Miracle-dz/UniFAR-FTUs huggingface dataset:
Functionally active TRPA1 ion channel is downregulated in peptidergic neurons of the Edinger-Westphal nucleus upon acute alcohol exposure

Introduction: The centrally projecting Edinger-Westphal nucleus (EWcp) contributes to the control of alcohol consumption by its urocortin 1 (UCN1) and cocaine- and amphetamine-regulated transcript (CART) co-expressing peptidergic neurons. Our group recently showed that the urocortinergic centrally projecting EWcp is the primary seat of central nervous system transient receptor potential ankyrin 1 (TRPA1) cation channel mRNA expression. Here, we hypothesized that alcohol and its metabolites, that pass through the blood-brain barrier, may influence the function of urocortinergic cells in centrally projecting EWcp by activating TRPA1 ion channels. We aimed to examine the functional activity of TRPA1 in centrally projecting EWcp and its possible role in a mouse model of acute alcohol exposure. Methods: Electrophysiological measurements were performed on acute brain slices of C57BL/6J male mice containing the centrally projecting EWcp to prove the functional activity of TRPA1 using a selective, potent, covalent agonist JT010. Male TRPA1 knockout (KO) and wildtype (WT) mice were compared with each other in the morphological studies upon acute alcohol treatment. In both genotypes, half of the animals was treated intraperitoneally with 1 g/kg 6% ethanol vs. physiological saline-injected controls. Transcardial perfusion was performed 2 h after the treatment. In the centrally projecting EWcp area, FOS immunohistochemistry was performed to assess neuronal activation. TRPA1, CART, and urocortin 1 mRNA expression as well as urocortin 1 and CART peptide content was semi-quantified by RNAscope in situ hybridization combined with immunofluorescence. Results: JT010 activated TRPA1 channels of the urocortinergic cells in acute brain slices. Alcohol treatment resulted in a significant FOS activation in both genotypes. Alcohol decreased the Trpa1 mRNA expression in WT mice. The assessment of urocortin 1 peptide immunoreactivity revealed lower basal urocortin 1 in KO mice compared to WTs. The urocortin 1 peptide content was affected genotype-dependently by alcohol: the peptide content decreased in WTs while it increased in KO mice. Alcohol exposure influenced neither CART and urocortin 1 mRNA expression nor the centrally projecting EWcp/CART peptide content. Conclusion: We proved the presence of functional TRPA1 receptors on urocortin 1 neurons of the centrally projecting EWcp. Decreased Trpa1 mRNA expression upon acute alcohol treatment, associated with reduced neuronal urocortin 1 peptide content suggesting that this cation channel may contribute to the regulation of the urocortin 1 release.
Novel homozygous silent mutation of ITGB3 gene caused Glanzmann thrombasthenia

Glanzmann thrombasthenia (GT) is a rare inherited disease characterized by mucocutaneous bleeding due to the abnormalities in quantity or quality of platelet membrane GP IIb (CD41) or GP IIIa (CD61). GP IIb and GP IIIa are encoded by the ITGA2B and ITGB3 genes, respectively. Herein, we described a 7-year-old Chinese boy of the consanguineous couple who was diagnosed with GT based on the typical clinical manifestations, absence of blood clot retraction and the reduced expression of CD41 and CD61 in platelets. A homozygous silent variant c.1431C > T (p. G477=) of the ITGB3 gene was identified by the Whole-exome sequencing and confirmed by Sanger sequencing. The variant was predicted to affect the splicing. RT-PCR and sequencing revealed that the variant caused a deletion of 95 base pairs and frameshift, and subsequently created a premature stop codon in exon 10 of ITGB3 (p. G477Afs*30). It was indicated that the variant c.1431C > T (p. G477=) of ITGB3 was the cause for Glanzmann thrombasthenia. Our findings expanded the mutation spectrum and provided the information for the genetic counseling, prenatal diagnosis and preimplantation genetic testing (PGT).
Photoresponse mechanisms of ultraviolet photodetectors based on colloidal ZnO quantum dot-graphene nanocomposites

Ultraviolet (UV) photodetectors were fabricated using the wet spin-coating for ZnO quantum dots (QDs) and the transfer method for the graphene sheet. High-resolution transmission electron microscopy images showed that the ZnO QDs were uniformly distributed between the voids of the surface circumferences on the graphene layers. Current-voltage measurements on the UV photodetector at 300 K showed that the ratio of the photocurrent to the dark current was about 1.1 × 104. The rise and the decay times of the UV photodetector were approximately 2 and 1 s, respectively. The photoresponse mechanisms are described on the basis of the experimental results.
Impacts on alternate bar geometry and dynamics in a trained sand bed river

This study investigates the occurrence and dynamics of single row alternate bars forming in a particular reach of the sand bed Elbe River in Germany. Although the formation and dynamics of alternate bars have been intensively investigated in the literature, there exists only a limited number of studies focusing on the characteristics of alternate bars forming under complex field conditions. This is particular the case for bars forming in trained sand bed rivers, as most previous field studies have focused on gravel bed rivers. Moreover, little is known on the impact of river training structures on bar characteristics in anthropogenic rivers. To close this gap, we present a comprehensive bed elevation data set that was collected over a period of 10 years within a 30 km long reach of the lower Elbe River in Germany by the Federal Waterways and Shipping Administration (WSV). The reach is characterized by a sand bed, has curved as well as straight parts, and exhibits a section that is less trained by groins than the neighboring sections. For our analyses, we propose a novel approach to estimate bar characteristics based on statistically derived geometrical parameters. The outcomes of the approach are used to show that bars in Elbe River belong to the free bar type and that their origin of formation and characteristics depend on hydrological and geometrical boundary conditions. The results reveal that the active width of the river bed, defined as the distance between the groin heads, is a crucial parameter for the occurrence of alternate in the reach. We further highlight the impact of river bends on bar characteristics, as bars in the outer bend were longer and higher than their inner bend counterparts. Finally, we show that simple predictors for bar formation can be successfully applied to predict bar formation in sand bed rivers but that care needs to be taken when applying such approaches to more complex boundary conditions.
Analysis of the wall thickness of intracranial aneurysms: Can computational fluid dynamics detect the translucent areas of saccular intracranial aneurysms and predict the rupture risk preoperatively?

Background and purpose The translucent area on the surface of intracranial aneurysms (IAs) is associated with rupture risk. In the present study, the Polyflow module of the Ansys software was used to simulate and analyze the thickness of the aneurysm wall to detect whether it was “translucent” and to assess the rupture risk. Methods Forty-five patients with 48 IAs who underwent microsurgery were retrospectively reviewed. The medical records, radiographic data, and intraoperative images of the patients were collected. The image data were analyzed using computational fluid dynamics (CFD) simulations to explore the relationship between the simulated thickness of the aneurysm wall, the translucent area, and the rupture point of the real aneurysm's surface to predict the rupture risk and provide a certain reference basis for clinical treatment. Results The Polyflow simulation revealed that the location of the minimum extreme point of the simulated aneurysm wall thickness was consistent with the translucent area or rupture point on the surface of the real aneurysm. There was a downward trend in the correlation between the change rate (IS) in the wall area and volume during aneurysm growth and rupture. Ruptured aneurysms have a greater inhomogeneity coefficient Iδ than the unruptured ones. In the unruptured group, translucent aneurysms also had greater inhomogeneity coefficients Iδ and more significant thickness changes (multiple IBA) than non-translucent ones. Conclusions The Ansys software Polyflow module could detect whether the unruptured aneurysms were translucent and predict the rupture risk and rupture point. Clinical trial registration https://clinicaltrials.gov/, Identifier, NCT03133624.
Disturbance auto-encoder generation model: Few-shot learning method for IGBT open-circuit fault diagnosis in three-phase converters

With the rapid development of converters in a variety of industrial fields, the fault diagnosis of power switching devices has become an important factor in ensuring the safe and reliable operation of related systems. In recent years, machine learning has performed well in many fault diagnosis tasks. The success of these advanced methods depends on sufficient marked samples for each fault type. However, in most industrial applications, it is expensive and difficult to collect fault samples, and the fault diagnosis model trained under the limited samples cannot meet the requirements of fault diagnosis accuracy. In order to solve this problem, this study proposes a few-shot learning method based on fault sample generation to realize the open-circuit fault diagnosis of IGBT in a three-phase PWM converter. This method is the deformation of the auto-encoder called the disturbance auto-encoder generation model. By designing the model structure and training algorithm constraints, the encoder learns the nonlinear transferable disturbance from the normal operating sample pairs. Then, the disturbance is applied to the decoder to synthesize new fault samples to realize the training of the fault diagnosis model with limited samples. The biggest advantage of this method is that it can achieve 95.90% fault diagnosis accuracy by only collecting the samples in the normal operating conditions of the target system. Finally, the feasibility and advantages of the proposed method are verified by comparative experiments.
High clinical diagnostic accuracy of combined salivary gland and myocardial metaiodobenzylguanidine scintigraphy in the diagnosis of Parkinson’s disease

Background Decreased myocardial uptake of 131I-metaiodobenzylguanidine (MIBG) is known to be an important feature to diagnose Parkinson’s disease (PD). However, the diagnosis accuracy of myocardial MIBG scintigraphy alone is often unsatisfying. Recent studies have found that the MIBG uptake of the major salivary glands was reduced in PD patients as well. Purpose To evaluate the diagnostic value of major salivary gland MIBG scintigraphy in PD, and explore the potential role of myocardial MIBG scintigraphy combined with salivary gland MIBG scintigraphy in distinguishing PD from non-PD (NPD). Methods Thirty-seven subjects were performed with 131I-MIBG scintigraphy. They were classified into the PD group (N = 18) and the NPD group (N = 19), based on clinical diagnostic criteria, DAT PET and 18F-FDG PET imaging findings. Images of salivary glands and myocardium were outlined to calculated the MIBG uptake ratios. Results The combination of left parotid and left submandibular gland early images had a good performance in distinguishing PD from NPD, with sensitivity, specificity, and accuracy of 50.00, 94.74, and 72.37%, respectively. Combining the major salivary gland and myocardial scintigraphy results in the early period showed a good diagnostic value with AUC, sensitivity and specificity of 0.877, 77.78, and 94.74%, respectively. Meanwhile, in the delayed period yield an excellent diagnostic value with AUC, sensitivity and specificity of 0.904, 88.89, and 84.21%, respectively. Conclusion 131I-MIBG salivary gland scintigraphy assisted in the diagnosis and differential diagnosis of PD. The combination of major salivary gland and myocardial 131I-MIBG scintigraphy further increased the accuracy of PD diagnosis.
A study on differences about the influencing factors of depressive symptoms between medical staff and residents during 2022 city-wide temporary static management period to fighting against COVID-19 pandemic in Shanghai

Objectives Our study aimed to identify the latent class of depressive symptoms in the Shanghai population during the city-wide temporary static management period and compare differences in the factors influencing depressive symptoms between medical staff and residents. Methods An online cross-sectional survey was conducted with 840 participants using questionnaires, including Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Pittsburgh Sleep Quality Index (PSQI), and self-compiled questionnaire (demographic characteristics and internet usage time). Latent class analysis (LCA) was performed based on participants' depressive symptoms. The latent class subgroups were compared using the chi-square test and t-test. Logistic regression was used in our study to analyze the factors influencing depressive symptoms within the medical staff group and residents group and then compare their differences. Results Two distinct subgroups were identified based on the LCA: the group with low-depressive symptoms and the group with high-depressive symptoms. There were significant differences between the two groups (P < 0.05) on age, education level, marital status, internet usage time, identity characteristics (medical staff or residents), family income level, living style, overall quality of sleep, and anxiety levels. Furthermore, logistic regression analysis results showed that compared with the residents group, the participants in the group of medical staff with “increasing internet usage time” and the “daytime dysfunction” would have nearly two times the possibility of getting serious depressive symptoms. Conclusions There are differences in the factors influencing depression symptoms between medical staff and residents during the 2022 city-wide temporary static management period to fighting against the COVID-19 pandemic in Shanghai. We should pay special attention to those with increasing internet usage time and daytime dysfunction in medical staff working in a special environment such as the COVID-19 pandemic.
Emergent dynamics in a robotic model based on the Caenorhabditis elegans connectome

We analyze the neural dynamics and their relation with the emergent actions of a robotic vehicle that is controlled by a neural network numerical simulation based on the nervous system of the nematode Caenorhabditis elegans. The robot interacts with the environment through a sensor that transmits the information to sensory neurons, while motor neurons outputs are connected to wheels. This is enough to allow emergent robot actions in complex environments, such as avoiding collisions with obstacles. Working with robotic models makes it possible to simultaneously keep track of the dynamics of all the neurons and also register the actions of the robot in the environment in real time, while avoiding the complex technicalities of simulating a real environment. This allowed us to identify several relevant features of the neural dynamics associated with the emergent actions of the robot, some of which have already been observed in biological worms. These results suggest that some basic aspects of behaviors observed in living beings are determined by the underlying structure of the associated neural network.
Naso-oropharyngeal microbiome from breast cancer patients diagnosed with COVID-19

Due to immunosuppressive cancer therapies, cancer patients diagnosed with COVID-19 have a higher chance of developing severe symptoms and present a higher mortality rate in comparison to the general population. Here we show a comparative analysis of the microbiome from naso-oropharyngeal samples of breast cancer patients with respect to SARS-CoV-2 status and identified bacteria associated with symptom severity. Total DNA of naso-oropharyngeal swabs from 74 women with or without breast cancer, positive or negative for SARS-CoV-2 were PCR-amplified for 16S-rDNA V3 and V4 regions and submitted to massive parallel sequencing. Sequencing data were analyzed with QIIME2 and taxonomic identification was performed using the q2-feature-classifier QIIME2 plugin, the Greengenes Database, and amplicon sequence variants (ASV) analysis. A total of 486 different bacteria were identified. No difference was found in taxa diversity between sample groups. Cluster analysis did not group the samples concerning SARS-CoV-2 status, breast cancer diagnosis, or symptom severity. Three taxa (Pseudomonas, Moraxella, and Klebsiella,) showed to be overrepresented in women with breast cancer and positive for SARS-CoV-2 when compared to the other women groups, and five bacterial groups were associated with COVID-19 severity among breast cancer patients: Staphylococcus, Staphylococcus epidermidis, Scardovia, Parasegitibacter luogiensis, and Thermomonas. The presence of Staphylococcus in COVID-19 breast cancer patients may possibly be a consequence of nosocomial infection.
Physiological and molecular implications of multiple abiotic stresses on yield and quality of rice

Abiotic stresses adversely affect rice yield and productivity, especially under the changing climatic scenario. Exposure to multiple abiotic stresses acting together aggravates these effects. The projected increase in global temperatures, rainfall variability, and salinity will increase the frequency and intensity of multiple abiotic stresses. These abiotic stresses affect paddy physiology and deteriorate grain quality, especially milling quality and cooking characteristics. Understanding the molecular and physiological mechanisms behind grain quality reduction under multiple abiotic stresses is needed to breed cultivars that can tolerate multiple abiotic stresses. This review summarizes the combined effect of various stresses on rice physiology, focusing on grain quality parameters and yield traits, and discusses strategies for improving grain quality parameters using high-throughput phenotyping with omics approaches.
The miR169b/NFYA1 module from the halophyte Halostachys caspica endows salt and drought tolerance in Arabidopsis through multi-pathways

Salt and drought are the major abiotic stress factors plaguing plant growth, development and crop yields. Certain abiotic-stress tolerant plants have developed special mechanisms for adapting to adverse environments in the long process of evolution. Elucidating the molecular mechanisms by which they can exert resistance to abiotic stresses is beneficial for breeding new cultivars to guide agricultural production. Halostachys caspica, a perennial halophyte belonging to Halostachys in Amaranthaceae, is extremely tolerant to harsh environments, which is commonly grown in the saline-alkali arid desert area of Northwest, China. However, the molecular mechanism of stress tolerance is unclear. Nuclear Factor Y-A (NFYA) is a transcription factor that regulates the expression of downstream genes in plant response to adverse environments. It has also been reported that some members of the NFYA family are the main targets of miR169 in plants. In this study, we mainly focused on exploring the functions and preliminary mechanism of the miR169b/NFYA1 module from H. caspica to abiotic stress. The main results showed that RLM-RACE technology validated that HcNFYA1 was targeted by HcmiR169b, qRT-PCR revealed that HcmiR169b was repressed and HcNFYA1 was induced in the H. caspica branches under various abiotic stress as well ABA treatment and Arabidopsis stable transformation platform with molecular methods was applied to elucidate that the HcmiR169b/HcNFYA1 module conferred the salt and drought tolerance to plants by enhancing ABA synthesis and ABA signal transduction pathways, maintaining ROS homeostasis and the stability of cell membrane. HcNFYA1 is expected to be a candidate gene to improve plant resistance to salt and drought stresses.
Identification and validation of immune cells and hub genes alterations in recurrent implantation failure: A GEO data mining study

Introduction: Recurrent implantation failure (RIF) is a distressing problem in assisted reproductive technology (ART). Immunity plays a vital role in recurrent implantation failure (RIF) occurrence and development, but its underlying mechanism still needs to be fully elucidated. Through bioinformatics analysis, this study aims to identify the RIF-associated immune cell types and immune-related genes. Methods: The differentially expressed genes (DEGs) were screened based on RIF-associated Gene Expression Omnibus (GEO) datasets. Then, the enrichment analysis and protein-protein interaction (PPI) analysis were conducted with the DEGs. The RIF-associated immune cell types were clarified by combining single sample gene set enrichment analysis (ssGSEA) and CIBERSORT. Differentially expressed immune cell types-related modules were identified by weighted gene co-expression network analysis (WGCNA) and local maximal quasi-clique merger (lmQCM) analysis. The overlapping genes between DEGs and genes contained by modules mentioned above were delineated as candidate hub genes and validated in another two external datasets. Finally, the microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) that interacted with hub genes were predicted, and the competing endogenous RNA (ceRNA) regulatory network was structured. Results: In the present study, we collected 324 DEGs between RIF and the control group, which functions were mainly enriched in immune-related signaling pathways. Regarding differential cell types, the RIF group had a higher proportion of activated memory CD4 T cells and a lower proportion of γδ T cells in the endometrial tissue. Finally, three immune-related hub genes (ALOX5AP, SLC7A7, and PTGS2) were identified and verified to effectively discriminate RIF from control individuals with a specificity rate of 90.8% and a sensitivity rate of 90.8%. In addition, we constructed a key ceRNA network that is expected to mediate molecular mechanisms in RIF. Conclusion: Our study identified the intricate correlation between immune cell types and RIF and provided new immune-related hub genes that offer promising diagnostic and therapeutic targets for RIF.
Leber’s hereditary optic neuropathy: Update on current diagnosis and treatment

Leber’s hereditary optic neuropathy (LHON) is a fairly prevalent mitochondrial disorder (1:50,000) arising from the dysfunction of the mitochondrial respiratory chain, which eventually leads to apoptosis of retinal ganglion cells. The usual presentation is that of a young male with a sequential reduction in visual acuity. OCT has been used to study the pattern of optic nerve involvement in LHON, showing early thickening of the inferior and superior retinal nerve fibre layer and ganglion cell layer thinning corresponding with the onset of symptoms. Of the three primary mutations for LHON, the m.14484T>C mutation has the best visual prognosis. Recent emerging therapeutic options for LHON include idebenone and the introduction of genetic vector therapy, which is currently in phase III clinical trials. Screening of family members and adequate advice to avoid environmental triggers, such as smoking and alcohol consumption, are also cornerstones in the management of LHON.