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Abstract This study investigated how resting-state functional connectivity (rsFC) of the subgenual anterior cingulate cortex (sgACC) predicts antidepressant response in patients with major depressive disorder (MDD). Eighty-seven medication-free MDD patients underwent baseline resting-state functional MRI scans. After 12 weeks of escitalopram treatment, patients were classified into remission depression (RD, n = 42) and nonremission depression (NRD, n = 45) groups. We conducted two analyses: a voxel-wise rsFC analysis using sgACC as a seed to identify group differences, and a prediction model based on the sgACC rsFC map to predict treatment efficacy. Haufe transformation was used to interpret the predictive rsFC features. The RD group showed significantly higher rsFC between the sgACC and regions in the fronto-parietal network (FPN), including the bilateral dorsolateral prefrontal cortex (DLPFC) and bilateral inferior parietal lobule (IPL), compared to the NRD group. These sgACC rsFC measures correlated positively with symptom improvement. Baseline sgACC rsFC also significantly predicted treatment response after 12 weeks, with a mean accuracy of 72.64% (p

Abstract Suicidal ideation (SI) is a significant precursor and risk marker for suicide behaviors in major depressive disorder (MDD). Exploration of SI trajectory from a longitudinal framework are essential for treatment guidelines and clinical management of suicide risk. This study sought to explore SI trajectories and its associated clinical, sociodemographic characteristics, and initial treatment among patients with MDD. We used data from a non-interventional, national multi-centered prospective cohort study. 1 461 patients with MDD were included in the growth mixture modeling using SI at baseline, 2 weeks, 4 weeks, 8 weeks, 12 weeks, and 6 months, 9 months, and 12 months as the indicator. A multinomial regression was employed with SI trajectory as the outcome and anhedonia, depressive symptoms, atypical depressive symptoms, pharmacological treatments, and other covariates as the predictors. Four distinct SI trajectories were identified: a consistently low SI trajectory(50.7%), a persistently mild SI trajectory(20.6%), a fast declined SI trajectory(8.9%), and a slowly declined trajectory(19.8%). Compared to those with a consistently low SI trajectory, a higher score of anhedonia was associated with an increased risk of experiencing persistently mild (RRR = 1.20, 95%CI: 1.05, 1.38) and slowly declined SI (1.54, 95%CI: 1.32, 1.80). Severity of depressive symptom was also positively associated with the risk of experiencing persistently mild (1.15, 95%CI: 1.13, 1.18) and slowly declined SI (1.17, 95%CI: 1.14, 1.21). And the risk of experiencing slowly declined SI was higher for those use SSRI(1.49, 95%CI: 1.02, 2.31), and for those use antidepressant and antipsychotic/mood stabilizer combined therapy (3.78, 95%CI: 1.48, 9.61). The findings of this study are potentially useful for clinical practice as critical indicators of profiles and interventions for prognosis among patients with MDD. Further research is warranted to explore potential modifiable factors and the association between SI trajectories and suicide behavior.

This study involved the ultrasonic modification of water-soluble pectin, chelator-soluble pectin, and sodium carbonate-soluble pectin in blueberries using different ultrasonic treatments (688, 1376, 2063 W/cm2, 10, 20, 30 min). The research explored the relationship between the modified pectin structure and the interaction between pectin and cyanidin-3-O-glucoside (C3G). The results showed that ultrasonic modification resulted in enhanced interaction between pectin and C3G. After the ultrasonic treatment of 2063 W/cm2 for 10 min, all three pectins showed the maximum binding capacity with C3G, which was about 2~6 times higher than that without the ultrasonic modification. Whereas, prolonged ultrasonic time (20~30 min) was unfavorable for the interaction between modified pectin and C3G. After ultrasonic modification, the particle size of the pectin-C3G complexes became smaller, the Zeta potential was increased, and the physical stability was thus improved. In three different pectin samples, ultrasonic treatment induced a reduction in molecular weight and methyl esterification of the pectin, facilitated the degradation of the branched structures, promoted the number of free carboxyl groups, and increased the presence of structural network voids. The alteration of the structural properties of pectin by ultrasonic treatment facilitated the interactions between pectin and C3G.

Abstract While rapid demographic changes in Asia are driving the incidence of chronic aging-related diseases, the limited availability of high-quality in vivo data hampers our ability to understand complex multi-factorial contributions, including gut microbial, to healthy aging. Leveraging a well-phenotyped cohort of community-living octogenarians in Singapore, we used deep shotgun-metagenomic sequencing for high-resolution taxonomic and functional characterization of their gut microbiomes (n = 234). Joint species-level analysis with other Asian cohorts identified distinct age-associated shifts characterized by reduction in microbial richness, and specific Alistipes and Bacteroides species enrichment (e.g., Alistipes shahii and Bacteroides xylanisolvens). Functional analysis confirmed these changes correspond to metabolic potential expansion in aging towards alternate pathways synthesizing and utilizing amino-acid precursors, vis-à-vis dominant microbial guilds producing butyrate in gut from pyruvate (e.g., Faecalibacterium prausnitzii, Roseburia inulinivorans). Extending these observations to key clinical markers helped identify >10 robust microbial associations to inflammation, cardiometabolic and liver health, including potential probiotic species (e.g., Parabacteroides goldsteinii) and pathobionts (e.g., Klebsiella pneumoniae), highlighting the microbiome’s role as biomarkers and potential targets for promoting healthy aging.

Abundance sensitivity is an important technical index of magnetic mass spectrometer, which describes the extent to which the tailing of intense ion peaks at a mass number in its neighborhood affects the weak ion peaks during isotope ratio measurement. It is particularly important in the measurement of isotope ratios containing low abundance nuclides, such as 234U/238U, 236U/238U, and 230Th/232Th. However, the abundance sensitivity of magnetic mass spectrometer is only of the order of 10−6 without taking additional technical measures. To further improve the abundance sensitivity, the techniques of tandem mass spectrometer, such as magnetic-electric, magnetic-magnetic and magnetic-electric-quadrupole tandem mass spectrometer, and retarding filter can be adopted. In fact, while various tandem mass spectrometer techniques can effectively improve the abundance sensitivity of an instrument, they also significantly increase the size, complexity, and cost of instrument, and therefore are not widely used. In contrast, due to its simple structure, small size, and excellent performance, the retarding filter has become a key component for commercial magnetic mass spectrometers to improve abundance sensitivity. Based on the basic principles of ion optics, a retarding filter consisting of five electrodes with a compact structure of only (40×50×50) mm3 was developed by utilizing the ion optics simulation software SIMION8.1. In addition to the function of energy retarding, the retarding filter also has the function of direction retarding, which greatly enhances the filtering capability to scatter ions. To test the ion transmission efficiency and the abundance sensitivity under different voltages, the retarding filter was installed on a domestic double-focusing thermal ionization mass spectrometer (TIMS). The instrument mainly consists of a thermal ionization source, a double focusing mass analyzer consisting of an electrostatic analyzer and a magnetic mass analyzer, a zoom lens, and a multi-collector detector, which can be configured with up to 16 faraday cups, 4 electron multipliers, and 2 retarding filters. The results showed that the abundance sensitivity of the mass spectrometer is successfully improved from

Abstract Neurons rely heavily on high mitochondrial metabolism to provide sufficient energy for proper development. However, it remains unclear how neurons maintain high oxidative phosphorylation (OXPHOS) during development. Mitophagy plays a pivotal role in maintaining mitochondrial quality and quantity. We herein describe that G protein-coupled receptor 50 (GPR50) is a novel mitophagy receptor, which harbors the LC3-interacting region (LIR) and is required in mitophagy under stress conditions. Although it does not localize in mitochondria under normal culturing conditions, GPR50 is recruited to the depolarized mitochondrial membrane upon mitophagy stress, which marks the mitochondrial portion and recruits the assembling autophagosomes, eventually facilitating the mitochondrial fragments to be engulfed by the autophagosomes. Mutations Δ502-505 and T532A attenuate GPR50-mediated mitophagy by disrupting the binding of GPR50 to LC3 and the mitochondrial recruitment of GPR50. Deficiency of GPR50 causes the accumulation of damaged mitochondria and disrupts OXPHOS, resulting in insufficient ATP production and excessive ROS generation, eventually impairing neuronal development. GPR50-deficient mice exhibit impaired social recognition, which is rescued by prenatal treatment with mitoQ, a mitochondrially antioxidant. The present study identifies GPR50 as a novel mitophagy receptor that is required to maintain mitochondrial OXPHOS in developing neurons.

Abstract Background The traumatic spinal cord injury (SCI) can cause immediate multi-faceted function loss or paralysis. Microglia, as one of tissue resident macrophages, has been reported to play a critical role in regulating inflammation response during SCI processes. And transplantation with M2 microglia into SCI mice promotes recovery of motor function. However, the M2 microglia can be easily re-educated and changed their phenotype due to the stimuli of tissue microenvironment. This study aimed to find a way to maintain the function of M2 microglia, which could exert an anti-inflammatory and pro-repair role, and further promote the repair of spinal cord injury. Methods To establish a standard murine spinal cord clip compression model using Dumont tying forceps. Using FACS, to sort microglia from C57BL/6 mice or CX3CR1GFP mice, and further culture them in vitro with different macrophage polarized medium. Also, to isolate primary microglia using density gradient centrifugation with the neonatal mice. To transfect miR-145a-5p into M2 microglia by Lipofectamine2000, and inject miR-145a-5p modified M2 microglia into the lesion sites of spinal cord for cell transplanted therapy. To evaluate the recovery of motor function in SCI mice through behavior analysis, immunofluorescence or histochemistry staining, Western blot and qRT-PCR detection. Application of reporter assay and molecular biology experiments to reveal the mechanism of miR-145a-5p modified M2 microglia therapy on SCI mice. Results With in vitro experiments, we found that miR-145a-5p was highly expressed in M2 microglia, and miR-145a-5p overexpression could suppress M1 while promote M2 microglia polarization. And then delivery of miR-145a-5p overexpressed M2 microglia into the injured spinal cord area significantly accelerated locomotive recovery as well as prevented glia scar formation and neuron damage in mice, which was even better than M2 microglia transplantation. Further mechanisms showed that overexpressed miR-145a-5p in microglia inhibited the inflammatory response and maintained M2 macrophage phenotype by targeting TLR4/NF-κB signaling. Conclusions These findings indicate that transplantation of miR-145a-5p modified M2 microglia has more therapeutic potential for SCI than M2 microglia transplantation from epigenetic perspective. Graphical Abstract

Abstract Connected and autonomous driving technologies offer a novel solution for intersection control optimization. Connected and autonomous vehicles (CAVs) can access signal plans and optimize trajectories to minimize delays and reduce fuel consumption. However, optimizing trajectories for individual vehicles significantly increases complexity, especially for joint optimization of traffic signals and vehicle trajectories. Given the current technical, regulatory, and policy constraints, a superior intersection management approach is necessary before fully automated driving is achieved. This paper introduces an adaptive coupling control (ACC) method based on vehicle platooning to optimize signal timings and vehicle trajectories in mixed traffic. Initially, vehicle platoon segmentation is conducted, led by CAVs. The study then proposes a single‐layer coupled optimization model based on vehicle platoons, simplifying the joint optimization model. To address logistic constraint difficulties, a linearization of the coupled model (LCM) method is developed. Numerical experiments demonstrate that the ACC method significantly reduces vehicle delay and fuel consumption. At high CAV penetration rates (0.8 < R

Abstract Background The rumen is a crucial digestive organ for dairy cows. The rumen microbiota assists in the digestion of plant feed through microbe-mediated fermentation, during which the plant feed is transformed into nutrients for the cow's use. Variations in the composition and function of the rumen microbiome affect the energy utilization efficiency of dairy cows, which is one of the reasons for the varying body condition scores (BCSs). This study focused on prepartum Holstein dairy cows to analyze differences in rumen microbiota and metabolites among cows with different BCSs. Twelve prepartum dairy cows were divided into two groups, low BCS (LBCS, BCS = 2.75, n = 6) and high BCS (HBCS, BCS = 3.5, n = 6), to explore differences in microbial composition and metabolites. Results In the HBCS group, the genera within the phylum Firmicutes exhibited stronger correlations and greater abundances. Phyla such as Firmicutes, Patescibacteria, Acidobacteriota, Euryarchaeota, and Desulfobacterota, in addition to most of their constituent microbial groups, were significantly more abundant in the HBCS group than in the LBCS group. At the genus level, the abundances of Anaerovibrio, Veillonellaceae_UCG_001, Ruminococcus_gauvreauii_group, Blautia, Eubacterium, Prevotellaceae_YAB2003_group, Schwartzia, and Halomonas significantly increased in the HBCS group. The citrate cycle, involved in carbohydrate metabolism, exhibited a significant enrichment trend, with a notable increase in the abundance of its key substrate, citrate, in the HBCS group. This increase was significantly positively correlated with the differential bacterial genera. Conclusion In this study, prepartum dairy cows with higher BCS exhibited greater abundance of Firmicutes. This study provides theoretical support for microbiological research on dairy cows with different BCSs and suggests that regulating the rumen microbiome could help maintain prepartum dairy cows within an optimal BCS range.

Dust pollution can harm the urban environment and the health of citizens. Each stage in highway construction generates unorganized dust emissions to varying degrees, which complicates their quantification. To precisely forecast dust emissions during the construction of highway subgrades and reduce the associated pollution risks, this study introduces a predictive model based on a deep neural network (DNN) for dust emissions during highway subgrade-filling operations. Dust concentration is treated as a nonlinear multivariate problem, with predictive indicators encompassing particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), ground surface temperature, wind speed, air temperature, surface pressure, and relative humidity. Using a DNN model, this study forecasts the concentrations of PM2.5 and PM10 at highway construction sites. Based on a highway project in Hebei Province, this study predicts dust-emission concentrations via field monitoring conducted using self-developed equipment. The model’s predictions exhibit a small mean-absolute-percentage error and root-mean-square error compared with the actual values, and the model’s accuracy significantly surpasses that of conventional regression models. Accurate forecasting can facilitate the timely control of dust concentrations at construction sites, thus facilitating more environmentally friendly and efficient construction. Doi: 10.28991/HIJ-2024-05-02-03 Full Text: PDF

Abstract In 2022, China’s Educational Ministry, for the first time, released an industry standard for teachers’ digital literacy. This standard provides a holistic framework for teachers’ digital literacy (TDL) in five dimensions. Since few studies have investigated EFL teachers’ digital literacy, the relationships among the five dimensions proposed for EFL teachers’ digital literacy remain unknown. Therefore, this research applied a quantitative method using a five-point Likert questionnaire designed based on TDL. Ninety-two EFL teachers from two universities and one higher vocational college in China participated in this questionnaire research. Partial least squares structural equation modeling was used to assess the relationships between these five dimensions. The relationships between the five TDL dimensions were highlighted by the findings, which supported the proposed model. In addition, implications for enhancing EFL teachers’ future digital literacy have been provided to facilitate and favor EFL teachers’ digital literacy development.

Abstract Primordial black holes (PBHs) are the plausible candidates for the cosmological dark matter. Theoretically, PBHs with masses $$M_{\textrm{PBH}}$$ M PBH in the range of $$4\times 10^{14}\sim 10^{17}\,\textrm{g}$$ 4 × 10 14 ∼ 10 17 g can emit sub-GeV electrons and positrons through Hawking radiation. Some of these particles could undergo diffusive reacceleration during propagation in the Milky Way, potentially reaching energies up to the GeV level observed by AMS-02. In this work, we utilize AMS-02 data to constrain the PBH abundance $$f_{\textrm{PBH}}$$ f PBH by employing the reacceleration mechanism. Under the assumption of a monochromatic PBH mass distribution, our findings reveal that the limit is stricter than that derived from Voyager 1 data. This difference is particularly pronounced when $$M_{\textrm{PBH}}\lesssim 10^{15}\,\textrm{g}$$ M PBH ≲ 10 15 g , exceeding an order of magnitude. The constraints are even more robust in a more realistic scenario involving a log-normal mass distribution of PBHs. Moreover, we explore the impact of varying propagation parameters and solar modulation potential within reasonable ranges, and find that such variations have minimal effects on the final results.

Abstract Background Flies are acknowledged as vectors of diseases transmitted through mechanical means and represent a significant risk to human health. The study aimed to determine the prevalence of enteropathogens carried by flies in Pudong New Area to inform strategies for preventing and controlling flies. Methods Samples were collected from various locations in the area using cage trapping techniques between April and November 2021, encompassing various habitats such as parks, residential areas, restaurants, and farmers’ markets. The main fly species were identified using cryomicrography and taxonomic enumeration, with 20 samples per tube collected from different habitats. Twenty-five enteropathogens were screened using GI_Trial v3 TaqManTM microbial arrays. Results A total of 3,875 flies were collected from 6,400 placements, resulting in an average fly density of 0.61 flies per cage. M. domestica were the most common species at 39.85%, followed by L. sericata at 16.57% and B. peregrina at 13.14%. Out of 189 samples, 93 tested positive for enteropathogens, with nine different pathogens being found. 12.70% of samples exclusively had parasites, a higher percentage than those with only bacteria or viruses. The study found that M. domestica had fewer enteropathogens than L. sericata and B. peregrina, which primarily harbored B. hominis instead of bacteria and viruses such as E. coli, Astrovirus, and Sapovirus. During spring testing, all three fly species exhibited low rates of detecting enteropathogens. M. domestica were found in residential areas with the highest number of pathogen species, totaling six. In contrast, L. sericata and B. peregrina were identified in farmers’ markets with the highest number of pathogen species, totaling six and seven, respectively. Conclusions Flies have the potential to serve as vectors for the transmission of enteropathogens, thereby posing a substantial risk to public health.

The interplay between personality traits and impulsivity has long been a central theme in psychology and psychiatry. However, the potential association between Greed Personality Traits (GPT) and impulsivity, encompassing both trait and state impulsivity and future time perspective, remains largely unexplored. To address these issues, we employed questionnaires and an inter-temporal choice task to estimate corresponding trait/state impulsivity and collected multi-modal neuroimaging data (resting-state functional imaging: n = 430; diffusion-weighted imaging: n = 426; task-related functional imaging: n = 53) to investigate the underlying microstructural and functional substrates. Behavioral analyses revealed that GPT mediated the association between time perspective (e.g., present fatalism) and trait impulsivity (e.g., motor impulsivity). Functional imaging analyses further identified that brain activation strengths and patterns related to delay length, particularly in the dorsomedial prefrontal cortex, superior parietal lobule, and cerebellum, were associated with GPT. Moreover, individuals with similar levels of greed exhibited analogous spontaneous brain activity patterns, predominantly in the Default Mode Network (DMN), Fronto-Parietal Network (FPN), and Visual Network (VIS). Diffusion imaging analysis observed specific microstructural characteristics in the spinocerebellar/pontocerebellar fasciculus, internal/external capsule, and corona radiata that support the formation of GPT. Furthermore, the corresponding neural activation pattern, spontaneous neural activity pattern, and analogous functional couplings among the aforementioned brain regions mediated the relationships between time perspective and GPT and between GPT and motor impulsivity. These findings provide novel insights into the possible pathway such as time perspective → dispositional greed → impulsivity and uncover their underlying microstructural and functional substrates.

Background Few large‐scale studies have evaluated the effectiveness of percutaneous coronary intervention (PCI) technological advances in the treatment of patients with unprotected left main coronary artery disease (LM‐CAD). We aim to identify independent factors that affect the prognosis of PCI in patients with unprotected LM‐CAD and to assess the impact of PCI technological advances on long‐term clinical outcomes. Methods and Results A total of 4512 consecutive patients who underwent unprotected LM‐CAD PCI at Fuwai Hospital from 2004 to 2016 were enrolled. Multivariable Cox proportional hazards model was used to identify which techniques can independently affect the incidence of major adverse cardiac events (MACEs; a composite of cardiac death, myocardial infarction, or target vessel revascularization). The incidence of 3‐year MACEs was 9.0% (406/4512). Four new PCI techniques were identified as the independent protective factors of MACEs, including second‐generation drug‐eluting stents (hazard ratio [HR], 0.61 [95% CI, 0.37–0.99]), postdilatation (HR, 0.75 [95% CI, 0.59–0.94]), final kissing balloon inflation (HR, 0.78 [95% CI, 0.62–0.99]), and using intravascular ultrasound (HR, 0.78 [95% CI, 0.63–0.97]). The relative hazard of 3‐year MACEs was reduced by ≈50% with use of all 4 techniques compared with no technique use (HR, 0.53 [95% CI, 0.32–0.87]). Conclusions PCI technological advances including postdilatation, second‐generation drug‐eluting stent, final kissing balloon inflation, and intravascular ultrasound guidance were associated with improved clinical outcomes in patients who underwent unprotected LM‐CAD PCI.

Summary: Background: Rituximab and lenalidomide is a preferred option for relapsed indolent B cell non-Hodgkin lymphoma. Obinutuzumab may be a superior combination partner with lenalidomide given enhanced antibody dependent cellular cytotoxicity and phagocytosis compared to rituximab. Our aim was to determine the recommended phase 2 dose, safety, and activity of lenalidomide in combination with fixed dose of obinutuzumab in relapsed and refractory indolent B cell non-Hodgkin lymphoma. Methods: In this single-arm, open-label, phase 1/2 trial, we enrolled patients with relapsed or refractory WHO Grade 1–3A follicular lymphoma, marginal zone lymphoma and small lymphocytic lymphoma and adequate performance status (ECOG 0–2) at the MD Anderson Cancer Center. We excluded patients with evidence of ongoing transformation to aggressive lymphoma. During phase 1, 1000 mg intravenous obinutuzumab was administered with three predefined levels of oral lenalidomide in a 3 + 3 dose escalation design to establish lenalidomide 20 mg as the recommended phase 2 dose. During phase 2, patients received induction therapy with six 28-day cycles of lenalidomide 20 mg with intravenous obinutuzumab 1000 mg. In accordance with our prior experience with lenalidomide plus rituximab, patients who were responding to the combination could receive up to 6 additional cycles (up to 12 cycles in total) of combination therapy. Dosing of obinutuzumab was continued in all responding patients after cycle 6 every 2 months for a total of 30 months from the start of therapy. The decision of number of cycles of combination therapy beyond 6 was at discretion of the investigator and was included to allow individualisation of therapy to maximise response while minimising exposure. The co-primary objectives were to evaluate the safety and overall response, defined as the proportion of patients who achieved a complete or partial response in relapsed and refractory indolent non-Hodgkin lymphoma at the end of induction therapy, according to Cheson and colleagues (2007 criteria). The secondary endpoints were complete response after induction therapy and time to event endpoints including time to progression, progression free survival, and overall survival. Analyses were intent to treat in the efficacy cohort and per-treated in the safety population in all patients who received at least one dose of either investigational agent. This trial is registered with ClinicalTrials.gov, NCT01995669. Findings: Between June 03, 2014, and 07 March 2019, we completed planned enrolment, and 66 patients started therapy including 9 patients in phase 1 and 57 patients in phase 2. All patients were evaluated for safety and the 60 patients treated at the recommended phase 2 dose of lenalidomide 20 mg were evaluable for activity. Grade 3–4 haematological toxicities included neutropenia 21% (14/66) and thrombocytopenia 11% (7/66) with no cases of febrile neutropenia. Grade 3–4 non-haematological toxicities included lung infection 8% (5/66), fatigue 8% (5/66) and rash 6% (4/66). By Cheson 2007 criteria, 90% (54/60, 95% CI: 79–96) achieved an overall response at the end of induction meeting the prespecified activity endpoint. Complete responses were seen in 33% (20/60, 95% CI: 22–47) at the end of induction. Median progression free survival, time to progression and overall survival have not been reached after median follow-up of 41.7 months. Estimated 4-year progression free survival rates were 55% (95% CI: 42–73), time to progression of 56% (95% CI: 43–74) and overall survival of 84% (95% CI: 74–95). Interpretation: Our findings suggest that oral lenalidomide with obinutuzumab is safe and highly active in patients with relapsed and refractory indolent B cell non-Hodgkin lymphoma and is associated with prolonged remission duration. The study is limited by the lack of a control arm leading to cross-trial comparisons to evaluate activity. Future randomised trials comparing this regime to rituximab and lenalidomide are warranted. Funding: Genentech and an MD Anderson Core grant.

A fundamental question in the study of happiness is whether there is neural evidence to support a well-known hypothesis that happy people are always similar while unfortunate people have their own misfortunes. To investigate this, we employed several happiness-related questionnaires to identify potential components of happiness, and further investigated and confirmed their associations with personality, mood, aggressive behaviors, and amygdala reactivity to fearful faces within a substantial sample size of college students (n = 570). Additionally, we examined the functional and morphological similarities and differences among happy individuals using the inter-subject representational similarity analysis (IS-RSA). IS-RSA emphasizes the geometric properties in a high-dimensional space constructed by brain or behavioral patterns and focuses on individual subjects. Our behavioral findings unveiled two factors of happiness: individual and social, both of which mediated the effect of personality traits on individual aggression. Subsequently, mood mediated the impact of happiness on aggressive behaviors across two subgroup splits. Functional imaging data revealed that individuals with higher levels of happiness exhibited reduced amygdala reactivity to fearful faces, as evidenced by a conventional face-matching task (n = 104). Moreover, IS-RSA demonstrated that these participants manifested similar neural activation patterns when processing fearful faces within the visual pathway, but not within the emotional network (e.g., amygdala). Morphological observations (n = 425) indicated that individuals with similar high happiness levels exhibited comparable gray matter volume patterns within several networks, including the default mode network, fronto-parietal network, visual network, and attention network. Collectively, these findings offer early neural evidence supporting the proposition that happy individuals may share common neural characteristics.

Background/aims Lipid profiles have been changed in numerous chronic conditions. The impact of uveitis on lipid metabolism remains unclear.Methods This is a cross-sectional study included 416 patients with non-infectious uveitis (NIU) and 416 healthy subjects. Standard techniques were used to measure total cholesterol (TC), triglycerides (TG), high-density lipoprotein-cholesterol (HDLc), low-density lipoprotein-cholesterol (LDLc) levels. Quantitative optical coherence tomography angiography (OCTA) parameters were obtained from 500 eyes in each group. Correlation analysis examined the relationship between lipid profile and OCTA parameters.Results Patients with NIU exhibited significantly elevated TC, TG and LDLc levels compared with controls (p=0.003; p

Abstract Background The study set out to develop an accurate and clinically valuable prognostic nomogram to assess the risk of in-hospital death in patients with acute decompensated chronic heart failure (ADCHF) and diabetes. Methods We extracted clinical data of patients diagnosed with ADCHF and diabetes from the Medical Information Mart for Intensive Care III database. Risk variables were selected utilizing least absolute shrinkage and selection operator regression analysis, and were included in multivariate logistic regression and presented in nomogram. bootstrap was used for internal validation. The discriminative power and predictive accuracy of the nomogram were estimated using the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve analysis (DCA). Results Among 867 patients with ADCHF and diabetes, In-hospital death occurred in 81 (9.3%) patients. Age, heart rate, systolic blood pressure, red blood cell distribution width, shock, β-blockers, angiotensin converting enzyme inhibitors or angiotensin receptor blockers, assisted ventilation, and blood urea nitrogen were brought into the nomogram model. The calibration curves suggested that the nomogram was well calibrated. The AUC of the nomogram was 0.873 (95% CI: 0.834–0.911), which was higher that of the Simplified Acute Physiology Score II [0.761 (95% CI: 0.711–0.810)] and sequential organ failure assessment score [0.699 (95% CI: 0.642–0.756)], and Guidelines-Heart Failure score [0.782 (95% CI: 0.731–0.835)], indicating that the nomogram had better ability to predict in-hospital mortality. In addition, the internally validated C-index was 0.857 (95% CI: 0.825–0.891), which again verified the validity of this model. Conclusions This study constructed a simple and accurate nomogram for predicting in-hospital mortality in patients with ADCHF and diabetes, especially in those who admitted to the intensive care unit for more than 48 hours, which contributed clinicians to assess the risk and individualize the treatment of patients, thereby reducing in-hospital mortality.

Abstract Aims A therapeutic strategy for chronic heart failure (HF) is to lower resting heart rate (HR). Ivabradine is a well‐known HR‐lowering agent, but limited prospective data exist regarding its use in Chinese patients. This study aimed to evaluate the effectiveness and safety of ivabradine in Chinese patients with chronic HF. Methods and results This multicentre, single‐arm, prospective, observational study enrolled Chinese patients with chronic HF. The primary outcome was change from baseline in HR at 1 and 6 months, measured by pulse counting. Effectiveness was also evaluated using laboratory tests, the Kansas City Cardiomyopathy Questionnaire (KCCQ) clinical summary score (CSS) and overall summary score (OSS), and New York Heart Association (NYHA) class. Treatment‐emergent adverse events (TEAEs) were assessed. A post hoc analysis examined the effectiveness and safety of ivabradine combined with an angiotensin receptor–neprilysin inhibitor (ARNI) or beta‐blocker. A total of 1003 patients were enrolled [mean age 54.4 ± 15.0 years, 773 male (77.1%), mean baseline HR 88.5 ± 11.3 b.p.m., mean blood pressure 115.7/74.4 ± 17.2/12.3 mmHg, mean left ventricular ejection fraction 30.9 ± 7.6%, NYHA Classes III and IV in 48.8% and 22.0% of patients, respectively]. HR decreased by a mean of 12.9 and 16.1 b.p.m. after 1 and 6 months, respectively (both P

Abstract Wireless traffic prediction is vital for intelligent cellular network operations, such as load-aware resource management and predictive control. Traditional centralized training addresses this but poses issues like excessive data transmission, disregarding delays, and user privacy. Traditional federated learning methods can meet the requirement of jointly training models while protecting the privacy of all parties’ data. However, challenges arise when the local data features among participating parties exhibit inconsistency, making the training process difficult to sustain. Our study introduces an innovative framework for wireless traffic prediction based on split learning (SL) and vertical federated learning. Multiple edge clients collaboratively train high-quality prediction models by utilizing diverse traffic data while maintaining the confidentiality of raw data locally. Each participant individually trains dimension-specific prediction models with their respective data, and the outcomes are aggregated through collaboration. A partially global model is formed and shared among clients to address statistical heterogeneity in distributed machine learning. Extensive experiments on real-world datasets demonstrate our method’s superiority over current approaches, showcasing its potential for network traffic prediction and accurate forecasting.

Abstract Background The clinical course and surgical outcomes of undifferentiated sarcomatoid carcinoma of the pancreas (USCP) remain poorly characterized owing to its rarity. This study aimed to describe the histology, clinicopathologic features, perioperative outcomes, and overall survival (OS) of 23 resected USCP patients. Methods We retrospectively described the histology, clinicopathologic features, perioperative outcomes and OS of patients who underwent pancreatectomy with a final diagnosis of USCP in a single institution. Results A total of 23 patients were included in this study. Twelve patients were male, the median age at diagnosis was 61.5 ± 13.0 years (range: 35–89). Patients with USCP had no specific symptoms and characteristic imaging findings. The R0 resection was achieved in 21 cases. The En bloc resection and reconstruction of mesenteric–portal axis was undertaken in 9 patients. There were no deaths attributed to perioperative complications in this study. The intraoperative tumor-draining lymph nodes (TDLNs) dissection was undergone in 14 patients. The 1-, 3- and 5-year survival rates were 43.5%, 4.8% and 4.8% in the whole study, the median survival was 9.0 months. Only 1 patient had survived more than 5 years and was still alive at last follow-up. The presence of distant metastasis (p = 0.004) and the presence of pathologically confirmed mesenteric–portal axis invasion (p = 0.007) was independently associated with poor OS. Conclusions USCP was a rare subgroup of pancreatic malignancies with a bleak prognosis. To make a diagnose of USCP by imaging was quite difficult because of the absence of specific manifestations. Accurate diagnosis depended on pathological biopsy, and the IHC profile of USCP was mainly characterized by co-expression of epithelial and mesenchymal markers. A large proportion of patients have an early demise, especially for patients with distant metastasis and pathologically confirmed mesenteric–portal axis invasion. Long-term survival after radical resection of USCPs remains rare.

ABSTRACTOxidative stress and neuronal dysfunction caused by intracerebral haemorrhage (ICH) can lead to secondary injury. The m6A modification has been implicated in the progression of ICH. This study aimed to investigate the role of the m6A reader YTHDC2 in ICH-induced secondary injury. ICH models were established in rats using autologous blood injection, and neuronal cell models were induced with Hemin. Experiments were conducted to overexpress YTH domain containing 2 (YTHDC2) and examine its effects on neuronal dysfunction, brain injury, and neuronal ferritinophagy. RIP-qPCR and METTL3 silencing were performed to investigate the regulation of YTHDC2 on nuclear receptor coactivator 4 (NCOA4). Finally, NCOA4 overexpression was used to validate the regulatory mechanism of YTHDC2 in ICH. The study found that YTHDC2 expression was significantly downregulated in the brain tissues of ICH rats. However, YTHDC2 overexpression improved neuronal dysfunction and reduced brain water content and neuronal death after ICH. Additionally, it reduced levels of ROS, NCOA4, PTGS2, and ATG5 in the brain tissues of ICH rats, while increasing levels of FTH and FTL. YTHDC2 overexpression also decreased levels of MDA and Fe2+ in the serum, while promoting GSH synthesis. In neuronal cells, YTHDC2 overexpression alleviated Hemin-induced injury, which was reversed by Erastin. Mechanistically, YTHDC2-mediated m6A modification destabilized NCOA4 mRNA, thereby reducing ferritinophagy and alleviating secondary injury after ICH. However, the effects of YTHDC2 were counteracted by NCOA4 overexpression. Overall, YTHDC2 plays a protective role in ICH-induced secondary injury by regulating NCOA4-mediated ferritinophagy.

Background: Serum concentration of soluble growth stimulation expressed gene 2 (sST2) appears to have prognostic value in patients with aneurysmal subarachnoid hemorrhage (aSAH) by now. This study aimed to investigate the relationship between cerebrospinal fluid (CSF) sST2 concentration and outcome in patients with aSAH. Methods: A total of 65 aSAH patients who met the inclusion criteria in the Neurosurgery Department of Jining No.1 People's Hospital from March 2021 to August 2022 were selected as the research objects. 35 patients with the third month Modified-Rankin-Scale (mRS) score of 0–2 were divided into good prognosis group, and 30 patients with the third month mRS score of 3–5 were divided into poor prognosis group. CSF was collected by lumbar puncture for the first 5 days after aneurysm surgery. CSF sST2 concentration was determined using an enzyme-linked immunosorbent assay. Results: In all patients, CSF sST2 concentrations initially increased, peaked on day 2, and then decreased. Compared with the good prognosis group, the sST2 concentration was significantly increased in the poor prognosis group at 1, 2, 3, 4 and 5 days after aSAH surgery. CSF sST2 concentration exhibited good diagnostic performance for predicting outcome (area under the receiver operating characteristic curve = 0.988). Additionally, CSF sST2 concentration has good performance for predicting cerebral edema, but only in the poor prognosis group (area under the curve = 0.93). Conclusions: Elevated CSF sST2 concentration is associated with poor outcome in aSAH patients. CSF sST2 may have a role as a predictive biomarker in these patients.

Changes in land use and land cover (LULC) are critical for evaluating global spatiotemporal trends, especially regarding climate change and urbanization. This study investigates the dynamics of Landsat surface temperature (LST) in response to LULC changes and their effects on the seasonal microclimate in Kasur District, Pakistan. Using the Google Earth Engine platform, we employed a random forest algorithm to detect LULC changes (cropland, forest, built-up, fallow, barren, and water) and analyze seasonal spectral indices from Landsat imagery for 1988, 2002, and 2022. Significant LULC changes were observed, including a 9.8% increase in built-up areas, a 4.2% decrease in cropland, and a 1.4% decrease in forested areas, linked to urban heat island effects and population growth. Additionally, there was a 2.7% increase in fallow and open land, contributing to the district's impervious surface area. Significant correlations (p < 0.001) were found between LST and spectral indices—normalized difference vegetation index, enhanced vegetation index, and normalized difference built index (NDBI)—ranging from 0.7 to 0.8 in both winter and summer. In summer, the maximum LST increased from 43 °C in 1988 to 44 °C in 2002, with a linear correlation (R²) increase from 0.57 to 0.75 and a polynomial correlation (R²) increase from 0.63 to 0.76 with NDBI from 1988 to 2022. Understanding these dynamics is crucial as LULC changes and the resulting temperature variations have significant implications for local climate, agriculture, and human health. This study underscores the need for effective LULC policies to mitigate impacts, protect vegetation cover, and ensure sustainable land management. These findings provide valuable insights for policymakers and urban planners aiming to balance development with environmental sustainability.

Long-term failures in flexible converter valve equipment pose significant risks, potentially compromising operational efficiency or leading to complete malfunction. Accurately identifying equipment faults is essential to improve overall reliability and minimize downtime. This study introduces an innovative fault diagnosis method utilizing an attention mechanism. The method integrates a lightweight model incorporating one-dimension depthwise convolutional layers for spatial feature extraction and bidirectional long short-term memory for capturing temporal dynamics. A pioneering time-channel joint attention module enhances the extraction of fault-related data from time series and channel maps. Experimental results underscore the method’s efficacy in fault diagnosis under varying Gaussian noise conditions. Notably, the approach demonstrates remarkable consistency in accuracy across various experimental setups, underscoring its robust performance and potential applicability in real-world scenarios where reliability is critical. In addition, the proposed method has a moderate number of parameters and training time, indicating that the model can be embedded in front-end equipment.

Abstract Background An appropriate prediction model for adverse prognosis before peritoneal dialysis (PD) is lacking. Thus, we retrospectively analysed patients who underwent PD to construct a predictive model for adverse prognoses using machine learning (ML). Methods A retrospective analysis was conducted on 873 patients who underwent PD from August 2007 to December 2020. A total of 824 patients who met the inclusion criteria were included in the analysis. Five commonly used ML algorithms were used for the initial model training. By using the area under the curve (AUC) and accuracy (ACC), we ranked the indicators with the highest impact and displayed them using the values of Shapley additive explanation (SHAP) version 0.41.0. The top 20 indicators were selected to build a compact model that is conducive to clinical application. All model-building steps were implemented in Python 3.8.3. Results At the end of follow-up, 353 patients withdrew from PD (converted to haemodialysis or died), and 471 patients continued receiving PD. In the complete model, the categorical boosting classifier (CatBoost) model exhibited the strongest performance (AUC = 0.80, 95% confidence interval [CI] = 0.76–0.83; ACC: 0.78, 95% CI = 0.72–0.83) and was selected for subsequent analysis. We reconstructed a compression model by extracting 20 key features ranked by the SHAP values, and the CatBoost model still showed the strongest performance (AUC = 0.79, ACC = 0.74). Conclusions The CatBoost model, which was built using the intelligent analysis technology of ML, demonstrated the best predictive performance. Therefore, our developed prediction model has potential value in patient screening before PD and hierarchical management after PD.

Abstract Cockroaches are considered mechanical transmitters of infectious diseases, posing a threat to human health. This study assessed the potential of cockroaches in food-related environments to mechanically transmit intestinal pathogens. Cockroaches captured with traps were placed together into a low temperature refrigerator at − 80° for 2 h. Standard taxonomic keys and Fluorescent quantitative PCR techniques were applied for species identification and digestive tract etiological examination. A total of 360 cockroach traps were placed, with a positive rate of 20.8%, and 266 cockroaches were captured. In general, compared with other places and areas, the degree of infestation of cockroaches was more serious in catering places and kitchens. Blattella germanica were most found in catering places (40.2%), followed by Periplaneta fuliginosa in schools (22.2%). According to the life stage, among the 128 cockroach samples, 23 were positive for nymphs and 13 were positive for adults. There were statistically significant differences in the intestinal pathogen detection rates between nymphs and adults (P

Abstract Intelligent reflecting surface (IRS) stands as a promising technology to revolutionize wireless communication by manipulating incident signal amplitudes and phases to enhance system performance. While existing research primarily centers around optimizing the phase shifts of IRS, the deployment of IRS on movable platforms introduces a new degree of freedom in the design of IRS-assisted systems. Leveraging flexible deployment strategies for IRS holds the potential to further amplify network throughput and extend coverage. This paper addresses the challenging non-convex joint optimization problem of the movable IRS and proposes a dynamic optimization algorithm based on proximal policy optimization (PPO) for dynamically optimizing the aerial position and phase configuration of IRS. Simulation results show the effectiveness of the proposed approach, demonstrating significant performance improvements compared to communication schemes without IRS assistance and conventional static IRS-assisted methods.

Abstract Aerial base stations (AeBS), as crucial components of air-ground integrated networks, can serve as the edge nodes to provide flexible services to ground users. Optimizing the deployment of multiple AeBSs to maximize system energy efficiency is currently a prominent and actively researched topic in the AeBS-assisted edge-cloud computing network. In this paper, we deploy AeBSs using multi-agent deep reinforcement learning (MADRL). We describe the multi-AeBS deployment challenge as a decentralized partially observable Markov decision process (Dec-POMDP), taking into consideration the constrained observation range of AeBSs. The hypergraph convolution mix deep deterministic policy gradient (HCMIX-DDPG) algorithm is designed to maximize the system energy efficiency. The proposed algorithm uses the value decomposition framework to solve the lazy agent problem, and hypergraph convolutional (HGCN) network is introduced to strengthen the cooperative relationship between agents. Simulation results show that the suggested HCMIX-DDPG algorithm outperforms alternative baseline algorithms in the multi-AeBS deployment scenario.

Abstract Radiotherapy is an important strategy in the comprehensive treatment of esophageal squamous cell carcinoma (ESCC). However, effectiveness of radiotherapy is still restricted by radioresistance. Herein, we aimed to understand the mechanisms underlying ESCC radioresistance, for which we looked into the potential role of YY1. YY1 was upregulated in radioresistant tissues and correlated with poor prognosis of patients with ESCC. YY1 depletion enhanced the radiosensitivity of ESCC in vitro and in vivo. Multi-group sequencing showed that downregulation of YY1 inhibited the transcriptional activity of Kinesin Family Member 3B (KIF3B), which further activated the Hippo signaling pathway by interacting with Integrin-beta1 (ITGB1). Once the Hippo pathway was activated, its main effector, Yes-associated protein 1 (YAP1), was phosphorylated in the cytoplasm and its expression reduced in the nucleus, thus enhancing the radiosensitivity by regulating its targeted genes. Our study provides new insights into the mechanisms underlying ESCC radioresistance and highlights the potential role of YY1 as a therapeutic target for ESCC.

Abstract Chimeric antigen receptor T-cell therapy (CAR-T) has been successful in treating relapsed/refractory B-cell lymphomas. However, its role in the treatment of diseases involving the central nervous system (CNS) is not well studied. We performed a multicenter retrospective cohort study to evaluate the outcomes of patients with secondary CNS lymphoma (SCNSL) who received CAR-T. Eligibility required active CNSL at the time of apheresis. The objectives included evaluation of overall survival (OS), progression-free survival (PFS), identification of predictors of complete response (CR) post-CAR-T, and assessment of risk factors for cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). Sixty-one patients were included in the analysis. The overall response rate was 68% with a CR rate of 57%. In the multivariable analysis, patients who experienced any grade CRS had higher odds of achieving CR (OR = 3.9, 95% CI = 1.01–15.39, p = 0.047). The median PFS was 3.3 months (95% CI = 2.6–6.0 months) with 6- and 12-month PFS rates of 35% and 16%, respectively. The median OS was 7.6 months (95% CI = 5.0–13.5 months) with 6- and 12-month OS rates of 59% and 41%, respectively. Any grade CRS and ICANS were 70% (n = 43) and 57% (n = 34), respectively with grade ≥ 3 CRS and ICANS rates of 16% and 44%. Factors associated with increased risk of CRS and ICANS included receiving axi-cel or having leptomeningeal ± parenchymal + CNS involvement, respectively. Despite achieving high response rates, most patients experience early relapse or death following CAR-T in SCNSL. The current study provides a benchmark for future trials exploring novel therapeutic options in SCNSL.

In order to develop nutrient rich personalized food, the effects of different guar gum concentrations on rheological, gelation, 3D printing, microstructural properties and functional groups of purple sweet potato gels were explored by rheological analysis, scanning electron microscopy and Fourier transform infrared spectroscopy. The results showed that apparent viscosity, storage modulus, loss modulus, L*, gumminess and chewiness of purple sweet potato gels increased, the micro pore size decreased, and the gel network structure was denser with the increase of guar gum concentration. The water holding capacity of purple sweet potato gels was 80.49% and the gel strength was 72.67 g when guar gum concentration was 1.6%. The addition of guar gum significantly improved 3D printability of purple sweet potato gels. When guar gum was added at 1.2% and 1.6%, 3D printed purple sweet potato gels had good formability, the average accuracy deviation was less than 1%, and the stability deviation was less than 5% after 6 hours of storage. The addition of guar gum would not produce new functional groups in 3D printed purple sweet potato gels, but mainly strengthened interactions of CH2 bonds and O-H bonds. This study provided a theoretical basis for the development of 3D printing of plant-based ingredients, which was very important for the personalization of functional foods.

Abstract INTRODUCTION Patients with Alzheimer's disease present with difficulty in lexical retrieval and reversal of the concreteness effect in nouns. Little is known about the phenomena before the onset of symptoms. We anticipate early linguistic signs in the speech of people who suffer from amnestic mild cognitive impairment (MCI). Here, we report the results of a corpus‐linguistic approach to the early detection of cognitive impairment. METHODS One hundred forty‐eight English‐speaking Singaporeans provided natural speech data, on topics of their choice; 74 were diagnosed with single‐domain MCI (38 amnestic, 36 non‐amnestic), 74 cognitively healthy. The recordings yield 267,310 words, which are tagged for parts of speech. We calculate the per‐minute word counts and concreteness scores of all tagged words, nouns, and verbs in the dataset. RESULTS Compared to controls, subjects with amnestic MCI produce fewer but more abstract nouns. Verbs are not affected. DISCUSSION Slower retrieval of nouns and the reversal of the concreteness effect in nouns are manifested in natural speech and can be detected early through corpus‐based analysis. Highlights Reversal of the concreteness effect is manifested in patients with Alzheimer's disease (AD) and semantic dementia. The paper reports a corpus‐based analysis of natural speech by people with amnestic and non‐amnestic mild cognitive impairment (MCI) and cognitively healthy controls. People with amnestic MCI produce fewer and more abstract nouns than people with non‐amnestic MCI and healthy controls. Verbs appear to be unaffected. The imageability problem can be detected in natural everyday speech by people with amnestic MCI, which carries a higher risk of conversion to AD.

Introduction: Precise fault diagnosis is crucial for enhancing the reliability and lifespan of the flexible converter valve equipment. To address this issue, depthwise separable convolution, bidirectional gate recurrent unit, and multi-head attention module (DSC-BiGRU-MAM) based fault diagnosis approach is proposed.Methods: By DSC and BiGRU operation, the model can capture the correlation between local features and temporal information when processing sequence data, thereby enhancing the representation ability and predictive performance of the model for complex sequential data. In addition, by incorporating a multi-head attention module, the proposed method dynamically learns important information from different time intervals and channels. The proposed MAM continuously stimulates fault features in both time and channel dimensions during training, while suppressing fault independent expressions. As a result, it has made an important contribution to improving the performance of the fault diagnosis model.Results and Discussion: Experimental results demonstrate that the proposed method achieves higher accuracy compared to existing methods, with an average accuracy of 95.45%, average precision of 88.67%, and average recall of 89.03%. Additionally, the proposed method has a moderate number of model parameters (17,626) and training time (935 s). Results indicate that the proposed method accurately diagnoses faults in flexible converter valve equipment, especially in real-world situations with noise overlapping signals.

Purpose: To explore the association between the cause of amblyopia and pre-treatment contrast sensitivity, stereoacuity, fixation and nystagmus. Design: Retrospective cohort study. Methods: A retrospective review was conducted for 3408 patients with amblyopia who had not yet started amblyopia treatment utilizing a large amblyopia patient database maintained at Zhongshan Ophthalmic Centre. Six amblyogenic factor subtypes were identified: anisometropia, isoametropia, strabismus, anisometropia and strabismus, monocular visual deprivation, and binocular visual deprivation amblyopia. Monocular best corrected visual acuity (BCVA), the contrast sensitivity function (CSF), fixation, and stereopsis were compared between the subtypes before and after propensity score matching (PSM) for age and sex. Results: The two deprivation groups had poorer BCVA and CSF than the other groups. There were no systematic differences in CSF between the non-deprivation groups. Nystagmus was more common in the bilateral amblyopia groups compared to the monocular amblyopia groups. Eccentric fixation was uncommon with the exception of the anisometropia and strabismus group which had an eccentric fixation rate of 20%. Distance stereoacuity measured without monocular cues was absent for almost all patients. The results were consistent when analyzed using PSM. Conclusion: Visual deprivation causes more severe amblyopia than other amblyogenic factors. For non-deprivation amblyopia subtypes, individual differences such as variation in the severity of the amblyogenic factor might be more important in determining pre-treatment vision than whether amblyopia was caused by refractive error, strabismus or both.

The thermal performance of a flat plate solar collector (FPSC) is a critical indicator that depends on the environment, operational parameters, and dimensions. This study examines the impact of size on thermal performance improvement mechanisms. Firstly, numerical simulation models are introduced as the foundation for optimization research. This involves analyzing the flow resistance of microchannels and defining their structural parameters. Furthermore, experimental tests were conducted on a stainless steel flat plate solar collector (S/S FPSC) with the best design parameters to validate the accuracy of the mathematical model during the design phase. The results indicate that increasing the width of the microchannel and the height of corrugations can effectively enhance the thermal performance of the S/S FPSC. The momentary efficiency is projected to reach a remarkable 86.10% under ideal circumstances. Additionally, a mathematical expression was proposed to establish the relationship between the surrounding conditions and the momentary efficiency of the S/S FPSC. Moreover, the microchannel comprises S/S material, maintaining a homogeneous temperature distribution to maximize heat absorption. The use of stainless steel also extends the lifespan of the FPSC.

Soil nitrogen (N) availability is one of the limiting factors of crop productivity, and it is strongly influenced by global change and agricultural management practices. However, very few studies have assessed how the winter drought affected soil N availability during the subsequent growing season under chemical fertilization. We conducted a field investigation involving snow removal to simulate winter drought conditions in a Mollisol cropland in Northeast China as part of a 6-year fertilization experiment, and we examined soil physicochemical properties, microbial characteristics, and N availability. Our results demonstrated that chemical fertilization significantly increased soil ammonium and total N availability by 42.9 and 90.3%, respectively; a combined winter drought and fertilization treatment exhibited the highest soil N availability at the end of the growing season. As the growing season continued, the variation in soil N availability was explained more by fertilization than by winter drought. The Mantel test further indicated that soil Olsen-P content and microbial carbon use efficiency (CUE) were significantly related to soil ammonium availability. A microbial community structure explained the largest fraction of the variation in soil nitrate availability. Microbial CUE showed the strongest correlation with soil N availability, followed by soil available C:P and bacteria:fungi ratios under winter drought and chemical fertilization conditions. Overall, we clarified that, despite the weak effect of the winter drought on soil N availability, it cannot be ignored. Our study also identified the important role of soil microorganisms in soil N transformations, even in seasonally snow-covered northern croplands.

Exosomes, vesicular structures originating from cells, participate in the conveyance of proteins and nucleic acids. Presently, the centrality of epigenetic modifications in neurological disorders is widely acknowledged. Exosomes exert influence over various epigenetic phenomena, thereby modulating post-transcriptional regulatory processes contingent upon their constituent makeup. Consequently, the heightened attention directed toward exosomes as instigators of epigenetic alterations has burgeoned in recent years. Notably, exosomes serve as vehicles for delivering methyltransferases to recipient cells. More significantly, non-coding RNAs, particularly microRNAs (miRNAs), represent pivotal contents within exosomes, wielding the capacity to influence the expression of diverse factors within the cerebral milieu. The transfer of these exosomal contents amidst brain cells, encompassing neuronal cells and microglia, assumes a critical role in the genesis and progression of neurological disorders, also, this role is not limited to neurological disorders, it may deal with any human disease, such as cancer, and cardiovascular diseases. This review will concentrate on elucidating the regulation of exosome-induced epigenetic events and its subsequent ramifications for neurological diseases. A more profound comprehension of the involvement of exosome-mediated epigenetic regulation in neurological disorders contributes to a heightened awareness of the etiology and advancement of cerebral afflictions.

IntroductionWe have demonstrated that transposons derived from ctDNA can be transferred between cancer cells. The present research aimed to investigate the cellular uptake and intracellular trafficking of Multiple Myeloma-zip code (MM-ZC), a cell-specific zip code, in myeloma cell lines. We demonstrated that MM-ZC uptake by myeloma cells was concentration-, time- and cell-type-dependent.MethodsFlow cytometry and confocal microscopy methods were used to identify the level of internalization of the zip codes in MM cells. To screen for the mechanism of internalization, we used multiple inhibitors of endocytosis. These experiments were followed by biotin pulldown and confocal microscopy for validation. Single interference RNA (siRNA) targeting some of the proteins involved in endocytosis was used to validate the role of this pathway in ZC cell internalization.ResultsEndocytosis inhibitors identified that Monensin and Chlorpromazine hydrochloride significantly reduced MM-ZC internalization. These findings suggested that Clathrin-mediated endocytosis and endosomal maturation play a crucial role in the cellular uptake of MM-ZC. Biotin pulldown and confocal microscopic studies revealed the involvement of proteins such as Clathrin, Rab5a, Syntaxin-6, and RCAS1 in facilitating the internalization of MM-ZC. Knockdown of Rab5a and Clathrin proteins reduced cellular uptake of MM-ZC and conclusively demonstrated the involvement of Clathrin-Rab5a pathways in MM-ZC endocytosis. Furthermore, both Rab5a and Clathrin reciprocally affected their association with MM-ZC when we depleted their proteins by siRNAs. Additionally, the loss of Rab5a decreased the Syntaxin-6 association with MMZC but not vice versa. Conversely, MM-ZC treatment enhanced the association between Clathrin and Rab5a.ConclusionOverall, the current study provides valuable insights into the cellular uptake and intracellular trafficking of MM-ZC in myeloma cells. Identifying these mechanisms and molecular players involved in MM-ZC uptake contributes to a better understanding of the delivery and potential applications of cell-specific Zip-Codes in gene delivery and drug targeting in cancer research.

We investigated the effect of melatonin on bisphenol A (BPA)-induced oxidative stress damage in testicular tissue and Leydig cells. Mice were gavaged with 50 mg/kg BPA for 30 days, and concurrently, were injected with melatonin (10 mg/kg and 20 mg/kg). Leydig cells were treated with 10 μmol/L of BPA and melatonin. The morphology and organ index of the testis and epididymis were observed and calculated. The sperm viability and density were determined. The expressions of melatonin receptor 1A and luteinizing hormone receptor, and the levels of malonaldehyde, antioxidant enzymes, glutathione, steroid hormone synthases, aromatase, luteinizing hormone, testosterone, and estradiol were measured. TUNEL assay was utilized to detect testicular cell apoptosis. The administration of melatonin at 20 mg/kg significantly improved the testicular index and epididymis index in mice treated with BPA. Additionally, melatonin promoted the development of seminiferous tubules in the testes. Furthermore, the treatment with 20 mg/kg melatonin significantly increased sperm viability and sperm density in mice, while also promoting the expressions of melatonin receptor 1A and luteinizing hormone receptor in Leydig cells of BPA-treated mice. Significantly, melatonin reduced the level of malonaldehyde in testicular tissue and increased the expression of antioxidant enzymes (superoxide dismutase 1, superoxide dismutase 2, and catalase) as well as the content of glutathione. Moreover, melatonin also reduced the number of apoptotic Leydig cells and spermatogonia, aromatase expression, and estradiol level, while increasing the expression of steroid hormone synthases (steroidogenic acute regulatory protein, cytochrome P450 family 17a1, cytochrome P450 17α-hydroxylase/20-lyase, and, 17β-hydroxysteroid dehydrogenase) and the level of testosterone. Melatonin exhibited significant potential in alleviating testicular oxidative stress damage caused by BPA. These beneficial effects may be attributed to melatonin’s ability to enhance the antioxidant capacity of testicular tissue, promote testosterone synthesis, and reduce testicular cell apoptosis.

Background: Type 2 diabetes mellitus (T2DM) and inflammatory bowel disease (IBD) have been associated, according to various epidemiological research. This study uses Mendelian randomization (MR) to investigate the causal link between T2DM and IBD.Methods: To investigate the causal relationship between IBD and T2DM risk using European population data from the genome-wide association study (GWAS) summary datasets, we constructed a two-sample MR study to evaluate the genetically predicted impacts of liability towards IBD outcomes on T2DM risk. As instrumental variables (IVs), we chose 26 single nucleotide polymorphisms (SNPs) associated with IBD exposure data. The European T2DM GWAS data was obtained from the IEU OpenGWAS Project database, which contains 298,957 cases as the outcome data. The causal relationship between T2DM and IBD using a reverse MR analysis was also performed.Results: The two-sample MR analysis, with the Bonferroni adjustment for multiple testing, revealed that T2DM risk in Europeans is unaffected by their IBD liability (odds ratio (OR): 0.950–1.066, 95% confidence interval (CI): 0.885–1.019, p = 0.152–0.926). The effects of liability to T2DM on IBD were not supported by the reverse MR analysis either (OR: 0.739–1.131, 95% confidence interval (CI): 0.651–1.100, p = 0.058–0.832). MR analysis of IBS on T2DM also have no significant causal relationship (OR: 0.003–1.007, 95% confidence interval (CI): 1.013–5.791, p = 0.069–0.790). FUMA precisely mapped 22 protein-coding genes utilizing significant SNPs of T2DM acquired from GWAS.Conclusion: The MR study showed that the existing evidence did not support the significant causal effect of IBD on T2DM, nor did it support the causal impact of T2DM on IBD.

Abstract Aerial base stations (AeBSs), as crucial components of air-ground integrated networks, are widely employed in cloud computing, disaster relief, and various applications. How to quickly and efficiently deploy multi-AeBSs for higher capacity gain has become a key research issue. In this paper, we address the 3D deployment optimization problem of multi-AeBSs with the objective of maximizing system capacity. To overcome communication overhead and privacy challenges in multi-agent deep reinforcement learning (MADRL), we propose a federated deep deterministic policy gradient (Fed-DDPG) algorithm for the multi-AeBS deployment decision. Specifically, a high-altitude platform (HAP)-assisted multi-AeBS deployment architecture is designed, in which low-altitude AeBS act as the local nodes to train its own deployment decision model, while the HAP acts as the global node to aggregate the weights of local models. In this architecture, AeBSs do not exchange raw data, addressing data privacy concerns and reducing communication overhead. Simulation results show that the proposed algorithm outperforms fully distributed MADRL algorithms and closely approximates the performance of multi-agent deep deterministic policy gradient (MADDPG), which requires global information during training, but with less training time.

Abstract The interaction between cerebral endothelial cells (CEC) and brain parenchymal cells is critical to maintain neurovascular homeostasis, whereas extracellular vesicles (EVs) are essential to mediate the cell–cell communication. Previous researches demonstrated that CEC-derived EVs (CEC-EVs) confer neuroprotective actions. However, the molecular mechanisms remain unknown. In this study, we isolated EVs from CEC and assessed their immune-regulatory actions in microglial cells and mice following lipopolysaccharide (LPS) exposure. We found that CEC-EVs treatment significantly ameliorated LPS-induced inflammatory activation, shifting microglial polarization from pro-inflammatory phenotype to anti-inflammatory phenotype. Meanwhile, microglial cells can effectively internalize CEC-EVs and this process was further enhanced by immune activation. Next, the miRNA microarray analysis revealed that CEC-EVs increased expression of miR-672-5p, which was demonstrated to be the cargo of CEC-EVs. TGFβ-activated kinase 1 (TAK1)-binding proteins 2 (TAB2) was identified to be the target of miR-672-5p. Through inhibiting TAB2, miR-672-5p derived from CEC-EVs suppressed TAK1-TAB signaling and thereby mitigating the downstream NF-κB activation. Furthermore, we found that by delivering miR-672-5p, CEC-EVs promoted autophagy and hence stimulating autophagic degradation of NLRP3 inflammasome. Our work firstly revealed the neuroimmune-modulating actions of CEC-EVs and further demonstrated that miR-672-5p secreted from CEC-EVs inhibits microglial pro-inflammatory polarization and facilitates autophagic process via targeting TAB2.

With a large amount of new energy access and the wide application of high voltage direct current (HVDC) transmission technology based on line commutated converter (LCC), it is of great significance to study the impedance frequency characteristics of the converter to analyze the stability of the LCC-HVDC system. Due to the complexity and inefficiency of the existing modeling techniques, in this paper, a simplified impedance modeling method for the DC side of LCC based on the simplified switching function is proposed. Firstly, the commutation process of LCC is deduced according to the converter valve opening sequence and circuit principle, and the simplified switching function of LCC is proposed. Next, based on the dynamic phasor method, through the analysis and calculation of harmonic transmission between the AC and DC sides of LCC, the simplified impedance of the DC side of LCC is obtained. Then, a simulation model is established in PSCAD, and the impedance scanning results of the simulation model show that the error is small between the method proposed in this paper and the method without simplification, which verifies the validity of the proposed model. The proposed method can reduce modeling complexity and provide a fast calculation model of the DC side impedance of LCC for analyzing the stability of large complex transmission systems.

Abstract Background To explore the impact of preoperative 3D printing on the fixation of posterior rib fractures utilizing a memory alloy embracing device of rib under thoracoscopy. Methods The enrolled patients were divided into the 3D printing (11 patients) and the non-3D printing (18 patients) groups, based on whether a 3D model of ribs was prepared prior to surgery. Analysis was conducted comparing the average fixation time per fracture, postoperative fixation loss, and poor reduction of fractured end between the two groups. Results The average fixation time of each fracture was 27.2 ± 7.7 min in the 3D printing group and 29.3 ± 8.2 min in the non-3D printing group, with no statistically significant difference observed between the two groups (P > 0.05). The incidence of poor fracture fixation in the 3D printing group was statistically lower than that in the non-3D printing group (12.9% vs. 44.7%, P 0.05), and the dislocation rate of the fractured end was (9.7% vs. 31.9%, P

Abstract To explore the minds of others, which is traditionally referred to as Theory of Mind (ToM), is perhaps the most fundamental ability of humans as social beings. Impairments in ToM could lead to difficulties or even deficits in social interaction. The present study focuses on two core components of ToM, the ability to infer others’ beliefs and the ability to infer others’ emotions, which we refer to as cognitive and affective ToM respectively. Charting both typical and atypical trajectories underlying the cognitive-affective ToM promises to shed light on the precision identification of mental disorders, such as depressive disorders (DD) and autism spectrum disorder (ASD). However, most prior studies failed to capture the underlying processes involved in the cognitive-affective ToM in a fine-grained manner. To address this problem, we propose an innovative conceptual framework, referred to as visual theory of mind (V-ToM), by constructing visual scenes with emotional and cognitive meanings and by depicting explicitly a four-stage process of how humans make inferences about the beliefs and emotions of others. Through recording individuals’ eye movements while looking at the visual scenes, our model enables us to accurately measure each stage involved in the computation of cognitive-affective ToM, thereby allowing us to infer about potential difficulties that might occur in each stage. Our model is based on a large sample size (n > 700) and a novel audio-visual paradigm using visual scenes containing cognitive-emotional meanings. Here we report the obtained differential features among healthy controls, DD and ASD individuals that overcome the subjectivity of conventional questionnaire-based assessment, and therefore could serve as valuable references for mental health applications based on AI-aided digital medicine.

The persistent increase in forest pest outbreaks requires timely detection methods to monitor the disaster precisely. However, early detection is challenging due to insufficient temporal observation and subtle tree changes. This article proposed a novel framework that collaborates multi-source remote sensing data and uses a change detection algorithm to archive early detection of infestation caused by Dendrolimus tabulaeformis Tsai et Liu (D. tabulaeformis) attacks. First, all available Sentinel-2 images with less than 20% cloud cover were utilized. During periods with long intervals (>16 days) between Sentinel-2 images, Landsat-8 images with less than 20% cloud cover were downscaled to a spatial resolution of 10 m using a deep learning algorithm to meet the requirement for a high temporal frequency of clear observations. Second, the spectral index differences between healthy and infested trees were examined to address the challenge of detecting subtle changes in pest attacks. The Enhanced Vegetation Index (EVI) was selected for early defoliation detection. On this basis, the EWMACD (Exponentially Weighted Moving Average Change Detection) algorithm, which is sensitive to subtle changes, was enhanced to improve the capability of detecting early D. tabulaeformis attacks. The assessment showed that the overall accuracy of the change detection (F1 score) reached 0.86 during the early stage and 0.88 during the late stage. The temporal accuracy (Precision) was 84.1% during the early stage. The accuracy significantly improved compared to using a single remote sensing data source. This study presents a new framework capable of monitoring early forest defoliation caused by D. tabulaeformis attacks and offering opportunities for predicting future outbreaks and implementing preventive measures.