Miracle-dz/UniFAR-FTUs huggingface dataset:
Variations in high density cholesterol levels based on apolipoprotein E variant and exercise type

In various cross-sectional and longitudinal studies, exercise has been associated with cardiometabolic outcomes, including high-density lipoprotein (HDL) cholesterol. Exercise-induced changes in HDL cholesterol seem to be affected by genetic polymorphisms. In this study, we examined whether variant APOE rs7412 is involved in the association between HDL cholesterol and exercise. From adults assessed in Taiwan Biobank (TWB) between 2008 and 2019, we analyzed data from 57,638 normolipidemic subjects. To examine the association between exercise, APOE rs7412, and HDL cholesterol, a multiple linear regression model was used. A higher HDL was associated with both aerobic exercise (regression coefficient [mg/dL] beta- (β), 1.112; 95% confidence interval (CI); 0.903–1.322) and resistance exercise (β, 2.530; 95% CI, 2.093–2.966). In comparison with the APOE rs7412-CC genotype, the β was 2.589 (95% CI, 2.329–2.848) among those with the CT + TT genotype. Compared to adults who had the CC genotype and did not exercise (the CC/no exercise group), the β-coefficient determined for the different genotype and exercise groups was 1.135 (95% CI, 0.911–1.359) for the CC genotype and aerobic exercise group, 2.753 (95% CI, 2.283–3.322) for the CC genotype and resistance exercise group, 2.705 (95% CI, 2.390–3.020) for the CT + TT genotype and no exercise group, 3.682 (95% CI, 3.218–4.146) for the CT + TT genotype and aerobic exercise group, and 3.855 (95% CI, 2.727–4.982) for the CT + TT genotype and resistance exercise group, respectively. This study demonstrates that self-reported aerobic and resistance exercise both raised HDL levels, yet resistance exercise was associated with a greater increase, particularly among Taiwanese subjects carrying the APOE rs7412-CT+TT genotype.
Being where, with whom, and when it happens: spatial, interpersonal, and temporal presence while viewing live streaming of collegiate sports in virtual reality

Introduction: Although virtual reality (VR) is most popularly known for its applications to gaming, other entertainment applications are increasingly being explored including in the sports media industry, but little research has so far examined the experiences induced by VR viewing of a live sporting event. Materials and methods: Participants (n = 93) were university students who were approached in the context of a field study from a nearby community eatery area on the university campus to watch brief segments of a 360° live stream of the home games of their university volleyball and basketball teams both while wearing and not wearing an inexpensive smart-phone based head-mounted display (HMD). Immediately afterward, participants then reported on their relative experience of spatial, interpersonal, and temporal presence, as well as their satisfaction-preference with each of the two viewing modalities, in response to brief face-valid screening questions. Results: The majority of participants experienced greater presence while wearing the VR headset, and approximately one in every two reported preferring to watch the games in VR. Participants’ experience of spatial presence independently correlated with preferring to watch the games in VR. Discussion: Media vendors should offer VR viewing of sports including via inexpensive, smart-phone mediated VR as an additional, cost-effective alternative means of heightening fans’ experience of virtual presence at the games when fans are unable to go to the games in person.
Response of the soil microbial community to petroleum hydrocarbon stress shows a threshold effect: research on aged realistic contaminated fields

Introduction Microbes play key roles in maintaining soil ecological functions. Petroleum hydrocarbon contamination is expected to affect microbial ecological characteristics and the ecological services they provide. In this study, the multifunctionalities of contaminated and uncontaminated soils in an aged petroleum hydrocarbon-contaminated field and their correlation with soil microbial characteristics were analyzed to explore the effect of petroleum hydrocarbons on soil microbes. Methods Soil physicochemical parameters were determined to calculate soil multifunctionalities. In addition, 16S high-throughput sequencing technology and bioinformation analysis were used to explore microbial characteristics. Results The results indicated that high concentrations of petroleum hydrocarbons (565–3,613 mg•kg−1, high contamination) reduced soil multifunctionality, while low concentrations of petroleum hydrocarbons (13–408 mg•kg−1, light contamination) might increase soil multifunctionality. In addition, light petroleum hydrocarbon contamination increased the richness and evenness of microbial community (p < 0.01), enhanced the microbial interactions and widened the niche breadth of keystone genus, while high petroleum hydrocarbon contamination reduced the richness of the microbial community (p < 0.05), simplified the microbial co-occurrence network, and increased the niche overlap of keystone genus. Conclusion Our study demonstrates that light petroleum hydrocarbon contamination has a certain improvement effect on soil multifunctionalities and microbial characteristics. While high contamination shows an inhibitory effect on soil multifunctionalities and microbial characteristics, which has significance for the protection and management of petroleum hydrocarbon-contaminated soil.
Predicting fish species richness and abundance in the Lower Mekong Basin

Predictive models are widely used to investigate relationships between the distribution of fish diversity, abundance, and the environmental conditions in which they inhabit, and can guide management actions and conservation policies. Generally, the framework to model such relationships is established; however, which models perform best in predicting fish diversity and abundance remain unexplored in the Mekong River Basin. Here, we evaluated the performance of six single statistical models namely Generalized Linear Model, Classification and Regression Tree, Artificial Neural Network, k-Nearest Neighbor, Support Vector Machine and Random Forest in predicting fish species richness and abundance in the Lower Mekong Basin. We also identified key variables explaining variability and assessed the variable’s sensitivity in prediction of richness and abundance. Moreover, we explored the usefulness of an ensemble modeling approach and investigated if this approach improved model performance. Our results indicated that, overall, the six single statistical models successfully predicted the fish species richness and abundance using 14 geo-hydrological, physicochemical and climatic variables. The Random Forest model consistently out-performed all single statistical models for predicting richness (R2 = 0.85) and abundance (R2 = 0.77); whereas, Generalized Linear Model performed the worst of all models (R2 = 0.60 and 0.56 for richness and abundance). The most important predictors of variation in both richness and abundance included water level, distance from the sea and alkalinity. Additionally, dissolved oxygen, water temperature and total nitrate were important predictors of species richness, while conductivity was important for fish abundance. We found that species richness increased with increasing water level, dissolved oxygen and water temperature, but decreased with increasing distance from the sea, alkalinity and total nitrate. Fish abundance increased with conductivity, but decreased with increasing distance from the sea, water level and alkalinity. Finally, our results highlighted the usefulness of ensemble modeling (R2 = 0.90 and 0.85 for richness and abundance) for providing better predictive power than any of the six single statistical models. Our results can be used to support Mekong River management, particularly fisheries in the context of contemporary regional and global changes.
Nest-associated scent marks help bumblebees localizing their nest in visually ambiguous situations

Social insects such as ants and bees are excellent navigators. To manage their daily routines bumblebees, as an example, must learn multiple locations in their environment, like flower patches and their nest. While navigating from one location to another, they mainly rely on vision. Although the environment in which bumblebees live, be it a meadow or a garden, is visually stable overall, it may be prone to changes such as moving shadows or the displacement of an object in the scenery. Therefore, bees might not solely rely on visual cues, but use additional sources of information, forming a multimodal guidance system to ensure their return home to their nest. Here we show that the home-finding behavior of bumblebees, when confronted with a visually ambiguous scenario, is strongly influenced by natural scent marks they deposit at the inconspicuous nest hole when leaving their nest. Bumblebees search for a longer time and target their search with precision at potential nest locations that are visually familiar, if also marked with their natural scent. This finding sheds light on the crucial role of odor in helping bees find their way back to their inconspicuous nest.
The prognosis value of CONUT and SIS score for recurrent or metastatic esophageal squamous cell carcinoma patients treated with second-line immunotherapy

Objective To investigate the predictive value of Controlling Nutritional Status (CONUT) score and systemic inflammation (SIS) score in the prognosis, short-term efficacy, and immune-related side effects of patient with recurrent or metastatic esophageal squamous cell carcinoma (R/M ESCC) receiving immunotherapy as second line therapy combined with or without radiotherapy. Methods Forty-eight patients with R/M ESCC who received second-line therapy with Camrelizumab were retrospectively studied. They were divided into the high and low score groups according to the CONUT and SIS score. Univariate and multivariate analyses were used to analyze factors that might affect patient prognosis and the effects of different CONUT score and SIS on the short-term efficacy and immune-related toxic and side effects of patients. Results The 1- and 2-year overall survival (OS) and progression-free survival (PFS) rates were 42.9% and 22.5%, and 29.0% and 5.8%, respectively. The CONUT score ranged from 0 to 6 (3.31 ± 1.43), whereas the SIS score ranged from 0 to 2 (1.19 ± 0.73). Multivariate analysis showed that treatment related toxicity, number of cycles of Camrelizumab used, short-term effect and SIS score were independent prognostic factors for OS (P=0.044, 0.021, 0.021, 0.030, respectively), whereas SIS and CONUT scores were independent prognostic factors for PFS (P=0.005, 0.047, respectively). Patients with low CONUT/SIS score had a low incidence rate of immune-related adverse reactions (X2 = 9.735, 5.693; P=0.002, 0.017) and better short-term efficacy (X2 = 4.427, 7.438; P=0.035, 0.006). Conclusion R/M ESCC patients with low CONUT/SIS score have better prognosis, higher objective response rate, lower incidence of immune-related toxic and side effects after receiving immunotherapy as second-line therapy. CONUT scores and SIS scores may be reliable prognostic indicators for patient receiving immunotherapy as second-line therapy for R/M ESCC.
Medicago truncatula PHO2 genes have distinct roles in phosphorus homeostasis and symbiotic nitrogen fixation

Three PHO2-like genes encoding putative ubiquitin-conjugating E2 enzymes of Medicago truncatula were characterized for potential roles in phosphorous (P) homeostasis and symbiotic nitrogen fixation (SNF). All three genes, MtPHO2A, B and C, contain miR399-binding sites characteristic of PHO2 genes in other plant species. Distinct spatiotemporal expression patterns and responsiveness of gene expression to P- and N-deprivation in roots and shoots indicated potential roles, especially for MtPHO2B, in P and N homeostasis. Phenotypic analysis of pho2 mutants revealed that MtPHO2B is integral to Pi homeostasis, affecting Pi allocation during plant growth under nutrient-replete conditions, while MtPHO2C had a limited role in controlling Pi homeostasis. Genetic analysis also revealed a connection between Pi allocation, plant growth and SNF performance. Under N-limited, SNF conditions, Pi allocation to different organs was dependent on MtPHO2B and, to a lesser extent, MtPHO2C and MtPHO2A. MtPHO2A also affected Pi homeostasis associated with nodule formation. Thus, MtPHO2 genes play roles in systemic and localized, i.e., nodule, P homeostasis affecting SNF.
Parent-implemented augmented communication intervention and young children with Down syndrome: an exploratory report

Introduction Young children with Down syndrome (DS) present with speech and language impairments very early in childhood. Historically, early language intervention for children with DS included manual signs, though recently there has been an interest in the use of speech-generating devices (SGDs). This paper examines the language and communication performance of young children with DS who participated in parent-implemented communication interventions that included SGDs. Specifically, we compared the functional vocabulary usage and communication interaction skills of children with DS who received augmented communication interventions (AC) that included an SGD with those children with DS who received spoken communication intervention (SC). Methods Twenty-nine children with DS participated in this secondary data analysis. These children were part of one of two longitudinal RCT studies investigating the effectiveness of parent-implemented augmented communication interventions in a larger sample of 109 children with severe communication and language impairments. Results There were significant differences between children with DS in the AC and SC groups in terms of the number and proportion of functional vocabulary targets used and the total vocabulary targets provided during the intervention at sessions 18 (lab)and 24 (home). Discussion Overall, the AC interventions provided the children with a way to communicate via an SGD with visual-graphic symbols and speech output, while the children in the SC intervention were focused on producing spoken words. The AC interventions did not hinder the children’s spoken vocabulary development. Augmented communication intervention can facilitate the communication abilities of young children with DS as they are emerging spoken communicators.
Effects of the COVID-19 pandemic on mental health, working, and life situation of employees in the Swedish hospitality industry

Introduction Previous studies reported that the coronavirus disease (COVID-19) pandemic has negatively affected the mental health of employees in the hospitality industry internationally, however, its effect in Sweden has not been studied. Unlike several other countries, Sweden never enforced a lockdown. Restaurants, bars, and hotels could remain open and host a limited number of guests but had to abide by certain restrictions. Methods A cross-sectional survey was distributed among hospitality industry employees containing questions regarding the perceived effects of the pandemic on the respondents’ working and life situations and their physical and psychological health. The sample consisted of 699 individuals, with a response rate of 47.9%. Results Although several respondents had been laid off or furloughed, the majority of the sample remained at the same employer. However, more than half of the respondents reported that their economic situation had deteriorated. Compared to before the pandemic, 38.1% experienced elevated levels of stress, 48.3% experienced elevated levels of worry, and 31.4% reported worsened mood. A deteriorating personal economy and difficulty in following COVID-19-related restrictions at work were associated with the worsening of these three mental health aspects. While the fear of becoming infected with COVID-19 was related to higher levels of stress, the fear of infecting others was related to higher levels of worry. Conclusion Although Sweden imposed less strict measures than most other countries, the personal economy and mental health of hospitality workers were negatively affected by the COVID-19 pandemic.
The Oncolytic herpes simplex virus type-1 (HSV-1) vaccine strain VC2 causes intratumor infiltration of functionally active T cells and inhibition of tumor metastasis and pro-tumor genes VEGF and PDL1 expression in the 4T1/Balb/c mouse model of stage four breast cancer

Introduction: Oncolytic viruses (OVs) provide new modalities for cancer therapy either alone or in combination with synergistic immunotherapies and/or chemotherapeutics. Engineered Herpes Simplex Virus Type-1 (HSV-1) has shown strong promise for the treatment of various cancers in experimental animal models as well as in human patients, with some virus strains licensed to treat human melanoma and gliomas. In the present study we evaluated the efficacy of mutant HSV-1 (VC2) in a late stage, highly metastatic 4T1 murine syngeneic. Method: VC2 was constructed VC2 using double red recombination technology. For in-vivo efficacy we utilized a late stage 4T1 syngeneic and immunocompetent BALB/cJ mouse model breast cancer model which exhibits efficient metastasis to the lung and other organs. Results: VC2 replicated efficiently in 4T1 cells and in cell culture, achieving titers similar to those in African monkey kidney (Vero) cells. Intra-tumor treatment with VC2 did not appreciably reduce average primary tumor sizes but a significant reduction of lung metastasis was noted in mice treated intratumorally with VC2, but not with ultraviolet-inactivated VC2. This reduction of metastasis was associated with increased T cell infiltration comprised of CD4+ and CD4+CD8+ double-positive T cells. Characterization of purified tumor infiltrating T cells revealed a significant improvement in their proliferation ability compared to controls. In addition, significant T cell infiltration was observed in the metastatic nodules associated with reduction of pro-tumor PD-L1 and VEGF gene transcription. Conclusion: These results show that VC2 therapy can improve anti-tumor response associated with a better control of tumor metastasis. improve T cell responses and reduce pro-tumor biomarker gene transcription. VC2 holds promise for further development as an oncolytic and immunotherapeutic approach to treat breast and other cancers.
Climate and fragment area jointly affect the annual dynamics of seedlings in different functional groups in the Thousand Island Lake

Habitat fragmentation and climate change are the two main threats to global biodiversity. Understanding their combined impact on plant community regeneration is vital for predicting future forest structure and conserving biodiversity. This study monitored the seed production, seedling recruitment and mortality of woody plants in the Thousand Island Lake, a highly fragmented anthropogenic archipelago, for 5 years. We analyzed the seed-seedling transition, seedling recruitment and mortality of different functional groups in the fragmented forests and conducted correlation analyses involving climatic factors, island area, and plant community abundance. Our results showed that: 1) shade-tolerant and evergreen species had higher seed-seedling transition, seedling recruitment and survival rate than shade-intolerant and deciduous species in time and space, and these advantages increased with the island area. 2) Seedlings in different functional groups responded differently to island area, temperature and precipitation. 3) Increasing active accumulated temperature (the sum of the mean daily temperature above 0 °C) significantly increased seedling recruitment and survival, and warming climate favored the regeneration of evergreen species. 4) The seedling mortality rate of all plant functional groups increased with the increase of island area, but the increasing strength weakened significantly with the increase of the annual maximum temperature. These results suggested that the dynamics of woody plant seedlings varied among functional groups, and can be regulated separately and jointly by fragmentation and climate.
Impact of non-neuronal cells in Alzheimer’s disease from a single-nucleus profiling perspective

The role of non-neuronal cells has been relatively overlooked in Alzheimer’s disease (AD) neuropathogenesis compared to neuronal cells since the first characterization of the disease. Genome wide-association studies (GWAS) performed in the last few decades have greatly contributed to highlighting the critical impact of non-neuronal cells in AD by uncovering major genetic risk factors that are found largely in these cell types. The recent development of single cell or single nucleus technologies has revolutionized the way we interrogate the transcriptomic and epigenetic profiles of neurons, microglia, astrocytes, oligodendrocytes, pericytes, and endothelial cells simultaneously in the same sample and in an individual manner. Here, we review the latest advances in single-cell/nucleus RNA sequencing and Assay for Transposase-Accessible Chromatin (ATAC) sequencing to more accurately understand the function of non-neuronal cells in AD. We conclude by giving an overview of what still needs to be achieved to better appreciate the interconnected roles of each cell type in the context of AD.
LSnet: detecting and genotyping deletions using deep learning network

The role and biological impact of structural variation (SV) are increasingly evident. Deletion accounts for 40% of SV and is an important type of SV. Therefore, it is of great significance to detect and genotype deletions. At present, high accurate long reads can be obtained as HiFi reads. And, through a combination of error-prone long reads and high accurate short reads, we can also get accurate long reads. These accurate long reads are helpful for detecting and genotyping SVs. However, due to the complexity of genome and alignment information, detecting and genotyping SVs remain a challenging task. Here, we propose LSnet, an approach for detecting and genotyping deletions with a deep learning network. Because of the ability of deep learning to learn complex features in labeled datasets, it is beneficial for detecting SV. First, LSnet divides the reference genome into continuous sub-regions. Based on the alignment between the sequencing data (the combination of error-prone long reads and short reads or HiFi reads) and the reference genome, LSnet extracts nine features for each sub-region, and these features are considered as signal of deletion. Second, LSnet uses a convolutional neural network and an attention mechanism to learn critical features in every sub-region. Next, in accordance with the relationship among the continuous sub-regions, LSnet uses a gated recurrent units (GRU) network to further extract more important deletion signatures. And a heuristic algorithm is present to determine the location and length of deletions. Experimental results show that LSnet outperforms other methods in terms of the F1 score. The source code is available from GitHub at https://github.com/eioyuou/LSnet.