Miracle-dz/UniFAR-FTUs huggingface dataset:
Children with familial hypercholesterolemia display changes in LDL and HDL function: A cross‐sectional study

The functional status of lipoprotein particles contributes to atherogenesis. The tendency of plasma low‐density lipoprotein (LDL) particles to aggregate and the ability of igh‐density lipoprotein (HDL) particles to induce and mediate reverse cholesterol transport associate with high and low risk for cardiovascular disease in adult patients, respectively. However, it is unknown whether children with familial hypercholesterolemia (FH) display lipoprotein function alterations.
Dynamics of HIV-1 Molecular Networks Reveal Effective Control of Large Transmission Clusters in an Area Affected by an Epidemic of Multiple HIV Subtypes

This study reconstructed molecular networks of human immunodeficiency virus (HIV) transmission history in an area affected by an epidemic of multiple HIV-1 subtypes and assessed the efficacy of strengthened early antiretroviral therapy (ART) and regular interventions in preventing HIV spread. We collected demographic and clinical data of 2221 treatment-naïve HIV-1–infected patients in a long-term cohort in Shenyang, Northeast China, between 2008 and 2016. HIV pol gene sequencing was performed and molecular networks of CRF01_AE, CRF07_BC, and subtype B were inferred using HIV-TRACE with separate optimized genetic distance threshold. We identified 168 clusters containing ≥ 2 cases among CRF01_AE-, CRF07_BC-, and subtype B-infected cases, including 13 large clusters (≥ 10 cases). Individuals in large clusters were characterized by younger age, homosexual behavior, more recent infection, higher CD4 counts, and delayed/no ART (P < 0.001). The dynamics of large clusters were estimated by proportional detection rate (PDR), cluster growth predictor, and effective reproductive number (Re). Most large clusters showed decreased or stable during the study period, indicating that expansion was slowing. The proportion of newly diagnosed cases in large clusters declined from 30 to 8% between 2008 and 2016, coinciding with an increase in early ART within 6 months after diagnosis from 24 to 79%, supporting the effectiveness of strengthened early ART and continuous regular interventions. In conclusion, molecular network analyses can thus be useful for evaluating the efficacy of interventions in epidemics with a complex HIV profile.
Exploring the Influence of Signal Molecules on Marine Biofilms Development

Microbes respond to environmental stimuli through complicated signal transduction systems. In microbial biofilms, because of complex multiple species interactions, signals transduction systems are of an even higher complexity. Here, we performed a signal-molecule-treatment experiment to study the role of different signal molecules, including N-hexanoyl-L-homoserine lactone (C6-HSL), N-dodecanoyl-L-homoserine lactone (C12-HSL), Pseudomonas quinolone signal (PQS), and cyclic di-GMP (c-di-GMP), in the development of marine biofilms. Comparative metagenomics suggested a distinctive influence of these molecules on the microbial structure and function of multi-species biofilm communities in its developing stage. The PQS-treated biofilms shared the least similarity with the control and initial biofilms. The role of PQS in biofilm development was further explored experimentally with the strain Erythrobacter sp. HKB8 isolated from marine biofilms. Comparative transcriptomic analysis showed that 314 genes, such as those related to signal transduction and biofilm formation, were differentially expressed in the untreated and PQS-treated Erythrobacter sp. HKB8 biofilms. Our study demonstrated the different roles of signal molecules in marine biofilm development. In particular, the PQS-based signal transduction system, which is frequently detected in marine biofilms, may play an important role in regulating microbe-microbe interactions and the assemblage of biofilm communities.
Extended Stability Evaluation of Selected Cathinones

Understanding the stability of drugs in a forensic toxicology setting is critical for the evaluation of drug concentrations. Synthetic cathinones are new psychoactive substances structurally derived from cathinone, the psychoactive component of Catha edulis (“khat”), a shrub that is indigenous to the Middle East and East Africa. Previous research has evaluated the stability of synthetic cathinones in biological matrices, including blood preserved with the combination of NaF and K2C2O4 used in gray-top tubes. However, it does not assess their stability in blood preserved with Na2EDTA, used for some clinical samples. Further, stability in unpreserved urine samples was only studied for two weeks. This research evaluates the stabilities of four Schedule I synthetic cathinones: mephedrone, MDPV (3,4-methylenedioxypyrovalerone), naphyrone, and α-PVP (alpha-pyrrolidinopentiophenone) at 20°C (room temperature), 4°C (refrigerator), and −20°C (freezer). Stability was assessed in methanolic and acetonitrile solutions, as well as in Na2EDTA-preserved blood and unpreserved urine. Solutions (1 mg/L) of each drug in each matrix stored in aliquots (100 μL, solvents; 1.2 mL, biological samples; n = 12) at each of the three temperatures for triplicate analysis on days 3, 7, 14, and 30. On day 0 of each study, three additional aliquots of each solution were analyzed. Biological samples underwent solid-phase extraction before analysis. All samples were analyzed in full-scan by gas chromatography-mass spectrometry (GC-MS). The results of this study show that under room temperature and refrigerator storage conditions, mephedrone, naphyrone, and MDPV will degrade in methanol. This degradation starts are early as day 3. Additionally, all four drugs will degrade in Na2EDTA-preserved human whole blood samples in at least one evaluated storage environment. However, when in acetonitrile-based working solutions and unpreserved urine samples, they proved to be more stable. Methanolic working solutions and samples of Na2EDTA-preserved blood containing these cathinones should be stored in the freezer and used or tested with urgency to ensure that quantitative sample analysis is as accurate as possible in forensic casework.
Identification of COVID-19 Clinical Phenotypes by Principal Component Analysis-Based Cluster Analysis

Background: COVID-19 has been quickly spreading, making it a serious public health threat. It is important to identify phenotypes to predict the severity of disease and design an individualized treatment. Methods: We collected data from 213 COVID-19 patients in Wuhan Pulmonary Hospital from January 1 to March 30, 2020. Principal component analysis (PCA) and cluster analysis were used to classify patients. Results: We identified three distinct subgroups of COVID-19. Cluster 1 was the largest group (52.6%) and characterized by oldest age, lowest cellular immune function, and albumin levels. 38.5% of subjects were grouped into Cluster 2. Most of the lab results in Cluster 2 fell between those of Clusters 1 and 3. Cluster 3 was the smallest cluster (8.9%), characterized by youngest age and highest cellular immune function. The incidence of respiratory failure, acute respiratory distress syndrome (ARDS), heart failure, and usage of non-invasive mechanical ventilation in Cluster 1 was significantly higher than others (P < 0.05). Cluster 1 had the highest death rate of 30.4% (P = 0.005). Although there were significant differences in age between Clusters 2 and 3 (P < 0.001), we found that there was no difference in demand for medical resources. Conclusions: We identified three distinct clusters of the COVID-19 patients. The results show that age alone could not be used to assess a patient's condition. Specifically, management of albumin, and immune function are important in reducing the severity of disease.
Pleiotropic Role of Tenascin-C in Central Nervous System Diseases: From Basic to Clinical Applications

The extracellular matrix is composed of a variety of macromolecular substances secreted by cells, which form a complex network that supports and connects tissue structures, regulates the morphogenesis of tissues, and maintains the physiological activities of cells. Tenascin-C, a secreted extracellular matrix glycoprotein, is abundantly expressed after exposure to pathological stimuli. It plays an important regulatory role in brain tumors, vascular diseases, and neurodegenerative diseases by mediating inflammatory responses, inducing brain damage, and promoting cell proliferation, migration, and angiogenesis through multiple signaling pathways. Therefore, tenascin-C may become a potential therapeutic target for intracranial diseases. Here, we review and discuss the latest literature regarding tenascin-C, and we comprehensively explain the role and clinical significance of tenascin-C in intracranial diseases.
Behavioral Cues of Humanness in Complex Environments: How People Engage With Human and Artificially Intelligent Agents in a Multiplayer Videogame

The development of AI that can socially engage with humans is exciting to imagine, but such advanced algorithms might prove harmful if people are no longer able to detect when they are interacting with non-humans in online environments. Because we cannot fully predict how socially intelligent AI will be applied, it is important to conduct research into how sensitive humans are to behaviors of humans compared to those produced by AI. This paper presents results from a behavioral Turing Test, in which participants interacted with a human, or a simple or “social” AI within a complex videogame environment. Participants (66 total) played an open world, interactive videogame with one of these co-players and were instructed that they could interact non-verbally however they desired for 30 min, after which time they would indicate their beliefs about the agent, including three Likert measures of how much participants trusted and liked the co-player, the extent to which they perceived them as a “real person,” and an interview about the overall perception and what cues participants used to determine humanness. T-tests, Analysis of Variance and Tukey's HSD was used to analyze quantitative data, and Cohen's Kappa and χ2 was used to analyze interview data. Our results suggest that it was difficult for participants to distinguish between humans and the social AI on the basis of behavior. An analysis of in-game behaviors, survey data and qualitative responses suggest that participants associated engagement in social interactions with humanness within the game.
Postdiagnostic Fruit and Vegetable Consumption and Breast Cancer Survival: Prospective Analyses in the Nurses' Health Studies

A large-scale study shows that high fruit and vegetable consumption may be associated with better overall survival among breast cancer patients, while high fruit juice consumption may be associated with poorer prognosis. Fruits and vegetables contain many bioactive components that may contribute to improved survival after diagnosis of breast cancer, however, evidence to date is insufficient. We prospectively assessed the associations of postdiagnostic fruit and vegetable consumption with breast cancer–specific and all-cause mortality among 8,927 women with stage I–III breast cancer identified during follow-up of the Nurses' Health Study (NHS; 1980–2010) and NHSII (1991–2011), using a validated food frequency questionnaire completed every 4 years after diagnosis. We prospectively documented 2,521 deaths, including 1,070 from breast cancer through follow-up until 2014 in the NHS and 2015 in the NHSII. Total fruit and vegetable and total vegetable consumption was related to lower all-cause [HRQ5vsQ1, 0.82; 95% confidence interval (CI), 0.71–0.94; Ptrend = 0.004, and HRQ5vsQ1, 0.84; 95% CI, 0.72–0.97; Ptrend = 0.001, respectively], but not breast cancer–specific mortality. Total fruit consumption was not related to breast cancer–specific or all-cause mortality. Greater intake of green leafy and cruciferous vegetables was associated with lower all-cause mortality. Each 2 servings/week of blueberries was associated with a 25% (HR, 0.75; 95% CI, 0.60–0.94) lower breast cancer–specific and a 17% (HR, 0.83; 95% CI, 0.72–0.96) lower all-cause mortality. In contrast, higher fruit juice consumption was associated with higher breast cancer–specific (HRQ5vsQ1, 1.33; 95% CI, 1.09–1.63; Ptrend = 0.002) and all-cause mortality (HRQ5vsQ1, 1.19; 95% CI, 1.04–1.36; Ptrend = 0.003). Apple juice largely accounted for these higher risks and orange juice was not associated with risk. Higher postdiagnostic fruit and vegetable consumption among breast cancer survivors was not associated with breast cancer–specific mortality. However, our findings suggest that higher vegetable consumption, particularly green leafy and cruciferous vegetables, was associated with better overall survival among patients with breast cancer. Higher fruit juice consumption, but not orange juice, was associated with poorer breast cancer–specific and all-cause survival. Significance: A large-scale study shows that high fruit and vegetable consumption may be associated with better overall survival among breast cancer patients, while high fruit juice consumption may be associated with poorer porgnosis.
Cooling our insatiable demand for data

Hyperscale data centers provide challenges and opportunities for energy use The world is driven by constant access to information. We have the entire world at our fingertips wherever we are, and access to data in its various forms is ubiquitous. The ability to retrieve this information, much of it now stored in the cloud, is supported by data centers of various sizes and scales. Although instant access to data from anywhere is a benefit in many ways, part of the cost of this access is in escalating energy demands, much of it from the cooling infrastructure needed to support these data centers.
A strategic plan for future USDA Agricultural Research Service erosion research and model development

Soil erosion is a natural process, and the erosion potential of a site is the result of complex interactions among soil, vegetation, topographic position, land use and management, and climate. Soil erosion occurs when aeolian and hydrologic processes exceed a soil’s inherent resistance to these forces (figures 1 and 2). Soil erosion was recognized as a significant problem at both local and national scales in the United States in the 1920s; by 1935 soil erosion was considered a national disaster, covering over one-half of the country (Sampson and Weyl 1918; Weaver 1935), and is still a concern with 21% of the western United States degraded and vulnerable to accelerated soil erosion (Herrick et al. 2010; Weltz et al. 2014a; Duniway et al. 2019). In 1995, it was estimated that 4 × 109 t (4.4 × 109 tn) of soil was lost from US cropland (Pimentel et al. 1995). The most vulnerable areas for soil movement and thus erosion occur where annual precipitation is 100 to 400 mm y–1 (4 to 16 in yr–1), which limits soil moisture available to sustain plant growth. Anthropogenic-driven dust emissions have dramatically increased across …
Tailored Interventions to Improve Medication Adherence for Cardiovascular Diseases

Over the past half-century, medical research on cardiovascular disease (CVD) has achieved a great deal; however, medication adherence is unsatisfactory. Nearly 50% of patients do not follow prescriptions when taking medications, which limits the ability to maximize their therapeutic effects and results in adverse clinical outcomes and high healthcare costs. Furthermore, the effects of medication adherence interventions are disappointing, and tailored interventions have been proposed as an appropriate way to improve medication adherence. To rethink and reconstruct methods of improving medication adherence for CVD, the literature on tailored interventions for medication adherence focusing on CVD within the last 5 years is retrieved and reviewed. Focusing on identifying nonadherent patients, detecting barriers to medication adherence, delivering clinical interventions, and constructing theories, this article reviews the present state of tailored interventions for medication adherence in CVD and also rethinks the present difficulties and suggests avenues for future development.
GluN2B but Not GluN2A for Basal Dendritic Growth of Cortical Pyramidal Neurons

NMDA receptors are important players for neuronal differentiation. We previously reported that antagonizing NMDA receptors with APV blocked the growth-promoting effects evoked by the overexpression of specific calcium-permeable or flip-spliced AMPA receptor subunits and of type I transmembrane AMPA receptor regulatory proteins which both exclusively modify apical dendritic length and branching of cortical pyramidal neurons. These findings led us to characterize the role of GluN2B and GluN2A for dendritogenesis using organotypic cultures of rat visual cortex. Antagonizing GluN2B with ifenprodil and Ro25-6981 strongly impaired basal dendritic growth of supra- and infragranular pyramidal cells at DIV 5–10, but no longer at DIV 15–20. Growth recovered after washout, and protein blots revealed an increase of synaptic GluN2B-containing receptors as indicated by a enhanced phosphorylation of the tyrosine 1472 residue. Antagonizing GluN2A with TCN201 and NVP-AAM077 was ineffective at both ages. Dendrite growth of non-pyramidal interneurons was not altered. We attempted to overexpress GluN2A and GluN2B. However, although the constructs delivered currents in HEK cells, there were neither effects on dendrite morphology nor an enhanced sensitivity to NMDA. Further, co-expressing GluN1-1a and GluN2B did not alter dendritic growth. Visualization of overexpressed, tagged GluN2 proteins was successful after immunofluorescence for the tag which delivered rather weak staining in HEK cells as well as in neurons. This suggested that the level of overexpression is too weak to modify dendrite growth. In summary, endogenous GluN2B, but not GluN2A is important for pyramidal cell basal dendritic growth during an early postnatal time window.
Mastermind: A Comprehensive Genomic Association Search Engine for Empirical Evidence Curation and Genetic Variant Interpretation

Design and interpretation of genome sequencing assays in clinical diagnostics and research labs is complicated by an inability to identify information from the medical literature and related databases quickly, comprehensively and reproducibly. This challenge is compounded by the complexity and heterogeneity of nomenclatures used to describe diseases, genes and genetic variants. Mastermind is a widely-used bioinformatic platform of genomic associations that has indexed more than 7.5 M full-text articles and 2.5 M supplemental datasets. It has automatically identified, disambiguated and annotated >6.1 M genetic variants and identified >50 K disease-gene associations. Here, we describe how Mastermind improves the sensitivity and reproducibility of clinical variant interpretation and produces comprehensive genomic landscapes of genetic variants driving pharmaceutical research. We demonstrate an alarmingly high degree of heterogeneity across commercially available panels for hereditary cancer that is resolved by evidence from Mastermind. We further examined the sensitivity of Mastermind for variant interpretation by examining 108 clinically-encountered variants and comparing the results to alternate methods. Mastermind demonstrated a sensitivity of 98.4% compared to 4.4, 45.6, and 37.4% for alternatives PubMed, Google Scholar, and ClinVar, respectively, and a specificity of 98.5% compared to 45.1, 57.6, and 68.8% as well as an increase in content yield of 22.6-, 2.2-, and 2.6-fold. When curated for clinical significance, Mastermind identified more than 4.9-fold more pathogenic variants than ClinVar for representative genes. For structural variants, we compared Mastermind’s ability to sensitively identify evidence for 10 representative disease-causing CNVs versus results identified in PubMed, as well as its ability to identify evidence for fusion events compared to COSMIC. Mastermind demonstrated a 4.0- to 43.9-fold increase in references for specific CNVs compared to PubMed, as well as 5.4-fold more fusion genes when compared with COSMIC’s curated database. Additionally, Mastermind produced an 8.0-fold increase in reference citations for fusion events common to Mastermind and outside databases. Taken together, these results demonstrate the utility and superiority of Mastermind in terms of both sensitivity and specificity of automated results for clinical diagnostic variant interpretation for multiple genetic variant types and highlight the potential benefit in informing pharmaceutical research.
Developing targeted antimicrobial treatment protocols for mastitis

Antimicrobial resistance (AMR) is a significant human health problem, with 10 million deaths from drug-resistant infections predicted by 2050.1 The use of antimicrobials in food-producing animals is associated with the emergence of resistant bacteria in those species,2 although there are now several studies suggesting that antibiotic use in food-producing animals is not the main driver of resistance seen in bacteria infecting people.3,4 The transmission of resistance in environmental reservoirs is believed to play a more dominant role.4,5 However, practising prudent antimicrobial use (AMU) is still paramount to reduce the development and spread of resistant bacteria in both animals and people. Despite there being reportedly low levels of resistance currently seen in food-producing species,6 reductions in antimicrobial treatments will have a positive effect on reducing the levels of resistant bacteria that could end up in our shared environment.7 Mastitis is one of the major diseases affecting dairy production and is the leading cause of antibiotic use on dairy farms.8 Historically, mastitis treatment has been aimed at reducing somatic cell counts by following the five-point plan,9 which led to the promotion of blanket dry cow therapy.10 However, blanket treatments are contrary to the principles of responsible AMU, as set out by the World Health Organization.11 The UK dairy industry has recently seen a rise of 9 per cent in total AMU,6 so studies aimed at reducing use are welcome. To this end, the study by Schmenger and colleagues,12 summarised on p 401 of this issue of Vet Record , is an important addition to our knowledge. This study followed five German dairy farms over a period of two and …
Mapping destination images and behavioral patterns from user-generated photos: a computer vision approach

ABSTRACT Destination image studies were traditionally based on questionnaire surveys, but the recent rise of user-generated content and social media big data analytics provide new opportunities for advancing tourism research. This study adopts one of the latest artificial intelligence computer vision technologies to identify the differences in the perceived destination image and behavioral patterns between residents and tourists from user-generated photos. Data were mined from Flickr, which yields 58,392 relevant geotagged photos taken in Hong Kong. The findings reveal that the perceptual differences between the two groups lay on seven types of perceptions. The differences in spatial distribution and behavioral trajectory were visualized through a series of maps. This study provides new insights into the destination image which has implications for the tourism promotion and spatial development of the destination.
Succinic Semialdehyde Dehydrogenase Deficiency Severe Lactic Acidosis Associated with a Suspected Succinic Semialdehyde Dehydrogenase ( SSADH ) Deficiency in a Young Chihuahua Dog

Kelmer, E. ,1* Gibson, K.M. ,2 Jakobs, C. ,3 Struys, E. ,3 Shelton, G.D. ,4 Aroch, I.1 and O’Brien, D.P.5 1 Koret School of Veterinary Medicine, The Hebrew University of Jerusalem, P.O. Box 12, Rehovot, 761001, Israel. 2 Department of Experimental and Systems Pharmacology, College of Pharmacy, Washington State University, Spokane, WA, USA. 3 VU University Medical Center, NL-1007 MB Amsterdam, Netherlands. 4 Department of Pathology, School of Medicine, University of California, La Jolla, CA, USA. 5 Department of Veterinary Medicine and Surgery, University of Missouri-Columbia, Columbia, MO, USA.