Miracle-dz/UniFAR-FTUs huggingface dataset:
The Residuum of Childhood Physical and Sexual Abuse: Coming to Terms in Couple Relationships

Childhood exposure to physical violence and sexual abuse is a public health concern and is empirically connected to poor outcomes in adulthood. The present study was designed to assess dyadic associations between exposure to childhood physical violence and sexual abuse, and resolution, or a sense that one has “come to terms” with events in one’s family of origin. The study was also aimed at assessing whether attachment behaviors mediated associations between abuse, violence, and resolution. The study was carried out using data from a community sample of 3,836 heterosexual couples who completed the Relationship Evaluation Questionnaire inventory. Actor–Partner Interdependence Modeling was employed within a structural equation model to examine associations. Results suggested inverse, direct actor associations for both men and women between physical violence and sexual abuse, and coming to terms. The results also showed inverse, direct partner associations for both men and women between sexual abuse and coming to terms. Furthermore, findings indicated the presence of inverse, indirect actor and partner effects for men and women between physical violence and coming to terms. Examination of these specific indirect partner and actor effects from physical violence to coming to terms implies partial mediation carried through one’s own rating of attachment behaviors. Finally, actor (but not partner) associations were noted between attachment behaviors and coming to terms. In aggregate, the findings support the potential benefit of enhancing investment in attachment behaviors as a resource to aid in the resolution process of exposure to physical violence and sexual abuse in childhood.
Recent evolutions of machine learning applications in clinical laboratory medicine

Abstract Machine learning (ML) is gaining increased interest in clinical laboratory medicine, mainly triggered by the decreased cost of generating and storing data using laboratory automation and computational power, and the widespread accessibility of open source tools. Nevertheless, only a handful of ML-based products are currently commercially available for routine clinical laboratory practice. In this review, we start with an introduction to ML by providing an overview of the ML landscape, its general workflow, and the most commonly used algorithms for clinical laboratory applications. Furthermore, we aim to illustrate recent evolutions (2018 to mid-2020) of the techniques used in the clinical laboratory setting and discuss the associated challenges and opportunities. In the field of clinical chemistry, the reviewed applications of ML algorithms include quality review of lab results, automated urine sediment analysis, disease or outcome prediction from routine laboratory parameters, and interpretation of complex biochemical data. In the hematology subdiscipline, we discuss the concepts of automated blood film reporting and malaria diagnosis. At last, we handle a broad range of clinical microbiology applications, such as the reduction of diagnostic workload by laboratory automation, the detection and identification of clinically relevant microorganisms, and the detection of antimicrobial resistance.
Impact of arginine supplementation on serum prolactin and mRNA abundance of amino acid transporter genes in mammary tissue of lactating sows.

This study was conducted to test the hypothesis that supplemental dietary Arg to late-pregnant and lactating sows increases serum prolactin concentrations and mRNA abundance of SLC7A1, SLC7A2 and SLC6A14 in mammary parenchymal tissue. From d 108 of gestation and until d 21 of lactation, sows were fed a diet either supplemented with 0.10 g of l-Arg/kg body weight (BW) per day (n = 10, ARG) or 0.34 g of l-Glu/kg BW per day (n = 10, control). Litters were standardized to 10 piglets on d 1 of lactation and piglets were weighed on d 1, 7, 14 and 21 of lactation. Sow BW was recorded on d 108 of gestation and d 1, 10 and 21 of lactation. Lactation sow feed intake was recorded daily. Mammary parenchymal tissue was biopsied on d 5 of lactation to measure mRNA abundance SLC7A1, SLC7A2 and SLC6A14. On d 4 and 18 of lactation, blood samples were collected from sows at 2, 4 and 6 h post-feeding to measure serum prolactin concentrations. Milk samples were collected on d 4, 10 and 18 of lactation to measure fat, lactose, urea N, and true protein concentrations. Sow BW, backfat and feed intake over all sampling days did not differ between treatments. Piglet BW on d 1 and mean BW during lactation tended to be greater for the ARG treatment than the control treatment (P = 0.12 and P = 0.15, respectively). Sow milk yield and composition (fat, protein, lactose and urea N) and mammary mRNA abundance of candidate genes did not differ between the ARG and the control group. Compared to controls, serum prolactin concentrations tended to be greater (P = 0.08) in ARG sows on d 4 of lactation, and did not differ on d 18. Current findings show a potential beneficial effect of dietary supplementation with Arg to late-pregnant multiparous sows on BW of their piglets on d 1. Dietary Arg supplementation at a rate of 0.10 g/kg BW during late pregnancy and lactation tended to increase serum prolactin concentrations with no increase in mammary transcript abundance of SLC7A1, SLC7A2 and SLC6A14 in early lactation.
Vibration Attraction Response (VAB) is a plastic trait in Blind Mexican tetra (Astyanax mexicanus), variable within subpopulations inhabiting the same cave.

Animals evolve their sensory systems and foraging behaviors to adapt and colonize new and challenging habitats such as the dark cave environment. Vibration attraction behavior (VAB) gives fish the ability to locate the source of a water disturbance in the darkness. VAB evolved in the blind Mexican cave tetra, Astyanax mexicanus. VAB is triggered in cavefish by vibration stimuli peaking at 35 Hz, which is within the main spectrum of water fluctuations produced by many prey crustaceans and insects. VAB has a genetic component and is correlated to an increased number of head mechanosensory neuromasts in the eye orbital region when compared to surface fish. Previous competitive prey capture assays have supported the advantage of VAB for foraging in the dark. Despite its putative adaptive function, VAB has been described as absent in some Astyanax cave populations (Tinaja and Molino) but present in others (Pachón, Piedras, Toro and Sabinos). Here we have tested the occurrence of VAB in the field and in multiple cave populations using a vibrating device in natural pools. Our results confirmed the presence of VAB in caves such as Pachón, Toro and Sabinos but showed that VAB is also present in the Tinaja and Molino cave populations, previously reported as VAB-negative in laboratory experiments. Thus, VAB is available throughout the range of hypogean A. mexicanus. However, and most notably, within a given cave the levels of VAB were highly variable among different pools. Fish at one pool may express no VAB, while fish at another nearby pool of the same cave may actively show VAB. While a variety of environmental conditions may foster this diversity, we found that individuals inhabiting pools with a high abundance of organic matter have reduced expression of VAB. In contrast, in pools with little organic debris where fish probably depend more on hunting than on scavenging, VAB is enhanced. Our results suggest that expression of VAB is a plastic trait whose variability can depend on local conditions. Such plasticity may be required within and among caves where high environmental variability between pools result in a diverse availability of food. This article is protected by copyright. All rights reserved.
A Cyclin D1–Dependent Transcriptional Program Predicts Clinical Outcome in Mantle Cell Lymphoma

Purpose: Mantle cell lymphoma (MCL) is characterized by the t(11;14)(q13;q32) translocation leading to cyclin D1 overexpression. Cyclin D1 is a major cell-cycle regulator and also regulates transcription, but the impact of cyclin D1–mediated transcriptional dysregulation on MCL pathogenesis remains poorly understood. The aim of this study was to define a cyclin D1–dependent gene expression program and analyze its prognostic value. Experimental Design: We integrated genome-wide expression analysis of cyclin D1–silenced and overexpressing cells with cyclin D1 chromatin-binding profiles to identify a cyclin D1–dependent transcriptional program in MCL cells. We analyzed this gene program in two MCL series of peripheral blood samples (n = 53) and lymphoid tissues (n = 106) to determine its biological and clinical relevance. We then obtained a simplified signature of this program and evaluated a third series of peripheral blood MCL samples (n = 81) by NanoString gene expression profiling to validate our findings. Results: We identified a cyclin D1–dependent transcriptional program composed of 295 genes that were mainly involved in cell-cycle control. The cyclin D1–dependent gene program was overexpressed in MCL tumors directly proportional to cyclin D1 levels. High expression of this program conferred an adverse prognosis with significant shorter overall survival of the patients. These observations were validated in an independent cohort of patients using a simplified 37-gene cyclin D1 signature. The cyclin D1–dependent transcriptional program was also present in multiple myeloma and breast tumors with cyclin D1 overexpression. Conclusions: We identified a cyclin D1–dependent transcriptional program that is overexpressed in MCL and predicts clinical outcome.
LncExpDB: an expression database of human long non-coding RNAs

Abstract Expression profiles of long non-coding RNAs (lncRNAs) across diverse biological conditions provide significant insights into their biological functions, interacting targets as well as transcriptional reliability. However, there lacks a comprehensive resource that systematically characterizes the expression landscape of human lncRNAs by integrating their expression profiles across a wide range of biological conditions. Here, we present LncExpDB (https://bigd.big.ac.cn/lncexpdb), an expression database of human lncRNAs that is devoted to providing comprehensive expression profiles of lncRNA genes, exploring their expression features and capacities, identifying featured genes with potentially important functions, and building interactions with protein-coding genes across various biological contexts/conditions. Based on comprehensive integration and stringent curation, LncExpDB currently houses expression profiles of 101 293 high-quality human lncRNA genes derived from 1977 samples of 337 biological conditions across nine biological contexts. Consequently, LncExpDB estimates lncRNA genes’ expression reliability and capacities, identifies 25 191 featured genes, and further obtains 28 443 865 lncRNA-mRNA interactions. Moreover, user-friendly web interfaces enable interactive visualization of expression profiles across various conditions and easy exploration of featured lncRNAs and their interacting partners in specific contexts. Collectively, LncExpDB features comprehensive integration and curation of lncRNA expression profiles and thus will serve as a fundamental resource for functional studies on human lncRNAs.
Lipid metabolic gene-wide pro�le and survival signature of lung adenocarcinoma

Background: Lung cancer is the cancer with high morbidity and mortality across the globe, and lung adenocarcinoma (LUAD) is the most common histologic subtype. The disorder of lipid metabolism is related to the development of cancer. Analysis of lipid-related transcriptome helps shed light on diagnosis and prognostic biomarkers of LUAD. Methods: In this study, we performed an expression analysis of 1045 lipid metabolism-related genes between LUAD tumors and normal tissues from the Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) cohort. The interaction network of differential expression genes (DEGs) was constructed to identify. The association between hub genes and overall survival was evaluated and formed a model to predict the prognosis of LUAD using a nomogram, and the model was validated by another cohort (GSE13213). Results: Finally, a total of 217 lipid metabolism-related DEGs were detected in LUAD. They were signi�cantly enriched in Glycerophospholipid metabolism, fatty acid metabolic process, and Eicosanoid Signaling. Then we identi�ed 6 hub genes through network and cytoHubba, including INS, LPL, HPGDS, DGAT1, UGT1A6, and CYP2C9. The high expression of CYP2C9, UGT1A6, and INS, whereas low expressions of DGAT1, HPGDS, and LPL, were associated with worse overall survival (OS) for 1925 LUAD patients. Our model found that the high-risk score group had a worse OS, and the validated cohort had the same result. Conclusion: This study constructed a signature of six lipid metabolic genes, which was signi�cantly associated with the diagnosis and prognosis of LUAD patients. The gene signature can be used as a biomarker for LUAD in the term of lipid metabolic.
The Cost of a Fall Among Older Adults Requiring Emergency Services

The cost of a fall among older adults requiring emergency services is unclear, especially beyond the acute care period. We evaluated medical expenditures (costs) to 1 year among community‐dwelling older adults who fell and required ambulance transport, including acute versus post‐acute periods, the primary drivers of cost, and comparison to baseline expenditures.
First- And Third-Person Video Co-Analysis By Learning Spatial-Temporal Joint Attention

Recent years have witnessed a tremendous increase of first-person videos captured by wearable devices. Such videos record information from different perspectives than the traditional third-person view, and thus show a wide range of potential usages. However, techniques for analyzing videos from different views can be fundamentally different, not to mention co-analyzing on both views to explore the shared information. In this paper, we take the challenge of cross-view video co-analysis and deliver a novel learning-based method. At the core of our method is the notion of “joint attention”, indicating the shared attention regions that link the corresponding views, and eventually guide the shared representation learning across views. To this end, we propose a multi-branch deep network, which extracts cross-view joint attention and shared representation from static frames with spatial constraints, in a self-supervised and simultaneous manner. In addition, by incorporating the temporal transition model of the joint attention, we obtain spatial-temporal joint attention that can robustly capture the essential information extending through time. Our method outperforms the state-of-the-art on the standard cross-view video matching tasks on public datasets. Furthermore, we demonstrate how the learnt joint information can benefit various applications through a set of qualitative and quantitative experiments.
Flow Cytometric Measurement of Efflux in Candida Species

A technique to assess the ability of distinct Candida strains to efflux substrates, as well as to compare the effectiveness of efflux inhibitors, is important for analysis of antifungal drug resistance mechanisms and the mode of action of antifungals. We describe a method that measures the ability of Candida species to extrude the fluorescent dye Nile red as an output for efflux activity. This involves exposing cells to Nile red and using flow cytometry to quantify cellular fluorescence, enabling numerous samples to be processed in a limited time frame. This protocol provides a simple, yet effective method for quantifying efflux in drug‐resistant Candida species. © 2020 Wiley Periodicals LLC
Analysis of B-RafV600E Regulated MicroRNAs and Proteins in Melanoma

Couts, Kasey Lyn (Ph.D., Biochemistry) Analysis of B-RafV600E Regulated MicroRNAs and Proteins in Melanoma Thesis directed by Professor Natalie G. Ahn Genome sequencing studies have identified oncogenic B-Raf mutations in over 70% of all sporadic melanomas. The B-RafV600E mutation leads to elevated kinase activity and constitutive activation of the mitogen-activated protein (MAP) kinase signaling pathway, which supports a variety of oncogenic functions critical to melanoma formation and progression. Metastatic melanomas are highly resistant to conventional chemotherapeutic treatments, and pharmacological inhibitors of B-RafV600E have been incompletely effective in pre-clinical studies. Understanding the global molecular responses to constitutive MAP kinase signaling in melanomas would allow the development of more effective therapeutics. Manipulation of microRNA (miRNA) expression is emerging as an important molecular mechanism by which oncogenes can broadly support tumorigenesis. In this study, strategic microarray profiling of melanoma cells identified a network of over 25 miRNAs that are controlled by B-RafV600E. Functional screening of all regulated microRNAs revealed that many were capable of altering cell growth and/or invasion, and I was able to identify important melanoma genes that were targeted by one or more B-RafV600E miRNA(s). Interestingly, several genes suppressed by multiple miRNAs were iii
Increased marrow adipogenesis does not contribute to age‐dependent appendicular bone loss in female mice

Marrow adipocytes and osteoblasts differentiate from common mesenchymal progenitors in a mutually exclusive manner, and diversion of these progenitors toward adipocytes in old age has been proposed to account for the decline in osteoblasts and the development of involutional osteoporosis. This idea has been supported by evidence that thiazolidinedione (TZD)‐induced activation of PPARγ, the transcription factor required for adipocyte differentiation, increases marrow fat and causes bone loss. We functionally tested this hypothesis using C57BL/6J mice with conditional deletion of PPARγ from early mesenchymal progenitors targeted by the Prx1‐Cre transgene. Using a longitudinal littermate‐controlled study design, we observed that PPARγ is indispensable for TZD‐induced increase in marrow adipocytes in 6‐month‐old male mice, and age‐associated increase in marrow adipocytes in 22‐month‐old female mice. In contrast, PPARγ is dispensable for the loss of cortical and trabecular bone caused by TZD or old age. Instead, PPARγ restrains age‐dependent development of cortical porosity. These findings do not support the long‐standing hypothesis that increased marrow adipocyte differentiation contributes to bone loss in old age but reveal a novel role of mesenchymal cell PPARγ in the maintenance of cortical integrity.
Multichannel Esophageal Heart Rate Monitoring of Preterm Infants

Objective: Autonomic dysregulation in preterm infants requires continuous monitoring of vital signs such as heart rate over days to months. Unfortunately, common surface electrodes are prone to electrocardiography (ECG) signal artifacts and cause serious skin irritations during long-term use. In contrast, esophageal ECG is known to be very sensitive due to the proximity of electrodes and heart and insensitive to external influences. This study addresses if multichannel esophageal ECG qualifies for heart rate monitoring in preterm infants. Methods: We recorded esophageal leads with a multi-electrode gastric feeding tube in a clinical study with 13 neonates and compared the heartbeat detection performance with standard surface leads. A computationally simple and versatile ECG wave detection algorithm was used. Results: Multichannel esophageal ECG manifested heartbeat sensitivity and positive predictive value greater than 98.5% and significant less false negative (FN) ECG waves as compared to surface ECG due to site-typical electrode motion artifacts. False positive bradycardia as indicated with more than 13 consecutive FN ECG waves was equally expectable in esophageal and surface channels. No adverse events were reported for the multi-electrode gastric feeding tube. Conclusion: Heart rate monitoring of preterm infants with multiple esophageal electrodes is considered as feasible and reliable. Less signal artifacts will improve the detection of bradycardia, which is crucial for immediate interventions, and reduce alarm fatigue. Significance: Due to the possibility to integrate the multichannel ECG into a gastric feeding tube and meanwhile omit harmful skin electrodes, the presented system has great potential to facilitate future intensive care of preterm infants.
Inulin alleviates adverse metabolic syndrome and regulates intestinal microbiota composition in Nile tilapia (Oreochromis niloticus) fed with high-carbohydrate diet

Abstract A high-carbohydrate diet could achieve a protein-sparing effect, but it may cause negative impacts on the growth condition of fish due to their poor utilisation ability of carbohydrate. How to reduce the adverse effects caused by a high-carbohydrate diet is important for the development of aquaculture. In the present study, we aimed to identify whether inulin could attenuate the metabolic syndrome caused by a high-carbohydrate diet in fish. Nile tilapia (Oreochromis niloticus) (1·19 (sd 0·01) g) were supplied with 35 % carbohydrate (CON), 45 % carbohydrate (HC) and 45 % carbohydrate + 5 g/kg inulin (HCI) diets for 10 weeks. The results showed that addition of inulin improved the survival rate when fish were challenged with Aeromonas hydrophila, indicating that inulin had an immunostimulatory effect. Compared with the HC group, the HCI group had lower lipid accumulation in liver and the gene expression analyses indicated that addition of inulin down-regulated genes related to lipogenesis and up-regulated genes relevant to β-oxidation significantly (P < 0·05). Higher liver glycogen and glucose tolerance were found in the HCI group compared with the HC group (P < 0·05). These results indicated that inulin could alleviate the metabolic syndrome induced by a high-carbohydrate diet. Furthermore, addition of inulin to a high-carbohydrate diet changed the intestinal bacterial composition and significantly increased the concentration of acetic acid and propionic acid in fish gut which have the potential to increase pathogen resistance and regulate metabolic characteristics in fish. Collectively, our results demonstrated a possible causal role for the gut microbiome in metabolic improvements induced by inulin in fish.
Innovative Empirical Model for Predicting National Banks’ Financial Failure with Artificial Intelligence Subset Data Analysis in the United States

Abstract The principal objective of this research study was to investigate the impact of the Great Economic Recession of 2008 on national banks’ equity investment valuations and create an empirical model for predicting national banks’ financial failure in the United States. The focal period of the study was from 2009 to 2012, and public data sources used. It is not known to what extent national banks’ stock value investments are based on the return on equity. This causal-comparative study explores the degree to which national banks’ value investment in terms of the price to earnings ratio impacts their return on equity and the extent to which these banks’ stock value investment in terms of dividend yield impacts their return on equity. We used statistical modeling and the machine learning model to find hidden patterns in the input data. The principal finding of this research is that the median earnings per share in 2012 and the dividend yield in 2009 were significantly larger than the median return on equity in 2009 and 2012. Additionally, the dividend yield in 2012 was significantly smaller than the median return on equity in 2012. These findings can contribute to improving our understanding of how banks can predict financial failure using the new machine learning features of artificial intelligence to build an early warning system with the innovative risk measurement tool.