Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of host admixture on wild house mouse gut microbiota is weak when accounting for spatial autocorrelation

The question of how interactions between the gut microbiome and vertebrate hosts contribute to host adaptation and speciation is one of the major problems in current evolutionary research. Using bacteriome and mycobiome metabarcoding, we examined how these two components of the gut microbiota vary with the degree of host admixture in secondary contact between two house mouse subspecies (Mus musculus musculus and M. m. domesticus). We used a large dataset collected at two replicates of the hybrid zone and model-based statistical analyses to ensure the robustness of our results. Assuming that the microbiota of wild hosts suffers from spatial autocorrelation, we directly compared the results of statistical models that were spatially naive with those that accounted for spatial autocorrelation. We showed that neglecting spatial autocorrelation can drastically affect the results and lead to misleading conclusions. The spatial analyses showed little difference between subspecies, both in microbiome composition and in individual bacterial lineages. Similarly, the degree of admixture had minimal effects on the gut bacteriome and mycobiome and was caused by changes in a few microbial lineages that correspond to the common symbionts of free-living house mice. In contrast to previous studies, these data do not support the hypothesis that the microbiota plays an important role in host reproductive isolation in this particular model system.
Heritable changes of epialleles in maize can be triggered in the absence of DNA methylation

Trans-chromosomal interactions resulting in changes in DNA methylation during hybridization have been observed in several plant species. However, very little is known about the causes or consequences of these interactions. Here, we compared DNA methylomes of F1 hybrids that are mutant for a small RNA biogenesis gene, Mop1 (mediator of paramutation1) with that of their parents, wild type siblings, and backcrossed progeny in maize. Our data show that hybridization triggers global changes in both trans-chromosomal methylation (TCM) and trans-chromosomal demethylation (TCdM), most of which involved changes in CHH methylation. In more than 60% of these TCM differentially methylated regions (DMRs) in which small RNAs are available, no significant changes in the quantity of small RNAs were observed. Methylation at the CHH TCM DMRs was largely lost in the mop1 mutant, although the effects of this mutant varied depending on the location of the CHH DMRs. Interestingly, an increase in CHH at TCM DMRs was associated with enhanced expression of a subset of highly expressed genes and suppressed expression of a small number of lowly expressed genes. Examination of the methylation levels in backcrossed plants demonstrates that TCM and TCdM can be maintained in the subsequent generation, but that TCdM is more stable than TCM. Surprisingly, although increased CHH methylation in F1 plants did require Mop1, initiation of the changes in the epigenetic state of TCM DMRs did not require a functional copy of this gene, suggesting that initiation of these changes is not dependent on RNA-directed DNA methylation.
Spectral methods for multi-scale feature extraction and data clustering

We address two issues that are fundamental to the analysis of naturally-occurring datasets: how to extract features that arise at multiple-scales and how to cluster items in a dataset using pairwise similarities between the elements. To this end we present two spectral methods: (1) Sparse Principal Component Analysis S-PCA—a framework for learning a linear, orthonormal basis representation for structure intrinsic to a given dataset; and (2) EigenCuts—an algorithm for clustering items in a dataset using their pairwise-similarities. S-PCA is based on the discovery that natural images exhibit structure in a low-dimensional subspace in a local, scale-dependent form. It is motivated by the observation that PCA does not typically recover such representations, due to its single minded pursuit of variance. In fact, it is widely believed that the analysis of second-order statistics alone is insufficient for extracting multi-scale structure from data and there are many proposals in the literature showing how to harness higher-order image statistics to build multi-scale representations. In this thesis, we show that resolving second-order statistics with suitably constrained basis directions is indeed sufficient to extract multi-scale structure. In particular, S-PCA basis optimizes an objective function which trades off correlations among output coefficients for sparsity in the description of basis vector elements. Using S-PCA we present new approaches to the problem of constrast-invariant appearance detection, specifically eye and face detection. EigenCuts is a clustering algorithm for finding stable clusters in a dataset. Using a Markov chain perspective, we derive an eigenflow to describe the flow of probability mass due to the Markov chain and characterize it by its eigenvalue, or equivalently, by the halflife of its decay as the Markov chain is iterated. The key insight in this work is that bottlenecks between weakly coupled clusters can be identified by computing the sensitivity of the eigenflow's halflife to variations in the edge weights. The EigenCuts algorithm performs clustering by removing these identified bottlenecks in an iterative fashion. As an efficient step in this process we also propose a specialized hierarchical eigensolver suitable for large stochastic matrices.
The impact of geriatric nutritional risk index on one-year outcomes in hospitalized elderly patients with heart failure

Background Strategies that accurately predict outcomes in elderly heart failure (HF) patients have not been sufficiently established. In previous reports, nutritional status, ability to perform activities of daily living (ADL), and lower limb muscle strength are known prognostic factors associated with cardiac rehabilitation (CR). In the present study, we investigated which CR factors can accurately predict one-year outcomes in elderly patients with HF among the above factors. Methods Hospitalized patients with HF over 65 years of age from January 2016 to January 2022 were retrospectively enrolled in the Yamaguchi Prefectural Grand Medical (YPGM) Center. They were consequently recruited to this single-center retrospective cohort study. Nutritional status, ADL, and lower limb muscle strength were assessed by geriatric nutritional risk index (GNRI), Barthel index (BI), and short physical performance battery (SPPB) at discharge, respectively. One year after discharge, the primary and secondary outcomes were evaluated by all-cause death or HF readmission and major adverse cardiac and cerebrovascular events (MACCE), respectively. Results Overall, 1,078 HF patients were admitted to YPGM Center. Of those, 839 (median age 84.0, 52% female) met the study criteria. During the follow-up of 228.0 days, 72 patients reached all-cause death (8%), 215 experienced HF readmission (23%), and 267 reached MACCE (30%: 25 HF death, six cardiac death, and 13 strokes). A multivariate Cox proportional hazard regression analysis revealed that the GNRI predicted the primary outcome (Hazard ratio [HR]: 0.957; 95% confidence interval [CI]: 0.934–0.980; p < 0.001) and the secondary outcome (HR: 0.963; 95%CI: 0.940–0.986; p = 0.002). Furthermore, a multiple logistic regression model using the GNRI most accurately predicted the primary and secondary outcomes compared to those with the SPPB or BI models. Conclusion A nutrition status model using GNRI provided a better predictive value than ADL ability or lower limb muscle strength. It should be recognized that HF patients with a low GNRI at discharge may have a poor prognosis at one year.
AAV9-mediated gene delivery to liver grafts during static cold storage in a rat liver transplant model

Introduction Recombinant adeno-associated virus (rAAV) is a novel strategy used clinically for gene delivery, but has not been characterized in the context of organ transplantation. We sought to determine the efficacy of rAAV-mediated gene delivery during static cold storage (SCS) prior to liver transplantation. Methods A triple-plasmid transfection protocol was used to produce rAAV subtype-9 vectors containing firefly luciferase genomes in HEK293 cells. Lewis rat liver grafts were flushed and stored in cold HTK solution. Three experimental groups received rAAV at different doses, administered via the portal vein as a bolus during SCS. A control group did not receive rAAV (N = 2). Recipients then underwent syngeneic liver transplantation. Bioluminescence imaging to quantify in vivo luciferase expression was performed on post-operative days 7, 14, 28, and 56. Results Control animals demonstrated no bioluminescent activity, while animals receiving rAAV-treated livers had increasing bioluminescence, peaking at four weeks but sustained to the eight-week endpoint. This result was confirmed by experimental endpoint tissue luciferase activity assay. Discussion rAAV mediates gene transduction in liver grafts when administered during SCS and has potential for gene therapy applications in solid organ transplantation.
Evaluation of the effect of the indoor environment on the physiological responses of early-gestation sows in a commercial house in China

Objective The environment influences the sow's health and physiology during gestation. This study was conducted to evaluate indoor environmental parameters and physiological responses of early-gestation sows and investigate the possible methods for assessing the thermal environment in commercial houses. Methods A total of 20 early-gestation sows (commercial purebred Yorkshire) with an average body weight of 193.20 ± 3.62 kg were used for this study in winter, spring, summer, and autumn. The indoor environment parameters comprising dry-bulb temperature (Tdb), relative humidity (RH), and carbon dioxide (CO2) were recorded in 30-min intervals. Physiological parameters including heart rate (HR) and respiration rate (RR) of sows were also measured every 30 min. Wet-bulb temperature (Twb) was calculated using Tdb, RH and atmospheric pressure was recorded at a nearby weather station. Results The average indoor Tdb and RH were 12.98 ± 2.03°C and 80.4 ± 6.4% in winter, 18.98 ± 2.68°C and 74.4 ± 9.0% in spring, 27.49 ± 2.05°C and 90.6 ± 6.4% in summer, and 17.10 ± 2.72°C and 64.5 ± 10.9% in autumn. A higher average concentration of CO2 was observed in winter (1,493 ± 578 mg/m3) than in spring (1,299 ± 489 mg/m3), autumn (1,269 ± 229 mg/m3), and summer (702 ± 128 mg/m3). Compared with the HR and RR in the optimum environment, high RH in the house led to a significant decrease in both HR and RR (P < 0.05). In addition, a significant decline in HR was also obtained at high temperatures (P < 0.05). A temperature humidity index (THI), THI = 0.82 × Tdb + 0.18 × Twb, was determined for early-gestation sows, and the THI thresholds were 25.6 for HR. The variation in THI in summer showed that heat stress still occurred under the pad-fan cooling system. Conclusion This study demonstrated the critical significance of considering physiological responses of early-gestation sows in commercial houses and THI thresholds. We recommend that much more cooling measures should be taken for early-gestation sows in summer.
Efficacy and safety of pharmacotherapy for recurrent high-grade glioma: a systematic review and network meta-analysis

Objective: To compare the efficacy and safety of treatments for patients with recurrent high-grade gliomas. Methods: Electronic databases including Pubmed, Embase, Cochrane Library and ClinicalTrials.gov were searched for randomized controlled trials (RCT) related to high-grade gliomas. The inclusion of qualified literature and extraction of data were conducted by two independent reviewers. The primary clinical outcome measures of network meta-analysis were overall survival (OS) while progression-free survival (PFS), objective response rate (ORR) and adverse event of grade 3 or higher were secondary measures. Results: 22 eligible trials were included in the systematic review, involving 3423 patients and 30 treatment regimens. Network meta-analysis included 11 treatments of 10 trials for OS and PFS, 10 treatments of 8 trials for ORR, and 8 treatments of 7 trials for adverse event grade 3 or higher. Regorafenib showed significant benefits in terms of OS in paired comparison with several treatments such as bevacizumab (hazard ratio (HR), 0.39; 95% confidence interval (CI), 0.21–0.73), bevacizumab plus carboplatin (HR, 0.33; 95%CI, 0.16–0.68), bevacizumab plus dasatinib (HR, 0.44; 95%CI, 0.21–0.93), bevacizumab plus irinotecan (HR, 0.4; 95%CI, 0.21–0.74), bevacizumab plus lomustine (90 mg/m2) (HR, 0.53; 95%CI, 0.33–0.84), bevacizumab plus lomustine (110 mg/m2) (HR, 0.21; 95%CI, 0.06–0.7), bevacizumab plus vorinostat (HR, 0.42; 95%CI, 0.18–0.99), lomustine (HR, 0.5; 95%CI, 0.33–0.76), and nivolumab (HR, 0.38; 95%CI, 0.19–0.73). For PFS, only the hazard ratio between bevacizumab plus vorinostat and bevacizumab plus lomustine (90 mg/m2) was significant (HR,0.51; 95%CI, 0.27–0.95). Lomustine and nivolumab conferred worse ORR. Safety analysis showed fotemustine as the best and bevacizumab plus temozolomide as the worst. Conclusion: The results suggested that regorafenib and bevacizumab plus lomustine (90 mg/m2) provide improvements in terms of survival but may have poor ORR in patients with recurrent high-grade glioma.
Head-cut gully erosion susceptibility mapping in semi-arid region using machine learning methods: insight from the high atlas, Morocco

Gully erosion has been identified in recent decades as a global threat to people and property. This problem also affects the socioeconomic stability of societies and therefore limits their sustainable development, as it impacts a nonrenewable resource on a human scale, namely, soil. The focus of this study is to evaluate the prediction performance of four machine learning (ML) models: Logistic Regression (LR), classification and regression tree (CART), Linear Discriminate Analysis (LDA), and the k-Nearest Neighbors (kNN), which are novel approaches in gully erosion modeling research, particularly in semi-arid regions with a mountainous character. 204 samples of erosion areas and 204 samples of non-erosion areas were collected through field surveys and high-resolution satellite images, and 17 significant factors were considered. The dataset cells of samples (70% for training and 30% for testing) were randomly prepared to assess the robustness of the different models. The functional relevance between soil erosion and effective factors was computed using the ML models. The ML models were evaluated using different metrics, including accuracy, the kappa coefficient. kNN is the ideal model for this study. The value of the AUC from ROC considering the testing datasets of KNN is 0.93; the remaining models are associated to ideal AUC and are similar to kNN in terms of values. The AUC values from ROC of GLM, LDA, and CART for testing datasets are 0.90, 0.91, and 0.84, respectively. The value of accuracy considering the validation datasets of LDA, CART, KNN, and GLM are 0.85, 0.82, 0.89, 0.84 respectively. The values of Kappa of LDA, CART, and GLM for testing datasets are 0.70, 0.65, and 0.68, respectively. ML models, in particular KNN, GLM, and LDA, have achieved outstanding results in terms of creating soil erosion susceptibility maps. The maps created with the most reliable models could be a useful tool for sustainable management, watershed conservation and prevention of soil and water losses.
The association between childhood trauma and adolescent cyberbullying: chain mediating roles of emotional intelligence and online social anxiety

Objective This study explored the impact of childhood trauma on adolescent cyberbullying and the mediating roles of emotional intelligence and online social anxiety between them. Methods The Childhood Trauma Scale, Emotional Intelligence Scale, and Chinese Brief Version of the Social Media User Social Anxiety Scale and Cyber Bullying Scale were used to assess 1,046 adolescents [boys: 297, girls: 749, average age = 15.79 years] from four schools in Shandong Province, China. SPSS 25.0 and AMOS 24.0 were used for statistical analysis. Results (1) Childhood trauma was positively associated with adolescents’ cyberbullying; (2) Emotional intelligence and online social anxiety played partial mediating roles in the relationship between childhood trauma and cyberbullying; (3) Emotional intelligence and online social anxiety played a chain mediating role in the relationship between childhood trauma and cyberbullying. Conclusion This study reveals the relationship and mediating mechanisms between childhood trauma and cyberbullying. It provides implications for the theory and prevention of cyberbullying.
Behind the scenes of the healthcare COVID-19 pandemic crisis: potential affecting factors of healthcare work sustainability in Romania during 2020–2022

Aim The COVID-19 pandemic represented a great disturbance for medical systems around the world, putting medical personnel on the front lines of the fight against the SARS-Cov2 virus. This fight was particularly impactful in countries with medical systems already facing various challenges, including Romania; where the pandemic unfolded in five waves that severely affected the psychological and physical well-being of medical professionals in terms of overload and continuous exposure to health threats. Against this background, our research aims to identify the mediating role of potential affecting factors of healthcare work sustainability during the change-related uncertainty conditions generated by the COVID 19 crisis. Dynamics and relations of nine carefully selected constructs were tracked along all five pandemic waves in Romania, which span from March 2020 to April 2022. The tested variables and constructs are perception of healthcare workers of their own state of health, their workplace safety, the work–family conflict, the satisfaction of basic needs, the work meaningfulness and work engagement, patient care, pandemic stress and burnout. Methods This cross-sectional study is based on an online snowball sampling of 738 health workers from 27 hospitals. Panel research is limited to a maximum of 61 respondents for two successive waves. The analytical part is built on means comparison of analysed variables between all five pandemic waves and an in-depth model to explain the relationships between the variables. Results The results indicate statistically significant correlations between the perception of health risks and all selected factors excluding patient care, which seems to be above the own health perception. The factors’ dynamics was followed along all five pandemic waves. The developed model identified that one’s health status satisfaction is a mediator of the family–work conflict and, together, of work engagement. In turn, work engagement plays a significant role in satisfying basic psychological needs and supporting work meaningfulness. Also, work meaningfulness influences the satisfaction of basic psychological needs. Discussion Health workers with higher levels of positive perceived health are better at managing pandemic stress, burnout effects and work-family imbalances. Adaptive behaviors and attitudes towards COVID-19 pandemic threats could be identified in later pandemic waves due to the progress in terms of medical protocols and procedures.
Solid-liquid equilibria of Sorel phases and Mg (OH)2 in the system Na-Mg-Cl-OH-H2O. Part I: experimental determination of OH− and H+ equilibrium concentrations and solubility constants at 25°C, 40°C, and 60°C

Sorel phases are the binder phases of the magnesia building material (Sorel cement/concrete) and of special concern for the construction of long-term stable geotechnical barriers in repositories for radioactive waste in rock salt, as potentially occurring brines are expected to contain MgCl2. Sorel phases, in addition to Mg(OH)2, are equally important as pH buffers to minimize solubility and potential mobilization of radionuclides in brine systems. In order to obtain a detailed database of the relevant solid-liquid equilibria and the related pHm values of the equilibrium solutions, extensive experimental investigations were carried out. Solid phase formation was studied by suspending MgO and Mg(OH)2 in NaCl saturated MgCl2-solutions at 25°C. Mg(OH)2 and the 3-1-8 Sorel phase were identified as the stable solid phases, while the 5-1-8 Sorel phase is metastable. Equilibration at 40°C did not lead to any solid phase changes. Both OH− and H+ equilibrium concentrations were analyzed as a function of MgCl2 concentration at 25°C and 40°C. In addition to our already published solid-liquid equilibria for the ternary system Mg-Cl-OH-H2O (25°C–120°C), the equilibrium H+ concentrations (pHm) determined at 25°C, 40°C and 60°C are now reported. Analyzing these data together with known ion-interaction Pitzer coefficients, the solubility constants for Mg(OH)2 and the 3-1-8 phase at these three temperatures, for the metastable 5-1-8 phase at 25°C and for the 2-1-4 phase at 60°C have been consistently calculated.
Prevalence, genomic characterization and antimicrobial resistance of Campylobacter spp. isolates in pets in Shenzhen, China

The prevalence of Campylobacter spp.in pets is a potential concern for human health. However, little is known about the pet-related Campylobacter spp. in China. A total of 325 fecal samples were collected from dogs, cats, and pet foxes. Campylobacter spp. were isolated by culture, and MALDI-TOF MS was used to identify 110 Campylobacter spp. isolates in total. C. upsaliensis (30.2%, 98/325), C. helveticus (2.5%, 8/325), and C. jejuni (1.2%, 4/325) were the three found species. In dogs and cats, the prevalence of Campylobacter spp. was 35.0% and 30.1%, respectively. A panel of 11 antimicrobials was used to evaluate the antimicrobial susceptibility by the agar dilution method. Among C. upsaliensis isolates, ciprofloxacin had the highest rate of resistance (94.9%), followed by nalidixic acid (77.6%) and streptomycin (60.2%). Multidrug resistance (MDR) was found in 55.1% (54/98) of the C. upsaliensis isolates. Moreover, 100 isolates, including 88 C. upsaliensis, 8 C. helveticus, and 4 C. jejuni, had their whole genomes sequenced. By blasting the sequence against the VFDB database, virulence factors were identified. In total, 100% of C. upsaliensis isolates carried the cadF, porA, pebA, cdtA, cdtB, and cdtC genes. The flaA gene was present in only 13.6% (12/88) of the isolates, while the flaB gene was absent. By analyzing the sequence against the CARD database, we found that 89.8% (79/88) of C. upsaliensis isolates had antibiotic target alteration in the gyrA gene conferring resistance to fluoroquinolone, 36.4% (32/88) had the aminoglycoside resistance gene, and 19.3% (17/88) had the tetracycline resistance gene. The phylogenetic analysis using the K-mer tree method obtained two major clades among the C. upsaliensis isolates. All eight isolates in subclade 1 possessed the gyrA gene mutation, the aminoglycoside and tetracycline resistance genes, and were phenotypically resistant to six classes of antimicrobials. It has been established that pets are a significant source of Campylobacter spp. strains and a reservoir for them. This study is the first to have documented the presence of Campylobacter spp. in pets in Shenzhen, China. In this study, C. upsaliensis of subclade 1 required additional attention due to its broad MDR phenotype and relatively high flaA gene prevalence.