Miracle-dz/UniFAR-FTUs huggingface dataset:
Urbanization Reduces Transfer of Diverse Environmental Microbiota Indoors

Expanding urbanization is a major factor behind rapidly declining biodiversity. It has been proposed that in urbanized societies, the rarity of contact with diverse environmental microbiota negatively impacts immune function and ultimately increases the risk for allergies and other immune-mediated disorders. Surprisingly, the basic assumption that urbanization reduces exposure to environmental microbiota and its transfer indoors has rarely been examined. We investigated if the land use type around Finnish homes affects the diversity, richness, and abundance of bacterial communities indoors. Debris deposited on standardized doormats was collected in 30 rural and 26 urban households in and near the city of Lahti, Finland, in August 2015. Debris was weighed, bacterial community composition determined by high throughput sequencing of bacterial 16S ribosomal RNA (rRNA) gene on the Illumina MiSeq platform, and the percentage of four different land use types (i.e., built area, forest, transitional, and open area) within 200 m and 2000 m radiuses from each household was characterized. The quantity of doormat debris was inversely correlated with coverage of built area. The diversity of total bacterial, Proteobacterial, Actinobacterial, Bacteroidetes, and Firmicutes communities decreased as the percentage of built area increased. Their richness followed the same pattern except for Firmicutes for which no association was observed. The relative abundance of Proteobacteria and particularly Gammaproteobacteria increased, whereas that of Actinobacteria decreased with increasing built area. Neither Phylum Firmicutes nor Bacteroidetes varied with coverage of built area. Additionally, the relative abundance of potentially pathogenic bacterial families and genera increased as the percentage of built area increased. Interestingly, having domestic animals (including pets) only altered the association between the richness of Gammaproteobacteria and diversity of Firmicutes with the built area coverage suggesting that animal ownership minimally affects transfer of environmental microbiota indoors from the living environment. These results support the hypothesis that people living in densely built areas are less exposed to diverse environmental microbiota than people living in more sparsely built areas.
Translational Insight Into Polycystic Ovary Syndrome (PCOS) From Female Monkeys with PCOS-like Traits.

Genetics-based studies of women with polycystic ovary syndrome (PCOS) implicate >20 PCOS risk genes that collectively account for <10% of PCOS. Clinicians now consider that either rare alleles or non-genetic, potentially epigenetic, developmental origins may contribute key pathogenic components to >90% of PCOS cases. Animal models convincingly demonstrate excess fetal testosterone exposure in females as a reliable, epigenetic, developmental origin for PCOS-like traits. In particular, nonhuman primates (NHPs) provide the most faithful emulation of PCOS-like pathophysiology, likely because of close similarities to humans in genomic, developmental, reproductive and metabolic characteristics, as well as aging. Recent appreciation of potential molecular mechanisms contributing to enhanced LH action in both PCOS women (GWAS-based) and PCOS-like monkeys (DNA methylation-based) suggest commonality in pathogenic origins. This review examines the translational relevance of NHP studies to PCOS, identifying characteristics of newborn females at risk for PCOS-like traits and potential prepubertal treatment interventions to ameliorate PCOS onset.
ouse models of ageing and their relevance to disease

Ageing is a process that gradually increases the organism’s vulnerability to death. It affects different biological pathways, and the underlying cellular mechanisms are complex. In view of the growing disease burden of ageing populations, increasing efforts are being invested in understanding the pathways and mechanisms of ageing. We review some mouse models commonly used in studies on ageing, highlight the advantages and disadvantages of the different strategies, and discuss their relevance to disease sus-
Neutrophil gelatinase-associated lipocalin is a better biomarker than cystatin C for the prediction of imminent acute kidney injury in critically ill patients

Aims The prevention of acute kidney injury can be lifesaving for the intensive care unit patients. However, conventional methods are not sufficient for the prediction of the risk of future acute kidney injury. In this study, the promising biomarker, neutrophil gelatinase-associated lipocalin, was compared with cystatin C as an indicator for the risk of future acute kidney injury. Methods One hundred and eighty-three adult patients without chronic kidney disease or renal replacement therapy were included in this study. The plasma and urine concentrations of neutrophil gelatinase-associated lipocalin and cystatin C were assessed on the second day after intensive care unit admission and were followed for seven days to monitor the development of acute kidney injury. Acute kidney injury diagnosis was based on the risk, injury, failure, loss, end-stage renal failure criteria. Results Thirty-four per cent of the patients had acute kidney injury; 17 patients who did not fulfil criteria at the beginning, developed acute kidney injury from days 3 to 7 after admission. The mean serum creatinine on admission did not significantly differ between this and control groups (0.72 ± 0.20 and 0.83 ± 0.21; P = 0.060); however, the serum and urinary neutrophil gelatinase-associated lipocalin concentrations on the second day were significantly different (median: 75.69 [54.18–91.18] and 123.68 [90.89–166.31], P = 0.001; and median: 17.60 [8.56–34.04] and 61.37 [24.59–96.63], P = 0.001). Notably, the 48-h serum cystatin C concentration did not differ. Conclusion Neutrophil gelatinase-associated lipocalin concentrations in the urine and serum on the second day of intensive care unit admission could be used to predict the development of acute kidney injury in the following three to seven days in the intensive care unit; however, the cystatin C concentration did not have predictive value.
Switching investigations on a SiC MOSFET in a TO-247 package

This paper deals with the switching behavior of a SiC MOSFET in a TO-247 package. Based on simulations, critical parasitic inductances in the circuit layout are analyzed and their effect on the switching losses highlighted. Especially the common source inductance, a critical parameter in a TO-247 package, has a major influence on the switching energy. Crucial design guidelines for an improved double pulse test circuit are introduced which are used for practical investigations on the switching behavior. Switching energies of a SiC MOSFET in a TO-247 package is measured depending on varying gate resistance and loop inductances. With total switching energy of 340.24 μJ, the SiC MOSFET has more than six times lower switching losses than a regular Si IGBT. Implementing the SiC switches in a 3kW T-Type inverter topology, efficiency improvements of 0.8 % are achieved and maximum efficiency of 97.7 % is reached.
Multi-Assay-Based Compound Prioritization via Assistance Utilization: A Machine Learning Framework

Effective prioritization of chemical compounds that show promising bioactivities from compound screenings represents a first critical step toward identifying successful drug candidates. Current development on computational approaches for compound prioritization is largely focused on devising advanced ranking algorithms that better learn the ordering among compounds. However, such methodologies are fundamentally limited by the scarcity of available data, particularly when the screenings are conducted at a relatively small scale over known promising compounds. Instead, in this work, we explore the structures of bioassay space and leverage such structures to improve ranking performance of an existing strong ranking algorithm. This is done by identifying assistance bioassays and assistance compounds intelligently and leveraging such assistance within the existing ranking algorithm. By leveraging the assistance bioassays and assistance compounds, the data scarcity can be properly compromised. Along this line, we develop a suite of assistance bioassay selection methods and assistance compound selection methods. Our experiments demonstrate an overall 8.34% improvement on the ranking performance over the state of the art.
Generic Object Recognition by Tree Conditional Random Field Based on Hierarchical Segmentation

Generic object recognition by a computer is strongly required in various fields like robot vision and image retrieval in recent years. Conventional methods use Conditional Random Field (CRF) that recognizes the class of each region using the features extracted from the local regions and the class co-occurrence between the adjoining regions. However, there is a problem that the discriminative ability of the features extracted from local regions is insufficient, and these methods is not robust to the scale variance. To solve this problem, we propose a method that integrates the recognition results in multi-scales by tree conditional random field based on hierarchical segmentation. As a result of the image dataset of 7 classes, the proposed method has improved the recognition rate by 2.2%.
Evaluation of RNA from human trabecular bone and identification of stable reference genes

The isolation of good quality RNA from tissues is an essential prerequisite for gene expression analysis to study pathophysiological processes. This study evaluated the RNA isolated from human trabecular bone and defined a set of stable reference genes. After pulverization, RNA was extracted with a phenol/chloroform method and then purified using silica columns. The A260/280 ratio, A260/230 ratio, RIN, and ribosomal ratio were measured to evaluate RNA quality and integrity. Moreover, the expression of six candidates was analyzed by qPCR and different algorithms were applied to assess reference gene stability. A good purity and quality of RNA was achieved according to A260/280 and A260/230 ratios, and RIN values. TBP, YWHAZ, and PGK1 were the most stable reference genes that should be used for gene expression analysis. In summary, the method proposed is suitable for gene expression evaluation in human bone and a set of reliable reference genes has been identified.
A Spawn Mobile Agent Itinerary Planning Approach for Energy-Efficient Data Gathering in Wireless Sensor Networks

Mobile agent (MA), a part of the mobile computing paradigm, was recently proposed for data gathering in Wireless Sensor Networks (WSNs). The MA-based approach employs two algorithms: Single-agent Itinerary Planning (SIP) and Multi-mobile agent Itinerary Planning (MIP) for energy-efficient data gathering. The MIP was proposed to outperform the weakness of SIP by introducing distributed multi MAs to perform the data gathering task. Despite the advantages of MIP, finding the optimal number of distributed MAs and their itineraries are still regarded as critical issues. The existing MIP algorithms assume that the itinerary of the MA has to start and return back to the sink node. Moreover, each distributed MA has to carry the processing code (data aggregation code) to collect the sensory data and return back to the sink with the accumulated data. However, these assumptions have resulted in an increase in the number of MA’s migration hops, which subsequently leads to an increase in energy and time consumption. In this paper, a spawn multi-mobile agent itinerary planning (SMIP) approach is proposed to mitigate the substantial increase in cost of energy and time used in the data gathering processes. The proposed approach is based on the agent spawning such that the main MA is able to spawn other MAs with different tasks assigned from the main MA. Extensive simulation experiments have been conducted to test the performance of the proposed approach against some selected MIP algorithms. The results show that the proposed SMIP outperforms the counterpart algorithms in terms of energy consumption and task delay (time), and improves the integrated energy-delay performance.
The X-Y factor: Females and males with urological chronic pelvic pain syndrome present distinct clinical phenotypes.

INTRODUCTION Urological chronic pelvic pain syndrome (UCPPS) in females is often attributed to the bladder (interstitial cystitis/ bladder pain syndrome), while UCPPS in males is often attributed to the prostate (chronic prostatitis/chronic pelvic pain syndrome). However, there is increasing awareness that bladder pain plays a role in both males and females and the degree of overlap of clinical characteristics in males and females with UCPPS is not well known. Our objective was to compare clinical phenotypes of females and males with UCPPS. METHODS We conducted a retrospective analysis of prospectively collected data from a single-centre patient population presenting between 1998 and 2016 to our UCPPS clinic. Demographics, symptom scores, pain scales, retrospectively described clinical UPOINT (urinary, psychosocial, organ-specific, infection, neurogenic, and tenderness) scoring, and presence of comorbid medical conditions were compared between females and males using comparative analyses. RESULTS We identified 2007 subjects (1523 males, 484 females) with UCPPS. Females had increased prevalence of irritable bowel syndrome (25% vs. 11.2%), chronic fatigue syndrome (13.6% vs. 1.6%), fibromyalgia (16.9% vs. 1.6%), drug allergies (56.6% vs. 13.5%), diabetes (20.2% vs. 3.9%), depression (31% vs. 18.4%), and alcohol use (44.2% vs. 10.8%) compared to males with UCPPS (all p<0.001). In respect to UPOINT domains, females had a higher "total" (3.2 vs. 2.4), "urinary" (92.8% vs. 67.6%), "organ-specific" (90.1% vs. 51.4%), and "neurogenic" (44.7% vs. 30%) prevalence compared to males (all p<0.001). CONCLUSIONS Females with UCPPS have greater prevalence of systemic disorders/symptoms and worse urinary symptoms than males with UCPPS. These findings demonstrate that females and males with UCPPS have distinct and different clinical phenotypes.
Constant power loads: A solution using sliding mode control

Rapidly increasing penetration of renewable energy sources into conventional power distribution systems has led to the rise in power electronic converter dominated power distribution systems. However, it has been a well established that the presence of tightly regulated point-of-load (POL) converters in the power distribution system, which act as Constant Power Loads (CPLs), cause serious stability challenge in spite of ensuring stability of individual converters. In this paper, we propose a sliding-mode controller with a non-linear sliding surface to mitigate negative impedance instabilities caused by the CPLs in dc distribution systems (dc Micro-grids). The stability of proposed surface and existence of sliding modes are proved. A simplified structure of a dc micro-grid system with dc/dc boost converter and CPL is used for the implementation of the proposed controller. Proposed controller is able to mitigate negative impedance instabilities and ensures stable operation of dc micro-grid system under various disturbances. The performance of the proposed controller, under steady state, line and load variations are validated through simulations in MATLAB Simulink environment.
Annotating High-Level Structures of Short Stories and Personal Anecdotes

Stories are a vital form of communication in human culture; they are employed daily to persuade, to elicit sympathy, or to convey a message. Computational understanding of human narratives, especially high-level narrative structures, remain limited to date. Multiple literary theories for narrative structures exist, but operationalization of the theories has remained a challenge. We developed an annotation scheme by consolidating and extending existing narratological theories, including Labov and Waletsky's (1967) functional categorization scheme and Freytag's (1863) pyramid of dramatic tension, and present 360 annotated short stories collected from online sources. In the future, this research will support an approach that enables systems to intelligently sustain complex communications with humans.
Multi-user, multi-display interaction with a single-user, single-display geospatial application

In this paper, we discuss our adaptation of a single-display, single-user commercial application for use in a multi-device, multi-user environment. We wrap Google Earth, a popular geospatial application, in a manner that allows for synchronized coordinated views among multiple instances running on different machines in the same co-located environment. The environment includes a touch-sensitive tabletop display, three vertical wall displays, and a TabletPC. A set of interaction techniques that allow a group to manage and exploit this collection of devices is presented.
Nurse value-added and patient outcomes in acute care.

OBJECTIVE The aims of the study were to (1) estimate the relative nurse effectiveness, or individual nurse value-added (NVA), to patients' clinical condition change during hospitalization; (2) examine nurse characteristics contributing to NVA; and (3) estimate the contribution of value-added nursing care to patient outcomes. DATA SOURCES/STUDY SETTING Electronic data on 1,203 staff nurses matched with 7,318 adult medical-surgical patients discharged between July 1, 2011 and December 31, 2011 from an urban Magnet-designated, 854-bed teaching hospital. STUDY DESIGN Retrospective observational longitudinal analysis using a covariate-adjustment value-added model with nurse fixed effects. DATA COLLECTION/EXTRACTION METHODS Data were extracted from the study hospital's electronic patient records and human resources databases. PRINCIPAL FINDINGS Nurse effects were jointly significant and explained 7.9 percent of variance in patient clinical condition change during hospitalization. NVA was positively associated with having a baccalaureate degree or higher (0.55, p = .04) and expertise level (0.66, p = .03). NVA contributed to patient outcomes of shorter length of stay and lower costs. CONCLUSIONS Nurses differ in their value-added to patient outcomes. The ability to measure individual nurse relative value-added opens the possibility for development of performance metrics, performance-based rankings, and merit-based salary schemes to improve patient outcomes and reduce costs.
Rapid Independent Trait Evolution despite a Strong Pleiotropic Genetic Correlation

Genetic correlations are the most commonly studied of all potential constraints on adaptive evolution. We present a comprehensive test of constraints caused by genetic correlation, comparing empirical results to predictions from theory. The additive genetic correlation between the filament and the corolla tube in wild radish flowers is very high in magnitude, is estimated with good precision (), and is caused by pleiotropy. Thus, evolutionary changes in the relative lengths of these two traits should be constrained. Still, artificial selection produced rapid evolution of these traits in opposite directions, so that in one replicate relative to controls, the difference between them increased by six standard deviations in only nine generations. This would result in a 54% increase in relative fitness on the basis of a previous estimate of natural selection in this population, and it would produce the phenotypes found in the most extreme species in the family Brassicaceae in less than 100 generations. These responses were within theoretical expectations and were much slower than if the genetic correlation was zero; thus, there was evidence for constraint. These results, coupled with comparable results from other species, show that evolution can be rapid despite the constraints caused by genetic correlations.
miR-144 Potentially Suppresses Proliferation and Migration of Ovarian Cancer Cells by Targeting RUNX1

Background Ovarian cancer (OC) is one of the most common malignant diseases of the female reproductive system worldwide. Evidence has shown that microRNAs are involved in the development of ovarian cancer. miR-144, one of these microRNAs, has been found have upregulated expression in various human malignancies. The present study aimed to investigate the role miR-144 in ovarian cancer cell lines and to elucidate the mechanism involved. Material/Methods Human ovarian cancer cell lines (SKOV3/OVCAR3) and a normal ovarian cell line (IOSE80) were used to identify the miR-144 expression though qRT-PCR method. SKOV3/OVCAR3 cells were transfected with miR-144 mimics by Lipofectamine, and the proliferation, migration, and invasion ability of these cells were detected by MTT assay, wound healing assay, and Transwell assays, respectively. MMP2 and MMP9 expression were detected at mRNA and protein levels. The results of dual luciferase reporter assay confirmed that miR-144 could down-regulate RUNX1 expression level. Finally, the expression of runt-related transcription factor 1 (RUNX1) was examined using qRT-PCR and Western blot analysis. Results Our results demonstrate that the expression level of miR-144 was downregulated in SKOV3/OVCAR3 compared to IOSE80, and we found that miR-144 suppresses the proliferation and migration of ovarian cancer cells. Moreover, RUNX1 was predicted and confirmed to be a target of miRNA-144. Additionally, after 48-h transfection with miR-144 mimics, the expression of RUNX1 was downregulated in OC cells. Conclusions miR-144 mimics can inhibit the proliferation and migration of ovarian cancer cells though regulating the expression of RUNX1.
Olfaction, experience and neural mechanisms underlying mosquito host preference

ABSTRACT Mosquitoes are best known for their proclivity towards biting humans and transmitting bloodborne pathogens, but there are over 3500 species, including both blood-feeding and non-blood-feeding taxa. The diversity of host preference in mosquitoes is exemplified by the feeding habits of mosquitoes in the genus Malaya that feed on ant regurgitation or those from the genus Uranotaenia that favor amphibian hosts. Host preference is also by no means static, but is characterized by behavioral plasticity that allows mosquitoes to switch hosts when their preferred host is unavailable and by learning host cues associated with positive or negative experiences. Here we review the diverse range of host-preference behaviors across the family Culicidae, which includes all mosquitoes, and how adaptations in neural circuitry might affect changes in preference both within the life history of a mosquito and across evolutionary time-scales. Summary: This Review discusses the environmental, neurobiological and genetic factors driving extreme host preference diversity and plasticity among the Culicidae, both within the life history of a mosquito and across evolutionary time-scales.