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Abstract Background Hyperactivity of the hypothalamic–pituitary–adrenal (HPA) axis constitutes a pivotal response by surgical trauma, manifesting as a critical aspect of the acute stress reaction. This hyperactivity resulted in adverse surgical outcomes and is often associated with increased postoperative anxiety. Increased evidence suggests that Nesfatin-1 plays a crucial role in stress responses and stress-related psychiatric disorders. Electroacupuncture (EA) is widely used to alleviate stress responses and anxiety, although its mechanism of action remains unclear. This study aimed to assess the mechanisms by which hypothalamic Nesfatin-1 contribute to the alleviation of HPA axis hyperactivity and anxiety by EA. Methods Partial hepatectomy (HT) was performed to simulate surgical trauma, and EA was applied at Zusanli (ST36) and Sanyinjiao (SP6). The levels of hypothalamic Nesfatin-1, c-Fos, and corticotropin-releasing hormone (CRH) were detected, and serum adrenocorticotropic hormone (ACTH) and corticosterone (CORT) were regarded as indicators of HPA axis activity. Anxiety levels were assessed through open field tests (OFT), elevated plus maze (EPM), and light–dark box tests (LDBT). To investigate the role of Nesfatin-1, its expression was modulated using stereotactic viral injections or plasmid transfections. Transcriptome sequencing was employed to explore the downstream signaling pathways of Nesfatin-1. Additionally, brain cannula implantation was performed to facilitate targeted drug administration. Results Our findings demonstrated that EA reduced the hypothalamic overexpression of CRH and Nesfatin-1, as well as serum levels of ACTH and CORT. Additionally, it alleviated anxiety-like behaviors resulting from surgical trauma. We observed that overexpression of Nesfatin-1 in the hypothalamic paraventricular nucleus (PVN) triggered hyperactivity of the HPA axis and anxiety. Conversely, knocking down Nesfatin-1 in the PVN reversed these effects caused by surgical trauma. Transcriptome sequencing identified the extracellular regulated protein kinases (ERK)/cAMP-response element binding protein (CREB) pathway as a key mediator in the impacts of surgical trauma and EA on the hypothalamus. Both in vivo and in vitro studies showed that overexpression of Nesfatin-1 activated the ERK/CREB pathway. Furthermore, administering ERK or CREB inhibitors into the PVN mitigated HPA axis hyperactivity and anxiety-like behaviors induced by surgical trauma. Finally, EA was observed to decrease the phosphorylation levels of ERK and CREB in the PVN. Conclusion EA alleviates HPA axis hyperactivity and anxiety-like behaviors caused by surgical trauma through inhibition of Nesfatin-1/ERK/CREB pathway in the hypothalamus.

Electroacupuncture (EA) has long been used to alleviate surgery-induced hypothalamic–pituitary–adrenal axis dysfunction. However, its downstream gene targets in the brain remain unclear. The aim of the present study was to clarify the potential targets of EA based on RNA sequencing techniques (RNA-seq). Rats were divided into normal control (NC), hepatectomy surgery (HT), HT + EA, and HT + sham EA groups followed by RNA-seq of two representative nuclei in the hypothalamus and amygdala. Weighted Gene Co-expression Network Analysis and Gene Set Enrichment Analysis identified six gene modules associated with neuroendocrine transmitters and neural remodeling in the hypothalamus. Furthermore, circRNA-miRNA-mRNA interaction networks revealed EA-related candidate miRNAs and circRNAs, of which opioid receptor mu 1 might be an EA-specific target, and showed regulation by competing endogenous RNA. We identified the neuroendocrine circRNA-miRNA-mRNA networks through which EA has an effect on HPA axis dysfunction, thus providing potential targets and future research directions for EA treatment.

Objective To systematically evaluate the prognostic factors for mortality in bullous pemphigoid. Methods PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, China Biology Medicine disc and Wanfang Database were searched to collect literature on the prognostic factors for mortality in bullous pemphigoid. The quality of studies was assessed by Newcastle–Ottawa Quality Assessment Scale. Two researchers extracted relevant data and scored study quality independently. The hazard ratio (HR) was calculated using the random effects model. Study heterogeneity was assessed using both Cochran’s Q test and I2 statistics. The causes of heterogeneity were assessed by subgroup analysis and/ or sensitivity analysis when heterogeneity was significant. When ten or more studies were included as outcome indicators, publication bias was evaluated by funnel plot and Egger’s test. Results Out of a total of 1,546 articles retrieved, 15 studies involving 2,435 patients were included. The meta-analysis showed that the mortality of patients with bullous pemphigoid increased with positive bullous pemphigoid 180 antibody (HR = 1.85, 95%CI: 1.25~2.75, P = 0.002); concomitant dementia (HR = 2.26, 95%CI: 1.43~3.59, PConclusion Positive bullous pemphigoid 180 antibody, dementia, stroke, heart disease and diabetes mellitus were the prognostic factors for mortality in bullous pemphigoid.

Dead trees significantly impact forest production and the ecological environment and pose constraints to the sustainable development of forests. A lightweight YOLOv4 dead tree detection algorithm based on unmanned aerial vehicle images is proposed to address current limitations in dead tree detection that rely mainly on inefficient, unsafe and easy-to-miss manual inspections. An improved logarithmic transformation method was developed in data pre-processing to display tree features in the shadows. For the model structure, the original CSPDarkNet-53 backbone feature extraction network was replaced by MobileNetV3. Some of the standard convolutional blocks in the original extraction network were replaced by depthwise separable convolution blocks. The new ReLU6 activation function replaced the original LeakyReLU activation function to make the network more robust for low-precision computations. The K-means++ clustering method was also integrated to generate anchor boxes that are more suitable for the dataset. The experimental results show that the improved algorithm achieved an accuracy of 97.33%, higher than other methods. The detection speed of the proposed approach is higher than that of YOLOv4, improving the efficiency and accuracy of the detection process. [ABSTRACT FROM AUTHOR]