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Soil microorganisms play critical roles in ecosystem function. However, the relative impact of the potassium (K) fertilizer gradient on the microbial community in wheat-maize double-cropping systems remains unclear. In this long-term field experiment (2008–2019), we researched bacterial and fungal diversity, composition, and community assemblage in the soil along a K fertilizer gradient in the wheat season (K0, no K fertilizer; K1, 45 kg ha−1 K2O; K2, 90 kg ha−1 K2O; K3, 135 kg ha−1 K2O) and in the maize season (K0, no K fertilizer; K1, 150 kg ha−1 K2O; K2, 300 kg ha−1 K2O; K3, 450 kg ha−1 K2O) using bacterial 16S rRNA and fungal internally transcribed spacer (ITS) data. We observed that environmental variables, such as mean annual soil temperature (MAT) and precipitation, available K, ammonium, nitrate, and organic matter, impacted the soil bacterial and fungal communities, and their impacts varied with fertilizer treatments and crop species. Furthermore, the relative abundance of bacteria involved in soil nutrient transformation (phylum Actinobacteria and class Alphaproteobacteria) in the wheat season was significantly increased compared to the maize season, and the optimal K fertilizer dosage (K2 treatment) boosted the relative bacterial abundance of soil nutrient transformation (genus Lactobacillus) and soil denitrification (phylum Proteobacteria) bacteria in the wheat season. The abundance of the soil bacterial community promoting root growth and nutrient absorption (genus Herbaspirillum) in the maize season was improved compared to the wheat season, and the K2 treatment enhanced the bacterial abundance of soil nutrient transformation (genus MND1) and soil nitrogen cycling (genus Nitrospira) genera in the maize season. The results indicated that the bacterial and fungal communities in the double-cropping system exhibited variable sensitivities and assembly mechanisms along a K fertilizer gradient, and microhabitats explained the largest amount of the variation in crop yields, and improved wheat-maize yields by 11.2–22.6 and 9.2–23.8% with K addition, respectively. These modes are shaped contemporaneously by the different meteorological factors and soil nutrient changes in the K fertilizer gradients.

Background Carotid atherosclerosis (CAS) is often considered an early warning signal for cardiovascular diseases (CVD). The diagnostic technique of carotid artery Doppler ultrasonography has not been included in public health service programs, and the Framingham Risk Score (FRS) lacks accuracy in assessing CAS risk, hindering the identification of CAS by primary healthcare personnel. Currently, there is a lack of research on machine learning methods to identify CAS in the medium-high risk population assessed by FRS. Objective To construct a CAS risk prediction model for the medium-high risk population assessed by FRS using machine learning methods, compare its discriminative efficacy, select the optimal model, and assist primary healthcare personnel in identifying CAS more conveniently and accurately. Methods Using convenience sampling method, a total of 674 local residents from two townships in Liuzhou City, Guangxi Zhuang Autonomous Region, who met the inclusion criteria from 2019 to 2021 and 2023, were selected as the study subjects. Relevant information was collected, and biochemical indicators were measured in fasting blood and urine samples. FRS was used to assess the risk of CVD occurrence, and carotid ultrasound was used to diagnose CAS. Among the 517 subjects from 2019 to 2021, a random 8∶2 split was used to create a training set and a validation set. The training set was used to build Logistic regression, Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Gradient Boosting Decision Tree (GBDT) models, while the validation set was used for internal validation. The 157 subjects from 2023 served as the test set for external validation. Feature variables were selected using Lasso regression analysis, and discriminative efficacy was evaluated using sensitivity, specificity, accuracy, F1 score, and area under curve (AUC) value. External validation assessed the generalization ability of the optimal model using AUC value, and the Shapley Additive exPlanation (SHAP) method explored the important variables influencing the optimal model's identification of CAS. Results Lasso regression analysis identified 15 feature variables: age, BMI, systolic blood pressure (SBP), smoking, drinking, hypertension, total cholesterol, high density lipoprotein cholesterol, C-reactive protein (CRP), fasting plasma glucose, apolipoprotein B (ApoB), lipoprotein a (LPA), aspartate aminotransferase (AST), AST/ alanine aminotransferase, urinary microalbumin creatinine ratio. The constructed Logistic regression, RF, SVM, XGBoost, and GBDT models exhibited high AUC values, with the GBDT model showing the best discriminative performance. Its sensitivity, specificity, accuracy, F1 score, and AUC value were 0.755 1, 0.836 4, 0.798 1, 0.778 9, and 0.834 9, respectively, and the external validation AUC value was 0.794 0. The SHAP method revealed that age, SBP, CRP, LPA, and ApoB were the top five factors influencing the GBDT model's identification of CAS. Conclusion Logistic regression, RF, SVM, XGBoost, and GBDT models for identifying CAS based on machine learning all demonstrated high discriminative performance, with the GBDT model exhibiting the best comprehensive discriminative efficacy and strong generalization ability.

Automatic modulation recognition (AMR) stands as a pivotal operation within industrial cognitive radio systems. State-of-the-art real-valued convolutional neural networks (CNNs) have innovated modulation recognition but view complex signal components as separate real inputs, impairing signal phase integrity and model interpretability. This paper presents an innovative AMR method known as the CVCNN-LSTM. Our study aims to leverage CNNs in conjunction with a long short-term memory network (LSTM) to harness the strengths of both networks while mitigating their weaknesses. This approach enhances the learning of original I/Q signal features, thus improving recognition performance. The proposed network is composed of multiple LFLBs and an LSTM layer. Each LFLBs is primarily composed of a convolutional layer and an average pooling layer, which play a key role in enabling local correlation learning and hierarchical correlation extraction. Recognizing that I/Q data inherently possesses a complex-valued structure, we advocate using end-to-end complex-valued CNN and complex-valued LSTM instead of dual-channel real-valued networks for modulation recognition. We conduct experiments to evaluate complex-valued networks and demonstrate that our method surpasses current state-of-the-art approaches in the AMR field.

Abstract Background The purpose of this network meta-analysis was to assess the impact of different protective ventilatory strategies on postoperative pulmonary complications (PPCs). Methods Several databases were searched for randomized controlled trials (RCTs) that were published before October 2023 in a network meta-analysis. We assessed the effect of different lung-protective ventilation strategies on the incidence of PPCs using Bayesian network meta-analysis. Results We included 58 studies (11610 patients) in this meta-analysis. The network meta-analysis showed that low tidal volumes (LTVs) combined with iPEEP and recruitment manoeuvres (RM) was associated with significantly lower incidence of PPCs [HTVs: OR = 0.38, 95%CrI (0.19, 0.75), LTVs: OR = 0.33, 95%CrI (0.12, 0.82)], postoperative atelectasis[HTVs: OR = 0.2, 95%CrI (0.08, 0.48), LTVs: OR = 0.47, 95%CrI (0.11, 0.93)], and pneumonia[HTVs: OR = 0.22, 95%CrI (0.09, 0.48), LTVs: OR = 0.27, 95%CrI (0.08,0.89)] than was High tidal volumes (HTVs) or LTVs. LTVs combined with medium-to-high PEEP and RM were associated with significantly lower incidence of postoperative atelectasis, and pneumonia. Conclusion LTVs combined with iPEEP and RM decreased the incidence of PPCs, postoperative atelectasis, and pneumonia in noncardiac surgery patients. Individual PEEP-guided ventilation was the optimal lung protection ventilation strategy. The quality of evidence is moderate. Trial registration PROSPERO identifier CRD42023399485.

Abstract Background Baryscapus dioryctriae (Chalcidodea: Eulophidae) is a parasitic wasp that parasitizes the pupae of many Pyralidae members and has been used as a biological control agent against Dioryctria pests of pinecones. Results This B. dioryctriae assembly has a genome size of 485.5 Mb with a contig N50 of 2.17 Mb, and scaffolds were assembled onto six chromosomes using Hi-C analysis, significantly increasing the scaffold N50 to 91.17 Mb, with more than 96.13% of the assembled bases located on chromosomes, and an analysis revealed that 94.73% of the BUSCO gene set. A total of 54.82% (279.27 Mb) of the assembly was composed of repetitive sequences and 24,778 protein-coding genes were identified. Comparative genomic analysis demonstrated that the chemosensory perception, genetic material synthesis, and immune response pathways were primarily enriched in the expanded genes. Moreover, the functional characteristics of an odorant-binding protein (BdioOBP45) with ovipositor-biased expression identified from the expanded olfactory gene families were investigated by the fluorescence competitive binding and RNAi assays, revealing that BdioOBP45 primarily binds to the D. abietella-induced volatile compounds, suggesting that this expanded OBP is likely involved in locating female wasp hosts and highlighting a direction for future research. Conclusions Taken together, this work not only provides new genomic sequences for the Hymenoptera systematics, but also the high-quality chromosome-level genome of B. dioryctriae offers a valuable foundation for studying the molecular, evolutionary, and parasitic processes of parasitic wasps.

Abstract Background Alfalfa (Medicago sativa L.) is an essential leguminous forage with high nutrition and strong adaptability. The TIFY family is a plant-specific transcription factor identified in many plants. However, few reports have been reported on the phylogenetic analysis and gene expression profiling of TIFY family genes in alfalfa. Result A total of 84 TIFY genes belonging to 4 categories were identified in alfalfa, including 58 MsJAZs, 18 MsZMLs, 4 MsTIFYs and 4 MsPPDs, respectively. qRT-PCR data from 8 genes in different tissues revealed that most MsTIFY genes were highly expressed in roots. The expression of MsTIFY14 was up-regulated after different times in both thrips-resistant and susceptible alfalfa after thrips feeding, and the expression of the remaining MsTIFYs had a strong correlation with the time of thrips feeding. Different abiotic stresses, including drought, salt, and cold, could induce or inhibit the expression of MsTIFY genes to varying degrees. In addition, the eight genes were all significantly up-regulated by JA and/or SA. Interestingly, MsTIFY77 was induced considerably by all the biotic, abiotic, or plant hormones (JA or SA) except ABA. Conclusion Our study identified members of the TIFY gene family in alfalfa and analyzed their structures and possible functions. It laid the foundation for further research on the molecular functions of TIFYs in alfalfa.

ABSTRACT: Salmonella is a major cause of foodborne diseases worldwide. Conventional rapid assays for detecting Salmonella in real samples often encounter severe matrix interference or detect a limited number of species of a genus, resulting in inaccurate detection. In this study, we developed a method that combined phage-based magnetic capture with real-time recombinase polymerase amplification (RPA) for the rapid, highly sensitive, and specific detection of Salmonella in milk with an ultra-low detection limit. The Felix O-1 phage-conjugated magnetic beads (O-1 pMBs) synthesized in this method showed excellent capture ability for Salmonella spp. and ideal specificity for non-Salmonella strains. After O-1 pMBs-based magnetic separation, the limit of detection of the real-time RPA assay was 50 cfu/mL in milk samples, which was significantly increased by a magnitude of 3 to 4 orders. The method exhibited a high sensitivity (compatibility) of 100% (14/14) for all tested Salmonella serotype strains and an ideal specificity (exclusivity) of 100% (7/7) for the tested non-Salmonella strains. The entire detection process, including Salmonella capture, DNA extraction, and real-time RPA detection, was completed within 1.5 h. Furthermore, milk samples spiked with 10 cfu/25 mL of Salmonella were detected positive after being cultured in buffered peptone water for only 3 h. Therefore, the proposed method could be an alternative for the rapid and accurate detection of Salmonella.

Ammonia is gaining increasing attention as a green alternative fuel for achieving large-scale carbon emission reduction. Despite its potential technical prospects, the harsh ignition conditions and slow flame propagation speed of ammonia pose significant challenges to its application in engines. Non-equilibrium plasma has been identified as a promising method, but current research on plasma-enhanced ammonia combustion is limited and primarily focuses on ignition characteristics revealed by kinetic models. In this study, low-temperature and low-pressure chemistry in plasma-assisted ammonia oxidative pyrolysis is investigated by integrated studies of steady-state GC measurements and mathematical simulation. The detailed kinetic mechanism of NH3 decomposition in plasma-driven Ar/NH3 and Ar/NH3/O2 mixtures has been developed. The numerical model has good agreements with the experimental measurements in NH3/O2 consumption and N2/H2 generation, which demonstrates the rationality of modelling. Based on the modelling results, species density profiles, path flux and sensitivity analysis for the key plasma-produced species such as NH2, NH, H2, OH, H, O, O(1D), O2(a1Δg), O2(b1Σg+), Ar∗, H−, Ar+, NH3+, O2− in the discharge and afterglow are analyzed in detail to illustrate the effectiveness of the active species on NH3 excitation and decomposition at low temperature and relatively higher E/N values. The results revealed that NH2, NH, H as well as H2 are primarily generated through the electron collision reactions e + NH3 → e + NH2 + H, e + NH3 → e + NH + H2 and the excited-argon collision reaction Ar∗ + NH3 + H → Ar + NH2 + 2H, which will then react with highly reactive oxidative species such as O2∗, O∗, O, OH, and O2 to produce stable products of NOx and H2O. NH3 → NH is found a specific pathway for NH3 consumption with plasma assistance, which further highlights the enhanced kinetic effects.

Numerical models serve as an essential tool to investigate the causes and effects of Arctic sea ice changes. Evaluating the simulation capabilities of the most recent CMIP6 models in sea ice volume flux provides references for model applications and improvements. Meanwhile, reliable long-term simulation results of the ice volume flux contribute to a deeper understanding of the sea ice response to global climate change. In this study, the sea ice volume flux through six Arctic gateways over the past four decades (1979–2014) were estimated in combination of satellite observations of sea ice concentration (SIC) and sea ice motion (SIM) as well as the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) reanalysis sea ice thickness (SIT) data. The simulation capability of 17 CMIP6 historical models for the volume flux through Fram Strait were quantitatively assessed. Sea ice volume flux simulated from the ensemble mean of 17 CMIP6 models demonstrates better performance than that from the individual model, yet IPSL-CM6A-LR and EC-Earth3-Veg-LR outperform the ensemble mean in the annual volume flux, with Taylor scores of 0.86 and 0.50, respectively. CMIP6 models display relatively robust capability in simulating the seasonal variations of volume flux. Among them, CESM2-WACCM performs the best, with a correlation coefficient of 0.96 and a Taylor score of 0.88. Conversely, NESM3 demonstrates the largest deviation from the observation/reanalysis data, with the lowest Taylor score of 0.16. The variability of sea ice volume flux is primarily influenced by SIM and SIT, followed by SIC. The extreme large sea ice export through Fram Strait is linked to the occurrence of anomalously low air temperatures, which in turn promote increased SIC and SIT in the corresponding region. Moreover, the intensified activity of Arctic cyclones and Arctic dipole anomaly could boost the southward sea ice velocity through Fram Strait, which further enhance the sea ice outflow.

With characteristics and advantages of functional composite materials, they are commendably adopted in numerous fields especially in oxygen electrocatalysis, which is due to the significant synergies between various components. Herein, a novel bifunctional oxygen electrocatalyst (Co-CNT@COF-Pyr) has been synthesized through in-situ growth of covalent organic frameworks (COFs) layers on the outer surface of highly conductive carbon nanotubes (CNTs) followed by coordination with Co(Ⅱ). For electrocatalytic OER, Co-CNT@COF-Pyr reveals a low overpotential (438 ​mV) in alkaline electrolyte (1.0 ​M aqueous solution of KOH) with a current density of 10 ​mA ​cm−2, which is comparable to most discovered COF-based catalysts. For electrocatalytic ORR, Co-CNT@COF-Pyr exhibits a low H2O2 yield range (9.0 ​%–10.1 ​%) and a reaction pathway close to 4e− (n ​= ​3.82–3.80) in alkaline electrolyte (0.1 ​M aqueous solution of KOH) within the test potential range of 0.1–0.6 ​V vs. RHE, which is superior to most reported COF-based catalysts. Hence, this research could not only offer an innovative insight into the construction of composites, but also facilitate the practical application of renewable fuel cells, closed water cycle, and rechargeable metal-air batteries.

Abstract Cracks are a common problem in concrete surfaces. With the continuous optimization of machine vision-based inspection systems, effective crack detection and recognition is the core of the entire system. In this study, support vector machine (SVM) was used to distinguish cracks from other regions. To complete the recognition system of the SVM, a framework consisting of an image processing and recognition model was proposed. An algorithm combining the Prewitt operator with the Otsu threshold was proposed for image segmentation. The binary image processed by the new algorithm combined with mathematical morphology can result in a more complete crack zone and fewer interference regions. After the initial parameter extraction, most of the impurity areas were screened by preliminary discrimination, removing 99% of the impurities. This processing step ensured the balance and effectiveness of the samples. To establish an automatic identification model based on SVM with a radial basis function, compactness, occupancy rate, and length–width ratio were selected as input parameters after comparing these three features with all six features of the crack. The recognition accuracy of this system reaches 97.14%, demonstrating that the proposed method is effective and satisfies practical requirements.

Abstract The current research looked at how to use the Internet of Things (IoT) to create a vital sign health monitoring system. Eight indications are employed to get critical patient information. Therefore, the number of nodes of the IoT embedded in the human body is 8, which have been worked on in different places of the body. Among the 8 nodes, node number 1 is located in the center of the grid (the center of the human body). The number of rounds is 9000 and the nodes are adopted with the initial energy of the nodes of 0.5 J and the radio range of 10 m. MATLAB software was used to simulate the WBAN network, which consists of IoT sensors embedded in the human body. The eight-item health assessment tool takes the following into account: pulse rate, blood pressure (mm Hg), serum cholesterol (mg/dl), temperature (°C), exercise-induced angina, and exercise-induced ST-wave depression, major blood vessels are counted using a medical procedure called endoscopy that involves examining the alveoli, which are small air sacs in the lungs where gas exchange occurs. We compared the number of major vessels at rest with the maximal heart rate during activity. The sensors were responsible for sending this data to the health center (base station). The data collected from the installation of these 8 sensors on 303 patients were collected and evaluated by machine learning method using MLP neural network method. Finally, it can be claimed that the present study has provided an automated method of determining the health of people using the IoT in a way that provides a state of health with an accuracy of over 99% and can be used in medical centers.

Abstract To achieve high power conversion efficiency in perovskite/silicon tandem solar cells, it is necessary to develop a promising wide-bandgap perovskite absorber and processing techniques in relevance. To date, the performance of devices based on wide-bandgap perovskite is still limited mainly by carrier recombination at their electron extraction interface. Here, we demonstrate assembling a binary two-dimensional perovskite by both alternating-cation-interlayer phase and Ruddlesden−Popper phase to passivate perovskite/C60 interface. The binary two-dimensional strategy takes effects not only at the interface but also in the bulk, which enables efficient charge transport in a wide-bandgap perovskite solar cell with a stabilized efficiency of 20.79% (1 cm2). Based on this absorber, a monolithic perovskite/silicon tandem solar cell is fabricated with a steady-state efficiency of 30.65% assessed by a third party. Moreover, the tandem devices retain 96% of their initial efficiency after 527 h of operation under full spectral continuous illumination, and 98% after 1000 h of damp-heat testing (85 °C with 85% relative humidity).

Abstract Background Focal cortical dysplasia (FCD) is the most common epileptogenic developmental malformation. The diagnosis of FCD is challenging. We generated a radiomics nomogram based on multiparametric magnetic resonance imaging (MRI) to diagnose FCD and identify laterality early. Methods Forty-three patients treated between July 2017 and May 2022 with histopathologically confirmed FCD were retrospectively enrolled. The contralateral unaffected hemispheres were included as the control group. Therefore, 86 ROIs were finally included. Using January 2021 as the time cutoff, those admitted after January 2021 were included in the hold-out set (n = 20). The remaining patients were separated randomly (8:2 ratio) into training (n = 55) and validation (n = 11) sets. All preoperative and postoperative MR images, including T1-weighted (T1w), T2-weighted (T2w), fluid-attenuated inversion recovery (FLAIR), and combined (T1w + T2w + FLAIR) images, were included. The least absolute shrinkage and selection operator (LASSO) was used to select features. Multivariable logistic regression analysis was used to develop the diagnosis model. The performance of the radiomic nomogram was evaluated with an area under the curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration and clinical utility. Results The model-based radiomics features that were selected from combined sequences (T1w + T2w + FLAIR) had the highest performances in all models and showed better diagnostic performance than inexperienced radiologists in the training (AUCs: 0.847 VS. 0.664, p = 0.008), validation (AUC: 0.857 VS. 0.521, p = 0.155), and hold-out sets (AUCs: 0.828 VS. 0.571, p = 0.080). The positive values of NRI (0.402, 0.607, 0.424) and IDI (0.158, 0.264, 0.264) in the three sets indicated that the diagnostic performance of Model-Combined improved significantly. The radiomics nomogram fit well in calibration curves (p > 0.05), and decision curve analysis further confirmed the clinical usefulness of the nomogram. Additionally, the contrast (the radiomics feature) of the FCD lesions not only played a crucial role in the classifier but also had a significant correlation (r = -0.319, p

Abstract Background Vitamin D deficiency, a common occurrence among pregnant women, is an emerging public health concern worldwide. According to research, prenatal vitamin D deficiency is associated with various complications. This study assessed the vitamin D status of pregnant women in Yanbian, Jilin Province, as well as the correlation and predictive value of their vitamin D levels in relation to gestational length (weeks) and fetal weight, aiming to provide a basis for clinical diagnosis and treatment. Methods We conducted a population-based retrospective study involving 510 pregnant women from August 2019 to October 2022. Blood samples were collected at 16–20 weeks of gestation for the detection of serum vitamin D levels. Statistical analyses were performed using SPSS 28.0 and R 4.1.0 software. Multifactorial logistic regression analysis was employed to establish whether each variable was a risk factor for deliveries at ≤ 38 gestational weeks and low fetal weight. These results were used to construct a risk prediction model, and the model’s predictive efficacy was evaluated. Results or differences with p

Abstract Background Persistent infection with high-risk human papillomavirus (HR-HPV) plays a key role in the onset of cervical cancer. This study was designed to examine the epidemiological trends and genotype distribution of HPV from 2014 to 2023 in the plateau region of Southwest China. Methods The findings could offer valuable insights for clinical screening of cervical cancer and the formulation of HPV vaccination policies. This retrospective study analyzed 66,000 women who received HPV-DNA testing at the First People’s Hospital of Qujing, Yunnan, China, between 2014 and 2023. The cohort consisted of 33,512 outpatients, 3,816 inpatients, and 28,672 individuals undergoing health examinations. Cervical cells were collected for DNA extraction, and PCR amplification along with Luminex xMAP technology were used to detect 27 HPV genotypes. The data analysis was conducted using GraphPad Prism and IBM SPSS Statistics 27 software. Results The overall HPV infection rate at the First People’s Hospital of Qujing declined from 24.92% in 2014 to 16.29% in 2023, averaging 16.02%. Specific infection rates were 18.50% among outpatients, 12.97% among inpatients, and 13.53% for health examination attendees. The predominant high-risk HPV genotypes identified were HPV52 (2.61%), HPV16 (2.06%), HPV58 (1.81%), HPV53 (1.55%), and HPV39 (1.09%). Meanwhile, the most frequent low-risk HPV genotypes were HPV6 (1.30%), HPV61 (1.21%), and HPV11 (0.85%). In HPV-positive cases, the distribution of single, double, triple, and quadruple or more infections were 79.90%, 15.17%, 3.59%, and 1.33%, respectively. The proportions of pure LR-HPV, pure HR-HPV, and mixed infections were 22.16%, 67.82%, and 10.02%, respectively. Age-specific analysis revealed a bimodal distribution of HPV infection, with the infection rate rapidly decreasing from 44.02% in the ≤ 19 age group to 19.55% in the 20–29 age group and 13.84% in the 30–39 age group, followed by a gradual increase to 14.64% in the 40–49 age group, 16.65% in the 50–59 age group, and 22.98% in the ≥ 60 age group. The coverage rates of the three available vaccines are all below 50%. The results of this study indicated a declining trend in HPV prevalence in the plateau region of Southwest China over the period from 2014 to 2023, especially in the reduction of genotypes targeted by vaccines. Conclusion There were significant variations in the genotypes prevalent among different age groups, years, and patient sources within the same region. The underwhelming vaccination rates emphasize the critical need for developing either a multivalent vaccine or a personalized vaccine that targets the HPV genotypes common in the Chinese population. Furthermore, vaccinating adolescents to curb HPV infection and ensuring regular cervical cancer screenings for postmenopausal women are crucial steps.

Objective: The present study aims to examine whether secondhand smoke exposure (SHSE) in university students can affect three indices of self-satisfaction related to depression as indiced by appearance, weight, and freedom of life choice. Participants: We collected data from 740 nonsmoking students in the summer of 2018, of which 57.84% were exposed to secondhand smoke. Methods: Depressive symptoms, SHSE, smoking status, weight satisfaction, appearance satisfaction, and freedom of life choice were self-reported via a questionnaire. Results: The generalized linear analyses revealed that SHSE was linked to lower scores of perceived freedom of life choice but not significantly associated with weight nor appearance satisfaction. The mediation analyses indicated that perceived freedom of life choice fully mediated the association between SHSE and depressive symptoms. Conclusions: These findings shed light on the importance of SHSE and its effects on mental health in university students. Preventive strategies should therefore locally target university campuses.

This study was performed in order to investigate the impact of steaming and boiling on the color, free and ester-type astaxanthin contents and in vitro antioxidant activity of different parts of crayfish. The results demonstrated that both cooking treatments had significant effects on the astaxanthin contents, color, and antioxidant activity of the different parts of crayfish. The astaxanthin contents of all crayfish parts increased initially and then declined with cooking time. Fresh crayfish tail shells were found to contain free astaxanthin and five astaxanthin monoesters. Free astaxanthin and one astaxanthin monoester were found in boiled crayfish tail shells, suggesting that boiling could promote the hydrolysis of esterified astaxanthin and the consequent generation of 98% free astaxanthin. With cooking time increasing, the L* value of crayfish increased slowly, and the a* value initially increased and later decreased, while the W value showed no significant change. Moreover, the a* value was strongly correlated with the astaxanthin content (r > 0.4). Both hydroxyl and 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging capacity increased first and subsequently declined. All parts of crayfish maintained high scavenging capacity against 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) cation radicals. For all parts of steamed crayfish, astaxanthin contents showed a strong correlation with DPPH radical scavenging capacity (r > 0.9), but had a significant positive correlation with hydroxyl radical scavenging capacity for both claws and meat (P 0.9, P < 0.05).

Abstract Objectives To compare color Doppler ultrasound and contrast-enhanced ultrasound (CEUS) in evaluating vascular invasion in pancreatic ductal adenocarcinoma (PDAC). Materials and methods This retrospective study included 210 patients with PDAC who were evaluated by color Doppler ultrasound, CEUS, and contrast-enhanced computed tomography (CECT) at our institution between January 2017 and December 2020. Pathologic results were used as the gold standard in patients who underwent surgical and intraoperative exploration. For nonsurgical patients, CECT results were used as the reference standard. The vessels evaluated included those in the peripancreatic arterial system and venous system. The diagnostic performances of color Doppler ultrasound and CEUS for vascular invasion were compared. Results In 51 patients who underwent surgery and intraoperative exploration, color Doppler ultrasound and CEUS differed only in assessing venous system invasion in patients with PDAC of the pancreatic body and tail, with the former being superior to the latter. In 159 nonsurgical patients, there was no difference between CEUS and color Doppler ultrasound in assessing superior mesenteric arteriovenous invasion. CEUS was superior to color Doppler ultrasound in evaluating the celiac artery and its branches, with an accuracy of up to 97.8% for some vessels. Color Doppler ultrasound was ideal for evaluating the splenic and portal veins. Conclusion CEUS is more suitable for the evaluation of peripancreatic arteries than color Doppler. CEUS combined with color Doppler ultrasound can be used as a potential supplement to CECT and is also expected to be used to evaluate vascular invasion of PDAC after chemotherapy. Critical relevance statement Contrast-enhanced US and color Doppler in the assessment of vascular invasion in pancreatic ductal adenocarcinoma have their respective advantages, through standardized ultrasound processes are expected to improve the efficiency of inspection. Key Points Contrast-enhanced US has unique advantages in assessing pancreatic ductal adenocarcinoma invasion of the celiac artery. Doppler imaging is of high value in assessing venous system invasion. Standardization of ultrasound imaging procedures for pancreatic ductal adenocarcinoma is expected to improve efficiency. Graphical Abstract

Abstract Host defense peptide (HDP)-mimicking polymers are promising therapeutic alternatives to antibiotics and have large-scale untapped potential. Artificial intelligence (AI) exhibits promising performance on large-scale chemical-content design, however, existing AI methods face difficulties on scarcity data in each family of HDP-mimicking polymers (105), and multi-constraints on properties and structures when exploring high-dimensional polymer space. Herein, we develop a universal AI-guided few-shot inverse design framework by designing multi-modal representations to enrich polymer information for predictions and creating a graph grammar distillation for chemical space restriction to improve the efficiency of multi-constrained polymer generation with reinforcement learning. Exampled with HDP-mimicking β-amino acid polymers, we successfully simulate predictions of over 105 polymers and identify 83 optimal polymers. Furthermore, we synthesize an optimal polymer DM0.8 iPen0.2 and find that this polymer exhibits broad-spectrum and potent antibacterial activity against multiple clinically isolated antibiotic-resistant pathogens, validating the effectiveness of AI-guided design strategy.

Abstract Background The feasibility of percutaneous intramyocardial septal radiofrequency ablation (PIMSRA) for the treatment of hypertrophic obstructive cardiomyopathy (HOCM) has been previously reported. However, limited investigation has been conducted regarding the complications associated with this procedure. Objective This study aims to analyze the risk factors affecting the occurrence of complications during PIMSRA, such as pericardial effusion, ventricular premature beats, and interventricular septal perforation. In this study, the optimal cut-off values for these risk factors are also explored, and corresponding strategies for prevention are proposed. Methods A total of 101 patients diagnosed with HOCM who underwent the PIMSRA procedure from 2021 to 2022 were included in this retrospective analysis. Patients were classified into subgroups with or without complications based on procedural records. Univariate and multivariate regression analyses were conducted to identify independent risk factors for complications during the PIMSRA procedure. Results There were 48 patients with complications and 53 patients without complications. The heart rate at the start of the procedure and the maximum left ventricular outflow tract gradient (LVOTG) were independent risk factors related to PIMSRA complications. The optimal cut-off values for predicting complication occurrence were a heart rate > 49 bpm at the start of the procedure (OR: 3.79, 95% CI: 1.64–8.78, p = 0.002) and a maximum LVOTG > 92 mmHg (OR: 2.57, 95% CI: 1.15–5.75, p = 0.022), respectively. Conclusions The occurrence of PIMSRA complications is primarily associated with the heart rate at the start of the procedure and the maximum LVOTG. It is recommended to establish a comprehensive control plan to minimize the risk of complications during PIMSRA procedures.

Abstract Background The incidence of pneumothorax is higher in patients with emphysema who undergo percutaneous lung biopsy. Needle embolization has been shown to reduce the incidence of pneumothorax in patients with emphysema. Existing studies have reported small sample sizes of patients with emphysema, or the degree of emphysema has not been graded. Therefore, the efficacy of biopsy embolization in the prevention of pneumothorax induced by percutaneous pulmonary biopsy in patients with emphysema remains to be determined. Methods In this retrospective, controlled study, patients with emphysema who underwent CT-guided PTLB were divided into two groups: group A (n = 523), without tract embolization, and Group B (n = 504), with tract embolization. Clinical and imaging features were collected from electronic medical records and Picture Archiving and Communication Systems. Univariate and multivariate analyses were performed to identify risk factors for pneumothorax and chest tube placement. Results The two groups did not differ significantly in terms of demographic characteristics and complications other than pneumothorax. The incidence of pneumothorax and chest tube placement in group B was significantly lower than in group A (20.36% vs. 46.12%, p

Abstract Background Transposable elements play a critical role in maintaining genome architecture during neurodevelopment. Short Interspersed Nuclear Elements (SINEs), a major subtype of transposable elements, are known to harbor binding sites for the CCCTC-binding factor (CTCF) and pivotal in orchestrating chromatin organization. However, the regulatory mechanisms controlling the activity of SINEs in the developing brain remains elusive. Results In our study, we conduct a comprehensive genome-wide epigenetic analysis in mouse neural precursor cells using ATAC-seq, ChIP-seq, whole genome bisulfite sequencing, in situ Hi-C, and RNA-seq. Our findings reveal that the SET domain bifurcated histone lysine methyltransferase 1 (SETDB1)-mediated H3K9me3, in conjunction with DNA methylation, restricts chromatin accessibility on a selective subset of SINEs in neural precursor cells. Mechanistically, loss of Setdb1 increases CTCF access to these SINE elements and contributes to chromatin loop reorganization. Moreover, de novo loop formation contributes to differential gene expression, including the dysregulation of genes enriched in mitotic pathways. This leads to the disruptions of cell proliferation in the embryonic brain after genetic ablation of Setdb1 both in vitro and in vivo. Conclusions In summary, our study sheds light on the epigenetic regulation of SINEs in mouse neural precursor cells, suggesting their role in maintaining chromatin organization and cell proliferation during neurodevelopment.

Abstract Background Diabetic cardiomyopathy (DCM) stands as the primary cause of heart failure and mortality among patients with diabetes. Nevertheless, conventional treatment approaches are limited in their ability to effectively prevent myocardial tissue damage itself. Mesenchymal stem cell (MSC) therapy exhibits immense potential for treating DCM; however, the precise mechanisms involved in regulating inflammatory responses and pyroptosis processes, an emerging form of cellular death, within myocardial cells remain elusive. Hence, it is imperative to further elucidate the precise underlying mechanisms to facilitate the clinical implementation of MSC therapy. Methods In vivo, we established a DCM mouse model by administering streptozotocin and fed the mice a high-glucose and high-fat diet, followed by MSC therapy. Cardiac function and myocardial injury were evaluated through echocardiography and histological analysis. Furthermore, the levels of inflammation and pyroptosis were assessed using ELISA, Western blotting, and qRT-PCR. In vitro experiments involved inducing H9C2 myocardial cell damage with high glucose treatment, followed by coculture with MSCs to investigate their role in modulating inflammation and pyroptosis mechanisms. Results MSCs can maintain cardiac function and alleviate myocardial injury in mice with DCM. Moreover, they effectively suppress the activation of NLRP3 and reduce the release of inflammatory factors (such as IL-1β and ROS), thereby further downregulating the expression of pyroptosis-related proteins including NLRP3, Caspase-1, and GSDMD. Additionally, we experimentally validated that MSCs exert their therapeutic effects by promoting the expression of miR-223-3p in cardiac myocytes; however, this effect can be reversed by an miR-223-3p inhibitor. Conclusion MSCs effectively mitigate the release of inflammatory factors and cell lysis caused by pyroptosis through the regulation of the miR-223-3p/NLRP3 pathway, thereby safeguarding cardiomyocytes against damage in DCM. This mechanism establishes a novel theoretical foundation for the clinical treatment of cardiac conditions utilizing MSCs.

Abstract Background and purpose Various deep learning auto-segmentation (DLAS) models have been proposed, some of which have been commercialized. However, the issue of performance degradation is notable when pretrained models are deployed in the clinic. This study aims to enhance precision of a popular commercial DLAS product in rectal cancer radiotherapy by localized fine-tuning, addressing challenges in practicality and generalizability in real-world clinical settings. Materials and methods A total of 120 Stage II/III mid-low rectal cancer patients were retrospectively enrolled and divided into three datasets: training (n = 60), external validation (ExVal, n = 30), and generalizability evaluation (GenEva, n = 30) datasets respectively. The patients in the training and ExVal dataset were acquired on the same CT simulator, while those in GenEva were on a different CT simulator. The commercial DLAS software was first localized fine-tuned (LFT) for clinical target volume (CTV) and organs-at-risk (OAR) using the training data, and then validated on ExVal and GenEva respectively. Performance evaluation involved comparing the LFT model with the vendor-provided pretrained model (VPM) against ground truth contours, using metrics like Dice similarity coefficient (DSC), 95th Hausdorff distance (95HD), sensitivity and specificity. Results LFT significantly improved CTV delineation accuracy (p

AIM: To explore ocular surface manifestations of dry eye disease (DED) and its influencing factors in systemic lupus erythematosus (SLE) patients. METHODS: Ophthalmological examinations were conducted in SLE patients (n=43) and controls (n=41), including Ocular Surface Disease Index (OSDI), objective scatter index (OSI), tear meniscus height (TMH), lipid layer thickness (LLT), non-invasive Keratograph tear breakup time (NIKBUT), corneal fluorescein score (CFS), Schirmer I test. DED was diagnosed according to the Tear Film and Ocular Surface Society Dry Eye Workshop II Criteria. SLE patients were further divided into DED group and non-DED group, the disease activity, clinical manifestations and laboratory investigations were compared between the two groups. The disease activity was evaluated by Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K). Receiver operative characteristic (ROC) curve and multiple-factor binary logistic regression were performed. RESULTS: SLE patients showed higher OSDI [9.1 (2.8-15.9) vs 6.3 (2.2-7.5), P=0.035], higher OSI [1.67 (1.09-2.60) vs 0.96 (0.87-1.60), P=0.001], higher CFS [1 (0-2) vs 0 (0-1), P=0.001], lower LLT [65 (42-100) vs 100 (79.5-100), P=0.010], and lower NIKBUT [8.03 (4.02-9.73) vs 9.67 (5.26-12.71), P=0.030] than controls. The 32.6% of SLE patients had DED, which was higher than 12.2% of healthy controls. DED group showed higher SLEDAI-2K score [9.7±6.1 vs 5.4±3.4, P=0.025], higher anti-cardiolipin antibody (ACL) [8.7 (3.5-13.2) vs 3.6 (2.0-6.9), P=0.035], and higher proportion of patients with cutaneous eruption [42.9% vs 6.9%, P=0.015] than non-DED group. According to multiple-factor binary logistic regression analysis, the SLEDAI-2K score (OR=1.194, P=0.041) and cutaneous eruption (OR=7.094, P=0.045) could be consider as risk factors for DED in SLE patients. The ROC curve of the combined factors including age, disease duration, SLEDAI-2K score, ACL, and cutaneous eruption was analyzed, with a sensitivity of 0.786, a specificity of 0.793, and an area under curve of 0.820. CONCLUSION: Ocular surface affection is frequent in SLE patients, and patients with high disease activity and cutaneous eruption show increased risk of DED.

The structural heterogeneity and complexity of plant cell wall polysaccharides limit the release of phytonutrients in food processing, ultimately affecting the sensory quality, nutritional value, and shelf stability of products. Efficient enzymatic hydrolysis using plant cell wall polysaccharide-degrading enzymes (PCWPE) is a key step in overcoming the plant cell wall, a chemically complex structure composed mostly of polysaccharides, in food processing. PCWPE include cellulase, hemi-cellulase and pectinase, which specifically and efficiently hydrolyze glycosidic bonds in plant cell wall polysaccharides, significantly improving the sensory flavor and nutritional value of products, enhancing the stability of multiphase systems, and increasing the product yield. In recent years, PCWPE have been widely used in beverage processing, phytonutrient extraction, functional sugar preparation, and the processing of emerging sustainable plant-based food and thereby have become a research hotspot in the field of green food processing. This article summarizes the latest research on the mechanism of action of PCWPE, efficient enzymatic hydrolysis techniques and their application in the food industry, with a view to providing a reference for technological innovation in the field of high-quality plant-based food processing.

Abstract Due to the advanced studies on stem cells in developmental biology, the roles of stem cells in the body and their phenotypes in related diseases have not been covered clearly. Meanwhile, with the intensive research on the mechanisms of stem cells in regulating various diseases, stem cell therapy is increasingly being attention because of its effectiveness and safety. As one of the most widely used stem cell in stem cell therapies, hematopoietic stem cell transplantation shows huge advantage in treatment of leukemia and other blood-malignant diseases. Besides, due to the effect of anti-inflammatory and immunomodulatory, mesenchymal stem cells could be a potential therapeutic strategy for variety infectious diseases. In this review, we summarized the effects of Staphylococcus aureus (S. aureus) and its components on different types of adult stem cells and their downstream signaling pathways. Also, we reviewed the roles of different kinds of stem cells in various disease models caused by S. aureus, providing new insights for applying stem cell therapy to treat infectious diseases.

Abstract Background Uric acid (UA), a liver-derived metabolite, is intimately tied to metabolic disorders. Although ample research underscores its connection with hypertriglyceridemia (HTG), studies focusing on adolescents remain limited. To fill the gaps in epidemiology,this study focused on analyzing the relationship between the levels of uric acid and HTG in a demographic sample comprising adolescents from the United States. Methods In this study, a total of 4,435 participants through the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2020. The exposure variable was serum uric acid (SUA), the effect variable was HTG, and the covariates included demographic, questionnaire, physical examination and laboratory indicators. We utilized weighted logistic regression and meticulous subgroup evaluations to discern the intrinsic link between SUA and HTG. Stratified analyses augmented the validation of this association, while smooth curve fitting probed for potential nonlinear correlations. Results The study included 4,435 participants. Male adolescents exhibit elevated SUA levels. After adjusting for all variables, the weighted multiple logistic regression model revealed that SUA was positively correlated with HTG risk (OR = 1.006, 95% CI: 1.005–1.007). This relationship was consistent across the three tertiles group of SUA (T1: OR = 1.006 [95% CI: 1.005–1.007]; T2: OR = 1.006 [95% CI: 1.005–1.007]; T3: OR = 1.004 [95% CI: 1.003–1.006]; P for trend

Abstract Helicobacter pylori is a prevalent bacterial pathogen globally, implicated in various gastrointestinal disorders. Current recommended antibiotic therapies for H. pylori infection have been proven to be therapeutically insufficient, with low eradication rates and high recurrence rates. Emerging evidence suggests that antibiotic therapy for H. pylori can lead to gastrointestinal and subsequent vaginal dysbiosis, posing challenges for conventional antibiotic approaches. Thus, this article proposes a novel probiotic therapy involving simultaneous oral and intra-vaginal probiotic administration alongside antibiotics for H. pylori treatment, aiming to enhance eradication rates and mitigate dysbiosis. We begin by providing an overview of gastrointestinal and vaginal microbiota and their interconnectedness through the vagina-gut axis. We then review the efficacy of current antibiotic regimens for H. pylori and discuss how antibiotic treatment impacts the vaginal microenvironment. To explore the feasibility of this approach, we evaluate the effectiveness of oral and intra-vaginal probiotics in restoring normal microbiota in the gastrointestinal and vaginal tracts, respectively. Additionally, we analyze the direct mechanisms by which oral and intra-vaginal probiotics act on their respective tracts and discuss potential cross-tract mechanisms. Considering the potential synergistic therapeutic effects of probiotics in both the gastrointestinal and vaginal tracts, dual-channel probiotic therapy holds promise as a more effective approach for H. pylori eradication and dysbiosis mitigation, presenting a novel concept in the collaborative treatment of gastrointestinal and genital disorders.

Abstract Background Alzheimer’s disease and related dementias (ADRD) and Parkinson’s disease (PD), pose growing global health challenges. Socio-demographic and economic development acts paradoxically, complicating the process that determines how governments worldwide designate policies and allocate resources for healthcare. Methods We extracted data on ADRD and PD in 204 countries from the Global Burden of Disease 2019 database. Health disparities were estimated using the slope index of inequality (SII), and concentration index (CIX) based on the socio-demographic index. Estimated annual percentage changes (EAPCs) were employed to evaluate temporal trends. Results Globally, the SII increased from 255.4 [95% confidence interval (CI), 215.2 to 295.5)] in 1990 to 559.3 (95% CI, 497.2 to 621.3) in 2019 for ADRD, and grew from 66.0 (95% CI, 54.9 to 77.2) in 1990 to 132.5 (95% CI, 118.1 to 147.0) in 2019 for PD; CIX rose from 33.7 (95% CI, 25.8 to 41.6) in 1990 to 36.9 (95% CI, 27.8 to 46.1) in 2019 for ADRD, and expanded from 22.2 (95% CI, 21.3 to 23.0) in 1990 to 29.0 (95% CI, 27.8 to 30.3) in 2019 for PD. Age-standardized disability-adjusted life years displayed considerable upward trends for ADRD [EAPC = 0.43 (95% CI, 0.27 to 0.59)] and PD [0.34 (95% CI, 0.29 to 0.38)]. Conclusions Globally, the burden of ADRD and PD continues to increase with growing health disparities. Variations in health inequalities and the impact of socioeconomic development on disease trends underscored the need for targeted policies and strategies, with heightened awareness, preventive measures, and active management of risk factors.

Abstract Background No reliable clinical tools exist to predict acute kidney injury (AKI) progression. We aim to explore a scoring system for predicting the composite outcome of progression to severe AKI or death within seven days among early AKI patients after cardiac surgery. Methods In this study, we used two independent cohorts, and patients who experienced mild/moderate AKI within 48 h after cardiac surgery were enrolled. Eventually, 3188 patients from the MIMIC-IV database were used as the derivation cohort, while 499 patients from the Zhongshan cohort were used as external validation. The primary outcome was defined by the composite outcome of progression to severe AKI or death within seven days after enrollment. The variables identified by LASSO regression analysis were entered into logistic regression models and were used to construct the risk score. Results The composite outcome accounted for 3.7% (n = 119) and 7.6% (n = 38) of the derivation and validation cohorts, respectively. Six predictors were assembled into a risk score (AKI-Pro score), including female, baseline eGFR, aortic surgery, modified furosemide responsiveness index (mFRI), SOFA, and AKI stage. And we stratified the risk score into four groups: low, moderate, high, and very high risk. The risk score displayed satisfied predictive discrimination and calibration in the derivation and validation cohort. The AKI-Pro score discriminated the composite outcome better than CRATE score, Cleveland score, AKICS score, Simplified renal index, and SRI risk score (all P

Abstract Background Zinc finger E-box binding homEeobox 1 (ZEB1) and ZEB2 are two anoikis-related transcription factors. The mRNA expressions of these two genes are significantly increased in kidney renal clear cell carcinoma (KIRC), which are associated with poor survival. Meanwhile, the mechanisms and clinical significance of ZEB1 and ZEB2 upregulation in KIRC remain unknown. Methods Through the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database, expression profiles, prognostic value and receiver operating characteristic curves (ROCs) of ZEB1 and ZEB2 were evaluated. The correlations of ZEB1 and ZEB2 with anoikis were further assessed in TCGA-KIRC database. Next, miRTarBase, miRDB, and TargetScan were used to predict microRNAs targeting ZEB1 and ZEB2, and TCGA-KIRC database was utilized to discern differences in microRNAs and establish the association between microRNAs and ZEBs. TCGA, TIMER, TISIDB, and TISCH were used to analyze tumor immune infiltration. Results It was found that ZEB1 and ZEB2 expression were related with histologic grade in KIRC patient. Kaplan-Meier survival analyses showed that KIRC patients with low ZEB1 or ZEB2 levels had a significantly lower survival rate. Meanwhile, ZEB1 and ZEB2 are closely related to anoikis and are regulated by microRNAs. We constructed a risk model using univariate Cox and LASSO regression analyses to identify two microRNAs (hsa-miR-130b-3p and hsa-miR-138-5p). Furthermore, ZEB1 and ZEB2 regulate immune cell invasion in KIRC tumor microenvironments. Conclusions Anoikis, cytotoxic immune cell infiltration, and patient survival outcomes were correlated with ZEB1 and ZEB2 mRNA upregulation in KIRC. ZEB1 and ZEB2 are regulated by microRNAs.

AIM: To investigate the morphological characteristics of retinal vessels in patients with different severity of diabetic retinopathy (DR) and in patients with or without diabetic macular edema (DME). METHODS: The 239 eyes of DR patients and 100 eyes of healthy individuals were recruited for the study. The severity of DR patients was graded as mild, moderate and severe non-proliferative diabetic retinopathy (NPDR) according to the international clinical diabetic retinopathy (ICDR) disease severity scale classification, and retinal vascular morphology was quantitatively analyzed in ultra-wide field images using RU-net and transfer learning methods. The presence of DME was determined by optical coherence tomography (OCT), and differences in vascular morphological characteristics were compared between patients with and without DME. RESULTS: Retinal vessel segmentation using RU-net and transfer learning system had an accuracy of 99% and a Dice metric of 0.76. Compared with the healthy group, the DR group had smaller vessel angles (33.68±3.01 vs 37.78±1.60), smaller fractal dimension (Df) values (1.33±0.05 vs 1.41±0.03), less vessel density (1.12±0.44 vs 2.09±0.36) and fewer vascular branches (206.1±88.8 vs 396.5±91.3), all P

A flexible wipe paper for rapid nondestructive detection of ferbam residues on the surface of fruits and vegetables by surface-enhanced Raman scattering (SERS) was prepared using filter paper as the substate by a simple soaking method. The synthesis and storage conditions were optimized to ensure that the SERS method has excellent performance. The results showed that concentration factor of silver nanoparticles (AgNPs), soaking time in AgNP solution and drying method greatly affected the performance of the SERS wipe paper. The performance under the condition of soaking for 8 h in a 5-fold concentrate of AgNP solution was significantly better than that under other conditions. The SERS wipe paper prepared by vacuum drying had better performance that those prepared by other drying methods. After 9 days of storage at −20 ℃, the optimized substrate retained approximately 50% of the original peak value. Besides, it exhibited good sensitivity, uniformity, and repeatability. The limit of detection (LOD) for ferbam on a glass plate was 4.07 × 10-6 mg/mL, and the LOD for ferbam on the surface of spinach and nectarine were 0.043 and 0.062 mg/kg, respectively. This study provides an excellent basis for the development and utilization of SERS wipe paper.

Abstract In this study, dynamic formation tracking and interception are performed by controlling multi-agent using a Euler-like Lagrangian model. The purpose is to use the distance-based rigid graph method to control multi-agent, and ultimately achieve dynamic formation tracking and target interception of multi-agent. Initially, distance-based graph stiffness and back-stepping techniques were considered to address the formation control challenge. This method helps achieve the initial expected formation and effectively complete the formation mission. Leaders continue to chase the moving target, while followers stick to the expected arrangement. The leader then precisely tracks the moving target and surrounds it within the formation. By using Lyapunov stability theory with adaptive control, it is ensured that the total distance meets finite and consistent error limits. Finally, the numerical simulation of the interception plan was carried out by 6 multi-agents and 1 target at different times to verify the effectiveness of the control method.

Abstract Taro is a widely utilized starch resource plant. It is essential to quantify the expression levels of functional genes associated with taro growth using real-time quantitative polymerase chain reaction (RT-qPCR). However, to obtain reliable RT-qPCR results, appropriate reference genes (RGs) are required for data normalization. In this study, we screened seven novel candidate RGs using transcriptome datasets from taro, encompassing data from growth corms and various tissues. The expression stability of these seven new RGs, along with the commonly used RGs Actin, EF1-α, and β-tubulin, was assessed using Delta Ct, BestKeeper, geNorm, and NormFinder algorithms. Furthermore, we conducted a comprehensive analysis using the RefFinder program and validated the results using the target gene, CeAGPL1. The findings revealed that ACY-1 and PIA2 were the optimal multiple RGs for normalization during corm growth, while COX10 and Armc8 were suitable for samples including various types of tissues. Furthermore, we found three RGs, Armc8, COX10 and CCX4L, were the optimal RGs for drought stress. This study assessed the suitability of RGs in taro for the first time. The identified RGs provide valuable resources for studying corm growth, diverse tissues, and drought stress. This study contributes to the advancement of our understanding of the underlying mechanisms that govern the growth of taro.

Abstract Microglia are natural immune cells in the central nervous system, and the activation of microglia is accompanied by a reprogramming of glucose metabolism. In our study, we investigated the role of long non-coding RNA taurine-upregulated gene 1 (TUG1) in regulating microglial glucose metabolism reprogramming and activation. BV2 cells were treated with Lipopolysaccharides (LPS)/Interferon-γ (IFN-γ) to establish a microglial activation model. The glycolysis inhibitor 2-Deoxy-D-glucose (2-DG) was used as a control. The expression levels of TUG1 mRNA and proinflammatory cytokines such as Interleukin-1β (IL-1β), Interleukin -6, and Tumor Necrosis Factor-α mRNA and anti-inflammatory cytokines such as IL-4, Arginase 1(Arg1), CD206, and Ym1 were detected by RT-qPCR. TUG1 was silenced using TUG1 siRNA and knocked out using CRISPR/Cas9. The mRNA and protein expression levels of key enzymes involved in glucose metabolism, such as Hexokinase2, Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), Lactate dehydrogenase, Glucose 6 phosphate dehydrogenase, and Pyruvate dehydrogenase (PDH), were determined by RT-qPCR and Western blotting. The glycolytic rate of microglial cells was measured using Seahorse. Differential metabolites were determined by metabolomics, and pathway enrichment was performed using these differential metabolites. Our findings revealed that the expression of TUG1 was elevated in proinflammatory-activated microglia and positively correlated with the levels of inflammatory factors. The expression of anti-inflammatory cytokines such as IL-4, Arg1, CD206, and Ym1 were decreased when induced with LPS/IFN-γ. However, this decrease was reversed by the treatment with 2-DG. Silencing of GAPDH led to an increase in the expression of TUG1 and inflammatory factors. TUG1 knockout (TUG1KO) inhibited the expression of glycolytic key enzymes and promoted the expression of oxidative phosphorylation key enzymes, shifting the metabolic profile of activated microglia from glycolysis to oxidative phosphorylation. Additionally, TUG1KO reduced the accumulation of metabolites, facilitating the restoration of the tricarboxylic acid cycle and enhancing oxidative phosphorylation in microglia. Furthermore, the downregulation of TUG1 was found to reduce the expression of both proinflammatory and anti-inflammatory cytokines under normal conditions. Interestingly, when induced with LPS/IFN-γ, TUG1 downregulation showed a potentially beneficial effect on microglia in terms of inflammation. Downregulation of TUG1 expression inhibits glycolysis and facilitates the shift of microglial glucose metabolism from glycolysis to oxidative phosphorylation, promoting their transformation towards an anti-inflammatory phenotype and exerting anti-inflammatory effects in BV2.

Abstract Pathologic α-synuclein (α-syn) spreads from cell-to-cell, in part, through binding to the lymphocyte-activation gene 3 (Lag3). Here we report that amyloid β precursor-like protein 1 (Aplp1) interacts with Lag3 that facilitates the binding, internalization, transmission, and toxicity of pathologic α-syn. Deletion of both Aplp1 and Lag3 eliminates the loss of dopaminergic neurons and the accompanying behavioral deficits induced by α-syn preformed fibrils (PFF). Anti-Lag3 prevents the internalization of α-syn PFF by disrupting the interaction of Aplp1 and Lag3, and blocks the neurodegeneration induced by α-syn PFF in vivo. The identification of Aplp1 and the interplay with Lag3 for α-syn PFF induced pathology deepens our insight about molecular mechanisms of cell-to-cell transmission of pathologic α-syn and provides additional targets for therapeutic strategies aimed at preventing neurodegeneration in Parkinson’s disease and related α-synucleinopathies.

At one time monitoring over 900 million people, China’s health code system is arguably the most controversial invention of the pandemic. This study explores how the system emerged and its implications for security governance in urban communities. By analysing 9,533 social media posts published during three key weeks, the study revealed that early pandemic responses in China were heavily shaped by private nodes, such as estate management companies, private security guards and homeowners. Homeowners’ demands for extra security clashed with migrants’ and tenants’ demands for mobility. The health code system was presented as a ‘solution’ to these conflicts. The findings of this study highlight the limitations of consumer-driven pluralisation in policing. Such pluralisation offered limited opportunities for democratisation. Instead, the radical pursuit of ‘club goods’ by consumer-denizens reinforced existing inequalities. Entrenched inequalities tempted marginalised social groups to accept ‘indiscriminate’ surveillance, which paved the way for a neo-panopticon. The study also warns against the alliance of state nodes and big-tech companies. Through collaboration, these powerful players can replace political dynamics in the community with data-driven modulation, thus destroying the foundation of nodal governance.

Abstract Macrophage-orchestrated inflammation contributes to multiple diseases including sepsis. However, the underlying mechanisms remain to be defined clearly. Here, we show that macrophage TP53-induced glycolysis and apoptosis regulator (TIGAR) is up-regulated in murine sepsis models. When myeloid Tigar is ablated, sepsis induced by either lipopolysaccharide treatment or cecal ligation puncture in male mice is attenuated via inflammation inhibition. Mechanistic characterizations indicate that TIGAR directly binds to transforming growth factor β-activated kinase (TAK1) and promotes tumor necrosis factor receptor-associated factor 6-mediated ubiquitination and auto-phosphorylation of TAK1, in which residues 152-161 of TIGAR constitute crucial motif independent of its phosphatase activity. Interference with the binding of TIGAR to TAK1 by 5Z-7-oxozeaenol exhibits therapeutic effects in male murine model of sepsis. These findings demonstrate a non-canonical function of macrophage TIGAR in promoting inflammation, and confer a potential therapeutic target for sepsis by disruption of TIGAR-TAK1 interaction.

Abstract High concentrations of organic aerosol (OA) occur in Asian countries, leading to great health burdens. Clean air actions have resulted in significant emission reductions of air pollutants in China. However, long-term nation-wide trends in OA and their causes remain unknown. Here, we present both observational and model evidence demonstrating widespread decreases with a greater reduction in primary OA than in secondary OA (SOA) in China during the period of 2013 to 2020. Most of the decline is attributed to reduced residential fuel burning while the interannual variability in SOA may have been driven by meteorological variations. We find contrasting effects of reducing NOx and SO2 on SOA production which may have led to slight overall increases in SOA. Our findings highlight the importance of clean energy replacements in multiple sectors on achieving air-quality targets because of high OA precursor emissions and fluctuating chemical and meteorological conditions.