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Soybean dreg is a by-product of soybean products production, with a large consumption in China. Low utilization value leads to random discarding, which is one of the important sources of urban pollution. In this work, porous biochar was synthesized using a one-pot method and potassium bicarbonate (KHCO3) with low-cost soybean dreg (SD) powder as the carbon precursor to investigating the adsorption of methylene blue (MB). The prepared samples were characterized with scanning electron microscopy (SEM), transmission electron microscopy (TEM), elemental analyzer (EA), Brunauer-Emmett-Teller (BET), X-ray diffractometer (XRD), Raman spectroscopy (Raman), Fourier transform infrared spectrometer (FTIR), and X-ray photoelectron spectroscopy (XPS). The obtained SDB-K-3 showed a high specific surface area of 1620 m2 g−1, a large pore volume of 0.7509 cm3 g−1, and an average pore diameter of 1.859 nm. The results indicated that the maximum adsorption capacity of SDB-K-3 to MB could reach 1273.51 mg g−1 at 318 K. The kinetic data were most consistent with the pseudo-second-order model and the adsorption behavior was more suitable for the Langmuir isotherm equation. This study demonstrated that the porous biochar adsorbent can be prepared from soybean dreg by high value utilization, and it could hold significant potential for dye wastewater treatment in the future.

Inflammation is considered to be a crucial factor in the development of chronic diseases, eight of which were listed among the top ten causes of death worldwide in the World Health Organization’s World Health Statistics 2019. Moreover, traditional drugs for inflammation are often linked to undesirable side effects. As gentler alternatives to traditional anti-inflammatory drugs, plant-derived bioactive peptides have been shown to be effective interventions against various chronic diseases, including Alzheimer’s disease, cardiovascular disease and cancer. However, an adequate and systematic review of the structures and anti-inflammatory activities of plant-derived bioactive peptides has been lacking. This paper reviews the latest research on plant-derived anti-inflammatory peptides (PAPs), mainly including the specific regulatory mechanisms of PAPs; the structure–activity relationships of PAPs; and their enzymatic processing based on the structure–activity relationships. Moreover, current research problems for PAPs are discussed, such as the shallow exploration of mechanisms, enzymatic solution determination difficulty, low yield and unknown in vivo absorption and metabolism and proposed future research directions. This work aims to provide a reference for functional activity research, nutritional food development and the clinical applications of PAPs.

HighlightsAn ultra-sensitive capture of NO2 molecules and fast charge collection and transfer has been realized by constructing the model of artificial neuron-likegas sensing structure based on CuS quantum dots (QDs)/Bi2S3 nanosheets (NSs)realizes.Simulation analysis revealed that CuS QDs and Bi2S3NSs can be used, respectively, as the main adsorption sites and charge transport pathways, thus leading to a greatly enhanced gas capture ability and charge conduction performance of NO2.Real-time rapid detection of toxic gases at room temperature is particularly important for public health and environmental monitoring. Gas sensors based on conventional bulk materials often suffer from their poor surface-sensitive sites, leading to a very low gas adsorption ability. Moreover, the charge transportation efficiency is usually inhibited by the low defect density of surface-sensitive area than that in the interior. In this work, a gas sensing structure model based on CuS quantum dots/Bi2S3 nanosheets (CuS QDs/Bi2S3 NSs) inspired by artificial neuron network is constructed. Simulation analysis by density functional calculation revealed that CuS QDs and Bi2S3 NSs can be used as the main adsorption sites and charge transport pathways, respectively. Thus, the high-sensitivity sensing of NO2 can be realized by designing the artificial neuron-like sensor. The experimental results showed that the CuS QDs with a size of about 8 nm are highly adsorbable, which can enhance the NO2 sensitivity due to the rich sensitive sites and quantum size effect. The Bi2S3 NSs can be used as a charge transfer network channel to achieve efficient charge collection and transmission. The neuron-like sensor that simulates biological smell shows a significantly enhanced response value (3.4), excellent responsiveness (18 s) and recovery rate (338 s), low theoretical detection limit of 78 ppb, and excellent selectivity for NO2. Furthermore, the developed wearable device can also realize the visual detection of NO2 through real-time signal changes.

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.

Water pollution by various toxic substances remains a serious environmental problem, especially the occurrence of organic micropollutants including endocrine disruptors, pharmaceutical pollutants and naphthol pollutants. Adsorption process has been an effective method for pollutant removal in wastewater treatment. However, the thermal regeneration process for the most widely used activated carbon is costly and energy-consuming. Therefore, there has been an increasing need to develop alternative low-cost and effective adsorption materials for pollutant removal. Herein, β-cyclodextrin (β-CD), a cheap and versatile material, was modified with methacrylate groups by reacting with methacryloyl chloride, giving an average degree of substitution of 3 per β-CD molecule. β-CD-methacrylate, which could function as a crosslinker, was then copolymerized with acrylamide monomer via free-radical copolymerization to form β-CD-polyacrylamide (β-CD-PAAm) hydrogel. Interestingly, in the structure of the β-CD-PAAm hydrogel, β-CD is not only a functional unit binding pollutant molecules through inclusion complexation, but also a structural unit crosslinking PAAm leading to the formation of the hydrogel 3D networks. Morphological studies showed that β-CD-PAAm gel had larger pore size than the control PAAm gel, which was synthesized using conventional crosslinker instead of β-CD-methacrylate. This was consistent with the higher swelling ratio of β-CD-PAAm gel than that of PAAm gel (29.4 vs. 12.7). In the kinetic adsorption studies, phenolphthalein, a model dye, and bisphenol A, propranolol hydrochloride, and 2-naphthol were used as model pollutants from different classes. The adsorption data for β-CD-PAAm gel fitted well into the pseudo-second-order model. In addition, the thermodynamic studies revealed that β-CD-PAAm gel was able to effectively adsorb the different dye and pollutants at various concentrations, while the control PAAm gel had very low adsorption, confirming that the pollutant removal was due to the inclusion complexation between β-CD units and pollutant molecules. The adsorption isotherms of the different dye and pollutants by the β-CD-PAAm gel fitted well into the Langmuir model. Furthermore, the β-CD-PAAm gel could be easily recycled by soaking in methanol and reused without compromising its performance for five consecutive adsorption/desorption cycles. Therefore, the β-CD-PAAm gel, which combines the advantage of an easy-to-handle hydrogel platform and the effectiveness of adsorption by β-CD units, could be a promising pollutant removal system for wastewater treatment applications.

Objective Mitochondrial fission regulator 2 (MTFR2) is upregulated in multiple cancers, including hepatocellular carcinoma (HCC); however, its mechanistic role in HCC progression remains poorly understood. Methods MTFR2 expression in HCC tissues was analyzed using TCGA and GEO databases. Validation of MTFR2 expression levels in clinical samples and HCC cell lines was performed through qRT-PCR and western blot. Functional effects of MTFR2 overexpression and knockdown on HCC cell proliferation, migration, and invasion were assessed via CCK-8, colony formation, wound healing, and transwell assays. In vivo tumor growth was evaluated in xenograft mouse models. Results MTFR2 was significantly overexpressed in HCC tissues and cell lines. Enhanced proliferation, migration, invasion, and colony formation were observed in MTFR2-overexpressing HCC cells, whereas knockdown of MTFR2 suppressed these malignant phenotypes. Mechanistic studies demonstrated that MTFR2 promotes proliferation, migration, and invasion of HCC cells via the PI3K/AKT signaling pathway. Additionally, MTFR2 knockdown significantly attenuated tumor growth in xenograft models. Conclusion These findings demonstrate that MTFR2 promotes HCC progression via modulation of the PI3K/AKT pathway, underscoring its potential as a therapeutic target for HCC. Highlights MTFR2 is up-regulated in hepatocellular carcinoma (HCC) tissues and cells. MTFR2 knockdown significantly reducing the proliferation rate of HCC cells by 21.6%. MTFR2 regulates HCC progression via activating PI3K/AKT signaling pathway. MTFR2 knockdown partially inhibits tumor growth rate in xenograft mice models.

To evaluate the risk factors of nosocomial infection during Extracorporeal membrane oxygenation (ECMO) treatment through systematic evaluation and meta-analysis, in order to provide evidence-based basis for clinical treatment and prevention of nosocomial infection during ECMO treatment. Computer search of Cochrane Library, PubMed, Embase, and Web of Science databases was conducted to establish a database of relevant literature published in March 2023. Two researchers independently screened literature, extracted data, and evaluated quality based on inclusion and exclusion criteria, and then analyzed the data using STATA 14.0 software. This plan is registered with PROSPERO as CRD42021271083. A total of 2955 ECMO patients, including 933 nosocomial infected patients, were included in 23 articles. Meta analysis showed that immunosuppression, Heart transplantation, VA-ECMO, CRRT, red blood cell input, ECMO support time, mechanical ventilation time, ICU hospitalization time, and total hospitalization time were the risk factors for nosocomial infection in patients supported by ECMO. ECMO treatment for nosocomial infections in patients is related to multiple factors. In clinical work, medical staff should identify high-risk groups of ECMO nosocomial infections, actively take preventive measures, and reduce the incidence and mortality of nosocomial infections.

Detecting Trichosanthes Kirilowii Maxim (Cucurbitaceae) in complex mountain environments is critical for developing automated harvesting systems. However, the environmental characteristics of brightness variation, inter-plant occlusion, and motion-induced blurring during harvesting operations, detection algorithms face excessive parameters and high computational intensity. Accordingly, this study proposes a lightweight T.Kirilowii detection algorithm for complex mountainous environments based on YOLOv7-tiny, named KPD-YOLOv7-GD. Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. The experimental results showed that the mean average precision of the improved network KPD-YOLOv7-GD reached 93.2%. Benchmarked against mainstream single-stage algorithms (YOLOv3-tiny, YOLOv5s, YOLOv6s, YOLOv7-tiny, and YOLOv8), KPD-YOLOv7-GD demonstrated mean average precision improvements of 4.8%, 0.6%, 3.0%, 0.6%, and 0.2% with corresponding model compression rates of 81.6%, 68.8%, 88.9%, 63.4%, and 27.4%, respectively. Compared with similar studies, KPD-YOLOv7-GD exhibits lower complexity and higher recognition speed accuracy, making it more suitable for resource-constrained T.kirilowii harvesting robots.

To investigate the role of periosteum on the treatment of buccal dehiscence defects comparing with collagen membrane in canine model. Bilateral dehiscence-type defects at the buccal side on the distal root of the lower 3rd/4th premolars were created in six beagle dogs with a total of 24 defects and assigned into three groups: Group A: blood clot in an untreated defect; Group B: deproteinized bovine bone material (DBBM) covered with an absorbable membrane; Group C: DBBM covered with the periosteum. The structural parameters for trabecular architecture and vertical bone regeneration were evaluated. Histological and histomorphometric evaluation were carried out to observe new bone formation and mineralization in the graft site. Immunohistochemical analysis was performed to identify the expression of osteopontin (OPN) and osteocalcin (OCN) at postoperative 3 months. Group C achieved greater vertical alveolar bone gain than that of group A and group B. The periosteum-covered group showed significantly greater new bone formation and accelerated mineralization. The greater immunolabeling for OPN and OCN was observed in group C than in group A. Periosteal coverage has explicit advantages over collagen membranes for the quality and quantity of new bone regeneration in dehiscence defects repairing.

To achieve automated harvesting of hydroponic Chinese flowering cabbage, the detection and localization of the cabbage are crucial. This study proposes a two stages detection and localization algorithm for hydroponic Chinese flowering cabbage, which includes macro-detection and micro-localization. The macro-detection algorithm is named P-YOLOv5s-GRNF. Its improvement strategies include adopting pruning techniques, the GSConv, receptive field attention convolution (RFAConv), normalization-based attention module (NAM), and the Focal-EIOU Loss module. The micro-localization algorithm is named YOLOv5s-SBC. Its improvement strategies include adding a 160×160 detection layer, removing a 20×20 detection layer, introducing a weighted bidirectional feature pyramid network (BiFPN) structure, and utilizing the coordinate attention (CA) mechanism. The experimental results showed that P-YOLOv5s-GRNF increased the mAP(mean average precision) by 0.8%, 4.3%, 3.2%, 0.7%, 19.3%, 9.8%, 3.1% compared to mainstream object detection algorithms YOLOv5s, YOLOv6s, YOLOv7-tiny, YOLOv8s, YOLOv5s-Shufflenetv2, YOLOv5s-Mobilenetv3, YOLOv5s-Ghost, respectively. Compared to the original model, P-YOLOv5s-GRNF decreased parameters by 18%, decreased model size to 11.9MB, decreased FLOPs to 14.5G, and increased FPS by 4.3. YOLOv5s-SBC also increased mAP by 4.0% compared to the original YOLOv5s, with parameters decreased by 65%, model size decreased by 60%, and FLOPs decreased to 15.3G. Combined with a depth camera, the improved models construct a positioning system that can provide technical support for the automated and intelligent harvesting of Chinese flowering cabbage.