Miracle-dz/UniFAR-FTUs huggingface dataset:
Hydroacoustic survey on fish spatial distribution in the early impoundment stage of Yuwanghe Reservoir in southwest China

Understanding the fish community structure and spatial distribution characteristics is essential for appropriate reservoir fishery management, especially in the early impoundment stage of the reservoir, which could help in obtaining basic data and performing artificial adjustments to biological communities. On the basis of this concept, we conducted a survey of the fish community and distribution at the newly constructed reservoir in southwest China by using a combination of methods, including hydroacoustic survey and fish sampling. Fish sampling showed a single fish community structure (six species belonging to four families) assembled in the reservoir, and the dominant species was Pseudorasbora parva which accounted for 98.79% of the fish population. In the hydroacoustic survey, the average fish density was 318.7 ± 256.1 individuals/1,000 m2. Irregular distribution of the fish was observed in the horizontal direction. The fish densities in the head area, middle area, and tail area of the reservoir were 168.5 ± 60.1, 306.8 ± 124.7, and 696.4 ± 288.9 individuals/1,000 m2, respectively, which showed a trend of increase in fish density with an increase in distance from the dam. More than 97.3% of the fish in the vertical direction were distributed in the water layer of depth 0 to 12 m. The average total length of fish was 75.4 mm, and the mean fish biomass in the reservoir was approximately 984.8 g/1,000 m2. According to Pearson correlation analysis, the main factors affecting the spatial distribution of fish were water depth, water temperature, dissolved oxygen, total nitrogen, and plankton density. Our results suggested that the fish community structure should be adjusted by releasing native carnivorous fish to control the abundance of small fish. Moreover, filter-feeding fish such as silver carp and bighead carp should be released in the reservoir to control the plankton community; this will enable the maintenance of the reservoir ecosystem in a healthy state while increasing the economic benefits to the local area.
Machine learning analysis of complex late gadolinium enhancement patterns to improve risk prediction of major arrhythmic events

Background Machine learning analysis of complex myocardial scar patterns affords the potential to enhance risk prediction of life-threatening arrhythmia in stable coronary artery disease (CAD). Objective To assess the utility of computational image analysis, alongside a machine learning (ML) approach, to identify scar microstructure features on late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) that predict major arrhythmic events in patients with CAD. Methods Patients with stable CAD were prospectively recruited into a CMR registry. Shape-based scar microstructure features characterizing heterogeneous (‘peri-infarct’) and homogeneous (‘core’) fibrosis were extracted. An ensemble of machine learning approaches were used for risk stratification, in addition to conventional analysis using Cox modeling. Results Of 397 patients (mean LVEF 45.4 ± 16.0) followed for a median of 6 years, 55 patients (14%) experienced a major arrhythmic event. When applied within an ML model for binary classification, peri-infarct zone (PIZ) entropy, peri-infarct components and core interface area outperformed a model representative of the current standard of care (LVEF<35% and NYHA>Class I): AUROC (95%CI) 0.81 (0.81–0.82) vs. 0.64 (0.63–0.65), p = 0.002. In multivariate cox regression analysis, these features again remained significant after adjusting for LVEF<35% and NYHA>Class I: PIZ entropy hazard ratio (HR) 1.88, 95% confidence interval (CI) 1.38–2.56, p < 0.001; number of PIZ components HR 1.34, 95% CI 1.08–1.67, p = 0.009; core interface area HR 1.6, 95% CI 1.29–1.99, p = <0.001. Conclusion Machine learning models using LGE-CMR scar microstructure improved arrhythmic risk stratification as compared to guideline-based clinical parameters; highlighting a potential novel approach to identifying candidates for implantable cardioverter defibrillators in stable CAD.
Initial Maintenance of Tropical Cyclone Size in the Western North Pacific

A tropical cyclone (TC) size parameter, which is defined here as the radius of 15 m s 21 near-surface wind speed (R15), is calculated for 145 TCs in the western North Pacific during 2000‐05 based on QuikSCAT oceanic winds. For the 73 TCs that intensified to typhoon intensity during their lifetimes, the 33% and 67% respective percentiles of R15 at tropical storm intensity and at typhoon intensity are used to categorize small, medium, and large TCs. Whereas many of the small TCs form from an easterly wave synoptic pattern, the monsoon-related formation patterns are favorable for forming medium to large TCs. Most of these 73 TCs stay in the same size category during intensification, which implies specific physical mechanisms for maintaining TC size in the basin. The 18 persistently large TCs from the tropical storm to the typhoon stage mostly havenorthwestward or north-northwestward tracks, while the 16 persistently small TCs either move westward‐ northwestward in lower latitudes or develop at higher latitudes with various track types. For the large TCs, strong low-level southwesterly winds exist in the outer core region south of the TC center throughout the intensification period. The small TCs are more influenced by the subtropical high during intensification. The conclusion is that it is the low-level environment that determines the difference between large and small size storms during the early intensification period in the western North Pacific.
Bilateral ankle deformities affects gait kinematics in chronic stroke patients

Objectives Stroke patients suffer from ankle joint deformities due to spastic ankle muscles. This study evaluated the viability of using 3D scanned surface images of the feet of stroke victims to visually assess the deformities of a hemiparetic foot and investigated the influences of deformed ankle joints on gait kinematics. Methods A total of 30 subjects with stroke-induced hemiparesis and 11 age-matched healthy controls completed the clinical assessments. We analyzed their feet's morphometric characteristics using a 3D scanner, identified convenient anthropometric measurements, and conducted gait trials on even and uneven terrains. The 3D foot morphometric characteristics were evaluated using the geometric morphometrics method (GMM). Results Results showed that there were significant differences in bilateral foot shapes between the chronic stroke patients and healthy controls and between the paretic and non-paretic sides in the chronic stroke patients. In stroke patients, those with the smaller medial malleoli's vertical tilt angles showed significantly different ankle ranges of motion of dorsi-/plantar flexion during gaits on uneven terrains (p = 0.009). In addition, those with the greater medial malleoli's vertical tilt angles showed significantly different ankle ranges of motion of inversion/eversion during gaits on even and uneven terrains (p < 0.05). Conclusion Using 3D scanning technology, bilateral morphometric changes in the feet of chronic stroke patients were shown by GMM and the simple anthropometric measurements identified its shape deformities in the feet. Their possible effects on gait kinematics while walking on uneven terrains were investigated. Current methodology can be potentially useful in applying conventional productions of clinically manufactured, patient-fitted ankle-foot-orthosis in orthotics and prosthetics, and in detecting various unidentified pathological deformities in the feet.
Drought stress prediction and propagation using time series modeling on multimodal plant image sequences

The paper introduces two novel algorithms for predicting and propagating drought stress in plants using image sequences captured by cameras in two modalities, i.e., visible light and hyperspectral. The first algorithm, VisStressPredict, computes a time series of holistic phenotypes, e.g., height, biomass, and size, by analyzing image sequences captured by a visible light camera at discrete time intervals and then adapts dynamic time warping (DTW), a technique for measuring similarity between temporal sequences for dynamic phenotypic analysis, to predict the onset of drought stress. The second algorithm, HyperStressPropagateNet, leverages a deep neural network for temporal stress propagation using hyperspectral imagery. It uses a convolutional neural network to classify the reflectance spectra at individual pixels as either stressed or unstressed to determine the temporal propagation of stress in the plant. A very high correlation between the soil water content, and the percentage of the plant under stress as computed by HyperStressPropagateNet on a given day demonstrates its efficacy. Although VisStressPredict and HyperStressPropagateNet fundamentally differ in their goals and hence in the input image sequences and underlying approaches, the onset of stress as predicted by stress factor curves computed by VisStressPredict correlates extremely well with the day of appearance of stress pixels in the plants as computed by HyperStressPropagateNet. The two algorithms are evaluated on a dataset of image sequences of cotton plants captured in a high throughput plant phenotyping platform. The algorithms may be generalized to any plant species to study the effect of abiotic stresses on sustainable agriculture practices.
Comparative analysis of five type II TA systems identified in Pseudomonas aeruginosa reveals their contributions to persistence and intracellular survival

Background Pseudomonas aeruginosa is a grave nosocomial pathogen that persistently inhabits the lungs of patients with cystic fibrosis (CF) and causes various chronic infections. The bacterial toxin–antitoxin (TA) system is associated with latent and long-term infections, but the underlying mechanisms remain to be fully characterized. Methods We here investigated the diversity and function of five genomic type II TA systems widely distributed among P. aeruginosa clinical isolates. We also examined the distinct structural features of the toxin protein from different TA systems and characterized their contributions to persistence, invasion ability, and intracellular infection caused by P. aeruginosa. Results ParDE, PA1030/PA1029, and HigBA could modulate persister cell formation under treatment with specific antibiotics. Furthermore, cell-based transcriptional and invasion assays revealed that PA1030/PA1029 and HigBA TA systems were critical for intracellular survival. Discussion Our results highlight the prevalence and diverse roles of type II TA systems in P. aeruginosa and evaluate the possibility of using PA1030/PA1029 and HigBA TA pairs as targets for novel antibiotic treatments.
Platforms, advances, and technical challenges in virus-like particles-based vaccines

Viral infectious diseases threaten human health and global stability. Several vaccine platforms, such as DNA, mRNA, recombinant viral vectors, and virus-like particle-based vaccines have been developed to counter these viral infectious diseases. Virus-like particles (VLP) are considered real, present, licensed and successful vaccines against prevalent and emergent diseases due to their non-infectious nature, structural similarity with viruses, and high immunogenicity. However, only a few VLP-based vaccines have been commercialized, and the others are either in the clinical or preclinical phases. Notably, despite success in the preclinical phase, many vaccines are still struggling with small-scale fundamental research owing to technical difficulties. Successful production of VLP-based vaccines on a commercial scale requires a suitable platform and culture mode for large-scale production, optimization of transduction-related parameters, upstream and downstream processing, and monitoring of product quality at each step. In this review article, we focus on the advantages and disadvantages of various VLP-producing platforms, recent advances and technical challenges in VLP production, and the current status of VLP-based vaccine candidates at commercial, preclinical, and clinical levels.
Simo decoction curing spleen deficiency constipation was associated with brain-bacteria-gut axis by intestinal mucosal microbiota

Background Simo decoction (SMD) is a traditional prescription for treating gastrointestinal diseases. More and more evidences prove that SMD can treat constipation by regulating intestinal microbiota and related oxidative stress indicators, but the specific mechanism is still unclear. Methods A network pharmacological analysis was used to predict the medicinal substances and potential targets of SMD to alleviate constipation. Then, 15 male mice were randomly divided into normal group (MN group), natural recovery group (MR group), and SMD treatment group (MT group). Constipation model mice were constructed by gavage of Folium sennae decoction and control of diet and drinking water, and SMD was used for intervention after successful modeling. The levels of 5-hydroxytryptamine (5-HT), vasoactive intestinal peptide (VIP), superoxide dismutase (SOD), malondialdehyde (MDA), and fecal microbial activities were measured, and the intestinal mucosal microbiota was sequenced. Result Network pharmacology analysis showed that a total of 24 potential active components were obtained from SMD, and 226 target proteins were obtained after conversion. Meanwhile, we obtained 1,273 and 424 disease-related targets in the GeneCards database and the DisGeNET database, respectively. After combination and deduplication, the disease targets shared 101 targets with the potential active components of SMD. When the mice were intervened with SMD, the 5-HT, VIP, MDA, SOD content, and microbial activity in MT group were close to MN group, and Chao 1 and ACE in MT group were significantly higher than that in MR group. In the Linear discriminant analysis Effect Size (LEfSe) analysis, the abundance of beneficial bacteria such as Bacteroides, Faecalibacterium, Alistipes, Subdoligranulum, Lactiplantibacillus, and Phascolarctobacterium in MT group increased. At the same time, there were some associations between microbiota and brain-gut peptides and oxidative stress indicators. Conclusion SMD can promote intestinal health and relieve constipation through brain-bacteria-gut axis associating with intestinal mucosal microbiota and alleviate oxidative stress.
Genome wide association study of thyroid hormone levels following challenge with porcine reproductive and respiratory syndrome virus

Introduction: Porcine reproductive and respiratory syndrome virus (PRRSV) causes respiratory disease in piglets and reproductive disease in sows. Piglet and fetal serum thyroid hormone (i.e., T3 and T4) levels decrease rapidly in response to Porcine reproductive and respiratory syndrome virus infection. However, the genetic control of T3 and T4 levels during infection is not completely understood. Our objective was to estimate genetic parameters and identify quantitative trait loci (QTL) for absolute T3 and/or T4 levels of piglets and fetuses challenged with Porcine reproductive and respiratory syndrome virus. Methods: Sera from 5-week-old pigs (N = 1792) at 11 days post inoculation (DPI) with Porcine reproductive and respiratory syndrome virus were assayed for T3 levels (piglet_T3). Sera from fetuses (N = 1,267) at 12 or 21 days post maternal inoculation (DPMI) with Porcine reproductive and respiratory syndrome virus of sows (N = 145) in late gestation were assayed for T3 (fetal_T3) and T4 (fetal_T4) levels. Animals were genotyped using 60 K Illumina or 650 K Affymetrix single nucleotide polymorphism (SNP) panels. Heritabilities, phenotypic correlations, and genetic correlations were estimated using ASREML; genome wide association studies were performed for each trait separately using Julia for Whole-genome Analysis Software (JWAS). Results: All three traits were low to moderately heritable (10%–16%). Phenotypic and genetic correlations of piglet_T3 levels with weight gain (0–42 DPI) were 0.26 ± 0.03 and 0.67 ± 0.14, respectively. Nine significant quantitative trait loci were identified for piglet_T3, on Sus scrofa chromosomes (SSC) 3, 4, 5, 6, 7, 14, 15, and 17, and collectively explaining 30% of the genetic variation (GV), with the largest quantitative trait loci identified on SSC5, explaining 15% of the genetic variation. Three significant quantitative trait loci were identified for fetal_T3 on SSC1 and SSC4, which collectively explained 10% of the genetic variation. Five significant quantitative trait loci were identified for fetal_T4 on SSC1, 6, 10, 13, and 15, which collectively explained 14% of the genetic variation. Several putative immune-related candidate genes were identified, including CD247, IRF8, and MAPK8. Discussion: Thyroid hormone levels following Porcine reproductive and respiratory syndrome virus infection were heritable and had positive genetic correlations with growth rate. Multiple quantitative trait loci with moderate effects were identified for T3 and T4 levels during challenge with Porcine reproductive and respiratory syndrome virus and candidate genes were identified, including several immune-related genes. These results advance our understanding of growth effects of both piglet and fetal response to Porcine reproductive and respiratory syndrome virus infection, revealing factors associated with genomic control of host resilience.
Research on named entity recognition method of marine natural products based on attention mechanism

Marine natural product (MNP) entity property information is the basis of marine drug development, and this entity property information can be obtained from the original literature. However, the traditional methods require several manual annotations, the accuracy of the model is low and slow, and the problem of inconsistent lexical contexts cannot be solved well. In order to solve the aforementioned problems, this study proposes a named entity recognition method based on the attention mechanism, inflated convolutional neural network (IDCNN), and conditional random field (CRF), combining the attention mechanism that can use the lexicality of words to make attention-weighted mentions of the extracted features, the ability of the inflated convolutional neural network to parallelize operations and long- and short-term memory, and the excellent learning ability. A named entity recognition algorithm model is developed for the automatic recognition of entity information in the MNP domain literature. Experiments demonstrate that the proposed model can properly identify entity information from the unstructured chapter-level literature and outperform the control model in several metrics. In addition, we construct an unstructured text dataset related to MNPs from an open-source dataset, which can be used for the research and development of resource scarcity scenarios.
Regulatory network characterization of anthocyanin metabolites in purple sweetpotato via joint transcriptomics and metabolomics

Introduction Sweet potato is an important staple food crop in the world and contains abundant secondary metabolites in its underground tuberous roots. The large accumulation of several categories of secondary metabolites result in colorful pigmentation of the roots. Anthocyanin, is a typical flavonoid compound present in purple sweet potatoes and it contributes to the antioxidant activity. Methods In this study, we developed joint omics research via by combing the transcriptomic and metabolomic analysis to explore the molecular mechanisms underlying the anthocyanin biosynthesis in purple sweet potato. Four experimental materials with different pigmentation phenotypes, 1143-1 (white root flesh), HS (orange root flesh), Dianziganshu No.88 (DZ88, purple root flesh), and Dianziganshu No.54 (DZ54, dark purple root flesh) were comparably studied. Results and discussion We identified 38 differentially accumulated pigment metabolites and 1214 differentially expressed genes from a total of 418 metabolites and 50893 genes detected. There were 14 kinds of anthocyanin detected in DZ88 and DZ54, with glycosylated cyanidin and peonidin as the major components. The significantly enhanced expression levels of multiple structural genes involved in the central anthocyanin metabolic network, such as chalcone isomerase (CHI), flavanone 3-hydroxylase (F3H), dihydroflavonol 4-reductase (DFR), anthocyanidin synthase/leucocyanidin oxygenase (ANS), and glutathione S-transferase (GST) were manifested to be the primary reason why the purple sweet potatoes had a much higher accumulation of anthocyanin. Moreover, the competition or redistribution of the intermediate substrates (i.e. dihydrokaempferol and dihydroquercetin) between the downstream production of anthocyanin products and the flavonoid derivatization (i.e. quercetin and kaempferol) under the regulation of the flavonol synthesis (FLS) gene, might play a crucial role in the metabolite flux repartitioning, which further led to the discrepant pigmentary performances in the purple and non-purple materials. Furthermore, the substantial production of chlorogenic acid, another prominent high-value antioxidant, in DZ88 and DZ54 seemed to be an interrelated but independent pathway differentiated from the anthocyanin biosynthesis. Collectively, these data from the transcriptomic and metabolomic analysis of four kinds of sweet potatoes provide insight to understand the molecular mechanisms of the coloring mechanism in purple sweet potatoes.
Bioeconomy-based tourism: A new concept responding to the support of bioeconomy

Tourism has experienced dynamic development in recent decades and has become one of the fastest growing industries; however, the COVID-19 pandemic caused unprecedented changes and declines in revenues and tourism trends. With the strong support of bioeconomy (BE) this period brings a great opportunity to transform the entire tourism sector into a model responding to that concept. The main aim of this article is to prove whether and under what possible conditions tourism is a part of the concept of BE. Selected European Union (EU) countries have been chosen so that every geographical area is represented. This analysis was therefore carried out for a total of 12 states and the EU as a whole (13 entities). Of these 13 entities, seven have their own BE strategy and six do not. According to the level of emphasis on the field of tourism in the examined documents, we divided the states into three categories. Although the selected and analysed countries mention tourism in their BE strategies with various emphasis and approach, the inclusion of tourism under this concept is evident. Bioeconomy-based tourism has been designed as a new concept that considers the approach of BE. It focuses above all on a sustainable level of tourism in the connection of economic and environmental pillars, where the main emphasis is placed on the effective use of natural resources and maximum effort not to waste these resources, as well as to support economic growth.