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Using drought-resistant cultivars is important to increase crop production in water limited regions. Cultivar performance is influenced by genetic, management and environmental factors, and selection good performance cultivars is often a challenge. Five seasons (2016–2021) of field experiments and three seedling growing durations in a greenhouse, both under three water supply levels (serious water deficit, moderate water deficit and normal water supply), were conducted to assess 10 winter wheat cultivars for their water use characteristics and drought tolerance ability based on seven drought resistance indices and agronomic traits. The performance of the cultivars varied seasonally under field growing conditions. Drought resistance screened by a single index or based on the results from a single season was inconsistent. To avoid seasonal changes in cultivar performance, principal component analyses (PCA) and hierarchical cluster analysis (HCA) were conducted based on the seven indices to classify the ten cultivars into four types of drought responses. The drought resistance classification under field growing conditions at the grain yield level was highly consistent with that obtained under greenhouse growing conditions for biomass at the seedling stage. The results showed that the biomass at the seedling growing stage of the winter wheat cultivars could be used to predict the yield performance and water use characteristics when grown in the field under different water supply conditions. Precisely controlled greenhouse pot experiments could amplify the water use characteristics of different wheat cultivars for assessment. The cultivars with strong stomatal control ability had higher drought resistance and biomass production. Under field growing conditions, lower canopy temperature, deep root growth, a high root/shoot ratio and the maintenance of stomatal conductance under water stress were associated with high drought resistance. These findings provide references for selection methods and indicators for assessing drought-resistant winter wheat cultivars under different growing conditions.

Plasmid-mediated conjugation is a common mechanism for most bacteria to transfer antibiotic resistance genes (ARGs). The conjugative transfer of ARGs is emerging as a major threat to human beings. Although several transfer-related factors are known to regulate this process, small RNAs (sRNAs)-based regulatory roles remain to be clarified. Here, the Hfq-binding sRNA GadY in donor strain Escherichia coli (E. coli) SM10λπ was identified as a new regulator for bacterial conjugation. Two conjugation models established in our previous studies were used, which SM10λπ carrying a chromosomally integrated IncP-1α plasmid RP4 and a mobilizable plasmid pUCP24T served as donor cells, and P. aeruginosa PAO1 or E. coli EC600 as the recipients. GadY was found to promote SM10λπ-PAO1 conjugation by base-pairing with its target mRNA SdiA, an orphan LuxR-type receptor that responds to exogenous N-acylated homoserine lactones (AHLs). However, SM10λπ-EC600 conjugation was not affected due to EC600 lacking AHLs synthase. It indicates that the effects of GadY on conjugation depended on AHLs-SdiA signalling. Further study found GadY bound SdiA to negatively regulate the global RP4 repressors KorA and KorB. When under ciprofloxacin or levofloxacin treatment, GadY expression in donor strain was enhanced, and it positively regulated quinolone-induced SM10λπ-PAO1 conjugation. Thus, our study provides a novel role for sRNA GadY in regulating plasmid-mediated conjugation, which helps us better understand bacterial conjugation to counter antibiotic resistance.

Abstract Purpose To explore the predictive potential of intratumoral and multiregion peritumoral radiomics features extracted from multiparametric MRI for predicting pathological differentiation in hepatocellular carcinoma (HCC) patients. Methods A total of 265 patients with 277 HCCs (training cohort n = 193, validation cohort n = 84) who underwent preoperative MRI were retrospectively analyzed. The risk factors identified through stepwise regression analysis were utilized to construct a clinical model. Radiomics models based on MRI (arterial phase, portal venous phase, delayed phase) across various regions (entire tumor, Peri_5mm, Peri_10mm, Peri_20mm) were developed using the LASSO approach. The features obtained from the intratumoral region and the optimal peritumoral region were combined to design the IntraPeri fusion model. Model performance was assessed using the area under the curve (AUC). Results Larger size, non-smooth margins, and mosaic architecture were risk factors for poorly differentiated HCC (pHCC). The clinical model achieved AUCs of 0.77 and 0.73 in the training and validation cohorts, respectively, while the intratumoral model achieved corresponding AUC values of 0.92 and 0.82. The Peri_10mm model demonstrated superior performance to the Peri_5mm and Peri_20mm models, with AUC values of 0.87 vs. 0.84 vs. 0.73 in the training cohort and 0.80 vs. 0.77 vs. 0.68 in the validation cohort, respectively. The IntraPeri model exhibited remarkable AUC values of 0.95 and 0.86 in predicting pHCC in the training and validation cohorts, respectively. Conclusions Our study highlights the potential of a multiparametric MRI-based radiomic model that integrates intratumoral and peritumoral features as a tool for predicting HCC differentiation. Critical relevance statement Both clinical and multiparametric MRI-based radiomic models, particularly the intratumoral radiomic model, are non-invasive tools for predicting HCC differentiation. Importantly, the IntraPeri fusion model exhibited remarkable predictiveness for individualized HCC differentiation. Key points • Both the intratumoral radiomics model and clinical features were useful for predicting HCC differentiation. • The Peri_10mm radiomics model demonstrated better diagnostic ability than other peritumoral region-based models. • The IntraPeri radiomics fusion model outperformed the other models for predicting HCC differentiation. Graphical Abstract

Abstract The applications of silica-based glass have evolved alongside human civilization for thousands of years. High-precision manufacturing of three-dimensional (3D) fused silica glass objects is required in various industries, ranging from everyday life to cutting-edge fields. Advanced 3D printing technologies have emerged as a potent tool for fabricating arbitrary glass objects with ultimate freedom and precision. Stereolithography and femtosecond laser direct writing respectively achieved their resolutions of ~50 μm and ~100 nm. However, fabricating glass structures with centimeter dimensions and sub-micron features remains challenging. Presented here, our study effectively bridges the gap through engineering suitable materials and utilizing one-photon micro-stereolithography (OμSL)-based 3D printing, which flexibly creates transparent and high-performance fused silica glass components with complex, 3D sub-micron architectures. Comprehensive characterizations confirm that the final material is stoichiometrically pure silica with high quality, defect-free morphology, and excellent optical properties. Homogeneous volumetric shrinkage further facilitates the smallest voxel, reducing the size from 2.0 × 2.0 × 1.0 μm3 to 0.8 × 0.8 × 0.5 μm3. This approach can be used to produce fused silica glass components with various 3D geometries featuring sub-micron details and millimetric dimensions. This showcases promising prospects in diverse fields, including micro-optics, microfluidics, mechanical metamaterials, and engineered surfaces.

Abstract Background Breast cancer is the most prevalent malignant tumor among women, with hormone receptor-positive cases constituting 70%. Fulvestrant, an antagonist for these receptors, is utilized for advanced metastatic hormone receptor-positive breast cancer. Yet, its inhibitory effect on tumor cells is not strong, and it lacks direct cytotoxicity. Consequently, there's a significant challenge in preventing recurrence and metastasis once cancer cells develop resistance to fulvestrant. Method To address these challenges, we engineered tumor-targeting nanoparticles termed 131I-fulvestrant-ALA-PFP-FA-NPs. This involved labeling fulvestrant with 131I to create 131I-fulvestrant. Subsequently, we incorporated the 131I-fulvestrant and 5-aminolevulinic acid (ALA) into fluorocarbon nanoparticles with folate as the targeting agent. This design facilitates a tri-modal therapeutic approach—endocrine therapy, radiotherapy, and PDT for estrogen receptor-positive breast cancer. Results Our in vivo and in vitro tests showed that the drug-laden nanoparticles effectively zeroed in on tumors. This targeting efficiency was corroborated using SPECT-CT imaging, confocal microscopy, and small animal fluorescence imaging. The 131I-fulvestrant-ALA-PFP-FA-NPs maintained stability and showcased potent antitumor capabilities due to the synergism of endocrine therapy, radiotherapy, and CR-PDT. Throughout the treatment duration, we detected no notable irregularities in hematological, biochemical, or histological evaluations. Conclusion We've pioneered a nanoparticle system loaded with radioactive isotope 131I, endocrine therapeutic agents, and a photosensitizer precursor. This system offers a combined modality of radiotherapy, endocrine treatment, and PDT for breast cancer. Graphical Abstract

Abstract Unmanned aerial vehicles (UAVs) offer a new approach to wireless communication, leveraging their high mobility, flexibility, and visual communication capabilities. Ambient backscatter communication enables Internet of Things devices to transmit data by reflecting and modulating ambient radio waves, eliminating the need for additional wireless channels, and reducing energy consumption and cost for sensors. However, passive ambient backscatter communication has limitations such as limited range and poor communication quality. By utilizing UAVs as communication nodes, these limitations can be overcome, expanding the communication range and improving the quality of communication. Although some research has been conducted on combining UAVs and ambient backscatter, several challenges remain. One key challenge is the strong direct link interference in ambient backscatter under UAV conditions, which significantly affects communication quality. In this paper, we propose an intelligent backward and forward straight link interference cancellation algorithm based on NOMA decoding technique to enhance ambient backscatter communication quality under UAV conditions and extract more ambient energy for UAV energy supply. The paper includes theoretical derivation, algorithm description, and simulation analysis to validate the error bit rate of labeled information bits. The results demonstrate that the forward algorithm reduces the error bit rate by approximately 20% under low signal-to-noise ratio (SNR) conditions, while the backward algorithm reduces the error bit rate under high SNR conditions. The combination of the forward and backward algorithms reduces the error bit rate under both high and low SNR conditions. The proposed method contributes to improving the quality of ambient backscatter communication in UAV settings.

Abstract Nasopharyngeal (NP) swab is one of the most effective sampling devices for clinical specimens. However, commercial NP swabs often release samples through diluents, lowering analyte concentration and causing inaccurate detections. Here, we developed 3D-printed open-cell microlattice NP swabs with user-friendly high-efficiency controlled sample release (CR) mode. Compared with traditional NP swabs, our microlattice NP swabs show higher (~7–11 times) flexibility, larger (~2.3 times) and customizable release volume, higher (dozens to thousands of times) release concentration, high recovery efficiency (~100%), and the ability to quantify analyte levels. Our microlattice NP swabs have been thus demonstrated to improve the sensitivity and accuracy of antibody detection experiments using rapid detection kits. This study offers a promising approach to enhance sensitivity and accuracy in clinical specimen detections, and is beneficial to inspire the design of a wider range of biomedical devices based on 3D-printed microlattice metamaterials.

Abstract Scutellarin is widely distributed in Scutellaria baicalensis, family Labiatae, and Calendula officinalis, family Asteraceae, and belongs to flavonoids. Scutellarin has a wide range of pharmacological activities, it is widely used in the treatment of cerebral infarction, angina pectoris, cerebral thrombosis, coronary heart disease, and other diseases. It is a natural product with great research and development prospects. In recent years, with in-depth research, researchers have found that wild scutellarin also has good therapeutic effects in anti-tumor, anti-inflammatory, anti-oxidation, anti-virus, treatment of metabolic diseases, and protection of kidney. The cancer treatment involves glioma, breast cancer, lung cancer, renal cancer, colon cancer, and so on. In this paper, the sources, pharmacological effects, in vivo and in vitro models of scutellarin were summarized in recent years, and the current research status and future direction of scutellarin were analyzed. Graphical Abstract

Objective To explore the photodynamic treatment method and therapeutic effect of oral verrucous carcinoma and to provide a reference for the clinic. Methods This study follows the requirements of medical ethics. This paper summarized the photodynamic treatment of an oral verrucous carcinoma with a diameter of approximately 2.5 cm in the right buccal mucosa and retrospectively analyzed the characteristics and treatment of oral verrucous carcinoma and the photodynamic treatment of potential malignant lesions of the oral mucosa through a review of the literature. Results After four rounds of photodynamic therapy, the size of the right buccal lesion was significantly reduced. After 6 months of follow-up, the white verrucous hyperplasia of the right buccal mucosa had completely subsided, and there was no obvious scar formation. Three years after treatment, there was no recurrence of the lesion in the right buccal mucosa and no obvious scar formation in the treated area. The degree of mouth opening was 3 fingers, and there was no lymph node enlargement in the bilateral submandibular, submental or neck. The literature review shows that oral verrucous carcinoma is a rare subtype of squamous cell carcinoma with the characteristics and biological behaviors of slow growth, low malignancy, and rare metastasis. Surgery is the preferred treatment, but there are some limitations. Photodynamic therapy is a minimally invasive, repeatable treatment with mild adverse reactions. In recent years, photodynamic therapy has been gradually applied for the treatment of potential malignant disorders of the oral mucosa and early oral squamous cell carcinoma and has achieved positive results, but it has not been reported for the treatment of oral verrucous cancer. Conclusion Photodynamic therapy is a new option for nonsurgical resection of oral verrucous carcinoma.

With the extensive application of wood-based panels in the home decor industry, determining formaldehyde release form wood-based panels (FRWBP) is crucial for ensuring environmental air quality and human health. This article addresses the issues of insufficient monitoring of the testing stages for FRWBP and the difficulty in tracing the operation records of operator during determining FRWBP by the chamber method. It proposes a system for monitoring and analyzing the testing stages of FRWBP based on electrical monitoring. The system employs non-invasive sensing technology that does not interfere with normal testing process to collect real-time electrical usage data from the devices. The data is uploaded to an industrial computer for storage and processing. Statistical features of the electrical time series data are extracted using a sliding window approach and optimized with Principal Component Analysis (PCA). Subsequently, the binary tree support vector machine algorithm (BTSVM) optimized by k-means clustering algorithm is used to identify the detection states of the wood-based panels. Experimental results show that the system can achieve traceability of the formaldehyde detection stage records of artificial boards, and the designed algorithm model can also effectively identify the detection status of wood-based panels. The system and methods proposed in this paper have significant prospects for implementation in monitoring and traceability management within the testing industry.

Feature selection plays a significant role in machine learning and data mining, where the goal is to screen out the most representative and relevant subset of features from a large collection of features to improve the performance and generalization ability of the model. In this paper, a hybrid feature selection algorithm that combines a filter algorithm and an improved particle swarm optimization algorithm is proposed, that is, the Information Gain and Maximum Pearson Minimum Mutual Information improved Adaptive Particle Swarm Optimization algorithm (IGMPMMIAPSO). First, combined with the characteristics of the Pearson correlation coefficient and mutual information, a filter algorithm called Maximum Pearson Minimum Mutual Information (MPMMI) is proposed. The algorithm balances the relevance and redundancy between the features by adjusting two weight parameters ( $w_{p1}$ and $w_{p2}$ ). Second, Adaptive Adjustment of Control (AAC) is introduced to update the particle swarm optimization algorithm, so that the particle velocity has a higher searching ability, and the diversity of population position changes is increased. The improved algorithm was used as the wrapper algorithm. Simultaneously, the concepts of the No Continuous Change (NCC) times and collision distance values are proposed. According to these, the IGMPMMIAPSO algorithm is proposed by combining the filter algorithm and wrapper algorithm. To verify the performance of the proposed algorithm, we experimented with other state-of-the-art hybrid algorithms using eight datasets. The experimental results show that the classification accuracy of the proposed algorithm is at least 0.1% higher than that of the other five algorithms, and the feature subset length is shorter.

Abstract Helicotylenchus comprises a significant group of plant-parasitic nematodes that primarily feed on plant roots. This study focuses on the description of a newly discovered species, Helicotylenchus zenchengensis n. sp., from China. The distinguishing characteristic of this species, as observed under a microscope, is the absence of head annulation. The stylet, measuring between 23.8 and 29.3 μm, exhibits anteriorly flattened or indented stylet knobs. The elongated tail has a c value ranging from 15.8 to 22.6 and a c’ value between 1.9 and 2.4. It bears 15 to 18 tail annuli, presenting a conical shape with projections. The phasmids are located at the 4th to 10th body annulations posterior to the anus, while no males were observed. Three phylogenetic trees were constructed to determine the evolutionary relationships using the 18S rRNA, ITS, and 28S D2-D3 expansion segments of the newly discovered species and related Helicotylenchus sequences obtained from the database. Based on the ITS sequences, a phylogenetic tree revealed that H. zenchengensis n. sp. clustered with H. cuspicaudatus. However, it was distinguished from H. cuspicaudatus when examining the 18S and 28S rRNA sequences and morphological characteristics. Additionally, comprehensive and diagnostic tables for all known species of Helicotylenchus in China are provided for reference.

Abstract High synthesis temperatures and specific growth substrates are typically required to obtain crystalline or oriented inorganic functional thin films, posing a significant challenge for their utilization in large-scale, low-cost (opto-)electronic applications on conventional flexible substrates. Here, we explore a pulse irradiation synthesis (PIS) to prepare thermoelectric metal chalcogenide (e.g., Bi2Se3, SnSe2, and Bi2Te3) films on multiple polymeric substrates. The self-propagating combustion process enables PIS to achieve a synthesis temperature as low as 150 °C, with an ultrafast reaction completed within one second. Beyond the photothermoelectric (PTE) property, the thermal coupling between polymeric substrates and bismuth selenide films is also examined to enhance the PTE performance, resulting in a responsivity of 71.9 V/W and a response time of less than 50 ms at 1550 nm, surpassing most of its counterparts. This PIS platform offers a promising route for realizing flexible PTE or thermoelectric devices in an energy-, time-, and cost-efficient manner.

For the coil misalignment problem in the charging process of automatic guidance vehicles (AGVs), this paper proposes an optimization method for the bilateral LCC compensation network parameters based on quadruple-D quadrature (4DQ) coils. By introducing two coefficients $K_{\text {T}}$ and $K_{\text {f1}}$ , the compensation capacitors $C_{\text {T}}$ and $C_{\text {f1}}$ are optimized, achieving smaller output power fluctuations. Firstly, the capacitor values $C_{\text {T}}$ and $C_{\text {f1}}$ at resonance in the SS and PS equivalent circuit topology are obtained, meanwhile, the relationship between the output power $P_{\text {out}}$ and the coupling coefficient $k$ , represented by the coefficients $K_{\text {T}}$ and $K_{\text {f1}}$ , is obtained. Furthermore, with the transmission efficiency as the limiting condition, the output power fluctuation is effectively suppressed by adjusting $K_{\text {T}}$ and $K_{\text {f1}}$ . Finally, the experimental results show that after optimization the output power is 427.08W, and the transmission efficiency is 93.506% when the coupling coil are aligned, the system can still maintain a power output of at least 382.36W with a coil offset of 0-153mm in the X/Y axis directions, and the transmission efficiency is always above 89.472%. At the same time, the maximum deviation value $\Delta P_{{\text {abs}\_{}\text{max}}}$ decreased from 213.1W before optimization to 111.0W after optimization, a decrease of 47.91%, effectively suppressing the power fluctuation and improving anti-offset performance.

AIM: To investigate the characteristics of anterior segment structure in first-degree relatives of patients with primary angle-closure glaucoma(PACG).METHODS: A total of 48 first-degree relatives of PACG patients aged 40-60 who were treated in the Affiliated Eye Hospital of Nanchang University from September 2020 to October 2022 were selected as the observation group. Additionally, 40 cases(40 eyes)of healthy individuals without glaucoma and family history of glaucoma at the same age group were collected as the control group. They were divided into younger group(40-49 years old)and elder group(50-60 years old). All subjects were examined with ultrasound biomicroscopy(UBM)and were measured using camera measure software. The parameters mainly included anterior chamber depth(ACD), anterior chamber area(ACA), anterior chamber width(ACW), anterior segment depth(ASD), angle open distance(AOD500), trabecular iris angle(TIA), trabecular iris area(TISA500), lens vault(LV), iris curve(IC), iris thickness(IT500), scleral ciliary process angle(SCPA), and iris ciliary process distance(ICPD).RESULTS: ACD, ACA, AOD500, TISA500 and TIA in the observation group were lower than those of the control group, and LV and IC were higher than those of the control group(all P

In this study, a practical and comprehensive experimental technique has been proposed to investigate the interlayer interference characteristics in multilayer tight sandstone gas reservoirs with multi-pressure systems and different reserves. Firstly, single-layer depletion simulation experiments were conducted to measure the gas flow rate and gas extraction efficiency for each of the six layers. A series of physical simulation experiments were then conducted to monitor gas production and pressure variations in commingled multilayer production scenarios under various conditions. Finally, interlayer interference characteristics and gas extraction efficiencies and the main controlling factors were evaluated, analyzed, and identified. The interlayer pressure differential is found to be the primary factor dictating both interference and gas production, followed by initial gas production rates, and permeability variations in the order of positive significance. A higher interlayer pressure differential, a lower initial gas production rate, and a larger permeability variation result in an increase in interlayer interference and a reduction in gas production during commingled production. Increasing the number of commingled layers leads to an overall increase in gas production losses of 10.95% for two layers to 13.35% for four layers. Layers exhibiting small interlayer pressure difference are positively compatible for commingled production.

To reduce the hygroscopicity of betaine (BET), three co-crystals were synthesized: betaine-3,5-dihydroxybenzoic acid (BET-3,5-DHB), betaine-2,4-dihydroxybenzoic acid (BET-2,4-DHB), and betaine-3-hydroxybenzoic acid (BET-3-HDB). BET, commonly present in natural products, is used to treat homocysteine methyltransferase and has additional benefits such as hepatoprotective and neuroprotective properties. However, BET is extremely hygroscopic. Three cocrystals are acquired to address the problem. Comprehensive characterization, such as X-ray diffraction analysis, spectral analysis and thermal analysis, were conducted for co-crystals and BET. Based on the evaluation results for dynamic vapor sorption, the three co-crystals, especially BET-3-HDB, significantly reduce BET’s hygroscopicity. At 90% RH, the weight changes of BET-2,4-DHB (0.36%), BET-3,5-DHB (1.79%) and BET-3-HDB (0.32%) are 306.9, 61.7, and 345.3 times greater than those of the raw material BET, respectively. Hygroscopicity results from BET’s ability to easily create hydrogen bonding interactions with water molecules due to its carboxylate ions. Nevertheless, carboxylate ions establish hydrogen bonds with CCFs in co-crystals, lowering BET’s hygroscopicity and minimizing the likelihood of contact with water molecules. The contributions of contacts in the co-crystals are shown by Hirschfeld surface analysis as follows: H-H > O-H > H-O. Coulomb forces are dominant in the co-crystals by 3D energy frameworks.

Cordyceps militaris extract (CME) contains many bioactive compounds, mainly cordycepin (CPN). This study aimed to investigate the possible mechanisms underlying the amelioration of LPS-induced acute liver injury in piglets by CME or CPN supplementation using multi-omics analysis. Twenty-four weaned piglets were randomly distributed into 4 groups (n = 6): the control and LPS groups were fed basal diets; the CPN + LPS (CPN-LPS) and CME + LPS (CME-LPS) groups were fed the basal diets supplemented with CME or CPN. The results showed that CPN or CME supplementation significantly decreased the C-reactive protein level (p < 0.05) and improved liver tissue pathology to prevent acute liver injury after LPS treatment. Compared with LPS, the transcriptomic analysis indicated that CPN supplementation significantly downregulated cell adhesion molecules, while CME supplementation significantly downregulated inflammatory mediator regulation of TRP channels, complement and coagulation cascades and cytokine-cytokine receptor interaction. The metabolomic results showed that CPN or CME supplementation significantly reduced disease biomarker of bicyclo-prostaglandin E2, and increased levels of deoxyinosine and 3-hydroxyanthranilic acid (p < 0.05). The combined transcriptome and metabolome helped identify two metabolites PC 34:2 and PC 36:0, which may be associated with the restoration of liver cell morphology. In conclusion, CPN and CME could attenuate LPS-induced acute liver injury by regulating immune-related genes and metabolites. This study elucidates the potential protective mechanism of CPN or CME supplementation against acute liver injury.

IntroductionGlobal illegal trade in timbers is a major cause of the loss of tree species diversity. The Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) has been developed to combat the illegal international timber trade. Its implementation relies on accurate wood identification techniques for field screening. However, meeting the demand for timber field screening at the species level using the traditional wood identification method depending on wood anatomy is complicated, time-consuming, and challenging for enforcement officials who did not major in wood science.MethodsThis study constructed a CITES-28 macroscopic image dataset, including 9,437 original images of 279 xylarium wood specimens from 14 CITES-listed commonly traded tree species and 14 look-alike species. We evaluated a suitable wood image preprocessing method and developed a highly effective computer vision classification model, SE-ResNet, on the enhanced image dataset. The model incorporated attention mechanism modules [squeeze-and-excitation networks (SENet)] into a convolutional neural network (ResNet) to identify 28 wood species.ResultsThe results showed that the SE-ResNet model achieved a remarkable 99.65% accuracy. Additionally, image cropping and rotation were proven effective image preprocessing methods for data enhancement. This study also conducted real-world identification using images of new specimens from the timber market to test the model and achieved 82.3% accuracy.ConclusionThis study presents a convolutional neural network model coupled with the SENet module to discriminate CITES-listed species with their look-alikes and investigates a standard guideline for enhancing wood transverse image data, providing a practical computer vision method tool to protect endangered tree species and highlighting its substantial potential for CITES implementation.

ObjectiveInsufficient motivation among post-stroke survivors may be an important factor affecting their motor function recovery. This study seeks to investigate the relationship between motivation and functional recovery in stroke patients undergoing rehabilitation training.Materials and methods103 stroke patients with upper limb impairments were studied during their hospital stays. Assessments were done before and after rehabilitation training to measure motivation, emotional state, motor function, and independence in daily activities. Data analysis was conducted to examine the distribution of these factors among the participants. Pearson and Spearman correlation analyses were used to study the relationships between motivation, emotional state, and motor function. Patients were divided into high and low motivation groups based on the Rehabilitation Motivation Scale (RMS), and chi-square and rank-sum tests were used to compare functional differences before and after treatment among patients with varying levels of motivation.Results66 participants were found to have low motivation in the initial assessment of the RMS (64.08%). Consistency in motivation levels was observed among patients with high motivation (r = 0.648, P

Abstract Gastric cancer (GC) presents a formidable global health challenge, and conventional therapies face efficacy limitations. Ubiquitin‐specific protease 7 (USP7) plays pivotal roles in GC development, immune response, and chemo‐resistance, making it a promising target. Various USP7 inhibitors have shown selectivity and efficacy in preclinical studies. However, the mechanistic role of USP7 has not been fully elucidated, and currently, no USP7 inhibitors have been approved for clinical use. In this study, DHPO is identified as a potent USP7 inhibitor for GC treatment through in silico screening. DHPO demonstrates significant anti‐tumor activity in vitro, inhibiting cell viability and clonogenic ability, and preventing tumor migration and invasion. In vivo studies using orthotopic gastric tumor mouse models validate DHPO's efficacy in suppressing tumor growth and metastasis without significant toxicity. Mechanistically, DHPO inhibition triggers ferroptosis, evidenced by mitochondrial alterations, lipid Reactive Oxygen Species (ROS), Malondialdehyde (MDA) accumulation, and iron overload. Further investigations unveil USP7's regulation of Stearoyl‐CoA Desaturase (SCD) through deubiquitination, linking USP7 inhibition to SCD degradation and ferroptosis induction. Overall, this study identifies USP7 as a key player in ferroptosis of GC, elucidates DHPO's inhibitory mechanisms, and highlights its potential for GC treatment by inducing ferroptosis through SCD regulation.

ABSTRACTThe mechanisms underpinning the replication of genomic DNA have recently been challenged in Archaea. Indeed, the lack of origin of replication has no deleterious effect on growth, suggesting that replication initiation relies on homologous recombination. Recombination-dependent replication (RDR) appears to be based on the recombinase RadA, which is of absolute requirement when no initiation origins are detected. The origin of this flexibility in the initiation of replication and the extent to which it is used in nature are yet to be understood. Here, we followed the process of DNA replication throughout the growth stages of Thermococcus barophilus. We combined deep sequencing and genetics to elucidate the dynamics of oriC utilization according to growth phases. We discovered that in T. barophilus, the use of oriC diminishes from the lag to the middle of the log phase, and subsequently increases gradually upon entering the stationary phase. Although oriC demonstrates no indispensability, RadA does exhibit essentiality. Notably, a knockdown mutant strain provides confirmation of the pivotal role of RadA in RDR for the first time. Thus, we demonstrate the existence of a tight combination between oriC utilization and homologous recombination to initiate DNA replication along the growth phases. Overall, this study demonstrates how diverse physiological states can influence the initiation of DNA replication, offering insights into how environmental sensing might impact this fundamental mechanism of life.IMPORTANCEReplication of DNA is highly important in all organisms. It initiates at a specific locus called ori, which serves as the binding site for scaffold proteins—either Cdc6 or DnaA—depending on the domain of life. However, recent studies have shown that the Archaea, Haloferax volcanii and Thermococcus kodakarensis could subsist without ori. Recombination-dependent replication (RDR), via the recombinase RadA, is the mechanism that uses homologous recombination to initiate DNA replication. The extent to which ori’s use is necessary in natural growth remains to be characterized. In this study, using Thermococcus barophilus, we demonstrated that DNA replication initiation relies on both oriC and RDR throughout its physiological growth, each to varying degrees depending on the phase. Notably, a knockdown RadA mutant confirmed the prominent use of RDR during the log phase. Moreover, the study of ploidy in oriC and radA mutant strains showed that the number of chromosomes per cell is a critical proxy for ensuring proper growth and cell survival.

Abstract Bystander‐killing payloads can significantly overcome the tumor heterogeneity issue and enhance the clinical potential of antibody‐drug conjugates (ADC), but the rational design and identification of effective bystander warheads constrain the broader implementation of this strategy. Here, graph attention networks (GAT) are constructed for a rational bystander killing scoring model and ADC construction workflow for the first time. To generate efficient bystander‐killing payloads, this model is utilized for score‐directed exatecan derivatives design. Among them, Ed9, the most potent payload with satisfactory permeability and bioactivity, is further used to construct ADC. Through linker optimization and conjugation, novel ADCs are constructed that perform excellent anti‐tumor efficacy and bystander‐killing effect in vivo and in vitro. The optimal conjugate T‐VEd9 exhibited therapeutic efficacy superior to DS‐8201 against heterogeneous tumors. These results demonstrate that the effective scoring approach can pave the way for the discovery of novel ADC with promising bystander payloads to combat tumor heterogeneity.

Physiological processes that cause a negative growth response to high night temperatures (HNTs) were investigated in soybean. An HNT (28​°C) was established in a phytotron during the first (HL) and second (LH) halves of the reproductive stage and the entire (HH) reproductive stage, along with a continuously low (LL) night temperature (22​°C). Plant biomass was lower in HH than that in LL, whereas the harvest index was relatively stable. N accumulation in the plants tended to decline with HNT. The leaf area and leaf N concentration tended to be lower in HL and HH than in LL, suggesting an earlier onset of leaf senescence under HNT in the early reproductive stage. The light-saturated leaf photosynthetic rate was lower in HH than in LL during the late reproductive stage, associated with a low stomatal conductance and leaf photosynthetic rate per intercellular CO2 concentration. A slower rise in the leaf photosynthetic rate in the morning occurred likely because of the HNT, coinciding with the low leaf water potential at predawn and low leaf photosynthetic rate to intercellular CO2 concentration ratio. A moderately increasing gradient of night temperature from 21.7 to 23.9​°C was created in a mini-field in another experiment using a temperature gradient chamber, and in this experiment, crop growth and N dynamics were similar to those obtained in the phytotron study. These results suggest that the biomass growth of soybean is affected by HNT, particularly during the early reproductive stage.

Abstract Background The entomogenous fungus Beauveria bassiana is used as a biological insecticide worldwide, wild B. bassiana strains with high pathogenicity in the field play an important role in controlling insect pests via not only screening of highly virulent strains but also natural infection, but the pathogenicity degeneration of wild strains severely affected aforementioned effects. Previous studies have showed that multiple factors contributed to this phenomenon. It has been extensively proved that the mycovirus infection caused hypovirulence of phytopathogenic fungi, which has been used for plant disease biocontrol. However, it remains unknown whether the mycovirus epidemics is a key factor causing hypovirulence of B. bassiana naturally in the field. Methods Wild strains of B. bassiana were collected from different geographic locations in Jilin Province, China, to clarify the epidemic and diversity of the mycoviruses. A mycovirus Beauveria bassiana chrysovirus 2 (BbCV2) we have previously identified was employed to clarify its impact on the pathogenicity of host fungi B. bassiana against the larvae of insect pest Ostrinia furnacalis. The serological analysis was conducted by preparing polyclonal antibody against a BbCV2 coat protein, to determine whether it can dissociate outside the host fungal cells and subsequently infect new hosts. Transcriptome analysis was used to reveal the interactions between viruses and hosts. Results We surprisingly found that the mycovirus BbCV2 was prevalent in the field as a core virus in wild B. bassiana strains, without obvious genetic differentiation, this virus possessed efficient and stable horizontal and vertical transmission capabilities. The serological results showed that the virus could not only replicate within but also dissociate outside the host cells, and the purified virions could infect B. bassiana by co-incubation. The virus infection causes B. bassiana hypovirulence. Transcriptome analysis revealed decreased expression of genes related to insect epidermis penetration, hypha growth and toxin metabolism in B. bassiana caused by mycovirus infection. Conclusion Beauveria bassiana infected by hypovirulence-associated mycovirus can spread the virus to new host strains after infecting insects, and cause the virus epidemics in the field. The findings confirmed that mycovirus infection may be an important factor affecting the pathogenicity degradation of B. bassiana in the field.

Abstract The interplay of water resources with social-economy spheres involves a reciprocal feedback mechanism. With the acceleration of the construction process of modernized water networks in Hunan Province, investigating the adaptation status of the "Water-Social-Economy " composite system (WSE) is crucial for promoting sustainability. This study clarifies the connotation of the adaptability of WSE, and the quantitative analyses were conducted through coupling coordinative degree, harmonious development capacity, and the evolution of development lag types among the 14 cities of Hunan Province from 2005 to 2020. The results show that: (1) The development index of the water resources subsystem (WRS) showed a “downward-fluctuation-upward” trend, while the development index of the social-economy subsystem (SES) showed signs of great improvement, the former didn’t catch up with the latter. (2) The coupling coordination degree of WSE developed well, and reached the coordinative development stage by 2020, but the unbalanced spatial pattern between north to south and east to west still exists and is further intensified. (3) The development ability of WSE improved while the harmony ability reduced, and the development rate of WRS and SES hasn’t achieved dynamic synchronization. Finally, the policies and suggestions to improve the adaptability are put forward, which is of instructive significance for the sustainable development of water suitability.

Abstract Post-surgical treatments of the human throat often require continuous monitoring of diverse vital and muscle activities. However, wireless, continuous monitoring and analysis of these activities directly from the throat skin have not been developed. Here, we report the design and validation of a fully integrated standalone stretchable device platform that provides wireless measurements and machine learning-based analysis of diverse vibrations and muscle electrical activities from the throat. We demonstrate that the modified composite hydrogel with low contact impedance and reduced adhesion provides high-quality long-term monitoring of local muscle electrical signals. We show that the integrated triaxial broad-band accelerometer also measures large body movements and subtle physiological activities/vibrations. We find that the combined data processed by a 2D-like sequential feature extractor with fully connected neurons facilitates the classification of various motion/speech features at a high accuracy of over 90%, which adapts to the data with noise from motion artifacts or the data from new human subjects. The resulting standalone stretchable device with wireless monitoring and machine learning-based processing capabilities paves the way to design and apply wearable skin-interfaced systems for the remote monitoring and treatment evaluation of various diseases.

Abstract Seawater electrolysis is a viable method for producing hydrogen on a large scale and low-cost. However, the catalyst activity during the seawater splitting process will dramatically degrade as salt concentrations increasing. Herein, CoP is discovered that could reject chloride ions far from catalyst in electrolyte based on molecular dynamic simulation. Thus, a binder-free electrode is designed and constructed by in-situ growth of homogeneous CoP on rGO nanosheets wrapped around the surface of Ti fiber felt for seawater splitting. As expected, the as-obtained CoP/rGO@Ti electrode exhibits good catalytic activity and stability in alkaline electrolyte. Especially, benefitting from the highly effective repulsive Cl− intrinsic characteristic of CoP, the catalyst maintains good catalytic performance with saturated salt concentration, and the overpotential increasing is less than 28 mV at 10 mA cm−2 from 0 M to saturated NaCl in electrolyte. Furthermore, the catalyst for seawater splitting performs superior corrosion-resistance with a low solubility of 0.04%. This work sheds fresh light into the development of efficient HER catalysts for salinity tolerance hydrogen evolution.

Objective: This study aimed to enrich the functional lactic acid bacteria resource bank and to search for excellent starting strains of lactic acid bacteria with the antagonistic ability of Vibrio parahaemolyticus. Methods: Lactobacillus strains with broad-spectrum bacteriostatic potential were screened by Oxford cup bacteriostatic test, and their biological characteristics were discussed by growth and metabolic performance, gastrointestinal fluid tolerance, salt tolerance, antibiotic sensitivity and bacteriostatic spectrum. Results: Six strains of lactic acid bacteria were screened by using V. parahaemolyticus as indicator bacteria. They were classified into L. paracasei, L. fermentus and L. plantarum by morphological, physiological and biochemical identification and molecular biological identification. Among them, the bacteriostatic activity of L. paracasei A1 was the best, the total number of colonies within 24 hours exceeded 1×109 CFU/mL, and the pH value of fermentation broth was stable at about 4.1. After artificial simulated gastric juice treatment for 2 h, the survival rate was 54.61%. After artificial simulated intestinal juice treatment for 8 h, the survival rate still reached 45.46%. After 10% NaCl stress treatment for 24 h, the total number of viable bacteria was ＞ 1×105 CFU/mL. Moreover, the crude bacteriocin extract of L. paracasei A1 showed good antibacterial activity against 13 pathogenic bacteria, had broad-spectrum antibacterial potential, and no resistance to 8 common antibiotics was found. Conclusion: L. paracasei A1, which can inhibit V. parahaemolyticus and has excellent biological characteristics, was obtained.

High-temperature water vapor (H2O) and carbon dioxide (CO2 ) improved the yield and quality of shale oil during oil shale pyrolysis. Aiming to fill knowledge gaps regarding the kinetic mechanism of oil shale pyrolysis in different atmospheres, the pyrolysis behavior and kinetics of Jimusar (JM) oil shale with H2O, CO2 and N2 injections were fully studied in this paper. The results revealed that compared with the N2 injection, the presence of both H2O and CO2 increased the mass loss and mass loss rate, advanced the initial precipitation temperature as well as peak temperature and moved the pyrolysis zone to the low-temperature zone, indicating that both H2O and CO2 injections promoted the pyrolysis behavior of oil shale. The comprehensive release characteristic index of volatiles during oil shale pyrolysis at the heating rate of 20 °C/min with H2O and CO2 injections increased by 37.02% and 18.94%, respectively, which significantly improved pyrolysis reactivity; so, the effect of the H2O injection was higher than that of the CO2 injection. The average activation energy of Jimusar oil shale pyrolysis was as follows: the first stage < the second stage < the third stage. During oil shale kerogen pyrolysis (the second stage), the activation energies with N2 , CO2 and H2O injections exhibited an initial rising trend, then a decreasing trend followed by a constantly decreasing trend and a fluctuating trend with an increase in the conversion rate, respectively. The presence of H2O and CO2 changed the pyrolysis mechanism of oil shale kerogen from a first-order model to a diffusion model. The kinetic mechanism functions of oil shale pyrolysis with N2 , CO2 and H2O injections were f(α) = 1âα, f(α) = [âln(1âα)]â1, and f(α) = 1.5(1âα)2/3[1â(1âα)1/3]â1, respectively. The pyrolysis conversion curves of Jimusar oil shale with N2, CO2 and H2O injections obtained from the kinetic parameters were consistent with the experimental curves.

Abstract Background Conus, a highly diverse species of venomous predators, has attracted significant attention in neuroscience and new drug development due to their rich collection of neuroactive peptides called conotoxins. Recent advancements in transcriptome, proteome, and genome analyses have facilitated the identification of conotoxins within Conus’ venom glands, providing insights into the genetic features and evolutionary patterns of conotoxin genes. However, the underlying mechanism behind the extraordinary hypervariability of conotoxins remains largely unknown. Results We analyzed the transcriptomes of 34 Conus species, examining various tissues such as the venom duct, venom bulb, and salivary gland, leading to the identification of conotoxin genes. Genetic variation analysis revealed that a subset of these genes (15.78% of the total) in Conus species underwent positive selection (Ka/Ks > 1, p

Abstract Background Colorectal cancer (CRC) can develop through various pathogenetic pathways, and one of the primary pathways is high microsatellite instability (MSI-H)/deficient mismatch repair (dMMR). This study investigated the correlation between preoperative contrast-enhanced CT (CECT) and clinicopathologic characteristics of colorectal cancer (CRC) according to different mismatch repair (MMR) statuses. Methods From April 2021 to July 2022, a total of 281 CRC patients with preoperative CECT and available MMR status were enrolled from a single centre for this retrospective study. Preoperative CECT features and clinicopathologic characteristics were analysed. Univariate and multivariate logistic regression analyses were used for statistical analysis. A nomogram was established based on the multivariate logistic regression results. Preoperative and postoperative dynamic nomogram prediction models were established. The C-index, a calibration plot, and clinical applicability of the two models were evaluated, and internal validation was performed using three methods. Results In total, 249 patients were enrolled in the proficient mismatch repair (pMMR) group and 32 patients in the deficient mismatch repair (dMMR) group. In multivariate analysis, tumour location (right-hemi colon vs. left-hemi colon, odds ratio (OR) = 2.90, p = .036), the hypoattenuation-within-tumour ratio (HR) (HR > 2/3 vs. HR

Abstract Fibrous dolomite widely formed in Neoproterozoic marine sedimentary environments, but apparently disappeared in the Phanerozoic. Here, fibrous dolomite is recognised in a Miocene methane seep limestone (Marmorito, Italy) by synchrotron X-ray diffraction, length slow crystal optics and primary zonation under cathodoluminescence, which is unexpected. Low δ13C values and their negative correlation with MgCO3 contents indicate a formation driven by highly alkaline pore waters and catalysis of dissolved sulphide generated by sulphate-driven anaerobic oxidation of methane. Cementing cavities of reefal carbonate, Neoproterozoic fibrous dolomite might have formed under sulphate-reducing conditions like Quaternary reef microbialites. Since the cavities of Neoproterozoic reefs were restricted microenvironments, the formation of fibrous dolomite was possibly favoured by catalysis similar to its Miocene seep counterpart. Our findings reinforce the concept of penecontemporaneous dolomite formation by sulphide catalysis and contribute to our understanding of the environmental conditions of the Neoproterozoic.

As the societal demand for precision in industrial robot operations increases, calibration can enhance the end-effector positioning accuracy of robots. Sampling data optimization plays an important role in improving the calibration effect. In this study, a robot calibration sampling point optimization method based on improved robot observability metrics and a Binary Simulated Annealing Algorithm is proposed. Initially, a robot kinematic model based on the Product of Exponentials (POE) model and a generalized error model is established. By utilizing the least squares method, the ideal pose transformation relationship between the robot’s base coordinate system and the laser tracker measurement coordinate system is derived, resulting in an error calibration model based on spatial single points. An improved robot observability metric combined with the Binary Simulated Annealing Algorithm (BSAA) is introduced to optimize the selection of calibration sampling data. Finally, the robot’s parameter errors are obtained using a nonlinear least squares method. Experimental results demonstrate that the average end-effector positioning error of the robot after calibration can be reduced from 0.356 mm to 0.254 mm using this method.

Singlet fission (SF), as an effective way to break through the Shockley–Queisser limit, can dramatically improve energy conversion efficiency in solar cell areas. The formation, separation, and relaxation of triplet-pair excitons directly affect the triplet yield, especially triplet-pair separation; thus, how to enhance the triplet-pair separation rate becomes one of the key points to improve SF efficiency; the decay mechanism where the singlet state is converted into two triplet states is significant for the study of the SF mechanism. Herein, we employ ultrafast transient absorption spectroscopy to study the singlet-fission process of nano-amorphous 6, 13-bis(triisopropylsilylethynyl)-Pentacene (TIPS-pentacene) films in a diamond anvil cell (DAC). A kinetics model related to the structural geometric details, as well as an evaluation of the pressure manipulation impacts, is demonstrated based on the experimental results. The results indicate that pressure manipulation enhanced the triplet-pair separation rates of SF-based materials according to their structural micro-environmental improvement when compressed in DAC, while the triplet-exciton transportation lifetime is prolonged. This work shows that pressure may effectively optimize the structural disorder of SF materials, which were found to improve triplet-pair separation efficiency and potentially offer an effective way to further improve SF efficiency.

With the continuous development and construction of new power systems, using drones to inspect the condition of transmission line insulators has become an inevitable trend. To facilitate the deployment of drone hardware equipment, this paper proposes IDD-YOLO (Insulator Defect Detection-YOLO), a lightweight insulator defect detection model. Initially, the backbone network of IDD-YOLO employs GhostNet for feature extraction. However, due to the limited feature extraction capability of GhostNet, we designed a lightweight attention mechanism called LCSA (Lightweight Channel-Spatial Attention), which is combined with GhostNet to capture features more comprehensively. Secondly, the neck network of IDD-YOLO utilizes PANet for feature transformation and introduces GSConv and C3Ghost convolution modules to reduce redundant parameters and lighten the network. The head network employs the YOLO detection head, incorporating the EIOU loss function and Mish activation function to optimize the speed and accuracy of insulator defect detection. Finally, the model is optimized using TensorRT and deployed on the NVIDIA Jetson TX2 NX mobile platform to test the actual inference speed of the model. The experimental results demonstrate that the model exhibits outstanding performance on both the proprietary ID-2024 insulator defect dataset and the public SFID insulator dataset. After optimization with TensorRT, the actual inference speed of the IDD-YOLO model reached 20.83 frames per second (FPS), meeting the demands for accurate and real-time inspection of insulator defects by drones.

With the development of robotics and vision measurement technology, the use of robots with line laser scanners for 3D scanning and measurement of parts has become a mainstream trend in the field of industrial inspection. Traditional scanning and measuring robots mainly use the teach-in scanning method, which has unstable scanning quality and low scanning efficiency. In this paper, the adaptive sampling method for a free-form surface, which can realize the adaptive distribution of surface measurement points according to the curvature features of free-form surfaces, is proposed first. Then, integrated with the proposed adaptive sampling method, the automatic path planning method is proposed. This method consists of adaptive sampling, scanning attitude calculation based on a quaternion, scanning viewpoint planning based on viewable cones, and scan path generation based on bi-directional scanning. Based on the proposed automatic path planning method, the scanning and measuring robot can obtain complete 3D information of the surface to be measured with high measurement accuracy and efficiency. The performance index of the laser scanner can be fully reached.

With the continuous improvement of wind power penetration in the power system, the volatility and unpredictability of wind power generation have increased the burden of system frequency regulation. With its flexible control mode and fast power adjustment speed, energy storage has obvious advantages in participating in power grid frequency regulation. Therefore, this paper studies the control strategy of wind energy storage combined with primary frequency regulation and proposes a control method of wind energy storage combined with primary frequency regulation based on the operation state of wind turbines. This paper analyzes the reserve power and rotor reserve kinetic energy of wind turbines operating in different wind speed ranges, introduces the fan frequency regulation operation state coefficient to quantify the real-time frequency regulation ability of the unit, regards the fan and energy storage system as independent frequency regulation sources, and designs the control strategy of joint frequency regulation of wind and storage in different wind speed ranges. The energy storage system is employed to participate in frequency control in the low-wind-speed range, thereby addressing the “blind spot” issue of wind turbine unit frequency control alone. In the medium- and high-wind-speed ranges, the real-time complementary output of wind and energy storage power is achieved by assigning weights based on the frequency control operation status coefficient. Finally, the effectiveness of the joint frequency modulation control strategy of wind storage in low-, medium-, and high-wind-speed regions is verified in the simulation model.

Research on wildfires and social vulnerability has gained significant importance due to the increasing frequency and severity of wildfires around the world. This study investigates the dynamic changes in social vulnerability to wildfires over a decade in Idaho, USA, utilizing GIS-based tools and a quasi-experimental design. We assess the evolving nature of social vulnerability at a local scale, emphasizing both spatial and temporal dynamics. Initially, we identified social vulnerability trends in relation to varying levels of wildfire risk. The research then employs propensity score matching to contrast areas affected by wildfires in 2012 with similar non-affected regions, thereby quantifying the short-term shifts in social vulnerability post-wildfires. The results indicate that regions with a high wildfire risk may display elevated vulnerability, characterized by an increase in unemployment rates and a reduction in high-income households. These findings tentatively demonstrate the compounded effect of wildfires on already vulnerable populations, highlighting the critical need for targeted interventions. Ultimately, this study underscores the importance of integrating dynamic social vulnerability assessments into wildfire management and planning, aiming to enhance community resilience and equitable resource distribution in the face of escalating wildfire threats.

Background With the population aging, mental health of the middle-aged and elderly adults is of great concern, especially in middle-aged and elderly women. Compared with urban women, rural women are more likely to suffer from mental diseases due to their poorer health status, lower education level and backward living conditions, however, the accessibility of mental health services among them is low. Objective To understand the prevalence of depression among middle-aged and elderly women in rural China and analyze its influencing factors, in order to provide empirical evidence for improving the mental health of middle-aged and elderly women. Methods From May to July 2021, the follow-up data of the 2018 China Health and Retirement Longitudinal Study (CHARLS) was extracted, and rural women aged 45 years and above were selected as the study subjects (n=6 736) . The scores of the simplified version of the Center for Epidemiologic Studies Depression Scale (CES-D) were used to determine the depression status of rural middle-aged and elderly women. Chi-square tests and multivariate Logistic regression model were used to analyze the influencing factors of the occurence of depressive symptoms among rural middle-aged and elderly women (including individual characteristics, health behaviors, social participation and utilization of medical services utilization) . Results The CES-D score of 6 736 rural middle-aged and elderly women was (20.0±6.9) , 42.46% (2 860/6 736) of whom had depressive symptoms. The results of multivariate Logistic regression analysis showed that satisfication with health status〔OR (95%CI) =0.40 (0.36, 0.45) 〕, sleep duration ≥6 h〔OR (95%CI) =0.48 (0.43, 0.54) 〕, Internet use〔OR (95%CI) =0.63 (0.50, 0.80) 〕 and satisfication with life 〔OR (95%CI) =0.25 (0.21, 0.30) 〕 were correlated with lower risk of depression; hysical disability〔OR (95%CI) =1.41 (1.16, 1.71) 〕, suffering from chronic diseases〔OR (95%CI) =1.35 (1.21, 1.50) 〕, receiving outpatient services within 1 month〔OR (95%CI) =1.25 (1.09, 1.43) 〕 and hospitalization services within 1 year〔OR (95%CI) =1.31 (1.13, 1.52) 〕 were correlated with higher risk of depression. Conclusion Based on the results of this study, the depression status of middle-aged and elderly women in rural China is relatively severe and affected by individual characteristics, health behaviors, social participation, and the medical services utilization. It is recommended that governments and civil affairs departments at all levels pay close attention to the mental health of rural middle-aged and elderly women, especially through the intervention and prevention from multiple dimensions such as health promotion and education, medical service quality, and accessibility of information, in order to promote the construction of healthy villages and process of health aging in China.

The differences in the chemical composition of Morus nigra (M. nigra) extracts from four different extraction methods, ultrasound-assisted extraction with pure water (WU), pure water decoction extraction (WD), ultrasonic-assisted extraction with formic acid water (FAU), and pure water heat reflux extraction (WHR), were identified using ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS) technology.

The aim of this study is to explore the prognostic value of vascular invasion (VI) in hepatocellular carcinoma (HCC) by searching for competing endogenous RNAs (ceRNA) network and constructing a new prognostic model for HCC. The differentially expressed genes (DEGs) between HCC and normal tissues were identified from GEO and TCGA. StarBase and miRanda prediction tools were applied to construct a circRNA-miRNA-mRNA network. The DEGs between HCC with and without VI were also identified. Then, the hub genes were screened to build a prognostic risk score model through the method of least absolute shrinkage and selection operator. The prognostic ability of the model was assessed using the Kaplan−Meier method and Cox regression analysis. In result, there were 221 up-regulated and 47 down-regulated differentially expressed circRNAs (DEcircRNAs) in HCC compared with normal tissue. A circRNA-related ceRNA network was established, containing 11 DEcircRNAs, 12 DEmiRNAs, and 161 DEmRNAs. Meanwhile, another DEG analysis revealed 625 up-regulated and 123 down-regulated DEGs between HCC with and without VI, and then a protein–protein interaction (PPI) network was built based on 122 VI-related DEGs. From the intersection of DEGs within the PPI and ceRNA networks, we obtained seven hub genes to build a novel prognostic risk score model. HCC patients with high-risk scores had shorter survival time and presented more advanced T/N/M stages as well as VI occurrence. In conclusion a novel prognostic model based on seven VI-associated DEGs within a circRNA-related ceRNA network was constructed in this study, with great ability to predict the outcome of HCC patients.

Abstract Background Spinal cord stimulation (SCS) is a surgical technique used in patients with chronic intractable pain, and its effectiveness and safety have been validated by multiple studies. However, to maintain an optimal and steady long-term effect is still challenging. Here, we report a new management paradigm integrating smartphone application and remote programming. Chronic pain patients with SCS implants can monitor their pain status on the phone and change stimulation parameters accordingly. The PreMaSy study is a randomized controlled trial to evaluate the clinical effectiveness and safety of this precise management system. Methods Patients with chronic intractable pain will be screened for eligibility, and 82 participants are anticipated to be enrolled in this trial. After the electrode implantation, the stimulation effectiveness will be tested. Participants with a reduction of more than 50% in the visual analog scale (VAS) will receive implantation of an implantable pulse generator and randomized (1:1) into the experimental group or control group. All participants will be asked to take online follow-ups and complete assessments using a smartphone application. Daily pain characteristic assessments and monthly quality of life questionnaires are integrated into the App, and participants will be required to complete these assessments. The daily VAS for pain intensity will be monitored and a threshold will be set based on baseline VAS score. The interventional appointment will be scheduled once the threshold is reached. The primary outcome is the health condition and quality of life assessed by the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L). Utility values of EQ-5D-5L will be assessed at baseline and 1, 3, and 6 months post-operative. Discussion The PreMaSy study aims to evaluate the effectiveness and safety of a novel App-based, patient-centered, self-assessment management system for chronic intractable pain. A randomized controlled trial is designed to test the non-inferiority of this precise management system compared to the monthly online follow-ups. It is also expected to yield valuable experiences regarding precision medicine. Trial registration ClinicalTrials.gov NCT05761392. Registered on March 07, 2023.

Abstract With various potential health-promoting bioactivities, genistein has great prospects in treatment of a series of complex diseases and metabolic syndromes such as cancer, diabetes, cardiovascular diseases, menopausal symptoms and so on. However, poor solubility and unsatisfactory bioavailability seriously limits its clinical application and market development. To optimize the solubility and bioavailability of genistein, the cocrystal of genistein and piperazine was prepared by grinding assisted with solvent based on the concept of cocrystal engineering. Using a series of analytical techniques including single-crystal X-ray diffraction, powder X-ray diffraction, Fourier transform infrared spectroscopy, differential scanning calorimetry and thermogravimetric analysis, the cocrystal was characterized and confirmed. Then, structure analysis on the basis of theoretical calculation and a series of evaluation on the stability, dissolution and bioavailability were carried out. The results indicated that the cocrystal of genistein and piperazine improved the solubility and bioavailability of genistein. Compared with the previous studies on the cocrystal of genistein, this is a systematic and comprehensive investigation from the aspects of preparation, characterization, structural analysis, stability, solubility and bioavailability evaluation. As a simple, efficient and green approach, cocrystal engineering can pave a new path to optimize the pharmaceutical properties of natural products for successful drug formulation and delivery. Graphical Abstract

In the field of precision agriculture, diagnosing rice diseases from images remains challenging due to high error rates, multiple influencing factors, and unstable conditions. While machine learning and convolutional neural networks have shown promising results in identifying rice diseases, they were limited in their ability to explain the relationships among disease features. In this study, we proposed an improved rice disease classification method that combines a convolutional neural network (CNN) with a bidirectional gated recurrent unit (BiGRU). Specifically, we introduced a residual mechanism into the Inception module, expanded the module's depth, and integrated an improved Convolutional Block Attention Module (CBAM). We trained and tested the improved CNN and BiGRU, concatenated the outputs of the CNN and BiGRU modules, and passed them to the classification layer for recognition. Our experiments demonstrate that this approach achieves an accuracy of 98.21% in identifying four types of rice diseases, providing a reliable method for rice disease recognition research.