Identification of differentially expressed genes of blood leukocytes for Schizophrenia.

Background: Schizophrenia (SCZ) is a severe neurodevelopmental disorder with brain dysfunction. This study aimed to use bioinformatic analysis to identify candidate blood biomarkers for SCZ. Methods: The study collected peripheral blood leukocyte samples of 9 SCZ patients and 20 healthy controls for RNA sequencing analysis. Bioinformatic analyses included differentially expressed genes (DEGs) analysis, pathway enrichment analysis, and weighted gene co-expression network analysis (WGCNA). Results: This study identified 1,205 statistically significant DEGs, of which 623 genes were upregulated and 582 genes were downregulated. Functional enrichment analysis showed that DEGs were mainly enriched in cell chemotaxis, cell surface, and serine peptidase activity, as well as involved in Natural killer cell-mediated cytotoxicity. WGCNA identified 16 gene co-expression modules, and five modules were significantly correlated with SCZ (p < 0.05). There were 106 upregulated genes and 90 downregulated genes in the five modules. The top ten genes sorted by the Degree algorithm were RPS28, BRD4, FUS, PABPC1, PCBP1, PCBP2, RPL27A, RPS21, RAG1, and RPL27. RAG1 and the other nine genes belonged to the turquoise and pink module respectively. Pathway enrichment analysis indicated that these 10 genes were mainly involved in processes such as Ribosome, cytoplasmic translation, RNA binding, and protein binding. Conclusion: This study finds that the gene functions in key modules and related enrichment pathways may help to elucidate the molecular pathogenesis of SCZ, and the potential of key genes to become blood biomarkers for SCZ warrants further validation.

Systemic delivery of full-length dystrophin in Duchenne muscular dystrophy mice.

Current gene therapy for Duchenne muscular dystrophy (DMD) utilizes adeno-associated virus (AAV) to deliver micro-dystrophin (µDys), which does not provide full protection for striated muscles as it lacks many important functional domains of full-length (FL) dystrophin. Here we develop a triple vector system to deliver FL-dystrophin into skeletal and cardiac muscles. We split FL-dystrophin into three fragments linked to two orthogonal pairs of split intein, allowing efficient assembly of FL-dystrophin. The three fragments packaged in myotropic AAV (MyoAAV4A) restore FL-dystrophin expression in both skeletal and cardiac muscles in male mdx4cv mice. Dystrophin-glycoprotein complex components are also restored at the sarcolemma of dystrophic muscles. MyoAAV4A-delivered FL-dystrophin significantly improves muscle histopathology, contractility, and overall strength comparable to µDys, but unlike µDys, it also restores defective cavin 4 localization and associated signaling in mdx4cv heart. Therefore, our data support the feasibility of a mutation-independent FL-dystrophin gene therapy for DMD, warranting further clinical development.

Gradient and curl optical torques.

Optical forces and torques offer the route towards full degree-of-freedom manipulation of matter. Exploiting structured light has led to the discovery of gradient and curl forces, and nontrivial optomechanical manifestations, such as negative and lateral optical forces. Here, we uncover the existence of two fundamental torque components, which originate from the reactive helicity gradient and momentum curl of light, and which represent the rotational analogues to the gradient and curl forces, respectively. Based on the two components, we introduce and demonstrate the concept of lateral optical torques, which act transversely to the spin of illumination. The orbital angular momentum of vortex beams is shown to couple to the curl torque, promising a path to extreme torque enhancement or achieving negative optical torques. These results highlight the intersection between the areas of structured light, Mie-tronics and rotational optomechanics, even inspiring new paths of manipulation in acoustics and hydrodynamics.

Identification of MAP1LC3A as a promising mitophagy-related gene in polycystic ovary syndrome.

Increasing evidence suggests that mitophagy is crucially involved in the progression of polycystic ovary syndrome (PCOS). Exploration of PCOS-specific biomarkers related to mitophagy is expected to provide critical insights into disease pathogenesis. In this study, we employed bioinformatic analyses and machine learning algorithms to determine novel biomarkers for PCOS that may be tied with mitophagy. A grand total of 12 differential expressed mitophagy-related genes (DE-MRGs) associated with PCOS were identified. TOMM5 and MAP1LC3A among the 12 DE-MRGs were recognized as potential marker genes by LASSO, RF and SVM-RFE algorithms. The area under the ROC curve (AUROC) of MAP1LC3A were all greater than 0.8 both in the training set and validation sets. The CIBERSORT analysis indicated a potential association between alterations in the immune microenvironment of PCOS individuals and MAP1LC3A expression. In addition, we found that MAP1LC3A was positively related to the testosterone levels of PCOS patients. Overall, MAP1LC3A was identified as optimal PCOS-specific biomarkers related to mitophagy. Our findings created a diagnostic strength and offered a perspective for investigating the mitophagy process in PCOS.

Dysregulated expression of miR-140 and miR-122 compromised microglial chemotaxis and led to reduced restriction of AD pathology.

BACKGROUND: Deposition of amyloid ß, which is produced by amyloidogenic cleavage of APP by ß- and γ-secretase, is one of the primary hallmarks of AD pathology. APP can also be processed by α- and γ-secretase sequentially, to generate sAPPα, which has been shown to be neuroprotective by promoting neurite outgrowth and neuronal survival, etc. METHODS: The global expression profiles of miRNA in blood plasma samples taken from 11 AD patients as well as from 14 age and sex matched cognitively normal volunteers were analyzed using miRNA-seq. Then, overexpressed miR-140 and miR-122 both in vivo and in vitro, and knock-down of the endogenous expression of miR-140 and miR-122 in vitro. Used a combination of techniques, including molecular biology, immunohistochemistry, to detect the impact of miRNAs on AD pathology. RESULTS: In this study, we identified that two miRNAs, miR-140-3p and miR-122-5p, both targeting ADAM10, the main α-secretase in CNS, were upregulated in the blood plasma of AD patients. Overexpression of these two miRNAs in mouse brains induced cognitive decline in wild type C57BL/6J mice as well as exacerbated dyscognition in APP/PS1 mice. Although significant changes in APP and total Aß were not detected, significantly downregulated ADAM10 and its non-amyloidogenic product, sAPPα, were observed in the mouse brains overexpressing miR-140/miR-122. Immunohistology analysis revealed increased neurite dystrophy that correlated with the reduced microglial chemotaxis in the hippocampi of these mice, independent of the other two ADAM10 substrates (neuronal CX3CL1 and microglial TREM2) that were involved in regulating the microglial immunoactivity. Further in vitro analysis demonstrated that both the reduced neuritic outgrowth of mouse embryonic neuronal cells overexpressing miR-140/miR-122 and the reduced Aß phagocytosis in microglia cells co-cultured with HT22 cells overexpressing miR-140/miR-122 could be rescued by overexpressing the specific inhibitory sequence of miR-140/miR-122 TuD as well as by addition of sAPPα, rendering these miRNAs as potential therapeutic targets. CONCLUSIONS: Our results suggested that neuroprotective sAPPα was a key player in the neuropathological progression induced by dysregulated expression of miR-140 and miR-122. Targeting these miRNAs might serve as a promising therapeutic strategy in AD treatment.

Exploration of leech therapy in treating gouty rats and its uric acid lowering mechanism.

BACKGROUND: Gout is a hyperuricemia (HUA)-related inflammatory reaction in the joints. Leech therapy has been effective in the gout, but the exact mechanism is unclear. OBJECTIVES: In this study, an exploration of the therapeutic mechanism of leech therapy in HUA and gouty arthritis (GA) rats was done. MATERIAL AND METHODS: HUA and GA construction utilizing sodium urate crystal, the potassium form of oxygen oxazine acid, and adenine. Serum and tissues were collected to measure uric acid (UA), creatinine (Cr), and urea nitrogen (UN). Enzyme linked immunosorbent assay was executed to evaluate the levels of xanthine oxidase (XOD), interleukin-6 (IL-6)and tumor necrosis factor α (TNF-α). The expression of glucose transporter 9 (GLUT9), organic anion transporter 3 (OAT3), adenosine triphosphate (ATP)-binding cassette efflux transporter G2 (ABCG2) and the nuclear factor kappa B (NF-kB), interleukin-1ß (IL-1ß), Toll-like Receptor 2 (TLR2) were assessed by Western blot and visualized in immunohistochemistry staining. RESULTS: Leech therapy reduces the levels of UA, Cr, and UN as well as the liver and serum levels of XOD activity, increasing the expressions of GLUT9, ABCG2, and OAT3 in the kidney. Meanwhile, it reduces joint swelling and lowers the levels of TNF-α, IL-6, IL-1ß, TLR2, and NF-kB. CONCLUSIONS: Leech therapy regulates the metabolism of uric acid and treats gouty arthritis with an anti-inflammatory effect.

GSK3: A potential target and pending issues for treatment of Alzheimer's disease.

Glycogen synthase kinase-3 (GSK3), consisting of GSK3α and GSK3ß subtypes, is a complex protein kinase that regulates numerous substrates. Research has observed increased GSK3 expression in the brains of Alzheimer's disease (AD) patients and models. AD is a neurodegenerative disorder with diverse pathogenesis and notable cognitive impairments, characterized by Aß aggregation and excessive tau phosphorylation. This article provides an overview of GSK3's structure and regulation, extensively analyzing its relationship with AD factors. GSK3 overactivation disrupts neural growth, development, and function. It directly promotes tau phosphorylation, regulates amyloid precursor protein (APP) cleavage, leading to Aß formation, and directly or indirectly triggers neuroinflammation and oxidative damage. We also summarize preclinical research highlighting the inhibition of GSK3 activity as a primary therapeutic approach for AD. Finally, pending issues like the lack of highly specific and affinity-driven GSK3 inhibitors, are raised and expected to be addressed in future research. In conclusion, GSK3 represents a target in AD treatment, filled with hope, challenges, opportunities, and obstacles.

The value of D-dimer and platelet-lymphocyte ratio combined with CT signs for predicting intestinal ischemia in patients with bowel obstruction.

OBJECTIVE: To investigate the diagnostic value of D-dimer, platelet-lymphocyte rate (PLR) and CT signs for intestinal ischemia in patients with bowel obstruction. METHODS: We retrospectively analyzed the clinical and imaging data of 105 patients diagnosed with bowel obstruction, and performed univariate and multivariate analyses to determine the independent risk factors for intestinal ischemia in patients with bowel obstruction. Moreover, the receiver operating characteristic curve (ROC) was plotted to examine the diagnostic value of D-dimer, PLR and CT signs in patients with bowel obstruction. Besides, Kappa tests were used to assess inter-observer agreement. RESULTS: We included 56 men (53%) and 49 women (47%) with mean age of 66.05 ± 16 years. Univariate and multivariate analyses showed that D-dimer, PLR and two significant CT signs (i.e., increased unenhanced bowel-wall attenuation and mesenteric haziness) were independent risk factors for intestinal ischemia in patients with bowel obstruction. ROC analysis showed that the combined use of D-dimer, PLR and the said two CT signs had better performance than single indicators in predicting intestinal ischemia in patients with bowel obstruction. The area under the curve (AUC) of the joint model III was 0.925 [95%CI: 0.876-0.975], with a sensitivity of 79.2% [95CI%: 67.2-91.1] and a specificity of 91.2% [95%CI: 83.7-98.9]. CONCLUSION: The combined use of D-dimer, PLR and CT signs has high diagnostic value for intestinal ischemia in patients with bowel obstruction and will prompt surgical exploration to evaluate intestinal blood flow.

Large Language Model-Based Natural Language Encoding Could Be All You Need for Drug Biomedical Association Prediction.

Analyzing drug-related interactions in the field of biomedicine has been a critical aspect of drug discovery and development. While various artificial intelligence (AI)-based tools have been proposed to analyze drug biomedical associations (DBAs), their feature encoding did not adequately account for crucial biomedical functions and semantic concepts, thereby still hindering their progress. Since the advent of ChatGPT by OpenAI in 2022, large language models (LLMs) have demonstrated rapid growth and significant success across various applications. Herein, LEDAP was introduced, which uniquely leveraged LLM-based biotext feature encoding for predicting drug-disease associations, drug-drug interactions, and drug-side effect associations. Benefiting from the large-scale knowledgebase pre-training, LLMs had great potential in drug development analysis owing to their holistic understanding of natural language and human topics. LEDAP illustrated its notable competitiveness in comparison with other popular DBA analysis tools. Specifically, even in simple conjunction with classical machine learning methods, LLM-based feature representations consistently enabled satisfactory performance across diverse DBA tasks like binary classification, multiclass classification, and regression. Our findings underpinned the considerable potential of LLMs in drug development research, indicating a catalyst for further progress in related fields.

Computational Modeling Interpretation Underlying Elevated Risk-Taking Propensity in the Dynamic Risky Investment Process of Non-Labor Income.

Introduction: Money source influences risk-taking behaviors. Although studies consistently indicated that individuals demonstrate a higher propensity to make risky investments when utilizing non-labor income as opposed to labor income, explanations as to why non-labor income leads to continuously blowing money into risky investments are scarce. Methods: The current study leverages a computational modeling approach to compare the differences in the dynamic risk investment process among individuals endowed with income from different sources (ie, non-labor income vs labor income) to understand the shaping force of higher risk-taking propensity in individuals with non-labor income. A total of 103 participants were recruited and completed the Balloon Analogue Risk Task (BART) with an equal monetary endowment, either as a token for completion of survey questionnaires (representing labor income) or as a prize from a lucky draw game (representing non-labor income). Results: We found that individuals endowed with non-labor income made more risky investments in BART compared to those with labor income. With computational modeling, we further identified two key differences in the dynamic risk investment processes between individuals endowed with labor and those with non-labor income. Specifically, individuals endowed with non-labor income had a higher preset expectation for risk-taking and displayed desensitization towards losses during risk investments, in contrast to individuals with labor income. Discussion: This study contributed to a better understanding of the psychological mechanisms of why individuals make more risk-taking behaviors with non-labor income, namely higher preset expectations of risk-taking and desensitization towards losses. Future research could validate these findings across diverse samples with varying backgrounds and adopt different manipulations of labor and non-labor income to enhance the external validity of our study.

Identification of a Hippocampus-to-Zona Incerta Projection involved in Motor Learning.

Motor learning (ML), which plays a fundamental role in growth and physical rehabilitation, involves different stages of learning and memory processes through different brain regions. However, the neural mechanisms that underlie ML are not sufficiently understood. Here, a previously unreported neuronal projection from the dorsal hippocampus (dHPC) to the zona incerta (ZI) involved in the regulation of ML behaviors is identified. Using recombinant adeno-associated virus, the projections to the ZI are surprisingly identified as originating from the dorsal dentate gyrus (DG) and CA1 subregions of the dHPC. Furthermore, projection-specific chemogenetic and optogenetic manipulation reveals that the projections from the dorsal CA1 to the ZI play key roles in the acquisition and consolidation of ML behaviors, whereas the projections from the dorsal DG to the ZI mediate the retrieval/retention of ML behaviors. The results reveal new projections from the dorsal DG and dorsal CA1 to the ZI involved in the regulation of ML and provide insight into the stages over which this regulation occurs.

Mechanical Neural Networks with Explicit and Robust Neurons.

Mechanical computing provides an information processing method to realize sensing-analyzing-actuation integrated mechanical intelligence and, when combined with neural networks, can be more efficient for data-rich cognitive tasks. The requirement of solving implicit and usually nonlinear equilibrium equations of motion in training mechanical neural networks makes computation challenging and costly. Here, an explicit mechanical neuron is developed of which the response can be directly determined without the need of solving equilibrium equations. A training method is proposed to ensure the robustness of the neuron, i.e., insensitivity to defects and perturbations. The explicitness and robustness of the neurons facilitate the assembly of various network structures. Two exemplified networks, a robust mechanical convolutional neural network and a mechanical recurrent neural network with long short-term memory capabilities for associative learning, are experimentally demonstrated. The introduction of the explicit and robust mechanical neuron streamlines the design of mechanical neural networks fulfilling robotic matter with a level of intelligence.

A new artificial intelligence system for both stomach and small bowel capsule endoscopy.

BACKGROUND AND AIMS: Despite the benefits of artificial intelligence (AI) in small bowel (SB) capsule endoscopy (CE) image reading, information on its application in the stomach and SB CE is lacking. METHODS: In this multicenter, retrospective diagnostic study, gastric imaging data were added to the deep learning (DL)-based SmartScan (SS), which has been described previously. A total of 1,069 magnetically controlled gastrointestinal (GI) CE examinations (comprising 2,672,542 gastric images) were used in the training phase for recognizing gastric pathologies, producing a new AI algorithm named SS Plus. 342 fully automated, magnetically controlled CE (FAMCE) examinations were included in the validation phase. The performance of both senior and junior endoscopists with both the SS Plus-Assisted Reading (SSP-AR) and conventional reading (CR) modes was assessed. RESULTS: SS Plus was designed to recognize 5 types of gastric lesions and 17 types of SB lesions. SS Plus reduced the number of CE images required for review to 873.90 (1000) (median, IQR 814.50-1,000) versus 44,322.73 (42,393) (median, IQR 31,722.75-54,971.25) for CR. Furthermore, with SSP-AR, endoscopists took 9.54 min (8.51) (median, IQR 6.05-13.13) to complete the CE video reading. In the 342 CE videos, SS Plus identified 411 gastric and 422 SB lesions, whereas 400 gastric and 368 intestinal lesions were detected with CR. Moreover, junior endoscopists remarkably improved their CE image reading ability with SSP-AR. CONCLUSIONS: Our study shows that the newly upgraded DL-based algorithm SS Plus can detect GI lesions and help improve the diagnostic performance of junior endoscopists in interpreting CE videos.

Disrupted default mode network connectivity in bipolar disorder: a resting-state fMRI study.

BACKGROUND: Theoretical and empirical evidence indicates the critical role of the default mode network (DMN) in the pathophysiology of the bipolar disorder (BD). This study aims to identify the specific brain regions of the DMN that is impaired in patients with BD. METHODS: A total of 56 patients with BD and 71 healthy controls (HC) underwent resting-state functional magnetic resonance imaging. Three commonly used functional indices, i.e., fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and degree centrality (DC), were utilized to identify the brain region showing abnormal spontaneous brain activity in patients with BD. Then, this region served as the seed region for resting-state functional connectivity (rsFC) analysis. RESULTS: Compared to the HC group, the BD group showed reduced fALFF, ReHo, and DC values in the left precuneus. Moreover, patients exhibited decreased rsFCs within the left precuneus and between the left precuneus and the medial prefrontal cortex. Additionally, there was diminished negative connectivity between the left precuneus and the left putamen, extending to the left insula (putamen/insula). The abnormalities in DMN functional connectivity were confirmed through various analysis strategies. CONCLUSIONS: Our findings provide convergent evidence for the abnormalities in the DMN, particularly located in the left precuneus. Decreased functional connectivity within the DMN and the reduced anticorrelation between the DMN and the salience network are found in patients with BD. These findings suggest that the DMN is a key aspect for understanding the neural basis of BD, and the altered functional patterns of DMN may be a potential candidate biomarker for diagnosis of BD.

Can a shift in dominant species of Microcystis alter growth and reproduction of waterfleas?

The bloom-forming species Microcystis wesenbergii and M. aeruginosa occur in many lakes globally, and may exhibit alternating blooms both spatially and temporally. As environmental changes increase, cyanobacteria bloom in more and more lakes and are often dominated by M. wesenbergii. The adverse impact of M. aeruginosa on co-existing organisms including zooplanktonic species has been well-studied, whereas studies of M. wesenbergii are limited. To compare effects of these two species on zooplankton, we explored effects of exudates from different strains of microcystin-producing M. aeruginosa (Ma905 and Ma526) and non-microcystin-producing M. wesenbergii (Mw908 and Mw929), on reproduction by the model zooplankter Daphnia magna in both chronic and acute exposure experiments. Specifically, we tested physiological, biochemical, molecular and transcriptomic characteristics of D. magna exposed to Microcystis exudates. We observed that body length and egg and offspring number of the daphnid increased in all treatments. Among the four strains tested, Ma526 enhanced the size of the first brood, as well as total egg and offspring number. Microcystis exudates stimulated expression of specific genes that induced ecdysone, juvenile hormone, triacylglycerol and vitellogenin biosynthesis, which, in turn, enhanced egg and offspring production of D. magna. Even though all strains of Microcystis affected growth and reproduction, large numbers of downregulated genes involving many essential pathways indicated that the Ma905 strain might contemporaneously induce damage in D. magna. Our study highlights the necessity of including M. wesenbergii into the ecological risk evaluation of cyanobacteria blooms, and emphasizes that consequences to zooplankton may not be clear-cut when assessments are based upon production of microcystins alone.

Multiomic analysis of monocyte-derived alveolar macrophages in idiopathic pulmonary fibrosis.

BACKGROUND: Monocyte-derived alveolar macrophages (Mo_AMs) are increasingly recognised as potential pathogenic factors for idiopathic pulmonary fibrosis (IPF). While scRNAseq analysis has proven valuable in the transcriptome profiling of Mo_AMs, the integration analysis of multi-omics may provide additional dimensions of understanding of these cellular populations. METHODS: We performed multi-omics analysis on 116 scRNAseq, 119 bulkseq and five scATACseq lung tissue samples from IPF. We built a large-scale IPF scRNAseq atlas and conducted the Monocle 2/3 as well as the Cellchat to explore the developmental path and intercellular communication on Mo_AMs. We also reported the difference in metabolisms, tissue repair and phagocytosis between Mo_AMs and tissue-resident alveolar macrophages (TRMs). To determine whether Mo_AMs affected pulmonary function, we projected clinical phenotypes (FVC%pred) from the bulkseq dataset onto the scRNAseq atlas. Finally, we used scATATCseq to uncover the upstream regulatory mechanisms and determine key drivers in Mo_AMs. RESULTS: We identified three Mo_AMs clusters and the trajectory analysis further validated the origin of these clusters. Moreover, via the Cellchat analysis, the CXCL12/CXCR4 axis was found to be involved in the molecular basis of reciprocal interactions between Mo_AMs and fibroblasts through the activation of the ERK pathway in Mo_AMs. SPP1_RecMacs (RecMacs, recruited macrophages) were higher in the low-FVC group than in the high-FVC group. Specifically, compared with TRMs, the functions of lipid and energetic metabolism as well as tissue repair were higher in Mo_AMs than TRMs. But, TRMs may have higher level of phagocytosis than TRMs. SPIB (PU.1), JUNB, JUND, BACH2, FOSL2, and SMARCC1 showed stronger association with open chromatin of Mo_AMs than TRMs. Significant upregulated expression and deep chromatin accessibility of APOE were observed in both SPP1_RecMacs and TRMs. CONCLUSION: Through trajectory analysis, it was confirmed that SPP1_RecMacs derived from Monocytes. Besides, Mo_AMs may influence FVC% pred and aggravate pulmonary fibrosis through the communication with fibroblasts. Furthermore, distinctive transcriptional regulators between Mo_AMs and TRMs implied that they may depend on different upstream regulatory mechanisms. Overall, this work provides a global overview of how Mo_AMs govern IPF and also helps determine better approaches and intervention therapies.

[Retracted] STK39, overexpressed in osteosarcoma, regulates osteosarcoma cell invasion and proliferation.

[This retracts the article DOI: 10.3892/ol.2017.6728.].

Comparative efficacy of modified Noel's technique and matrix phenolization on onychocryptosis: a retrospective study.

BACKGROUND: Onychocryptosis is a common pathological condition requiring clinical intervention. Selecting an appropriate and effective treatment based on individual patient circumstances is crucial. METHODS: We compared the efficacy and safety of the modified Noel's technique and matrix phenolization in 107 participants with onychocryptosis. Participants were divided into two groups: 75 nails (73 patients) were treated with the modified Noel's technique (modified Noel's group), while 42 nails (34 patients) were treated with matrix phenolization (Phenol group). Outcomes on clinical cure rates and postoperative complications from both groups were collected. Additionally, the efficacy of the modified Noel's technique was assessed in 31 nails with stage IV onychocryptosis. RESULTS: After 18 months, among the remaining 102 patients (110 nails), the modified Noel's group exhibited fewer complications (5.88% vs. 45.2%, P < 0.001) with similar cure rates (P = 0.62). Furthermore, there was a shorter healing time in the modified Noel's group (13.5 ± 1.4 vs. 27.6 ± 2.3 days, P < 0.001). Postoperative pain was notable in the modified Noel's group on the first postoperative day (P < 0.001), with a significant decrease in the pain score 2 weeks after surgery (P = 0.407). Postoperative nail plate narrowing was observed in the Phenol group (33%). Moreover, the modified Noel's technique achieved a 100% cure rate in stage IV patients. CONCLUSIONS: The modified Noel's technique, offering precise excision of the proliferative nail fold and strategic suturing, is suitable for stage IV patients and for those who find significant aesthetic impact unacceptable following narrowed plate postmatrix phenolization.

Exposure image correction of electrical equipment nameplate based on the LMPEC algorithm.

An optimization algorithm based on the LMPEC algorithm is proposed to rectify the nameplate image to address the problem that overexposure and underexposure of the nameplate image of electrical equipment will make subsequent nameplate recognition difficult. In the network structure, the PS-UNet++ network is based on the sub-pixel convolution upsampling module, and the UNet++ network is constructed as the feature extraction sub-network of the optimization algorithm to extract more detailed information from the model. Smooth L1 loss is substituted for L1 loss in the loss function to prevent model oscillation. In addition, to increase the robustness of the model, an improved method built on the multi-scale training method is applied. The experimental results indicate that, among all comparison algorithms, the optimized algorithm performs the best on the data set of electrical equipment nameplate exposure the experimenter generated. Compared to the original LMPEC algorithm, the SSIM, PSNR, and PI image evaluation indices are enhanced by 5.6%, 5.1%, and 7.96%, respectively.

Shared and unique alterations of large-scale network connectivity in drug-free adolescent-onset and adult-onset major depressive disorder.

Differences in clinical manifestations and biological underpinnings between Major Depressive Disorder (MDD) onset during adolescence and adulthood have been posited in previous studies, implying an influential role of age of onset (AOO) in the clinical subtyping and therapeutic approaches to MDD. However, direct comparisons between the two cohorts and their age-matched controls have been lacking in extant investigations. In this investigation, 156 volunteers participated, comprising 46 adolescents with MDD (adolescent-onset group), 35 adults with MDD (adult-onset group), 19 healthy adolescents, and 56 healthy adults. Resting-state functional MRI scans were undergone by all participants. Large-scale network analyses were applied. Subsequently, a 2 × 2 ANOVA was employed to analyze the main effects of diagnosis, age, and their interaction effect on functional connectivity (FC). Furthermore, regression analysis was employed to scrutinize the association between anomalous FC and HAMD sub-scores. Increased FC in visual network (VN), limbic network (LN), VN-dorsal attention network (DAN), VN-LN, and LN-Default Mode (DMN) was found in both adolescent-onset and adult-onset MDD; however, the increased FC in DAN and LN were only found in adult-onset MDD and the decreased FC in DAN was only found in adolescent-onset MDD. Additionally, the relationship between HAMD factor 1 anxiety somatization and altered FC of DAN, VN, and VN-DAN was moderated by AOO. In conclusion, shared and distinctive large-scale network alterations in adolescent-onset and adult-onset MDD patients were suggested by our findings, providing valuable contributions towards refining clinical subtyping and treatment approaches for MDD.