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Abstract Background Anxiety and depression often co-occur, exhibiting high comorbidity, with their trends evolving over time. However, the specific pathways through which comorbid symptoms of anxiety and depression evolve and interact remain unclear. To investigate these questions, this study employed Network Analysis (NA) and Longitudinal Network Analysis (LNA) to explore the central symptoms of anxiety and depression, as well as the temporal evolution of these central symptoms. Methods The study focused on 606 high school students who were not in their final year in Shandong of China, with assessments conducted from March to September 2022. The bootnet package in R was used for establishing NA and LNA models, as well as for conducting accuracy analysis and node stability analysis. Results The results of the NA indicated that adolescent highly susceptible to anxiety and depression. And uncontrollable worry was a common central symptom, while irritability emerged as a central bridging symptom across all three NAs. The LNA results revealed that suicidal ideation and worthlessness were key central symptoms in the LNA. Furthermore, worthlessness played a pivotal role in the developmental pathway of “suicidal ideation → worthlessness → anxiety and uncontrollable worry.” A reduction in suicidal ideation was associated with decreased severity in other symptoms. Conclusions The findings suggest that adolescent anxiety and depression are in a state of vulnerability, and that irritability, worthlessness, and suicidal ideation are potential targets for interventions to address adolescent anxiety and depression.

Abstract Background With suicide as a leading cause of death, the issue of children and adolescent suicide risks is in the spotlight today. To empower teachers in primary and secondary schools to serve as gatekeepers and to ensure the safety of children and adolescents, the systematically tailored and localized Life Gatekeeper suicide prevention program was designed for Chinese schools. Objective With the ultimate goal of preventing child and adolescent suicide, we aim to outline a research protocol for examining outcomes of the recently created standardized school-based Life Gatekeeper program in reducing teachers’ stigma, increasing their knowledge, willingness to intervene, and perceived competence. Methods Participants will be recruited from eligible primary and secondary schools. Cluster sampling will be used to randomly assign each school to either the intervention group or the control group. The primary outcomes are stigma against suicide, suicide literacy, perceived competence, and willingness to intervene with suicidal individuals, which will be measured using the Stigma of Suicide Scale, the Literacy of Suicide Scale, and the Willingness to Intervene Against Suicide Questionnaire, respectively. Measurements will be taken at four time points, including pre-intervention, immediately after the intervention, 6-month follow-up, and 1-year follow-up. Conclusions The current study features innovative implementation in the real world, by using a randomized controlled trial design to examine the effectiveness of a school-based gatekeeper program among primary and secondary school teachers, following a sequence of defined and refined steps. The research will also investigate the viability of a school-based gatekeeper program for primary and secondary school teachers that could be quickly and inexpensively implemented in a large number of schools.

Effective early pregnancy diagnosis is crucial for commercial rabbit breeding. Early pregnancy diagnosis enables the implementation of staged feeding for pregnant does, effectively preventing excessive weight gain and reducing the high mortality rates of kits during the birthing stage. This not only enhances production efficiency but also ensures the health and well-being of the breeding rabbits. The study introduces a method and device, the Rabbit Pregnancy Identification Device (RAPID), for detecting rabbit pregnancies using matrix optical sensing. RAPID comprises eight sensor modules and a central host unit. Each sensor module is equipped with three LEDs emitting light at wavelengths of 660 nm, 850 nm, and 940 nm, along with two photodiodes for data collection. A mobile application was developed to enable flexible control of the device. Signal-to-noise ratio tests were conducted to evaluate the stability of data collection by the device across varying light intensities. The experimental results reveal a direct correlation between light intensity levels and the signal-to-noise ratio of collected data. Notably, under a light intensity level of 4, RAPID achieves a signal-to-noise ratio ranging from 42 to 45 dB, satisfying the necessary criteria for data collection. Different classification models were trained using sample data from 216 does across various batches, and their generalization capabilities were evaluated. The experimental findings indicate that the optimal time for RAPID to diagnose the pregnancy status of does is on the 14th day after insemination, achieving an accuracy of 86.63 % and a recall of 80.49 %. Moreover, the model exhibits a degree of generalization, achieving an accuracy of 78.36 % when classifying another batch of sample data. RAPID achieves an accuracy of 97.25 % for pregnancy diagnosis of older does, which is 7.44 % higher than that of younger does; the accuracy rate for pregnancy diagnosis of does with sparse hair is 86.92 %, which is 4.78 % higher than that of does with dense hair. By comparing the effectiveness of using data from 8 sensor modules and data from a single sensor module for pregnancy diagnosis of different batches of does, it was found that the former exhibits more stable generalization capability in doe pregnancy detection.

Based on the whole virus or spike protein of pigs, δ coronavirus (PDCoV) as an immunogen may have unrelated antigenic epitope interference. Therefore, it is essential for screening and identifying advantageous protective antigen epitopes. In addition, immunoinformatic tools are described as an important aid in determining protective antigenic epitopes. In this study, the primary, secondary, and tertiary structures of vaccines were measured using ExPASy, PSIPRED 4.0, and trRosetta servers. Meanwhile, the molecular docking analysis and vector of the candidate nanovaccine were constructed. The immune response of the candidate vaccine was simulated and predicted using the C-ImmSim server. This experiment screened B cell epitopes with strong immunogenicity and high conservation, CTL epitopes, and Th epitopes with IFN-γ and IL-4 positive spike proteins. Ferritin is used as a self-assembled nanoparticle element for designing candidate nanovaccine. After analysis, it has been found to be soluble, stable, non-allergenic, and has a high affinity for its target receptor, TLR-3. The preliminary simulation analysis results show that the candidate nanovaccine has the ability to induce a humoral and cellular immune response. Therefore, it may provide a new theoretical basis for research on coronavirus self-assembled nanovaccines. It may be an effective candidate vaccine for controlling and preventing PDCoV.

Polystyrene microplastics (PS-MPs) are new types of environmental pollutant that have garnered significant attention in recent years since they were found to cause damage to the human respiratory system when they are inhaled. The pulmonary fibrosis is one of the serious consequences of PS-MPs inhalation. However, the impact and underlying mechanisms of PS-MPs on pulmonary fibrosis are not clear. In this study, we studied the potential lung toxicity and PS-MPs-developed pulmonary fibrosis by long-term intranasal inhalation of PS-MPs. The results showed that after exposing to the PS-MPs, the lungs of model mouse had different levels of damage and fibrosis. Meanwhile, exposing to the PS-MPs resulted in a markedly decrease in glutathione (GSH), an increase in malondialdehyde (MDA), and iron overload in the lung tissue of mice and alveolar epithelial cells (AECs). These findings suggested the occurrence of PS-MP-induced ferroptosis. Inhibitor of ferroptosis (Fer-1) had alleviated the PS-MPs-induced ferroptosis. Mechanically, PS-MPs triggered cell ferroptosis and promoted the development of pulmonary fibrosis via activating the cGAS/STING signaling pathway. Inhibition of cGAS/STING with G150/H151 attenuated pulmonary fibrosis after PS-MPs exposure. Together, these data provided novel mechanistic insights of PS-MPs-induced pulmonary fibrosis and a potential therapeutic paradigm.

Abstract Background Mesonephric carcinoma (MC) is a very rare tumor with less than 70 cases had been reported. The rarity of MC has restricted its research, resulting in the lack of published guidelines. Objective To summarize the characteristics and construct an external‐validated nomogram to predict the survival of MC patients. Method Sixty‐four qualified patients derived from the Surveillance, Epidemiology, and End Results Plus database, and one patient from the Guangzhou Red Cross Hospital were enrolled. The entire cohort was randomly divided into a development (70%) and a validation cohort (30%). The Kaplan–Meier method and univariate and multivariate Cox regression analyses were applied. Two nomograms were established to predict the 3‐to‐8‐year survival probability of MC patients, which were evaluated by C‐index, ROC curves, DCA curves, and calibration plots. Results The average survival time of MC patients was 84.22 ± 50.66 months. No significant difference was shown among different groups of race, primary site, tumor differentiated grade, and FIGO stages, while different SEER stages did distinguish patients' survival time, which indicated that the SEER stage standards might be a better staging system in the MC patients than FIGO stage (p = .0835). Additional survival analyses showed that MC patients benefited from shorter waiting times to begin treatment, accepting surgery, regional lymph node examination, radiotherapy, and chemotherapy. Two nomograms were established, both of which got satisfied scores in C‐index, ROC curves, DCA curves, and calibration plots. Conclusion Sufficient regional lymph nodes examined, and applying radiotherapy in high‐risk patients are recommended in MC patients. Nomograms established in the present study had good predicting and discriminating capabilities, which would be helpful in patients' individual risk estimation, management, counseling, and follow‐up.

After exposure to cold stress, animals enhance the production of beige adipocytes and expedite thermogenesis, leading to improved metabolic health. Although brown adipose tissue in rodents is primarily induced by β3-adrenergic receptor (ADRB3) stimulation, the activation of major β-adrenergic receptors (ADRBs) in pigs has been a topic of debate. To address this, we developed overexpression vectors for ADRB1, ADRB2, and ADRB3 and silenced the expression of these receptors to observe their effects on the adipogenic differentiation stages of porcine preadipocytes. Our investigation revealed that cold stress triggers the transformation of subcutaneous white adipose tissue to beige adipose tissue in pigs by modulating adrenergic receptor levels. Meanwhile, we found that ADRB3 promotes the transformation of white adipocytes into beige adipocytes. Notably, ADRB3 enhances the expression of beige adipose tissue marker genes, consequently influencing cellular respiration and metabolism by regulating lipolysis and mitochondrial expression. Therefore, ADRB3 may serve as a pivotal gene in animal husbandry and contribute to the improvement of cold intolerance in piglets.

BackgroundThe previous literature has demonstrated that depression, anxiety, and stress are significant predictors of problematic social media use. However, the manifestation of problematic social media use varies, and the predictive relationship between depression, anxiety, and stress with different subgroups of problematic social media use remains unclear. The aim of this research was to evaluate latent subgroups of problematic social media use among college students and to investigate the impact of depression, anxiety, and stress on these latent subgroups.MethodsA survey was carried out among college students in China using a cross-sectional approach. A total of 955 participants were included, with a mean age of 19.50 ± 1.22 years. Participants completed questionnaires containing the Bergen Social Media Addiction Scale (BSMAS) and the Depression, Anxiety, and Stress Scale-21 (DASS-21). The study employed latent profile analysis (LPA) to investigate latent subgroups of Chinese college students with problematic social media use, and a robust three-step approach was used to develop predictive regression mixed models of depression, anxiety, and stress on latent subgroups.ResultsProblematic social media use of Chinese college students can be categorized into four latent subgroups, namely, the high-risk group, the moderate-risk with pleasure group, the moderate-risk with compulsion group, and the low-risk group. The regression model showed that there was a significant difference between the high-risk group and the low-risk group on the stress scale. There was a significant difference between the moderate-risk with pleasure group and the moderate-risk with compulsion group on the depression scale.ConclusionProblematic social media use is heterogeneous, with depression and stress being potentially key factors influencing problematic social media use. Depression would make college students more likely to be moderate-risk with compulsion problematic social media users than moderate-risk with pleasure problematic social media users, and stress would make college students more likely to be high-risk problematic social media users than low-risk problematic social media users.

ObjectiveTo elucidate the functional role of gamma-aminobutyric acid (GABA)-ergic inhibition in suppressing epileptic brain activities such as spike-wave discharge (SWD), we recorded electroencephalogram (EEG) in knockout rats for Glutamate decarboxylase 1 (Gad1), which encodes one of the two GABA-synthesizing enzymes in mammals. We also examined how anti-epileptic drug valproate (VPA) acts on the SWDs present in Gad1 rats and affects GABA synthesis in the reticular thalamic nucleus (RTN), which is known to play an essential role in suppressing SWD.MethodsChronic EEG recordings were performed in freely moving control rats and homozygous knockout Gad1 (–/–) rats. Buzzer tones (82 dB) were delivered to the rats during EEG monitoring to test whether acoustic stimulation could interrupt ongoing SWDs. VPA was administered orally to the rats, and the change in the number of SWDs was examined. The distribution of GABA in the RTN was examined immunohistochemically.ResultsSWDs were abundant in EEG from Gad1 (–/–) rats as young as 2 months old. Although SWDs were universally detected in older rats irrespective of their Gad1 genotype, SWD symptom was most severe in Gad1 (–/–) rats. Acoustic stimulation readily interrupted ongoing SWDs irrespective of the Gad1 genotype, whereas SWDs were more resistant to interruption in Gad1 (–/–) rats. VPA treatment alleviated SWD symptoms in control rats, however, counterintuitively exacerbated the symptoms in Gad1 (–/–) rats. The immunohistochemistry results indicated that GABA immunoreactivity was significantly reduced in the somata of RTN neurons in Gad1 (–/–) rats but not in their axons targeting the thalamus. VPA treatment greatly increased GABA immunoreactivity in the RTN neurons of Gad1 (–/–) rats, which is likely due to the intact GAD2, another GAD isozyme, in these neurons.DiscussionOur results revealed two opposing roles of GABA in SWD generation: suppression and enhancement of SWD. To account for these contradictory roles, we propose a model in which GABA produced by GAD1 in the RTN neuronal somata is released extrasynaptically and mediates intra-RTN inhibition.

To obtain a continuous range of clear vision for pseudophakic eyes, a design of intraocular lens (IOL) with extended depth of focus (EDoF) was proposed. The IOL was optimized with a multi-configuration approach based on a pseudophakic eye model and the optical performances of the designed IOL were analyzed. The modulation transfer function (MTF) values remain above 0.2 at 50 lp/mm for object distance ranging from 0.35 m to infinity in both photopic vision and mesopic vision over a field of 4°. The optical performances remain stable when the pupil diameter changes from 2.25 mm to 5 mm. Besides, the presented theoretical analyses show the designed IOL has good optical performances for polychromatic light and corneal asphericity. The above shows that the IOL exhibits an excellent ability for pseudophakic eyes to see the object in a continuous range of distance.

Oxygen vacancies in metal oxides can serve as electron trap centers to capture CO2 and lower energy barriers for the electrochemical CO2 reduction reaction (CO2RR). Under aqueous electrolytes, however, such charge-enriched active sites can be occupied by adsorbed hydrogen (H∗) and lose their effectiveness for the CO2RR. Here, we develop an efficient catalyst consisting of Cu-doped, defect-rich ZnO (Cu–ZnO) for the CO2RR, which exhibits enhanced CO Faradaic efficiency and current density compared to pristine ZnO. The introduced Cu dopants simultaneously stabilize neighboring oxygen vacancies and modulate their local electronic structure, achieving inhibition of hydrogen evolution and acceleration of the CO2RR. In a flow cell test, a current density of more than 45 ​mA ​cm−2 and a CO Faradaic efficiency of > 80% is obtained for a Cu–ZnO electrocatalyst in the wide potential range of −0.76 ​V to −1.06 ​V vs. Reversible Hydrogen Electrode (RHE). This work opens up great opportunities for dopant-modulated metal oxide catalysts for the CO2RR.

Background To address the lack of mental health practitioners in developing countries, the current study explored the feasibility of a newly developed self-guided digital intervention program TEA (training for emotional adaptation) in alleviating depressive and anxiety symptoms, as one of a few studies which adapted from theoretical models with effective intervention techniques. Methods The first part of this study involved 11 professional mental health practitioners giving feedback on the feasibility of the TEA; while the second part involved a mixed-method single-arm study with 32 participants recruited online, who went through the seven intervention sessions within 14 days. The questionnaires were collected before, after, 14 days after, and 30 days after intervention. Additionally, 10 participants were invited to semi-structured interviews regarding their suggestions. Results Practitioners thought that the TEA showed high professionalism (8.91/10) and is suitable for treating emotional symptoms (8.09/10). The generalized estimating equation model showed that the TEA significantly reduced participants' depressive and anxiety symptoms, while the effects of the intervention remained 30 days post intervention (Cohen's d > 1). Thematic analysis revealed three main themes about future improvement, including content improvement, interaction improvement, and bug-fixing. Conclusions To address the current needs for digital mental health intervention programs to account for the insufficient availability of mental health services in China, the current study provides preliminary evidence of the effectiveness of TEA, with the potential to address the urgent need for remote mental health services. Trial registration The study was registered at the Chinese Clinical Trial Register (ChiCTR), with number [ChiCTR2200065944].

Abstract Rechargeable Li‐CO2 battery represents a sustainable technology by virtue of CO2 recyclability and energy storage capability. Unfortunately, the sluggish mass transport and electron transfer in bulky high‐crystalline discharge product of Li2CO3, severely hinder its practical capacity and rechargeability. Herein, a heterostructure of isolated metalloid Te atomic cluster anchored on N‐doped carbon nanosheets is designed (TeAC@NCNS) as a metal‐free cathode for Li‐CO2 battery. X‐ray absorption spectroscopy analysis demonstrates that the abundant and dispersed Te active centers can be stabilized by C atoms in form of the covalent bond. The fabricated battery shows an unprecedented full‐discharge capacity of 28.35 mAh cm−2 at 0.05 mA cm−2 and long‐term cycle life of up to 1000 h even at a high cut‐off capacity of 1 mAh cm−2. A series of ex situ characterizations combined with theoretical calculations demonstrate that the abundant Te atomic clusters acting as active centers can drive the electron redistribution of carbonate via forming TeO bonds, giving rise to poor‐crystalline Li2CO3 film during the discharge process. Moreover, the efficient electron transfer between the Te centers and intermediate species is energetically beneficial for nucleation and accelerates the decomposition of Li2CO3 on the TeAC@NCNS during the discharge/charge process.

How could soccer player migration impact national team performance, or vice versa? The answer to this question could play an essential role in making appropriate decisions and policies regarding the international mobility of soccer players. However, answering such a question faces two main challenges, including the complex relationship between variables in multi-attribute temporal data describing migrated players and national team performance, and the interpretation of analysis results in policymaking scenarios. In this work, we have closely collaborated with domain experts and characterized the problems of soccer player migration analysis. To address the first challenge, we adapt a cross-lagged panel analysis model into the player migration analysis problem. This cross-lagged panel analysis model is effective to evaluate the impact strength between player migration and national team performance, and straightforward to reveal the causal relationship. To address the second challenge, we design and develop a visual analytics system, MIG-Viewer, to help the experts to interpret the results of the proposed model efficiently. With MIG-Viewer, the experts can navigate the countries of interest in accordance with migration strategy, conduct comprehensive analysis with the comparison of impact strength, and adjust player migration and inspect further details of a specific country. We present two case studies using global player migration data since 1992 with three soccer analysis experts to demonstrate the effectiveness and usefulness of the system.

Abstract Background The therapeutic efficacy of mesenchymal stem cells (MSCs) of different tissue origins on metabolic disorders can be varied in many ways but remains poorly defined. Here we report a comprehensive comparison of human MSCs derived from umbilical cord Wharton’s jelly (UC-MSCs), dental pulp (PU-MSCs), and adipose tissue (AD-MSCs) on the treatment of glucose and lipid metabolic disorders in type II diabetic mice. Methods Fourteen-to-fifteen-week-old male C57BL/6 db/db mice were intravenously administered with human UC-MSCs, PU-MSCs, and AD-MSCs at various doses or vehicle control once every 2 weeks for 6 weeks. Metformin (MET) was given orally to animals in a separate group once a day at weeks 4 to 6 as a positive control. Body weight, blood glucose, and insulin levels were measured every week. Glucose tolerance tests (GTT) and insulin tolerance tests (ITT) were performed every 2 weeks. All the animals were sacrificed at week 6 and the blood and liver tissues were collected for biochemical and histological examinations. Results UC-MSCs showed the strongest efficacy in reducing fasting glucose levels, increasing fasting insulin levels, and improving GTT and ITT in a dose-dependent manner, whereas PU-MSCs showed an intermediate efficacy and AD-MSCs showed the least efficacy on these parameters. Moreover, UC-MSCs also reduced the serum low-density lipoprotein cholesterol (LDL-C) levels with the most prominent potency and AD-MSCs had only very weak effect on LDL-C. In contrast, AD-MSCs substantially reduced the lipid content and histological lesion of liver and accompanying biomarkers of liver injury such as serum aspartate transaminase (AST) and alanine aminotransferase (ALT) levels, whereas UC-MSCs and PU-MSCs displayed no or modest effects on these parameters, respectively. Conclusions Taken together, our results demonstrated that MSCs of different tissue origins can confer substantially different therapeutic efficacy in ameliorating glucose and lipid metabolic disorders in type II diabetes. MSCs with different therapeutic characteristics could be selected according to the purpose of the treatment in the future clinical practice.

Chimeric RNA is a crucial target for tumor diagnosis and drug therapy, also having its unique biological role in normal tissues. TNNI2-ACTA1-V1 (TA-V1), a chimeric RNA discovered by our laboratory in porcine muscle tissue, can inhibit the proliferation of Porcine Skeletal Muscle Satellite Cells (PSCs). The regulatory mechanism of TA-V1 in PSCs remains unclear, but we speculate that NCOA3, DDR2 and RDX may be the target genes of TA-V1. In this study, we explored the effects of NCOA3, DDR2 and RDX on cell viability and cell proliferation by CCK-8 assay, EdU staining and flow cytometry. Furthermore, the regulatory pathway of proliferation in PSCs mediated by TA-V1 through NCOA3 or CyclinD1 was elucidated by co-transfection and co-immunoprecipitation (Co-IP). The results revealed that overexpression of NCOA3 significantly increased cell viability and the expression level of CyclinD1, and also promotes cell proliferation by changing cells from the G1 phase to the S phase. In addition, inhibiting the expression of NCOA3 substantially reduced cell viability and inhibited cell proliferation. Overexpression of DDR2 and RDX had no significant effect on cell viability and proliferation. Co-transfection experiments showed that NCOA3 could rescue the proliferation inhibition of PSCs caused by TA-V1. Co-IP assay indicated that TA-V1 directly interacts with NCOA3. Our study explores the hypothesis that TA-V1 directly regulates NCOA3, indirectly regulating CyclinD1, thereby regulating PSCs proliferation. We provide new putative mechanisms of porcine skeletal muscle growth and lay the foundation for the study of chimeric RNA in normal tissues.

Chimeric RNA was considered a special marker of cancer. However, recent studies have demonstrated that chimeric RNAs also exist in non-cancerous cells and tissues. Here, we analyzed and predicted jointly 49 chimeric RNAs by Star-Fusion and FusionMap. One chimeric RNA, we named TNNI2-ACTA1, and its eight transcript variants were identified by reverse transcriptase–polymerase chain reaction. The overexpression of TNNI2-ACTA1 V1 inhibited the proliferation of porcine skeletal muscle satellite cells through down-regulating the mRNA expression levels of cell cycle–related genes cyclinD1. However, as parental genes, there is no such effect in the TNNI2 and ACTA1. To explore the underlying mechanism for this phenomenon, we used RNA-seq to profile the transcriptomes of PSCs with overexpression. Compared with the negative control group, 1,592 differentially expressed genes (DEGs) were upregulated and 1,077 DEGs downregulated in TNNI2 group; 1,226 DEGs were upregulated and 902 DEGs downregulated in ACTA1 group; and 13 DEGs were upregulated and 16 DEGs downregulated in TNNI2-ACTA1 V1 group, respectively. Compared with the parental gene groups, three specific genes were enriched in the TNNI2-ACTA1 V1 group (NCOA3, Radixin, and DDR2). These three genes may be the key to TNNI2-ACTA1 V1 regulating cell proliferation. Taken together, our study explores the role of chimeric RNAs in normal tissues. In addition, our study as the first research provides the foundation for the mechanism of chimeric RNAs regulating porcine skeletal muscle growth.

This paper is devoted to studying the passivity-based sliding mode control for nonlinear systems and its application to dock cranes through an adaptive neural network approach, where the system suffers from time-varying delay, external disturbance and unknown nonlinearity. First, relying on the generalized Lagrange formula, the mathematical model for the crane system is established. Second, by virtue of an integral-type sliding surface function and the equivalent control theory, a sliding mode dynamic system can be obtained with a satisfactory dynamic property. Third, based on the RBF neural network approach, an adaptive control law is designed to ensure the finite-time existence of sliding motion in the face of unknown nonlinearity. Fourth, feasible easy-checking linear matrix inequality conditions are developed to analyze passification performance of the resulting sliding motion. Finally, a simulation study is provided to confirm the validity of the proposed method.

Abstract Background Wilms’ tumor 1-associating protein (WTAP) is a nuclear protein, which is ubiquitously expressed in many tissues. Furthermore, in various types of malignancies WTAP is overexpressed and plays a role as an oncogene. The function of WTAP in diffuse large B-cell lymphoma (DLBCL), however, remains unclear. Methods Immunohistochemistry was applied to evaluate the levels of WTAP expression in DLBCL tissues and normal lymphoid tissues. Overexpression and knock-down of WTAP in DLBCL cell lines, verified on mRNA and protein level served to analyze cell proliferation and apoptosis in DLBCL cell lines by flow cytometry. Finally, co-immunoprecipitation (Co-IP), IP, and GST-pull down assessed the interaction of WTAP with Heat shock protein 90 (Hsp90) and B-cell lymphoma 6 (BCL6) as well as determined the extend of its ubiquitinylation. Results WTAP protein levels were consistently upregulated in DLBCL tissues. WTAP promoted DLBCL cell proliferation and improved the ability to confront apoptosis, while knockdown of WTAP in DLBCL cell lines allowed a significant higher apoptosis rate after treatment with Etoposide, an anti-tumor drug. The stable expression of WTAP was depended on Hsp90. In line, we demonstrated that WTAP could form a complex with BCL6 via Hsp90 in vivo and in vitro. Conclusion WTAP is highly expressed in DLBCL, promoting growth and anti-apoptosis in DLBCL cell lines. WTAP is a client protein of Hsp90 and can appear in a complex with BCL6 and Hsp90 in DLBCL. Down-regulation of WTAP could improve the chemotherapeutic treatments in DLBCL.

Background/Aims: Arterial fibrotic intimal thickening and arteriolar hyaline are considered common pathological features in immunoglobulin A nephropathy (IgAN), whereas little is known about the acute pathological manifestations of endothelial cell injury. The aim of this study was to investigate characteristics of intrarenal arterial lesions and to estimate their prognostic values in patients with IgAN. The primary renal endpoint was a 50% reduction in estimated glomerular filtration rate (eGFR) or end-stage renal disease (ESRD). Methods: Various renal arterial lesions (arterial fibrotic intimal thickening, arteriolar hyaline, arteriolar endotheliocyte swelling, arteriolar inflammatory cell infiltration, and arteriolar thrombosis) in 1683 patients with IgAN were reviewed and reclassified using a semi-quantitative scoring system. Their correlations with clinical features, pathological characteristics, and renal outcomes were evaluated. Results: The prevalence of intrarenal arterial lesions was up to 72.2% in IgAN patients. There were 978 patients (58.1%) with arterial fibrotic intimal thickening, 350 patients (20.8%) with arteriolar hyaline, 432 patients (25.7%) with arteriolar endotheliocyte swelling, 356 patients (21.2%) with arteriolar inflammatory cell infiltration and 43 patients (2.6%) with arteriolar thrombosis. Arterial fibrotic intimal thickening and arteriolar hyaline were strongly associated with higher mean arterial pressure (MAP) and reduced eGFR (P < 0.001) but were not related to proteinuria at the time of renal biopsy. In contrast, arteriolar endotheliocyte swelling and arteriolar thrombosis were correlated with heavier proteinuria as well as higher MAP and reduced eGFR. During follow-up, patients with vascular lesions received more renin-angiotensin system (RAS) blockade and less glucocorticoid and showed poorer renal outcomes. Univariate Cox model showed that the presence of renal vascular lesions [hazard ratio (HR) = 25.01, 95% confidence interval (CI): 6.19 to 101.03, P < 0.001] was a risk factor for renal outcomes. However, in multivariable Cox analysis, which included clinical factors and the Oxford-MEST-C, vascular lesions were not significantly associated with an increased risk of renal failure. Remarkably, the impact of vascular lesions on the survival from ESRD or 50% reduction in renal function was eliminated by the use of RAS blockade after adjustment for eGFR, proteinuria, and MAP. Conclusion: Our study demonstrates the high prevalence of vascular lesions, including the chronic and acute arterial pathological changes, in patients with IgAN. The presence of vascular lesions is associated with higher MAP, reduced eGFR and poorer renal outcomes, which could be influenced by the RAS blockade treatment.

The application of fiber-reinforced polymer (FRP) composites is gaining increasing popularity in impact-resistant devices, automotives, biomedical devices and aircraft structures due to their high strength-to-weight ratios and their potential for impact energy absorption. Impact-induced high loading rates can result in significant changes of mechanical properties (e.g., elastic modulus and strength) before strain softening occurs and failure characteristics inside the strain localization zone (e.g., failure mechanisms and fracture energy) for fiber-reinforced polymer composites. In general, these phenomena are called the strain rate effects. The underlying mechanisms of the observed rate-dependent deformation and failure of composites take place among multiple length and time scales. The contributing mechanisms can be roughly classified as: the viscosity of composite constituents (polymer, fiber and interfaces), the rate-dependency of the fracture mechanisms, the inertia effects, the thermomechanical dissipation and the characteristic fracture time. Numerical models, including the viscosity type of constitutive models, rate-dependent cohesive zone models, enriched equation of motion and thermomechanical numerical models, are useful for a better understanding of these contributing factors of strain rate effects of FRP composites.

Carbon emissions are a prominent issue for sustainable energy production and management. Energy policies under the growing competitive environment could change the priorities of emission reduction and investment decisions. This paper aims to forecast carbon emissions from China and to rank the importance of carbon emissions with interval type 2 (IT2) fuzzy sets (FS) for sustainable energy investments. For this purpose, the quadratic model is applied to measuring emission trends and the Qualitative Flexible Multiple Criteria Method (QUALIFLEX) is used for measuring sustainable energy investment alternatives by the several emission levels. Forecasted values of 29 provinces in China are converted into the linguistic and fuzzy numbers based on IT2 FS respectively to measure the priorities of emission reduction for sustainable economies. The novelty of this paper is to propose a hybrid decision-making approach based on quadratic modeling and the QUALIFLEX method and to discuss the overall energy emission trend and policies for sustainable economic growth. The results demonstrate that emission reduction policies are the most important phenomenon and the environmental factors should be widely considered to construct sustainable energy investments and production.

Inflammatory bowel disease (IBD) is generally considered as a major risk factor in the progression of colitis-associated carcinogenesis (CAC). Thus, it is well accepted that ameliorating inflammation creates a potential to achieve an inhibitory effect on CAC. Licorice flavonoids (LFs) possess strong anti-inflammatory activity, making it possible to investigate its pharmacologic role in suppressing CAC. The purpose of the present study was to evaluate the anti-tumor potential of LFs, and further explore the underlying mechanisms. Firstly, an azoxymethane (AOM)/dextran sulfate sodium (DSS)-induced mouse model was established and administered with or without LFs for 10 weeks, and then the severity of CAC was examined macroscopically and histologically. Subsequently, the effects of LFs on expression of proteins associated with apoptosis and proliferation, levels of inflammatory cytokine, expression of phosphorylated-Janus kinases 2 (p-Jak2) and phosphorylated-signal transducer and activator of transcription 3 (p-Stat3), and activation of nuclear factor-κB (NFκB) and P53 were assessed. We found that LFs could significantly reduce tumorigenesis induced by AOM/DSS. Further study revealed that LFs treatment substantially reduced activation of NFκB and P53, and subsequently suppressed production of inflammatory cytokines and phosphorylation of Jak2 and Stat3 in AOM/DSS-induced mice. Taken together, LFs treatment alleviated AOM/DSS induced CAC via P53 and NFκB/IL-6/Jak2/Stat3 pathways, highlighting the potential of LFs in preventing CAC.

Nonadiabatic molecular dynamics (NA-MD) is a powerful tool to model far-from-equilibrium processes, such as photochemical reactions and charge transport. NA-MD application to condensed phase has drawn tremendous attention recently for development of next-generation energy and optoelectronic materials. Studies of condensed matter allow one to employ efficient computational tools, such as density functional theory (DFT) and classical path approximation (CPA). Still, system size and simulation timescale are strongly limited by costly ab initio calculations of electronic energies, forces, and NA couplings. We resolve the limitations by developing a fully machine learning (ML) approach in which all the above properties are obtained using neural networks based on local descriptors. The ML models correlate the target properties for NA-MD, implemented with DFT and CPA, directly to the system structure. Trained on small systems, the neural networks are applied to large systems and long timescales, extending NA-MD capabilities by orders of magnitude. We demonstrate the approach with dependence of charge trapping and recombination on defect concentration in MoS2. Defects provide the main mechanism of charge losses, resulting in performance degradation. Charge trapping slows with decreasing defect concentration; however, recombination exhibits complex dependence, conditional on whether it occurs between free or trapped charges, and relative concentrations of carriers and defects. Delocalized shallow traps can become localized with increasing temperature, changing trapping and recombination behavior. Completely based on ML, the approach bridges the gap between theoretical models and realistic experimental conditions and enables NA-MD on thousand-atom systems and many nanoseconds. [ABSTRACT FROM AUTHOR]

Given the increasing severity of energy shortages, the exploration of effective strategies to optimize energy structures has become imperative. This requires careful consideration of energy consumption patterns, especially since these data are fundamental inputs for policy formulation. Given the uncertainty in the rate of change in energy consumption, this paper proposes an optimized multivariable grey Bernoulli model that is rooted in the grey Bernoulli model and incorporates background values and genetic algorithms. The grey Bernoulli model effectively linearizes nonlinear problems, thus simplifying computational procedures. In addition, to account for random fluctuations of relevant factors that may affect the model's predictions, this model introduces nonlinear correction terms that allow simulation and prediction values to adhere to the grey index law. The incorporation of background values enhances the model's ability to process information, providing it with a superior grasp of real data. Genetic algorithms can be used to refine the model's parameters, increasing its adaptability and precision. Finally, this paper applies the refined model to examine China's energy consumption patterns, validating its efficacy and versatility. Furthermore, energy consumption patterns for the next four years are forecast, with the analysis revealing that the growth rate of energy consumption from 2021 to 2024 shows a downward trend, particularly notable in 2024, where the growth rate is 1.64%. [ABSTRACT FROM AUTHOR]

Multivariate grey models are commonly used to evaluate the independent effects of related factors, but they may fail to account for any nonlinear interactions that could exist between them. To address this limitation, this study introduces the INDGM(1,N) model, which considers the nonlinear interactions between related factors. Simultaneously, to depict the nonlinear impact of both the system behavior sequence and corresponding factor sequences more accurately, varying power parameters have been incorporated into the model proposed in this paper. Moreover, by adjusting the parameter values of the INDGM(1,N) model, it can be converted into several other models, such as the DGM(1,N) model, GM(1,N) model, DGM(1,1) model, or GM(1,1) model. This study uses a genetic algorithm to obtain the time response of the INDGM(1,N) model by solving its nonlinear characteristic parameters. We then use the model to simulate and forecast China's CO2 emissions and compare its performance with that of other models. The results show that the INDGM(1,N) model provides more accurate simulation and prediction accuracy than other models, highlighting its effectiveness. [ABSTRACT FROM AUTHOR]

Enhancing the nighttime environment of urban green spaces to improve visitor's experiences plays a pivotal role in realizing the full functional potential of these spaces and promoting the health and well-being of residents. However, the predominant focus of designers tends to be on artificial illumination within nightscapes, often overshadowing the consideration of natural lights such as moonlight. In this study, a total of 44 photographs of nightscapes with and without artificial lights at half- and full-moon nights respectively were taken using digital cameras at 11 sample sites of urban green spaces. Scored by college students, these photographs were assessed according to visitors' experience in five dimensions. The results indicated that at both half- and full-moon nights, the average scores of the five experience dimensions in artificial lights were higher compared with moonlight conditions. However, at full-moon night, no significant difference in aesthetic preference, relaxation, and interestingness between artificial light and moonlight conditions was found; whereas, in terms of safety and willingness to visit, the scores under artificial light condition were significantly higher than those under moonlight. At half-moon night, there was no significant difference in aesthetic preference between artificial light and moonlight conditions, but the other four experience dimensions were significantly higher under the artificial light condition. These findings provide a theoretical basis to support the reintroduction of moonlight into urban green spaces. [ABSTRACT FROM AUTHOR]