Fine-grained recognition of bitter gourd maturity based on Improved YOLOv5-seg model.

Bitter gourd, being perishable, requires timely harvesting. Delayed harvesting can result in a substantial reduction in fruit quality. while premature harvesting leads to underdeveloped fruit and decreased yields, the continuous flowering pattern in bitter gourd underscores the significance of accurately assessing fruit growth and ensuring timely harvesting for subsequent fruit setting and development. The current reliance on the experience of production personnel represents a substantial inefficiency. We present an improved real-time instance segmentation model based on YOLOv5-seg. The utilization of dynamic snake convolution enables the extraction of morphological features from the curved and elongated structure of bitter gourd. Diverse branch blocks enhance feature space diversity without inflating model size and inference time, contributing to improved recognition of expansion stages during bitter gourd growth. Additionally, the introduction of Focal-EIOU loss accurately locates the boundary box and mask, addressing sample imbalances in the L2 stage. Experimental results showcase remarkable accuracy rates of 99.3%, 93.8%, and 98.3% for L1, L2, and L3 stages using mAP@0.5. In comparison, our model outperforms other case segmentation models, excelling in both detection accuracy and inference speed. The improved YOLOv5-seg model demonstrates strong performance in fine-grained recognition of bitter gourd during the expansion stage. It efficiently segments bitter gourd in real-time under varying lighting and occlusion conditions, providing crucial maturity information. This model offers reliable insights for agricultural workers, facilitating precise harvesting decisions.

Stellate ganglion block potentially ameliorates postoperative cognitive decline in aged rats by regulating the neuroendocrine response to stress.

Background: Postoperative cognitive dysfunction (POCD) is a common postoperative complication in elderly patients. The strong stress response causing by surgical trauma can induce POCD. We hypothesized that stellate ganglion block (SGB) can provide the neuroprotection to POCD by regulating the neuroendocrine response. Methods: Sprague-Dawley male rats, 18-20 months old and weighing 550-650 g were assigned into four groups: sham surgery group (Sham), sham surgery + saline group (Sham + NS), surgery group (Surgery), and surgery + SGB group (Surgery + SGB). The change of body weight, heart rate variability analysis, behavior testing, neuronal damage, inflammatory response, neuroendocrine hormone level were evaluated by their corresponding methods. Results: The results showed that SGB can reduce the number of both types of errors in the postoperative eight-arm maze assay, attenuate neural structural damage, inhibit neuroapoptosis, suppress inflammatory responses, increase the release of neurotrophic factors, accelerate postoperative weight recovery, and promote postoperative recovery in rats. Most importantly, SGB reduced the level of neuroendocrine hormone of TH, Cyp11b1, CRH, and SGB also activated dorsal motor nucleus of vagus (detected by c-fos immunohistochemistry). Conclusions: Our findings indicated that SGB could be a neuroprotective therapy for the cognitive dysfunction induced by exploratory laparotomy model of POCD, which might be attributable for balancing the autonomic nervous system, regulating hypothalamic-pituitary-adrenal (HPA) axis system.

Combining bioinformatics and machine learning algorithms to identify and analyze shared biomarkers and pathways in COVID-19 convalescence and diabetes mellitus.

Background: Most patients who had coronavirus disease 2019 (COVID-19) fully recovered, but many others experienced acute sequelae or persistent symptoms. It is possible that acute COVID-19 recovery is just the beginning of a chronic condition. Even after COVID-19 recovery, it may lead to the exacerbation of hyperglycemia process or a new onset of diabetes mellitus (DM). In this study, we used a combination of bioinformatics and machine learning algorithms to investigate shared pathways and biomarkers in DM and COVID-19 convalescence. Methods: Gene transcriptome datasets of COVID-19 convalescence and diabetes mellitus from Gene Expression Omnibus (GEO) were integrated using bioinformatics methods and differentially expressed genes (DEGs) were found using the R programme. These genes were also subjected to Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to find potential pathways. The hub DEGs genes were then identified by combining protein-protein interaction (PPI) networks and machine learning algorithms. And transcription factors (TFs) and miRNAs were predicted for DM after COVID-19 convalescence. In addition, the inflammatory and immune status of diabetes after COVID-19 convalescence was assessed by single-sample gene set enrichment analysis (ssGSEA). Results: In this study, we developed genetic diagnostic models for 6 core DEGs beteen type 1 DM (T1DM) and COVID-19 convalescence and 2 core DEGs between type 2 DM (T2DM) and COVID-19 convalescence and demonstrated statistically significant differences (p<0.05) and diagnostic validity in the validation set. Analysis of immune cell infiltration suggests that a variety of immune cells may be involved in the development of DM after COVID-19 convalescence. Conclusion: We identified a genetic diagnostic model for COVID-19 convalescence and DM containing 8 core DEGs and constructed a nomogram for the diagnosis of COVID-19 convalescence DM.

Identification of copper-related biomarkers and potential molecule mechanism in diabetic nephropathy.

Background: Diabetic nephropathy (DN) is a chronic microvascular complication in patients with diabetes mellitus, which is the leading cause of end-stage renal disease. However, the role of copper-related genes (CRGs) in DN development remains unclear. Materials and methods: CRGs were acquired from the GeneCards and NCBI databases. Based on the GSE96804 and GSE111154 datasets from the GEO repository, we identified hub CRGs for DN progression by taking the intersection of differentially expressed CRGs (DECRGs) and genes in the key module from Weighted Gene Co-expression Network Analysis. The Maximal Clique Centrality algorithm was used to identify the key CRGs from hub CRGs. Transcriptional factors (TFs) and microRNAs (miRNAs) targeting hub CRGs were acquired from publicly available databases. The CIBERSORT algorithm was used to perform comparative immune cell infiltration analysis between normal and DN samples. Results: Eighty-two DECRGs were identified between normal and DN samples, as were 10 hub CRGs, namely PTGS2, DUSP1, JUN, FOS, S100A8, S100A12, NAIP, CLEC4E, CXCR1, and CXCR2. Thirty-nine TFs and 165 miRNAs potentially targeted these 10 hub CRGs. PTGS2 was identified as the key CRG and FOS as the most significant gene among all of DECRGs. RELA was identified as the hub TF interacting with PTGS2 by taking the intersection of potential TFs from the ChEA and JASPAR public databases. let-7b-5p was identified as the hub miRNA targeting PTGS2 by taking the intersection of miRNAs from the miRwalk, RNA22, RNAInter, TargetMiner, miRTarBase, and ENCORI databases. Similarly, CREB1, E2F1, and RELA were revealed as hub TFs for FOS, and miR-338-3p as the hub miRNA. Finally, compared with those in healthy samples, there are more infiltrating memory B cells, M1 macrophages, M2 macrophages, and resting mast cells and fewer infiltrating activated mast cells and neutrophils in DN samples (all p< 0.05). Conclusion: The 10 identified hub copper-related genes provide insight into the mechanisms of DN development. It is beneficial to examine and understand the interaction between hub CRGs and potential regulatory molecules in DN. This knowledge may provide a novel theoretical foundation for the development of diagnostic biomarkers and copper-related therapy targets in DN.

Association between plasma dipeptidyl peptidase-4 levels and cognitive function in perinatal pregnant women with gestational diabetes mellitus.

BACKGROUND: Dipeptidyl peptidase-4 (DPP4) is associated with cognitive dysfunction in patients with type 2 diabetes. AIM: To assess a possible relationship between serum DPP4 and cognitive function in perinatal pregnant women with gestational diabetes mellitus (GDM). METHODS: The study subjects were divided into three groups: GDM group (n = 81), healthy pregnant (HP) group (n = 85), and control group (n = 51). The Montreal Cognitive Assessment (MoCA) was used to assess the cognitive status of each group. Venous blood samples were collected to measure blood lipids, glycated hemoglobin, and glucose levels. For each participant, a 3-mL blood sample was collected and centrifuged, and the serum was collected. Blood samples were stored at -80 ℃, and DPP4, interleukin-6 (IL-6), and 8-iso-prostaglandin F2α (8-iso-PGF2α), and brain-derived neurotrophic factor (BDNF) were detected using ELISA. RESULTS: The MoCA scores in the GDM and HP groups were significantly different from those in the control group in terms of visuospatial/executive function and attention (P < 0.05); however, the scores were not significantly different between the GDM and HP groups (P > 0.05). In terms of language, the GDM group had significantly different scores from those in the other two groups (P < 0.05). In terms of memory, a significant difference was found between the HP and control groups (P < 0.05), as well as between the GDM and HP groups. The levels of DPP4, IL-6, and 8-iso-PGF2α in the GDM group were significantly higher than those in the HP and control groups (P < 0.05); however, the differences between these levels in the HP and control groups were not significant (P > 0.05). The level of BDNF in the GDM group was significantly lower than that in the HP and control groups (P < 0.05), although the difference in this level between the HP and control groups was not significant (P > 0.05). CONCLUSION: Cognitive dysfunction in perinatal pregnant women with GDM mainly manifested as memory loss, which might be associated with elevated DPP4 levels.

Adiponectin ameliorates lung ischemia-reperfusion injury through SIRT1-PINK1 signaling-mediated mitophagy in type 2 diabetic rats.

BACKGROUND: Diabetes mellitus (DM) is a key contributing factor to poor survival in lung transplantation recipients. Mitochondrial dysfunction is recognized as a critical mediator in the pathogenesis of diabetic lung ischemia-reperfusion (IR) injury. The protective effects of adiponectin have been demonstrated in our previous study, but the underlying mechanism remains unclear. Here we demonstrated an important role of mitophagy in the protective effect of adiponectin during diabetic lung IR injury. METHODS: High-fat diet-fed streptozotocin-induced type 2 diabetic rats were exposed to adiponectin with or without administration of the SIRT1 inhibitor EX527 following lung transplantation. To determine the mechanisms underlying the action of adiponectin, rat pulmonary microvascular endothelial cells were transfected with SIRT1 small-interfering RNA or PINK1 small-interfering RNA and then subjected to in vitro diabetic lung IR injury. RESULTS: Mitophagy was impaired in diabetic lungs subjected to IR injury, which was accompanied by increased oxidative stress, inflammation, apoptosis, and mitochondrial dysfunction. Adiponectin induced mitophagy and attenuated subsequent diabetic lung IR injury by improving lung functional recovery, suppressing oxidative damage, diminishing inflammation, decreasing cell apoptosis, and preserving mitochondrial function. However, either administration of 3-methyladenine (3-MA), an autophagy antagonist or knockdown of PINK1 reduced the protective action of adiponectin. Furthermore, we demonstrated that APN affected PINK1 stabilization via the SIRT1 signaling pathway, and knockdown of SIRT1 suppressed PINK1 expression and compromised the protective effect of adiponectin. CONCLUSION: These data demonstrated that adiponectin attenuated reperfusion-induced oxidative stress, inflammation, apoptosis and mitochondrial dysfunction via activation of SIRT1- PINK1 signaling-mediated mitophagy in diabetic lung IR injury.

Cognitive Dysfunction of Pregnant Women with Gestational Diabetes Mellitus in Perinatal Period.

Purpose: To explore whether pregnant women with gestational diabetes mellitus (GDM) had cognitive impairment and assess cognitive function in normal pregnant women. Methods: A total of 75 consecutive women diagnosed with GDM (GDM group), 70 normal pregnant women (NP group) without diabetes and matched for age, and 51 female volunteers (CG group) with the similar age level, normal blood glucose, and nonpregnancy were included in the study. For the assessment of cognitive functions, Montreal Cognitive Assessment (MoCA) was performed. Venous blood samples were collected to measure blood glucose, glycated hemoglobin (HbA1c), methylglyoxal (MGO), beta amyloid (Aß), and tau protein. Results: The score of MoCA of GDM was lowest, and the score of the NP group was lower than volunteers (P < 0.05). The incidence of cognitive dysfunction increased significantly in the GDM group with statistical significance (P < 0.05). The levels of tau and MGO in the GDM group were significantly less than those in the NP and CG groups, and Aß in the GDM group was significantly more than that in the NP and CG groups (P < 0.05), but the differences between NP and CG groups were not statistically significant (P < 0.05). Conclusion: The pregnant women with GDM showed a significant decline in cognitive function, and the normal pregnant women also showed a decline in cognitive function which is very light.

Stellate ganglion block attenuates chronic stress induced depression in rats.

BACKGROUND: Stress is a significant factor in the etiology of depression. Stellate ganglion block (SGB) has been shown to maintain the stability of the autonomic system and to affect the neuroendocrine system, including the hypothalamic-pituitary-adrenal (HPA) axis. The objective of this study was to determine the antidepressant-like effects of SGB on the autonomic system and the HPA axis, apoptosis-related proteins, related spatial learning and memory impairment, and sensorimotor dysfunction. METHODS: Forty-eight Sprague Dawley rats were assigned to four experimental groups: control + saline (sham group), control + SGB (SGB group), unpredictable chronic mild stress (UCMS) + saline (UCMS group), and UCMS + SGB (UCSG group). Stress-induced effects and the function of SGB were assessed using measures of body weight, coat state, sucrose consumption, and behavior in open-field and Y-maze tests. Neuronal damage was assessed histologically using the hematoxylin-eosin (HE) staining method, while western blotting was used to investigate changes in the expression of apoptosis-related proteins. Plasma corticotropin-releasing factor (CRF), adrenocorticotropic hormone (ACTH), corticosterone (CORT), noradrenaline and adrenaline were measured to evaluate changes in the autonomic system and HPA axis. RESULTS: SGB treatment significantly improved sensorimotor dysfunction and spatial learning and memory impairment following UCMS. Moreover, UCMS significantly decreased body weight, sucrose preference and anti-apoptotic protein Bcl-2, and increased scores on measures of coat state, adrenal gland weight, levels of CORT, CRF, ACTH, noradrenaline and adrenaline, as well as increased neuronal loss, cell shrinkage, nuclear condensation, and the pro-apoptotic protein Bax. These symptoms were attenuated by treatment with SGB. CONCLUSIONS: These findings suggest that SGB can attenuate depression-like behaviors induced by chronic stress. These protective effects appear to be due to an anti-apoptotic mechanism of two stress pathways-the autonomic system and the HPA axis.