Miracle-dz/UniFAR-FTUs huggingface dataset:
DeteX: A highly accurate software for detecting SNV and InDel in single and paired NGS data in cancer research

Background: Genetic testing is becoming more and more accepted in the auxiliary diagnosis and treatment of tumors. Due to the different performance of the existing bioinformatics software and the different analysis results, the needs of clinical diagnosis and treatment cannot be met. To this end, we combined Bayesian classification model (BC) and fisher exact test (FET), and develop an efficient software DeteX to detect SNV and InDel mutations. It can detect the somatic mutations in tumor-normal paired samples as well as mutations in a single sample. Methods: Combination of Bayesian classification model (BC) and fisher exact test (FET). Results: We detected SNVs and InDels in 11 TCGA glioma samples, 28 clinically targeted capture samples and 2 NCCL-EQA standard samples with DeteX, VarDict, Mutect, VarScan and GatkSNV. The results show that, among the three groups of samples, DeteX has higher sensitivity and precision whether it detects SNVs or InDels than other callers and the F1 value of DeteX is the highest. Especially in the detection of substitution and complex mutations, only DeteX can accurately detect these two kinds of mutations. In terms of single-sample mutation detection, DeteX is much more sensitive than the HaplotypeCaller program in Gatk. In addition, although DeteX has higher mutation detection capabilities, its running time is only . 609 of VarDict, which is . 704 and . 343 longer than VarScan and MuTect, respectively. Conclusion: In this study, we developed DeteX to detect SNV and InDel mutations in single and paired samples. DeteX has high sensitivity and precision especially in the detection of substitution and complex mutations. In summary, DeteX from NGS data is a good SNV and InDel caller. Graphical Abstract Software running process and output results.
Involvement of three chemosensory proteins in perception of host plant volatiles in the tea green leafhopper, Empoasca onukii

Chemosensory proteins (CSPs) can bind and transport odorant molecules, which are believed to be involved in insect chemoreception. Here, we investigated three CSPs in perception of volatiles in Empoasca onukii. Expression profiles showed that although EonuCSP4, EonuCSP 6-1 and EonuCSP6-2 were ubiquitously expressed in heads, legs, thoraxes and abdomen, they were all highly expressed in the antennae of E. onukii. Further, fluorescence competitive binding assays revealed that EonuCSP4 and 6-1 had binding affinities for three plant volatiles, suggesting their possible involvement in the chemosensory process. Among them, EonuCSP6-1 showed relatively high binding affinities for benzaldehyde. Behavioral assays revealed that the adults of E. onukii showed a significant preference for two compounds including benzaldehyde. The predicted three-dimensional (3D) structures of these 3 CSP have the typical six α-helices, which form the hydrophobic ligand-binding pocket. We therefore suggest that Eoun6-1 might be involved in the chemoreception of the host-related volatiles for E. onukii. Our data may provide a chance of finding a suitable antagonist of alternative control strategies which block the perception of chemosensory signals in pest, preventing the food- orientation behaviors.
Real-time Volt-Var control of grid forming converters in DER-enriched distribution network

The growing installation of distributed energy resources (DERs) in a distribution network (DN) poses substantial issues related to voltage regulation. Due to constrained switching operation and slower response time, traditional voltage regulation devices cannot handle current voltage-related challenges. One alternative to solve these problems is to use smart converters to control the reactive power to regulate the voltage. Volt-Var control (VVC) is one of the simplest approaches for controlling the reactive power from smart converters. Among several converters, grid forming converters (GFCs) are more suitable in DER-enriched distribution networks. Since DER-enriched distribution networks have a higher fluctuation in voltage profile, real-time control is advantageous. Therefore, this work presents an advanced real-time reactive power control for handling voltage violations in a DN using GFC. The uniqueness of this method is that it controls the voltage magnitude of affected nodes by dispatching reactive power from smart converters in real-time. By running cyber-physical co-simulation (CPCS) between the Typhoon HIL 604 and OpenDSS, the Volt-Var control can be done in real time. The grid-forming converter is modelled in Typhoon HIL 604, which acts as a physical layer of the proposed cyber-physical system for real-time VVC. A CIGRE medium voltage distribution network is designed in OpenDSS and serves as one of the parts of the cyber layer. The CPCS between Typhoon HIL and OpenDSS and the control algorithm are both done by a programme written in Python. The execution of the control algorithm is performed in real time using the Supervisory Control and Data Acquisition (SCADA) developed in this study. The real-time simulation shows that the proposed real-time VVC is capable of handling voltage violations in real time in DER-enriched distribution networks.
Continuous-cropping-tolerant soybean cultivars alleviate continuous cropping obstacles by improving structure and function of rhizosphere microorganisms

Introduction Soybean continuous cropping will change soil microorganisms and cause continuous cropping obstacles, resulting in a significant yield decline. Different soybean cultivars have different tolerances to continuous cropping, but the relationship between continuous cropping tolerance and soil microorganisms is not clear. Methods Two soybean cultivars with different tolerances to continuous cropping were used to study the effects of continuous cropping on soil physical and chemical properties, nitrogen and phosphorus cyclic enzyme activities, rhizosphere soil microbial community and function. Results The results showed that the yield reduction rate of a continuous-cropping-tolerant cultivar (L14) was lower than that of a continuous-cropping-sensitive cultivar (L10) under continuous cropping. At R1 and R6 growth stages, soil nutrient content (NH4+-N, NO3−-N, AP, DOM, TK, and pH), nitrogen cycling enzyme (URE, NAG, LAP) activities, phosphorus cycling enzyme (ALP, NPA, ACP) activities, copy numbers of nitrogen functional genes (AOA, AOB, nirK, nirK) and phosphorus functional genes (phoA, phoB) in L14 were higher than those in L10. Soybean cultivar was an important factor affecting the structure and functional structure of bacterial community under continuous cropping. The relative abundances of Proteobacteria, Bacteroidota, Acidobacteriota and Verrucomicrobiota with L14 were significantly higher than those of L10. The complexity of the soil bacterial community co-occurrence network in L14 was higher than that in L10. Discussion The continuous-cropping-tolerant soybean cultivar recruited more beneficial bacteria, changed the structure and function of microbial community, improved soil nitrogen and phosphorus cycling, and reduced the impact of continuous cropping obstacles on grain yield.
The nutritional composition of the vegetable soybean (maodou) and its potential in combatting malnutrition

Introduction Global malnutrition continues to be a canker owing to poor eating habits and over-reliance on the major staple crops. Vegetable soybean (maodou) is gaining popularity globally as an affordable snack and vegetable. Methods In this study, we profiled the nutritional composition of 12 soybean cultivars at the vegetable (R6-R7) and mature (R8) stages. We also conducted an RNA-seq analysis during seed development, focusing on key biosynthesis enzymes for quality traits. Results The results showed that 100 g of maodou contained 66.54% moisture, 13.49% protein, 7.81% fatty acids, 2.47% soluble sugar, abundant content of minerals, and micronutrients, including folate (462.27 μg FW) and carotenoids (3,935.41 μg FW). Also, the isoflavone content of maodou ranged between 129.26 and 2,359.35 μg/g FW. With regard to the recommended daily allowance, 100 g fresh weight of maodou can contribute 26.98, 115.57, and 11.60% of protein, folate, and zinc, respectively, and significant proportions of other nutrients including linoleic acid (21.16%), linolenic acid (42.96%), zinc (11.60%), and iron (18.01%). On a dry weight basis, maodou has two to six folds higher contents of folate, tocopherol, and carotenoid than the mature soybean. Furthermore, RNA-seq analysis revealed that key biosynthesis enzymes of quality traits are differentially expressed during seed development and may contribute to variations in the content of quality traits at the vegetable and mature stages. Correlation analysis of quality traits at both stages revealed that protein only correlated positively with zinc at the vegetable stage but negatively correlated with total tocopherol and total fatty acid at the mature stage. Complex associations among folates, soluble sugar, and isoflavones were also identified. Discussion This study provides insight into the nutritional contents of vegetable soybean and demonstrates that maodou is essential for meeting the nutritional requirements of most countries. Graphical Abstract
Genome-wide association study of yield-related traits in common wheat (Triticum aestivum L.) under normal and drought treatment conditions

The primary goal of modern wheat breeding is to develop new high-yielding and widely adaptable varieties. We analyzed four yield-related agronomic traits in 502 wheat accessions under normal conditions (NC) and drought treatment (DT) conditions over three years. The genome-wide association analysis identified 51 yield-related and nine drought-resistance-related QTL, including 13 for the thousand-grain weight (TGW), 30 for grain length (GL), three for grain width (GW), five for spike length (SL) and nine for stress tolerance index (STI) QTL in wheat. These QTL, containing 72 single nucleotide polymorphisms (SNPs), explained 2.23 – 7.35% of the phenotypic variation across multiple environments. Eight stable SNPs on chromosomes 2A, 2D, 3B, 4A, 5B, 5D, and 7D were associated with phenotypic stability under NC and DT conditions. Two of these stable SNPs had association with TGW and STI. Several novel QTL for TGW, GL and SL were identified on different chromosomes. Three linked SNPs were transformed into kompetitive allele-specific PCR (KASP) markers. These results will facilitate the discovery of promising SNPs for yield-related traits and/or drought stress tolerance and will accelerate the development of new wheat varieties with desirable alleles.
A hybrid approach to study large conformational transitions of biomolecules from single particle XFEL diffraction data

X-ray free-electron laser (XFEL) is the latest generation of the X-ray source that could become an invaluable technique in structural biology. XFEL has ultrashort pulse duration, extreme peak brilliance, and high spatial coherence, which could enable the observation of the biological molecules in near nature state at room temperature without crystallization. However, for biological systems, due to their low diffraction power and complexity of sample delivery, experiments and data analysis are not straightforward, making it extremely challenging to reconstruct three-dimensional (3D) structures from single particle XFEL data. Given the current limitations to the amount and resolution of the data from such XFEL experiments, we propose a new hybrid approach for characterizing biomolecular conformational transitions by using a single 2D low-resolution XFEL diffraction pattern in combination with another known conformation. In our method, we represent the molecular structure with a coarse-grained model, the Gaussian mixture model, to describe large conformational transitions from low-resolution XFEL data. We obtain plausible 3D structural models that are consistent with the XFEL diffraction pattern by deforming an initial structural model to maximize the similarity between the target pattern and the simulated diffraction patterns from the candidate models. We tested the proposed algorithm on two biomolecules of different sizes with different complexities of conformational transitions, adenylate kinase, and elongation factor 2, using synthetic XFEL data. The results show that, with the proposed algorithm, we can successfully describe the conformational transitions by flexibly fitting the coarse-grained model of one conformation to become consistent with an XFEL diffraction pattern simulated from another conformation. In addition, we showed that the incident beam orientation has some effect on the accuracy of the 3D structure modeling and discussed the reasons for the inaccuracies for certain orientations. The proposed method could serve as an alternative approach for retrieving information on 3D conformational transitions from the XFEL diffraction patterns to interpret experimental data. Since the molecules are represented by Gaussian kernels and no atomic structure is needed in principle, such a method could also be used as a tool to seek initial models for 3D reconstruction algorithms.
Speech phoneme and spectral smearing based non-invasive COVID-19 detection

COVID-19 is a deadly viral infection that mainly affects the nasopharyngeal and oropharyngeal cavities before the lung in the human body. Early detection followed by immediate treatment can potentially reduce lung invasion and decrease fatality. Recently, several COVID-19 detections methods have been proposed using cough and breath sounds. However, very little study has been done on the use of phoneme analysis and the smearing of the audio signal in COVID-19 detection. In this paper, this problem has been addressed and the classification of speech samples has been carried out in COVID-19-positive and healthy audio samples. Additionally, the grouping of the phonemes based on reference classification accuracies have been proposed for effectiveness and faster detection of the disease at a primary stage. The Mel and Gammatone Cepstral coefficients and their derivatives are used as the features for five standard machine learning-based classifiers. It is observed that the generalized additive model provides the highest accuracy of 97.22% for the phoneme grouping “/t//r//n//g//l/. ” This smearing-based phoneme classification technique can also be used in the future to classify other speech-related disease detections.
The chronification mechanism of orofacial inflammatory pain: Facilitation by GPER1 and microglia in the rostral ventral medulla

Background Chronic orofacial pain is a common and incompletely defined clinical condition. The role of G protein-coupled estrogen receptor 1 (GPER1) as a new estrogen receptor in trunk and visceral pain regulation is well known. Here, we researched the role of GPER1 in the rostral ventral medulla (RVM) during chronic orofacial pain. Methods and Results A pain model was established where rats were injected in the temporomandibular joint with complete Freund’s adjuvant (CFA) to simulate chronic orofacial pain. Following this a behavioral test was performed to establish pain threshold and results showed that the rats injected with CFA had abnormal pain in the orofacial regions. Additional Immunostaining and blot analysis indicated that microglia were activated in the RVM and GPER1 and c-Fos were significantly upregulated in the rats. Conversely, when the rats were injected with G15 (a GPER1 inhibitor) the abnormal pain the CFA rats were experiencing was alleviated and microglia activation was prevented. In addition, we found that G15 downregulated the expression of phospholipase C (PLC) and protein kinase C (PKC), inhibited the expression of GluA1, restores aberrant synaptic plasticity and reduces the overexpression of the synapse-associated proteins PSD-95 and syb-2 in the RVM of CFA rats. Conclusion The findings indicate that GPER1 mediates chronic orofacial pain through modulation of the PLC-PKC signal pathway, sensitization of the RVM region and enhancement of neural plasticity. These results of this study therefore suggest that GPER1 may serve as a potential therapeutic target for chronic orofacial pain.
Evaluation of AQP4 functional variants and its association with fragile X-associated tremor/ataxia syndrome

Introduction Fragile X-associated tremor/ataxia syndrome (FXTAS, OMIM# 300623) is a late-onset neurodegenerative disorder with reduced penetrance that appears in adult FMR1 premutation carriers (55–200 CGGs). Clinical symptoms in FXTAS patients usually begin with an action tremor. After that, different findings including ataxia, and more variably, loss of sensation in the distal lower extremities and autonomic dysfunction, may occur, and gradually progress. Cognitive deficits are also observed, and include memory problems and executive function deficits, with a gradual progression to dementia in some individuals. Aquaporin 4 (AQP4) is a commonly distributed water channel in astrocytes of the central nervous system. Changes in AQP4 activity and expression have been implicated in several central nervous system disorders. Previous studies have suggested the associations of AQP4 single nucleotide polymorphisms (SNPs) with brain-water homeostasis, and neurodegeneration disease. To date, this association has not been studied in FXTAS. Methods To investigate the association of AQP4 SNPs with the risk of presenting FXTAS, a total of seven common AQP4 SNPs were selected and genotyped in 95 FMR1 premutation carriers with FXTAS and in 65 FMR1 premutation carriers without FXTAS. Results The frequency of AQP4-haplotype was compared between groups, denoting 26 heterozygous individuals and 5 homozygotes as carriers of the minor allele in the FXTAS group and 25 heterozygous and 2 homozygotes in the no-FXTAS group. Statistical analyses showed no significant associations between AQP4 SNPs/haplotypes and development of FXTAS. Discussion Although AQP4 has been implicated in a wide range of brain disorders, its involvement in FXTAS remains unclear. The identification of novel genetic markers predisposing to FXTAS or modulating disease progression is critical for future research involving predictors and treatments.
Phenotypic diversity and distinctiveness of the Belltall garlic landrace

Among the Mediterranean horticultural landraces, garlic is one of the crops most threatened by genetic erosion. Due to its sexual sterility and to the incidence of seed-borne diseases, historical varieties have been widely replaced by commercial cultivars. In Catalonia, despite the historical relevance of the crop, solely the Belltall garlic landrace is cultivated for commercial purposes. To assess the genotypic and phenotypic diversity within the Belltall garlic, we evaluated sixteen local accessions and five recognized traditional and modern varieties as controls. Genetic analysis with SSR and InDel markers showed low genetic diversity within the Belltall population, grouping modern and traditional varieties separately. Farmers and consumers were involved in the definition of the landrace ideotype and classified the materials by means of projective mapping. Scant phenotypic diversity was found within the Belltall landrace, which is characterized by its color profile and the small size of bulb and cloves. The Belltall landrace grown outside its area of origin lost the distinctive quality signals that differentiate the landrace from the commercial cultivars (clove appearance), indicating that the high quality of the landrace is under genotype-by-environment effects (i.e. local adaptation). Moreover, the size of the Belltall sowing clove had a strong effect on the harvested bulb size. Our research represents a case study for the description of the variability within garlic landraces and an approach to quantify the phenomenon of local adaptation that currently drives their conservation.
Artificial intelligence applicated in gastric cancer: A bibliometric and visual analysis via CiteSpace

Objective This study aimed to analyze and visualize the current research focus, research frontiers, evolutionary processes, and trends of artificial intelligence (AI) in the field of gastric cancer using a bibliometric analysis. Methods The Web of Science Core Collection database was selected as the data source for this study to retrieve and obtain articles and reviews related to AI in gastric cancer. All the information extracted from the articles was imported to CiteSpace to conduct the bibliometric and knowledge map analysis, allowing us to clearly visualize the research hotspots and trends in this field. Results A total of 183 articles published between 2017 and 2022 were included, contributed by 201 authors from 33 countries/regions. Among them, China (47.54%), Japan (21.86%), and the USA (13.11%) have made outstanding contributions in this field, accounting fsor 82.51% of the total publications. The primary research institutions were Wuhan University, Tokyo University, and Tada Tomohiro Inst Gastroenterol and Proctol. Tada (n = 12) and Hirasawa (n = 90) were ranked first in the top 10 authors and co-cited authors, respectively. Gastrointestinal Endoscopy (21 publications; IF 2022, 9.189; Q1) was the most published journal, while Gastric Cancer (133 citations; IF 2022, 8.171; Q1) was the most co-cited journal. Nevertheless, the cooperation between different countries and institutions should be further strengthened. The most common keywords were AI, gastric cancer, and convolutional neural network. The “deep-learning algorithm” started to burst in 2020 and continues till now, which indicated that this research topic has attracted continuous attention in recent years and would be the trend of research on AI application in GC. Conclusions Research related to AI in gastric cancer is increasing exponentially. Current research hotspots focus on the application of AI in gastric cancer, represented by convolutional neural networks and deep learning, in diagnosis and differential diagnosis and staging. Considering the great potential and clinical application prospects, the related area of AI applications in gastric cancer will remain a research hotspot in the future.