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Depression is one of the most common affective disorders in people’s life. Women are susceptibility to depression during puberty, peripartum and menopause transition, when they are suffering from sex hormone fluctuation. A lot of studies have demonstrated the neuroprotective effect of estrogen on depression in women, however, the effect of FSH on depression is unclear. In this study, we investigated the role of FSH on depression in mice. Our study demonstrated that FSH induced depression-like behaviors in mice in a dose-dependent manner. This induction was associated with elevated levels of pro-inflammatory cytokines, including IL-1β, IL-6, and TNF-α in both serum and hippocampal tissues. Additionally, FSH treatment resulted in impaired synaptic plasticity and a reduction in the expression of key synaptic proteins. It is noteworthy that the depression-like behaviors, inflammatory cytokines expression and synaptic plasticity impairment induced by FSH could be alleviated by knocking down the expression of FSH receptor (FSHR) in the hippocampus of the mice. Therefore, our findings reveal that FSH may play an important role in the pathogenesis of depression and targeting FSH may be a potential therapeutic strategy for depression during hormone fluctuation in women.

Atherosclerosis is an important cause of cerebrovascular and cardiovascular disease (CVD). Lipid infiltration, inflammation, and altered vascular stress are the critical mechanisms that cause atherosclerotic plaque formation. The hallmarks of the progression of atherosclerosis include plaque ulceration, rupture, neovascularization, and intraplaque hemorrhage, all of which are closely associated with the occurrence of CVD. Assessing the severity of atherosclerosis and plaque vulnerability is crucial for the prevention and treatment of CVD. Integrating imaging techniques for evaluating the characteristics of atherosclerotic plaques with computer simulations yields insights into plaque inflammation levels, spatial morphology, and intravascular stress distribution, resulting in a more realistic and accurate estimation of plaque state. Here, we review the characteristics and advancing techniques used to analyze intracranial and extracranial atherosclerotic plaques to provide a comprehensive understanding of atheroma.

Adipokines are biologically active factors secreted by adipose tissue that act on local and distant tissues through autocrine, paracrine, and endocrine mechanisms. However, adipokines are believed to be involved in an increased risk of atherosclerosis. Classical adipokines include leptin, adiponectin, and ceramide, while newly identified adipokines include visceral adipose tissue-derived serpin, omentin, and asprosin. New evidence suggests that adipokines can play an essential role in atherosclerosis progression and regression. Here, we summarize the complex roles of various adipokines in atherosclerosis lesions. Representative protective adipokines include adiponectin and neuregulin 4; deteriorating adipokines include leptin, resistin, thrombospondin-1, and C1q/tumor necrosis factor-related protein 5; and adipokines with dual protective and deteriorating effects include C1q/tumor necrosis factor-related protein 1 and C1q/tumor necrosis factor-related protein 3; and adipose tissue-derived bioactive materials include sphingosine-1-phosphate, ceramide, and adipose tissue-derived exosomes. However, the role of a newly discovered adipokine, asprosin, in atherosclerosis remains unclear. This article reviews progress in the research on the effects of adipokines in atherosclerosis and how they may be regulated to halt its progression.

Abstract Purpose The objective of this meta-analysis was to compare the clinical outcomes of using short implants (≤ 8 mm) inserted with osteotome sinus floor elevation (OSFE) and standard implants (≥ 10 mm) inserted with sinus floor elevation (SFE) in atrophic posterior maxillae with insufficient residual bone height (RBH). Methods An electronic search was performed on PubMed, EMBASE, and the Cochrane Library from 1994 to July 2022, in combination with a manual search of references in relevant articles. Randomized controlled trials (RCTs) that compared the clinical results between short and standard implant placement with SFE were included. The primary outcomes were implant survival rate and marginal bone loss (MBL); the secondary outcome was complication rate. Results Three RCTs were included, totaling 138 short and 156 standard implants. The results of the meta-analysis showed no significant differences between the short and standard implant groups in survival rate (RR = 1.02, 95% CI 0.96–1.08, p = 0.570), MBL (MD = − 0.13, 95% CI − 0.32 to 0.07, p = 0.190) and complication rate (intra-surgical complication: RR = 1.14, 95% CI 0.46–2.83, p = 0.770; post-operative complication: RR = 1.34, 95% CI 0.71–2.55, p = 0.370). Conclusions Using short implants (≤ 8 mm) combined with OSFE might be an alternative to standard implants (≥ 10 mm) with SFE when the RBH of the posterior maxilla is insufficient. Based on a short-term clinical observation, short implants with OSFE show good results in terms of survival rate, MBL, and complication incidence. Graphical Abstract

Recent advances in sensor technology have facilitated the development and use of personalized sensors in monitoring environmental factors and the associated health effects. No studies have reviewed the research advancement in examining population-based health responses to environmental exposure via portable sensors/instruments. This study aims to review studies that use portable sensors to measure environmental factors and health responses while exploring the environmental effects on health. With a thorough literature review using two major English databases (Web of Science and PubMed), 24 eligible studies were included and analyzed out of 16,751 total records. The 24 studies include 5 on physical factors, 19 on chemical factors, and none on biological factors. The results show that particles were the most considered environmental factor among all of the physical, chemical, and biological factors, followed by total volatile organic compounds and carbon monoxide. Heart rate and heart rate variability were the most considered health indicators among all cardiopulmonary outcomes, followed by respiratory function. The studies mostly had a sample size of fewer than 100 participants and a study period of less than a week due to the challenges in accessing low-cost, small, and light wearable sensors. This review guides future sensor-based environmental health studies on project design and sensor selection.

Neuromyelitis optica spectrum disorder (NMOSD), a relapsing autoimmune disease of the central nervous system, mainly targets the optic nerve and spinal cord. To date, all attempts at the establishment of NMOSD animal models have been based on neuromyelitis optica immunoglobulin G antibody (NMO-IgG) and mimic the disease in part. To solve this problem, we developed a rodent model by opening the blood-brain barrier (BBB) with low frequency ultrasound, followed by injection of NMO-IgG from NMOSD patients and complement to mice suffering pre-existing neuroinflammation produced by experimental autoimmune encephalomyelitis (EAE). In this study, we showed that ultrasound with NMO-IgG and complement caused marked inflammation and demyelination of both spinal cords and optic nerves compared to blank control group, as well as glial fibrillary acidic protein (GFAP) and aquaporin-4 (AQP4) loss of spinal cords and optic nerves compared to EAE mice and EAE mice with only BBB opening. In addition, magnetic resonance imaging (MRI) revealed optic neuritis with spinal cord lesions. We further demonstrated eye segregation defects in the dorsal lateral geniculate nucleus (dLGN) of these NMOSD mice.

ABSTRACTHuman coronavirus NL63 (HCoV-NL63) is primarily associated with common cold in children, elderly and immunocompromised individuals. Outbreaks caused by HCoV-NL63 are rare. Here we report a cluster of HCoV-NL63 cases with severe lower respiratory tract infection that arose in Guangzhou, China, in 2018. Twenty-three hospitalized children were confirmed to be HCoV-NL63 positive, and most of whom were hospitalized with severe pneumonia or acute bronchitis. Whole genomes of HCoV-NL63 were obtained using next-generation sequencing. Phylogenetic and single amino acid polymorphism analyses showed that this outbreak was associated with two subgenotypes (C3 and B) of HCoV-NL63. Half of patients were identified to be related to a new subgenotype C3. One unique amino acid mutation at I507 L in spike protein receptor binding domain (RBD) was detected, which segregated this subgenotype C3 from other known subgenotypes. Pseudotyped virus bearing the I507 L mutation in RBD showed enhanced entry into host cells as compared to the prototype virus. This study proved that HCoV-NL63 was undergoing continuous mutation and has the potential to cause severe lower respiratory disease in humans.

Purpose: To investigate the effect of lipoic acid combination with valsartan on diabetic nephropathy (DN) and its associated adverse reactions. Methods: A retrospective analysis was conducted on 120 patients who treated for DN at the Second Affiliated Hospital of Shenzhen University, China between August 2019 and October 2022. Based on different treatment approaches, control group comprised 55 patients receiving valsartan alone, while joint group consisted of 65 patients receiving a combination of valsartan and lipoic acid. Therapeutic effectiveness and adverse events were compared between the groups. Additionally, changes in blood glucose and renal function parameters were evaluated pre- and post-treatment. Results: Post-treatment, both groups exhibited improvements in blood glucose and renal function parameters compared to pre-treatment values (p < 0.05). However, joint group demonstrated superior improvements in these parameters compared to control group (p < 0.05). Total efficacy was significantly higher in the joint group than in control group (p < 0.05). No significant differences were observed between the groups' incidence of adverse reactions (p > 0.05). Conclusion: Concurrent therapy of lipoic acid and valsartan sly treats DN. It enhances the regulation of blood glucose levels and improves renal function with high safety. Further studies employing larger sample sizes and prospective designs with comprehensive patient follow-up are required to further validate and enhance the reliability of these findings. [ABSTRACT FROM AUTHOR]

Abstract Background The participation of long noncoding RNAs (lncRNAs) in myocardial infarction has recently been noted. However, their underlying roles in the border zone of myocardial infarction remain unclear. This study uses microarrays to determine the profiles of lncRNAs and mRNAs in the border zone. Methods Bioinformatics methods were employed to uncover their underlying roles. Highly dysregulated lncRNAs was further validated via PCR. Results Four hundred seven lncRNAs and 752 mRNAs were upregulated, while 132 lncRNAs and 547 mRNAs were downregulated in the border zone of myocardial infarction. A circos graph was constructed to visualize the chromosomal distribution and classification of the dysregulated lncRNAs and mRNAs. The upregulated mRNAs in the border zone were most highly enriched in cytokine activity, binding, cytokine receptor binding and related processes, as ascertained through Go analysis. Pathway analysis of the upregulated mRNAs showed the most significant changes were in the TNF signaling pathway, cytokine–cytokine receptor interaction and chemokine signaling pathway and similar pathways and interactions. An lncRNA–mRNA co-expression network was established to probe into the underlying functions of the 10 most highly dysregulated lncRNAs based on their co-expressed mRNAs. In the co-expression network, we found 16 genes directly involved in myocardial infarction, including Alox5ap, Itgb2 and B4galt1. The lncRNAs AY212271, EF424788 and MRAK088538, among others, might be associated with myocardial infarction. BC166504 is probably a key lncRNA in the border zone of myocardial infarction. Conclusions The results may have revealed some aberrantly expressed lncRNAs and mRNAs that contribute to the underlying pathophysiological mechanisms of myocardial infarction.

Cell-based assays (CBAs) and radioimmunoprecipitation assay (RIPA) are the most sensitive methods for identifying anti-acetylcholine receptor (AChR) antibody in myasthenia gravis (MG). But CBAs are limited in clinical practice by transient transfection. We established a stable cell line (KL525) expressing clustered AChR by infecting HEK 293T cells with dual lentiviral vectors expressing the genes encoding the human AChR α1, β1, δ, ϵ and the clustering protein rapsyn. We verified the stable expression of human clustered AChR by immunofluorescence, immunoblotting, and real-time PCR. Fluorescence-activated cell sorting (FACS) was used to detect anti-AChR antibodies in 103 MG patients and 58 healthy individuals. The positive results of MG patients reported by the KL525 was 80.6% (83/103), 29.1% higher than the 51.4% (53/103) of RIPA. 58 healthy individuals tested by both the KL525 CBA and RIPA were all negative. In summary, the stable expression of clustered AChR in our cell line makes it highly sensitive and advantageous for broad clinical application in CBAs.

This paper describes the construction a short-text aspect-based sentiment analysis method based on Convolutional Neural Network (CNN) and Bidirectional Gating Recurrent Unit (BiGRU). The hybrid model can fully extract text features, solve the problem of long-distance dependence on the sequence, and improve the reliability of training. This article reports empirical research conducted on the basis of literature research. The first step was to obtain the dataset and perform preprocessing, after which scikit-learn was used to perform TF-IDF calculations to obtain the feature word vector weight, obtain the aspect-level feature ontology words of the evaluated text, and manually mark the ontology of the reviewed text and the corresponding sentiment analysis polarity. In the sentiment analysis section, a hybrid model based on CNN and BiGRU (CNN + BiGRU) was constructed, which uses corpus sentences and feature words as the vector input and predicts the emotional polarity. The experimental results prove that the classification accuracy of the improved CNN + BiGRU model was improved by 12.12%, 8.37%, and 4.46% compared with the Convolutional Neural Network model (CNN), Long-Short Term Memory model (LSTM), and Convolutional Neural Network (C-LSTM) model.

For traditional computer-aided diagnosis, the feature extraction of lung nodules only relies on artificial design, and the use of morphological features may lose nodular information, causing differences in classification results. This paper proposes a method of lung nodule feature extraction and classification as benign or malignant. First, the region of interest (ROI) of lung nodules was obtained from the original CT image using a threshold probability map. Next, the deep features of the lung nodules were extracted using the deep belief network (DBN). Finally, an extreme learning machine (ELM) was used as the classifier for benign and malignant classification. On the publicly available LIDC database, our method reaches a high accuracy of 95±0.3% in the diagnosis of lung nodules, and the area under the ROC curve is 0.932, which is superior to other feature extraction methods. Our method also avoids the complexity of artificial extraction and differences in feature selection, and it can provide a reference for clinical diagnosis. [ABSTRACT FROM AUTHOR]

Previous studies have reported that short‑term vagus nerve stimulation (VNS) improves cardiac function in rats with chronic heart failure (CHF). The molecular mechanisms are unclear. The potential effect of microRNA (miR)‑205 in apoptosis of short‑term VNS was examined. A total of 3 weeks after inducing CHF, the rats were divided into three groups: Sham stimulation in sham operated rats, sham stimulation in CHF rats (CHF‑SS), and treated with VNS in CHF rats (CHF‑VNS). The right vagus nerve of the neck was stimulated for 72 h in CHF rats with rectangular pulses of 40 msec duration at 1 Hz and 5 V. miR‑205 was focused on, which exhibited differential expression in the miRNA microarray analysis of CHF rats, and the effects of VNS on apoptosis were examined. It was verified that the expression level of miR‑205 in the CHF‑SS group was increased, and the expression was reduced in the CHF‑VNS group. Furthermore, mimics or inhibitor of miR‑205 was transfected into H9c2 to investigate its function on apoptosis. Baculoviral IAP repeat‑containing protein 2 (Birc2) was confirmed a target of miR‑205 through a dual luciferase reporter assay and western blotting. It was demonstrated that downregulated miR‑205 decreased apoptosis in H9c2 cells. The apoptosis‑associated proteins were further detected in H9c2 cells and rat tissue. The mRNA and protein expression levels of caspase‑3 and Bcl‑2‑associated X protein were decreased in the CHF‑VNS group, the expression of Birc2 and B‑cell lymphoma 2 were increased. The results were consistent with the in vitro study in the miR‑205 inhibitor group. The present study demonstrated that short‑term VNS decreased apoptosis by downregulating miR‑205 in rats with CHF. Therefore, the results of the present study provide basic evidence for short‑term VNS in the clinical treatment of CHF. [ABSTRACT FROM AUTHOR]

Traditionally, the coagulation and fragmentation process in colloid or nanofluid has been estimated by diffusion-limited cluster aggregation (DLCA) or the population balance model. However, both models fail to give a clear physical meaning when considering the cluster fragmentation. In our present work, we developed a modified DLCA model by adding a new breaking mechanism with a clear physical meaning, which is elucidated by the stress concentration concept in materials science. When an impact (such as a collision) acts on the aggregate, one can compare whether the energy of the impact is larger than its binding energy. If the former is larger, the breaking of aggregates will happen. Otherwise, aggregates cannot be broken. A 2D experiment has been conducted to validate our model. The modeling results showed that Df (the fractal dimension of the clusters) is around 1.34 for the DLCA model, while it is estimated to be 1.43 by our modified model, which is in good agreement with the experimental value of Df  =  1.44  ±  0.08. Clearly, our model is more accurate than the DLCA model. The relationship between Df and initial particle size and particle concentration have also been investigated. Our work is expected to add new insight into the evaluation of aggregate morphology and size distribution in various nanoparticle suspension systems. [ABSTRACT FROM AUTHOR]