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•AD patients exhibit brain dysregulation in emotion, cognition and decision regions.•Alterations in regions like left ITG, STG, ORBsup, etc., may indicate anxious depression.•Predictive model differentiated anxious from non-anxious MDD with an AUC of 0.802. Anxious depression is a common subtype of major depressive disorder (MDD) associated with adverse outcomes and severely impaired social function. It is important to clarify the underlying neurobiology of anxious depression to refine the diagnosis and stratify patients for therapy. Here we explored associations between anxiety and brain structure/function in MDD patients. A total of 260 MDD patients and 127 healthy controls underwent three-dimensional T1-weighted structural scanning and resting-state functional magnetic resonance imaging. Demographic data were collected from all participants. Differences in gray matter volume (GMV), (fractional) amplitude of low-frequency fluctuation ((f)ALFF), regional homogeneity (ReHo), and seed point-based functional connectivity were compared between anxious MDD patients, non-anxious MDD patients, and healthy controls. A random forest model was used to predict anxiety in MDD patients using neuroimaging features. Anxious MDD patients showed significant differences in GMV in the left middle temporal gyrus and ReHo in the right superior parietal gyrus and the left precuneus than HCs. Compared with non-anxious MDD patients, patients with anxious MDD showed significantly different GMV in the left inferior temporal gyrus, left superior temporal gyrus, left superior frontal gyrus (orbital part), and left dorsolateral superior frontal gyrus; fALFF in the left middle temporal gyrus; ReHo in the inferior temporal gyrus and the superior frontal gyrus (orbital part); and functional connectivity between the left superior temporal gyrus(temporal pole) and left medial superior frontal gyrus. A diagnostic predictive random forest model built using imaging features and validated by 10-fold cross-validation distinguished anxious from non-anxious MDD with an AUC of 0.802. Patients with anxious depression exhibit dysregulation of brain regions associated with emotion regulation, cognition, and decision-making, and our diagnostic model paves the way for more accurate, objective clinical diagnosis of anxious depression.

Purpose Suicidal ideation (SI) is a major public health concern, especially in patients with major depressive disorder (MDD). Although various psychosocial factors are associated with SI, the complex interrelationships among childhood trauma (CT), anxiety symptoms, depressive symptoms, and anhedonia remain inadequately understood. This study examined these relationships and their associations with SI. Methods This cross-sectional study included 782 patients with MDD consecutively recruited from the inpatient and outpatient clinics of the Department of Psychiatry at Renmin Hospital of Wuhan University between April 2019 and August 2023. Assessments were conducted using validated Chinese versions of the Childhood Trauma Questionnaire-Short Form, Hamilton Anxiety Rating Scale, Snaith-Hamilton Pleasure Scale, Hamilton Depression Scale, Patient Health Questionnaire-15, and Life Event Scale. Statistical analyses comprised chi-square tests, t-tests, binary logistic regression, Pearson’s correlation analysis, and structural equation modeling (SEM). Results Anxiety symptoms were present in 425 patients (54.35%), of whom 84.24% reported SI. Patients with anxiety symptoms demonstrated significant differences in emotional neglect, physical neglect, emotional abuse, physical abuse, anhedonia, depressive symptoms, somatic symptoms, negative life events, and SI compared to those without anxiety. SEM analysis indicated direct associations of CT, depressive symptoms, and anhedonia with SI. Additionally, anxiety symptoms showed indirect associations with SI, linked through their connections with CT, anhedonia, and depressive symptoms. Conclusions The findings highlight the clinical relevance of assessing CT and the interrelated symptom cluster of anxiety, anhedonia, and depression in MDD patients with SI. This supports the consideration of integrated treatment strategies that concurrently address these domains. Clinical trial number Not applicable.

ABSTRACTBackgroundCortical morphometry is an intermediate phenotype that is closely related to the genetics and onset of major depressive disorder (MDD), and cortical morphometric networks are considered more relevant to disease mechanisms than brain regions. We sought to investigate changes in cortical morphometric networks in MDD and their relationship with genetic risk in healthy controls. MethodsWe recruited healthy controls and patients with MDD of Han Chinese descent. Participants underwent DNA extraction and magnetic resonance imaging, including T1-weighted and diffusion tensor imaging. We calculated polygenic risk scores (PRS) based on previous summary statistics from a genome-wide association study of the Chinese Han population. We used a novel method based on Kullback–Leibler divergence to construct the morphometric inverse divergence (MIND) network, and we included the classic morphometric similarity network (MSN) as a complementary approach. Considering the relationship between cortical and white matter networks, we also constructed a streamlined density network. We conducted group comparison and PRS correlation analyses at both the regional and network level. ResultsWe included 130 healthy controls and 195 patients with MDD. The results indicated enhanced connectivity in the MIND network among patients with MDD and people with high genetic risk, particularly in the somatomotor (SMN) and default mode networks (DMN). We did not observe significant findings in the MSN. The white matter network showed disruption among people with high genetic risk, also primarily in the SMN and DMN. The MIND network outperformed the MSN network in distinguishing MDD status. LimitationsOur study was cross-sectional and could not explore the causal relationships between cortical morphological changes, white matter connectivity, and disease states. Some patients had received antidepressant treatment, which may have influenced brain morphology and white matter network structure. ConclusionThe genetic mechanisms of depression may be related to white matter disintegration, which could also be associated with decoupling of the SMN and DMN. These findings provide new insights into the genetic mechanisms and potential biomarkers of MDD.

Ceramic aerogels are attractive for thermal insulation but plagued by poor mechanical stability and degradation under thermal shock. In this study, we designed and synthesized hyperbolic architectured ceramic aerogels with nanolayered double-pane walls with a negative Poisson’s ratio (−0.25) and a negative linear thermal expansion coefficient (−1.8 × 10−6 per °C). Our aerogels display robust mechanical and thermal stability and feature ultralow densities down to ∼0.1 milligram per cubic centimeter, superelasticity up to 95%, and near-zero strength loss after sharp thermal shocks (275°C per second) or intense thermal stress at 1400°C, as well as ultralow thermal conductivity in vacuum [∼2.4 milliwatts per meter-kelvin (mW/m·K)] and in air (∼20 mW/m·K). This robust material system is ideal for thermal superinsulation under extreme conditions, such as those encountered by spacecraft.

Chlorine (Cl 2 ) is one of the most important chemicals produced by the electrolysis of brine solutions and is a key raw material for many areas of industrial chemistry. For nearly half a century, dimensionally stable anode (DSA) made from a mixture of RuO 2 and TiO 2 solid oxides coated on Ti substrate has been the most widely used electrode for chlorine evolution reaction (CER). In harsh operating environments, the stability of DSAs remains a major challenge greatly affecting their lifetime. The deactivation of DSAs significantly increases the cost of the chlor-alkali industry due to the corrosion of Ru and the formation of the passivation layer TiO 2 . Therefore, it is urgent to develop catalysts with higher activity and stability, which requires a thorough understanding of the deactivation mechanism of DSA catalysts. This paper reviews existing references on the deactivation mechanisms of DSA catalysts, including both experimental and theoretical studies. Studies on how CER selectivity affects electrode stability are also discussed. Furthermore, studies on the effects of the preparation process, elemental composition, and surface/interface structures on the DSA stability and corresponding improvement strategies are summarized. The development of other non-DSA-type catalysts with comparable stability is also reviewed, and future opportunities in this exciting field are also outlined.

Purpose Non-small cell lung cancer (NSCLC) constitutes a substantial global health challenge, with surgical resection serving as a principal therapeutic approach. Nevertheless, the frequency of exploratory thoracotomy without en-bloc resection remains significant, particularly in advanced-stage cases, thereby adversely affecting prognosis. This study aims to predict risk scores for exploratory thoracotomy and analyze postoperative survival in patients with central NSCLC, utilizing CT (computed tomography) imaging subsequent to neoadjuvant therapy. Methods Clinical and radiological data of central NSCLC patients who underwent R0 resection or exploratory thoracotomy from January 2017 to June 2023 were retrospectively reviewed. Independent risk factors for exploratory thoracotomy were identified through a multivariate regression analysis. Subsequently, a nomogram model was developed to assess the risk of exploratory thoracotomy, and was validated through internal and external cohorts. Postoperative disease-free survival (DFS) and overall survival (OS) were analyzed using a Cox regression model. Results A total of 78 who underwent R0 resection following neoadjuvant therapy and 32 patients who underwent exploratory thoracotomy were included in the analysis. The nomogram model derived from tumor area and vascular deformation both identified as independent risk factors for exploratory thoracotomy, exhibited robust predictive performance. Furthermore, a tumor area of less than 250 mm² at the critical CT slice was associated with better DFS and OS following neoadjuvant therapy and R0 resection. Postoperative immunotherapy has the potential to extend survival in cases where exploratory thoracotomy was performed. Conclusion CT imaging at the critical slice post-neoadjuvant therapy is crucial for predicting the risk of exploratory thoracotomy and postoperative survival in patients with central NSCLC.

Objectives: The objective of the present study was to investigate the effects of Glucose oxidase (GOx) and Macleaya cordata extract (MCE) on immune response, antioxidant capacity, gut microbiota, and metabolome in cats. Methods: Twenty-four cats were randomly divided into four groups: basal diet (CON group), basal diet + 0.03% GOx (GOD group), basal diet + 0.03% MCE (MCE group), and basal diet + 0.03% GOx and 0.03% MCE (GM group). Results: Compared to the CON group, the GOD group exhibited elevated levels of total antioxidant capacity (T-AOC) and secretory immunoglobulin A (sIgA), and decreased levels of interleukin-6 (IL-6) and immunoglobulin A (IgA) (p < 0.05). MCE increased concentrations of IgA, immunoglobulin G (IgG) and sIgA, alongside a reduction in interleukin-2 (IL-2). The GM group exhibited markedly elevated concentrations of IL-2 and IgG, and decreased levels of interleukin-10 (IL-10). Moreover, 16S rRNA sequencing showed differences in the fecal microbiota among the four dietary groups. Analyses of fecal and serum metabolomics demonstrated that differential metabolites were primarily associated with cat amino acid metabolism and fatty acid metabolism. Conclusions: These findings suggest that Gox and MCE may enhance immune function, mitigate oxidative stress in cats, and increase the relative abundance of beneficial gut microbiota. Moreover, our results may provide evidence for GOx and MCE as novel nutritional additives in pet food. It should be noted that this study is limited by its sample size; while the results provide promising insights, future studies with larger-scale studies are warranted to confirm these observations.

Peripherally inserted central catheters (PICCs) are essential for long-term infusion in vulnerable pediatric patients. Optimal tip placement in the lower third of the superior vena cava or at the cavoatrial junction is critical to prevent serious complications. Verifying correct tip position in infants and toddlers is challenging because of very small anatomic target zones, non-standard radiograph acquisition, interference from other devices, low contrast, and high risk of catheter migration. Existing automated segmentation methods, mostly developed for adults, perform poorly on pediatric images. We retrospectively collected 1184 PICC patients from three medical centers, including 280 pediatric cases (210 neonates, 46 infants, 24 toddlers), with appropriate ethical approval. We introduce TopNet, a topology-preserving embedded network designed for automated PICC segmentation in pediatric patients. TopNet maintains catheter continuity and enables precise tip localization under difficult conditions. Quantitative and qualitative evaluations show superior segmentation and tip localization on both internal and external validation.

In this Research Communication we describe the effect of temperature and humidity index (THI) on various physiological traits, the plasma heat shock protein 70 (HSP70), heat shock protein 90 (HSP90) and cortisol levels and other blood parameters in crossbred buffalo (Nili-Ravi × Murrah) and Mediterranean buffalo to compare their tolerance to heat stress. As expected, crossbred buffalo had a significantly higher rectal temperature (RT), body surface temperature (BT), respiratory rate (RR), HSP70 and HSP90 levels in summer compared to spring and winter. RT and BT were also significantly higher in spring compared to winter. A significant correlation existed between THI and RT (r = 0·81) and RR (r = 0·84). Importantly, in summer the crossbred buffalo had a significantly lower RT, BT and RR and higher HSP70, HSP90 and cortisol levels than the Mediterranean buffalo. In conclusion, higher THI was associated with significant increase in RT, RR, BT, HSP70, HSP90 and cortisol levels, and the crossbred buffalo were more heat tolerant than Mediterranean buffalo.

The combination of idle computing resources in mobile devices and the computing capacity of mobile edge servers enables all available devices in an edge network to complete all computing tasks in coordination to effectively improve the computing capacity of the edge network. This is a research hotspot for 5G technology applications and integrating collaborative computing techniques into edge computing. Previous research has focused on the minimum energy consumption and/or delay to determine the formulation of the computational offloading strategy but neglected the cost required for the computation of collaborative devices (mobile devices, mobile edge servers, etc.); therefore, we propose a cost-based collaborative computation offloading model. In this model, when a task requests these devices’ assistance in computing, it needs to pay the corresponding calculation cost; and on this basis, the task is offloaded and computed. In addition, for the model, we propose an adaptive neighborhood search based on simulated annealing algorithm (ANSSA) to jointly optimize the offloading decision and resource allocation with the goal of minimizing the sum of both the energy consumption and calculation cost. The adaptive mechanism enables different operators to update the probability of selection according to historical experience and environmental perception, which makes the individual evolution have certain autonomy. A large number of experiments conducted on different scales of mobile user instances show that the ANSSA can obtain satisfactory time performance with guaranteed solution quality. The experimental results demonstrate the superiority of the mobile edge computing (MEC) offloading system. It is of great significance to strike a balance between maintaining the life cycle of smart mobile devices and breaking the performance bottleneck of MEC servers.