Impact of co-substrate molecular weight on methane production potential, microbial community dynamics, and metabolic pathways in waste activated sludge anaerobic co-digestion.

Proteins and carbohydrates are important organics in waste activated sludge, and greatly affect methane production and microbial community composition in anaerobic digestion systems. Here, a series of co-substrates with different molecular weight were applied to investigate the interactions between microbial dynamics and the molecular weight of co-substrates. Biochemical methane production assays conducted in batch co-digesters showed that feeding high molecular weight protein and carbohydrate substrates resulted in higher methane yield and production rates. Moreover, high-molecular weight co-substrates increased the microbial diversity, enriched specific microbes including Longilinea, Anaerolineaceae, Syner-01, Methanothrix, promoted acidogenic and acetoclastic methanogenic pathways. Low-molecular weight co-substrates favored the growth of JGI-0000079-D21, Armatimonadota, Methanosarcina, Methanolinea, and improved hydrogenotrophic methanogenic pathway. Besides, Methanoregulaceae and Methanolinea were indicators of methane yield. This study firstly revealed the complex interactions between co-substrate molecular weight and microbial communities, and demonstrated the feasibility of adjusting co-substrate molecular weight to improve methane production process.

Potassium Decahydrido-closo-Decaborane Urea Complex as a Potential Solid-State Electrolyte for Potassium Metal Batteries.

All-solid-state potassium metal batteries have been considered promising candidates for large-scale energy storage because of abundance and wide availability of K resources, elimination of flammable liquid organic electrolytes, and incorporation of high-capacity K metal anode. However, unideal K-ion conductivities of most reported K-ion solid electrolytes have restricted the development of these batteries. Herein, a novel K2B10H10·CO(NH2)2 complex is reported, forming by incorporating urea into K2B10H10, to achieve an enhanced K-ion conductivity. The crystal structure of K2B10H10·CO(NH2)2 was determined as a monoclinic lattice with the space group of C2/c (No. 15). K2B10H10·CO(NH2)2 delivers an ionic conductivity of 2.7 × 10-8 S cm-1 at 25 °C, and reaching 1.3 × 10-4 S cm-1 at 80 °C, which is about 4 orders of magnitude higher than that of K2B10H10. One possible reason is the anion expansion in size due to the presence of dihydrogen bonds in K2B10H10·CO(NH2)2, resulting in an increase in the K-H bond distance and the electrostatic potential, thereby enhancing the mobility of K+. The K-ion conductivity is also higher than those of most hydridoborate-based K-ion conductors reported. Besides, K2B10H10·CO(NH2)2 reveals a wide electrochemical stability window and remarkable interface compatibility with K metal electrodes, suggesting a promising electrolyte for all-solid-state K metal batteries.

TRPV1+ sensory nerves suppress conjunctival inflammation via SST-SSTR5 signaling in murine allergic conjunctivitis.

Allergic conjunctivitis (AC), an allergen-induced ocular inflammatory disease, primarily involves mast cells (MCs) and eosinophils. The role of neuroimmune mechanisms in AC, however, remains to be elucidated. We investigated the effects of transient receptor potential vanilloid 1 (TRPV1)-positive sensory nerve ablation (using resiniferatoxin) and TRPV1 blockade (using Acetamide, N-[4-[[6-[4-(trifluoromethyl)phenyl]-4-pyrimidinyl]oxy]-2-benzothiazolyl] (AMG-517)) on ovalbumin-induced conjunctival allergic inflammation in mice. The results showed an exacerbation of allergic inflammation as evidenced by increased inflammatory gene expression, MC degranulation, tumor necrosis factor-α production by MCs, eosinophil infiltration and activation, and C-C motif chemokine 11 (CCL11) (eotaxin-1) expression in fibroblasts. Subsequent findings demonstrated that TRPV1+ sensory nerves secrete somatostatin (SST), which binds to SST receptor 5 (SSTR5) on MCs and conjunctival fibroblasts. SST effectively inhibited tumor necrosis factor-α production in MCs and CCL11 expression in fibroblasts, thereby reducing eosinophil infiltration and alleviating AC symptoms, including eyelid swelling, lacrimation, conjunctival chemosis, and redness. These findings suggest that targeting TRPV1+ sensory nerve-mediated SST-SSTR5 signaling could be a promising therapeutic strategy for AC, offering insights into neuroimmune mechanisms and potential targeted treatments.

A High-Rate and Long-Life Sodium Metal Battery Based on a NaB3H8 ⋠xNH3@NaB3H8 Composite Solid-State Electrolyte.

All-solid-state sodium metal batteries are promising for large-scale energy storage applications owing to their intrinsic safety and cost-effectiveness. However, they generally suffer from sodium dendrite growth or rapid capacity fading, especially at high rates, mainly due to poor wettability, sluggish ionic transport, or low interfacial stability of the solid electrolytes. Herein, we report a novel composite, NaB3H8 ⋅ xNH3@NaB3H8 (x<1), as a new class of solid electrolyte for high-rate batteries. NaB3H8 ⋅ xNH3@NaB3H8 is obtained from the sticky NaB3H8 ⋅ NH3 after removal of NH3 partially at room temperature. It delivers an ionic conductivity of 0.84 mS cm-1 at 25 °C and reaches 20.64 mS cm-1 at 45 °C after an order-disorder phase transformation. It also reveals a good capability of dendrite suppression and remarkable stability against sodium metal. These performances enable the all-solid-state Na//TiS2 battery with a high capacity of 232.4 mAh g-1 (97.2 % of theoretical capacity) and long-term cycling stability at 1 C. Notably, this battery shows superior long-life cycling stability even at 5 and 10 C, which has been rarely reported in all-solid-state sodium metal batteries. This work opens a new group of solid electrolytes, contributing to fast-charging or high-power-density sodium metal batteries.

IL13Rα2 as a crucial receptor for Chi3l1 in osteoclast differentiation and bone resorption through the MAPK/AKT pathway.

BACKGROUND: Previous research has revealed that the 18 glycoside hydrolase gene family (GH18) member Chitinase 3-like 1 (Chi3l1) can regulate osteoclast differentiation and bone resorption. However, its downstream receptors and molecular mechanisms during osteoclastogenesis have yet to be elucidated. METHODS: Initially, we conducted a comprehensive investigation to evaluate the effects of recombinant Chi3l1 protein or Chi3l1 siRNA on osteoclast differentiation and the RANKL-induced MAPK/AKT signaling pathways. Moreover, we used immunofluorescence and immunoprecipitation assays to identify IL13Rα2 as the downstream receptor of Chi3l1. Subsequently, we investigated the impact of IL13Rα2 recombinant protein or IL13Rα2-siRNA on osteoclast differentiation and the associated signaling pathways. Finally, we performed in vivo experiments to examine the effect of recombinant IL13Rα2 protein in an LPS-induced mouse model of cranial osteolysis. RESULTS: Our findings highlight that the administration of recombinant Chi3l1 protein increased the formation of osteoclasts and bolstered the expression of several osteoclast-specific genes (TRAP, NFATC1, CTR, CTSK, V-ATPase d2, and Dc-STAMP). Additionally, Chi3l1 significantly promoted the RANKL-induced MAPK (ERK/P38/JNK) and AKT pathway activation, whereas Chi3l1 silencing inhibited this process. Next, using immunofluorescence and co-immunoprecipitation assays, we identified IL13Rα2 as the binding partner of Chi3l1 during osteoclastogenesis. IL13Rα2 recombinant protein or IL13Rα2-siRNA also inhibited osteoclast differentiation, and IL13Rα2-siRNA attenuated the RANKL-induced activation of the MAPK (ERK/P38/JNK) and AKT pathways, similar to the effects observed upon silencing of Chi3l1. Moreover, the promoting effect of recombinant Chi3l1 protein on osteoclastogenesis and the activation of the MAPK and AKT pathways was reversed by IL13Rα2 siRNA. Finally, recombinant LI13Rα2 protein significantly attenuated the LPS-induced cranial osteolysis and the number of osteoclasts in vivo. CONCLUSIONS: Our findings suggested that IL13Rα2 served as a crucial receptor for Chi3l1, enhancing RANKL-induced MAPK and AKT activation to promote osteoclast differentiation. These findings provide valuable insights into the molecular mechanisms of Chi3l1 in osteoclastogenesis, with potential therapeutic implications for osteoclast-related diseases. Video Abstract.

A ROS-responsive microsphere capsule encapsulated with NADPH oxidase 4 inhibitor ameliorates macrophage inflammation and ferroptosis.

Inflammatory macrophages within the synovium play a pivotal role in the progression of arthritis inflammation. Effective drug therapy targeting inflammatory macrophages has long been a goal for clinicians and researchers. The standard approach for treating osteoarthritis (OA) involves systemic treatment and local injection. However, the high incidence of side effects associated with long-term drug administration increases the risk of complications in patients. Additionally, the rapid clearance of the joint cavity poses a biological barrier to the therapeutic effect. NADPH oxidase 4 (NOX4) is an enzyme protein regulating the cellular redox state by generating reactive oxygen species (ROS) within the cell. In this study, we designed and fabricated a hydrogel microsphere consisting of methyl methacrylate (MMA) and polyvinyl acetate (PVA) as the outer layer structure. We then loaded GLX351322 (GLX), a novel selective NOX4 inhibitor, into hydrogel microspheres through self-assembly with the compound polyethylene glycol ketone mercaptan (mPEG-TK) containing a disulfide bond, forming nanoparticles (mPEG-TK-GLX), thus creating a two-layer drug-loaded microspheres capsule with ROS-responsive and slow-releasing capabilities. Our results demonstrate that mPEG-TK-GLX@PVA-MMA effectively suppressed TBHP-induced inflammation, ROS production, and ferroptosis, indicating a promising curative strategy for OA and other inflammatory diseases in the future.

Effect and potential mechanisms of sludge-derived chromium, nickel, and lead on soil nitrification: Implications for sustainable land utilization of digested sludge.

Increasing occurrence of heavy metals (HMs) in sewage sludge threatens its widespread land utilization in China due to its potential impact on nutrient cycling in soil, requiring a better understanding of HM-induced impacts on nitrification. Herein, lab-scale experiments were conducted over 185-day, evaluating the effect of sludge-derived chromium (Cr3+), nickel (Ni2+), and lead (Pb2+) on soil nitrification at different concentrations. Quantitative polymerase chain reaction and linear regression results revealed an inhibitory sequence of gene abundance by HMs' labile fraction: ammonia-oxidizing bacteria (AOB)-ammonia monooxygenase (amoA)> nitrite oxidoreductase subunit alpha (nxrA)> nitrite oxidoreductase subunit beta (nxrB). The toxicity of HMs' incremental labile fraction decreased in the order of Ni2+>Cr3+>Pb2+, with respective threshold values of 5.01, 24.03 and 38.42 mg·kg-1. Furthermore, extending incubation time reduced HMs inhibition on ammonia oxidation, mainly related to their fraction bound to carbonate minerals. Random Forest analysis, variation partitioning analysis, and Mantel test indicated that soil physicochemical properties primarily affected nitrification genes, especially in the test of Cr3+ on AOB-amoA, nxrA, nxrB, Ni2+ for complete ammonia-oxidizing bacteria-amoA, and Pb2+ for nxrA and nxrB. These findings underline the importance of labile HMs fractions and soil physicochemical properties to nitrification, guiding the establishment of HM control standards for sludge utilization.

Correction: Sugarcane stem node identification algorithm based on improved YOLOv5.

[This corrects the article DOI: 10.1371/journal.pone.0295565.].

Hypoxia-based critical gene biomarkers as prognostic reporters for gastric adenocarcinoma.

BACKGROUND: Gastric cancer is the most common malignant tumour of the digestive system, yet there is a lack of reported prognostic biomarkers for STAD patients. METHODS: Transcriptomic expression data of STAD from GEO database, single cell sequencing data from OMIX gastric cancer database. Conservative molecular typing of gastric cancer was constructed using non-negative matrix factorization (NMF). The abundance of 28 immune cells in the tumour samples was assessed using ssGSEA. The R package "oncoPredict" was used to predict chemotherapy response. TIDE website for immunotherapy response prediction. Finally, single cell analysis was performed to clarify the specific type annotation of STAD cells and to analysis their spatial expression. RESULTS: Hypoxia-score demonstrated excellent prognostic discrimination in TCGA gastric cancer samples. Among multiple deconvolution-based algorithms for immune infiltration, Hypoxia-score presented a general immunosuppressive efficacy across multiple datasets, as evidenced by a broad negative correlation with immune cell infiltration. By the likelihood that each group may have specific drug sensitivity to multiple chemotherapeutic and targeted agents. Results showed that high-risk scoring patients were more sensitive to Staurosporine, Sabutoclax, and AZD8055, while low-risk patients were more sensitive to Bortezomib, Dactinomycin, Docetaxel, Daporinad, Sepantronium, and bromide. In the immunotherapy cohort, the Hypoxia-score presented the ability to discriminate for immunotherapy efficacy. The distribution of Hypoxia-score in single-cell descending space was calculated using AddModuleScore and was found to be distributed across the various cell types annotated in the single-cell analysis. It is suggested that various cells in the tumour microenvironment are involved in hypoxia gene set processes to varying degrees. CONCLUSION: The Hypoxia-score proves to be a valuable tool for assessing the prognosis of gastric cancer patients and guiding drug treatments, providing significant guidance for clinical diagnosis and treatment in the context of gastric cancer.

Sugarcane stem node identification algorithm based on improved YOLOv5.

Identification of sugarcane stem nodes is generally dependent on high-performance recognition equipment in sugarcane seed pre-cutting machines and inefficient. Accordingly, this study proposes a novel lightweight architecture for the detection of sugarcane stem nodes based on the YOLOv5 framework, named G-YOLOv5s-SS. Firstly, the study removes the CBS and C3 structures at the end of the backbone network to fully utilize shallow-level feature information. This enhances the detection performance of sugarcane stem nodes. Simultaneously, it eliminates the 32 times down-sampled branches in the neck structure and the 20x20 detection heads at the prediction end, reducing model complexity. Secondly, a Ghost lightweight module is introduced to replace the conventional convolution module in the BottleNeck structure, further reducing the model's complexity. Finally, the study incorporates the SimAM attention mechanism to enhance the extraction of sugarcane stem node features without introducing additional parameters. This improvement aims to enhance recognition accuracy, compensating for any loss in precision due to lightweight modifications. The experimental results showed that the average precision of the improved network for sugarcane stem node identification reached 97.6%, which was 0.6% higher than that of the YOLOv5 baseline network. Meanwhile, a model size of 2.6MB, 1,129,340 parameters, and 7.2G FLOPs, representing respective reductions of 82%, 84%, and 54.4%. Compared with mainstream one-stage target detection algorithms such as YOLOv4-tiny, YOLOv4, YOLOv5n, YOLOv6n, YOLOv6s, YOLOv7-tiny, and YOLOv7, G-YOLOv5s-SS achieved respective average precision improvements of 12.9%, 5.07%, 3.6%, 2.1%, 1.2%, 3%, and 0.4% in sugarcane stem nodes recognition. Meanwhile, the model size was compressed by 88.9%, 98.9%, 33.3%, 72%, 92.9%, 78.8% and 96.3%, respectively. Compared with similar studies, G-YOLOv5s-SS not only enhanced recognition accuracy but also considered model size, demonstrating an overall excellent performance that aligns with the requirements of sugarcane seed pre-cutting machines.

N4-acetylcytidine-dependent GLMP mRNA stabilization by NAT10 promotes head and neck squamous cell carcinoma metastasis and remodels tumor microenvironment through MAPK/ERK signaling pathway.

N4-acetylcytidine (ac4C) is a post-transcriptional RNA modification that regulates in various important biological processes. However, its role in human cancer, especially lymph node metastasis, remains largely unknown. Here, we demonstrated N-Acetyltransferase 10 (NAT10), as the only known "writer" of ac4C mRNA modification, was highly expressed in head and neck squamous cell carcinoma (HNSCC) patients with lymph node metastasis. High NAT10 levels in the lymph nodes of patients with HNSCC patients are a predictor of poor overall survival. Moreover, we found that high expression of NAT10 was positively upregulated by Nuclear Respiratory Factor 1 (NRF1) transcription factor. Gain- and loss-of-function experiments displayed that NAT10 promoted cell metastasis in mice. Mechanistically, NAT10 induced ac4C modification of Glycosylated Lysosomal Membrane Protein (GLMP) and stabilized its mRNA, which triggered the activation of the MAPK/ERK signaling pathway. Finally, the NAT10-specific inhibitor, remodelin, could inhibit HNSCC tumorigenesis in a 4-Nitroquinoline 1-oxide (4NQO)-induced murine tumor model and remodel the tumor microenvironment, including angiogenesis, CD8+ T cells and Treg recruitment. These results demonstrate that NAT10 promotes lymph node metastasis in HNSCC via ac4C-dependent stabilization of the GLMP transcript, providing a potential epitranscriptomic-targeted therapeutic strategy for HNSCC.

LensAge index as a deep learning-based biological age for self-monitoring the risks of age-related diseases and mortality.

Age is closely related to human health and disease risks. However, chronologically defined age often disagrees with biological age, primarily due to genetic and environmental variables. Identifying effective indicators for biological age in clinical practice and self-monitoring is important but currently lacking. The human lens accumulates age-related changes that are amenable to rapid and objective assessment. Here, using lens photographs from 20 to 96-year-olds, we develop LensAge to reflect lens aging via deep learning. LensAge is closely correlated with chronological age of relatively healthy individuals (R2 > 0.80, mean absolute errors of 4.25 to 4.82 years). Among the general population, we calculate the LensAge index by contrasting LensAge and chronological age to reflect the aging rate relative to peers. The LensAge index effectively reveals the risks of age-related eye and systemic disease occurrence, as well as all-cause mortality. It outperforms chronological age in reflecting age-related disease risks (p < 0.001). More importantly, our models can conveniently work based on smartphone photographs, suggesting suitability for routine self-examination of aging status. Overall, our study demonstrates that the LensAge index may serve as an ideal quantitative indicator for clinically assessing and self-monitoring biological age in humans.

Dlk2 interacts with Syap1 to activate Akt signaling pathway during osteoclast formation.

Excessive osteoclast formation and bone resorption are related to osteolytic diseases. Delta drosophila homolog-like 2 (Dlk2), a member of the epidermal growth factor (EGF)-like superfamily, reportedly regulates adipocyte differentiation, but its roles in bone homeostasis are unclear. In this study, we demonstrated that Dlk2 deletion in osteoclasts significantly inhibited osteoclast formation in vitro and contributed to a high-bone-mass phenotype in vivo. Importantly, Dlk2 was shown to interact with synapse-associated protein 1 (Syap1), which regulates Akt phosphorylation at Ser473. Dlk2 deletion inhibited Syap1-mediated activation of the AktSer473, ERK1/2 and p38 signaling cascades. Additionally, Dlk2 deficiency exhibits increased bone mass in ovariectomized mice. Our results reveal the important roles of the Dlk2-Syap1 signaling pathway in osteoclast differentiation and osteoclast-related bone disorders.

Surface-independent CO2 and CO reduction on two-dimensional kagome metal KV3Sb5.

Two-dimensional kagome metals possess rich band structure characteristics, including Dirac points, flat bands, and van Hove singularities, because of their special geometric structures. Furthermore, kagome metals AV3Sb5 (A = K, Rb, and Cs) have garnered significant attention due to their nontrivial topological electronic structures. In this study, we theoretically demonstrate that the KV3Sb5 (001) surface is conducive to CO2 and CO reduction. The thermodynamic stability and electrochemical states of various surface types are investigated. The reaction paths reveal that the product is identical on different surfaces, and the free energy profiles exhibit low onset potentials. This paper elucidates the effect of two-dimensional topological kagome metals on CO2 and CO reduction.

A Combined Model Integrating Radiomics and Deep Learning Based on Contrast-Enhanced CT for Preoperative Staging of Laryngeal Carcinoma.

RATIONALE AND OBJECTIVES: Accurate staging of laryngeal carcinoma can inform appropriate treatment decision-making. We developed a radiomics model, a deep learning (DL) model, and a combined model (incorporating radiomics features and DL features) based on the venous-phase CT images and explored the performance of these models in stratifying patients with laryngeal carcinoma into stage I-II and stage III-IV, and also compared these models with radiologists. MATERIALS AND METHODS: Three hundreds and nineteen patients with pathologically confirmed laryngeal carcinoma were randomly divided into a training set (n = 223) and a test set (n = 96). In the training set, the radiomics features with inter- and intraclass correlation coefficients (ICCs)> 0.75 were screened by Spearman correlation analysis and recursive feature elimination (RFE); then support vector machine (SVM) classifier was applied to develop the radiomics model. The DL model was built using ResNet 18 by the cropped 2D regions of interest (ROIs) in the maximum tumor ROI slices and the last fully connected layer of this network served as the DL feature extractor. Finally, a combined model was developed by pooling the radiomics features and extracted DL features to predict the staging. RESULTS: The area under the curves (AUCs) for radiomics model, DL model, and combined model in the test set were 0.704 (95% confidence interval [CI]: 0.588-0.820), 0.724 (95% CI: 0.613-0.835), and 0.849 (95% CI: 0.755-0.943), respectively. The combined model outperformed the radiomics model and the DL model in discriminating stage I-II from stage III-IV (p = 0.031 and p = 0.020, respectively). Only the combined model performed significantly better than radiologists (p < 0.050 for both). CONCLUSION: The combined model can help tailor the therapeutic strategy for laryngeal carcinoma patients by enabling more accurate preoperative staging.

[Analysis of efficacy and prognosis of neoadjuvant chemotherapy and （or） surgery plus radiotherapy for hypopharyngeal squamous cell carcinoma].

Objective:To analyze the risk factors that affect the prognosis of patients with hypopharyngeal squamous cell carcinoma（HPSCC） and to compare the efficacy of surgical resection followed by adjuvant radiotherapy（SR） with that of neoadjuvant therapy consisting of platinum-based chemotherapy and fluorouracil combined with either cetuximab or nimotuzumab, followed by SR. The study also aimed to evaluate the overall survival（OS） of patients, their postoperative eating function, tracheostomy decannulation rate, and tumor response to the two neoadjuvant chemotherapies. Methods:A retrospective analysis was performed on the medical records of HPSCC patients who received SR or neoadjuvant therapy followed by SR treatment at the Shanghai General Hospital from 2012 to 2019 and had not undergone any prior treatment. The prognostic factors were analyzed, and the survival analysis of patients who underwent SR treatment with two neoadjuvant chemotherapy regimens was performed. Results:A total of 108 patients were included in the study. The results of the univariate analysis showed that gender（P=0.850） had no significant correlation with the survival rate of HPSCC patients who underwent SR. However, age, smoking history, alcohol consumption history, platelet-to-lymphocyte ratio（PLR）, neutrophil-to-lymphocyte ratio（NLR）, T stage, N stage, neoadjuvant therapy with either cetuximab or nimotuzumab combined with platinum-based chemotherapy and fluorouracil, and histological grade were significantly associated with prognosis（P<0.05）. The multivariate analysis revealed that smoking history, histological grade, and neoadjuvant therapy with either cetuximab or nimotuzumab combined with platinum-based chemotherapy and fluorouracil were independent risk factors affecting the prognosis of HPSCC（P<0.05）. Patients who received neoadjuvant therapy had longer OS than those who underwent SR only（P<0.001）. There was no significant difference in tumor response to the two neoadjuvant therapies and in OS（P>0.05）, and there was no significant difference in the rate of oral feeding and tracheostomy decannulation among the three treatment groups（P>0.05）. Conclusion:Univariate analysis showed that age at tumor onset, smoking history, alcohol consumption history, NLR, PLR, T stage, N stage, whether receiving neoadjuvant chemotherapy, and pathological grade were associated with the prognosis of HPSCC patients receiving SR treatment. Multivariate analysis showed that smoking history, pathological grade, and neoadjuvant chemotherapy were independent risk factors affecting the prognosis. Neoadjuvant chemotherapy with cetuximab or nimotuzumab can prolong the OS of patients, providing a certain basis and reference for the treatment of HPSCC.

Enzymatic synthesis of indigo derivatives by tuning P450 BM3 peroxygenases.

Indigoids, a class of bis-indoles, have long been applied in dyeing, food, and pharmaceutical industries. Recently, interest in these 'old' molecules has been renewed in the field of organic semiconductors as functional building blocks for organic electronics due to their excellent chemical and physical properties. However, these indigo derivatives are difficult to access through chemical synthesis. In this study, we engineer cytochrome P450 BM3 from an NADPH-dependent monooxygenase to peroxygenases through directed evolution. A select number of P450 BM3 variants are used for the selective oxidation of indole derivatives to form different indigoid pigments with a spectrum of colors. Among the prepared indigoid organic photocatalysts, a majority of indigoids demonstrate a reduced band gap than indigo due to the increased light capture and improved charge separation, making them promising candidates for the development of new organic electronic devices. Thus, we present a useful enzymatic approach with broad substrate scope and cost-effectiveness by using low-cost H2O2 as a cofactor for the preparation of diversified indigoids, offering versatility in designing and manufacturing new dyestuff and electronic/sensor components.

Selenium-enriched peptides identified from selenium-enriched soybean protein hydrolysate: protective effects against heat damage in Caco-2 cells.

Our previous study evaluated the antioxidant and anti-inflammatory activities of selenium-enriched soybean peptides (SePPs) in vivo. In this study, we purified SePPs via gel filtration chromatography and obtained five fractions (F1, F2, F3, F4 and F5), among which F3 displayed the highest antioxidant and anti-inflammatory activities. Nineteen selenium-enriched peptides were identified in F3 by mass spectrometry. Two selenium-enriched peptides with sequences ESeCQIQKL (Sep-1) and SELRSPKSeC (Sep-2) were selected for synthesis based on their score and the number of hydrophobic amino acids, acidic and basic amino acids. Both Sep-1 and Sep-2 exhibited preventive effects on the heat stress-induced impairment of intestinal epithelial cell integrity, oxidative stress and inflammatory responses in a Caco-2 cell model. Pretreatment of the cells with Sep-1 or Sep-2 for 24 h reduced intracellular reactive oxygen species (ROS) generation, prevented the disruption of tight junction (TJ) proteins, and decreased paracellular permeability. Western blot results showed that Sep-1 and Sep-2 could improve the abnormal expressions of Nrf2, Keap1, NLRP3, caspase-1 and ASC/TMS1, thereby enhancing the glutathione (GSH) redox system and reducing IL-1ß and IL-18 concentrations. Sep-1 activated the Nrf2-Keap1 signaling pathway significantly more than Sep-2. Molecular docking results indicated that Sep-1 and Sep-2 are both bound to Keap1 and NLRP3 in the form of hydrogen bonds, hydrophobic interactions and salt bridges, which interferes with Nrf2 and NLRP3 signaling. Molecular dynamics simulations suggested that more hydrogen bonds were formed during the resultant process of Sep-1 with Keap1, and the compactness and stability of the complex structure were better than those of Sep-2. These findings confirm the value of both Sep-1 and Sep-2 in the development of dietary supplements as potential alternatives for heat damage and related disease prevention.

White matter hyperintensities burden in the frontal regions is positively correlated to the freezing of gait in Parkinson's disease.

Objective: Previous studies have reported that white matter hyperintensities (WMHs) are associated with freezing of gait (FOG), but it is not clear whether their distribution areas have correlations with FOG in Parkinson's disease (PD) and the potential influencing factors about WMHs. Methods: Two hundred and forty-six patients with PD who underwent brain MRI were included. Participants were divided into PD with FOG (n = 111) and PD without FOG (n = 135) groups. Scheltens score was used to assess the WMHs burden in the areas of deep white matter hyperintensities (DWMHs), periventricular hyperintensities (PVHs), basal ganglia hyperintensities (BGHs), and infratentorial foci of hyperintensities (ITF). Whole brain WMHs volume was evaluated by automatic segmentation. Binary logistic regression was used to evaluate relationships between WMHs and FOG. The common cerebrovascular risk factors that may affect WMHs were evaluated by mediation analysis. Results: There were no statistical differences between PD with and without FOG groups in whole brain WMHs volume, total Scheltens score, BGHs, and ITF. Binary logistic regression showed that the total scores of DWMHs (OR = 1.094; 95% CI, 1.001, 1.195; p = 0.047), sum scores of PVHs and DWMHs (OR = 1.080; 95% CI, 1.003, 1.164; p = 0.042), especially the DWMHs in frontal (OR = 1.263; 95% CI, 1.060, 1.505 p = 0.009), and PVHs in frontal caps (OR = 2.699; 95% CI, 1.337, 5.450; p = 0.006) were associated with FOG. Age, hypertension, and serum alkaline phosphatase (ALP) are positively correlated with scores of DWMHs in frontal and PVHs in frontal caps. Conclusion: These results indicate that WMHs distribution areas especially in the frontal of DWMHs and PVHs play a role in PD patients with FOG.

Deep learning-assisted diagnosis of benign and malignant parotid tumors based on contrast-enhanced CT: a multicenter study.

OBJECTIVES: To develop deep learning-assisted diagnosis models based on CT images to facilitate radiologists in differentiating benign and malignant parotid tumors. METHODS: Data from 573 patients with histopathologically confirmed parotid tumors from center 1 (training set: n = 269; internal-testing set: n = 116) and center 2 (external-testing set: n = 188) were retrospectively collected. Six deep learning models (MobileNet V3, ShuffleNet V2, Inception V3, DenseNet 121, ResNet 50, and VGG 19) based on arterial-phase CT images, and a baseline support vector machine (SVM) model integrating clinical-radiological features with handcrafted radiomics signatures were constructed. The performance of senior and junior radiologists with and without optimal model assistance was compared. The net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the clinical benefit of using the optimal model. RESULTS: MobileNet V3 had the best predictive performance, with sensitivity increases of 0.111 and 0.207 (p < 0.05) in the internal- and external-testing sets, respectively, relative to the SVM model. Clinical benefit and overall efficiency of junior radiologist were significantly improved with model assistance; for the internal- and external-testing sets, respectively, the AUCs improved by 0.128 and 0.102 (p < 0.05), the sensitivity improved by 0.194 and 0.120 (p < 0.05), the NRIs were 0.257 and 0.205 (p < 0.001), and the IDIs were 0.316 and 0.252 (p < 0.001). CONCLUSIONS: The developed deep learning models can assist radiologists in achieving higher diagnostic performance and hopefully provide more valuable information for clinical decision-making in patients with parotid tumors. KEY POINTS: • The developed deep learning models outperformed the traditional SVM model in predicting benign and malignant parotid tumors. • Junior radiologist can obtain greater clinical benefits with assistance from the optimal deep learning model. • The clinical decision-making process can be accelerated in patients with parotid tumors using the established deep learning model.