizes the kinetics of oxidase-catalyzed reactions. This approach eliminates the issue of "oxygen deficiency" at the traditional solid-liquid diphase interface. Consequently, the triphase enzyme electrode exhibits a 12-fold higher linear detection range than the diphase system and possesses good detection accuracy in electrolytes even with fluctuating oxygen levels. This work proposes a novel approach to construct triphase reaction systems for addressing the gas deficiency problem in heterogeneous catalysis.