Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the Evolution of Pandemic Influenza A(H1N1) Virus Neuraminidase Reveals Entanglement of Different Phenotypic Characteristics

Since its emergence in 2009, the pandemic H1N1 influenza A virus (IAV) has caused significant disease and mortality in humans. IAVs contain two envelope glycoproteins, the receptor-binding hemagglutinin (HA) and the receptor-destroying neuraminidase (NA). ABSTRACT The influenza A virus (IAV) neuraminidase (NA) is essential for virion release from cells and decoy receptors and an important target of antiviral drugs and antibodies. Adaptation to a new host sialome and escape from the host immune system are forces driving the selection of mutations in the NA gene. Phylogenetic analysis shows that until 2015, 16 amino acid substitutions in NA became fixed in the virus population after introduction in the human population of the pandemic IAV H1N1 (H1N1pdm09) in 2009. The accumulative effect of these substitutions, in the order in which they appeared, was analyzed using recombinant proteins and viruses in combination with different functional assays. The results indicate that NA activity did not evolve to a single optimum but rather fluctuated within a certain bandwidth. Furthermore, antigenic and enzymatic properties of NA were intertwined, with several residues affecting multiple properties. For example, the substitution K432E in the second sialic acid binding site, next to the catalytic site, was shown to affect catalytic activity, substrate specificity, and the pH optimum for maximum activity. This substitution also altered antigenicity of NA, which may explain its selection. We propose that the entanglement of NA phenotypes may be an important determining factor in the evolution of NA. IMPORTANCE Since its emergence in 2009, the pandemic H1N1 influenza A virus (IAV) has caused significant disease and mortality in humans. IAVs contain two envelope glycoproteins, the receptor-binding hemagglutinin (HA) and the receptor-destroying neuraminidase (NA). NA is essential for virion release from cells and decoy receptors, is an important target of antiviral drugs, and is increasingly being recognized as an important vaccine antigen. Not much is known, however, about the evolution of this protein upon the emergence of the novel pandemic H1N1 virus, with respect to its enzymatic activity and antigenicity. By reconstructing the evolutionary path of NA, we show that antigenic and enzymatic properties of NA are intertwined, with several residues affecting multiple properties. Understanding the entanglement of NA phenotypes will lead to better comprehension of IAV evolution and may help the development of NA-based vaccines.
Integrated profiling identifies ITGB3BP as prognostic biomarker for hepatocellular carcinoma

ABSTRACT Hepatocellular carcinoma (HCC) is a highly malignant tumor. In this study, we sought to identify a novel biomarker for HCC by analyzing transcriptome and clinical data. The R software was used to analyze the differentially expressed genes (DEGs) in the datasets GSE74656 and GSE84598 downloaded from the Gene Expression Omnibus database, followed by a functional annotation. A total of 138 shared DEGs were screened from two datasets. They were mainly enriched in the “Metabolic pathways” pathway (Padj = 8.21E-08) and involved in the carboxylic acid metabolic process (Padj = 0.0004). The top 10 hub genes were found by protein-protein interaction analysis and were upregulated in HCC tissues compared to normal tissues in The Cancer Genome Atlas database. Survival analysis distinguished 8 hub genes CENPE, SPDL1, Hyaluronan-mediated motility receptor, Rac GTPase activating protein 1, Thyroid hormone receptor interactor 13, cytoskeleton-associated protein (CKAP) 2, CKAP5, and Integrin subunit beta 3 binding protein (ITGB3BP) were considered as prognostic hub genes. Multivariate cox regression analysis indicated that all the prognostic hub genes were independent prognostic factors for HCC. Furthermore, the receiver operating characteristic curve revealed that the 8-hub genes model had better prediction performance for overall survival compared to the T stage (p = 0.008) and significantly improved the prediction value of the T stage (p = 0.002). The Human Protein Atlas showed that the protein expression of ITGB3BP was upregulated in HCC, so the expression of ITGB3BP was further verified in our cohort. The results showed that ITGB3BP was upregulated in HCC tissues and was significantly associated with lymph node metastasis.
Systems genetic analysis of binge‐like eating in a C57BL/6J x DBA/2J‐F2 cross

Binge eating is a heritable trait associated with eating disorders and refers to the rapid consumption of a large quantity of energy‐dense food that is, associated with loss of control and negative affect. Binge eating disorder is the most common eating disorder in the United States; however, the genetic basis is unknown. We previously identified robust mouse inbred strain differences between C57BL/6J and DBA/2J in binge‐like eating of sweetened palatable food in an intermittent access, conditioned place preference paradigm. To map the genetic basis of changes in body weight and binge‐like eating (BLE) and to identify candidate genes, we conducted quantitative trait locus (QTL) analysis in 128 C57BL/6J x DBA/2J‐F2 mice combined with PheQTL and trait covariance analysis in GeneNetwork2 using legacy BXD‐RI trait datasets. We identified a QTL on Chromosome 18 influencing changes in body weight across days in females (log of the odds [LOD] = 6.3; 1.5‐LOD: 3–12 cM) that contains the candidate gene Zeb1. We also identified a sex‐combined QTL influencing initial palatable food intake on Chromosome 5 (LOD = 5.8; 1.5‐LOD: 21–28 cM) that contains the candidate gene Lcorl and a second QTL influencing escalated palatable food intake on Chromosome 6 in males (LOD = 5.4; 1.5‐LOD: 50–59 cM) that contains the candidate genes Adipor2 and Plxnd1. Finally, we identified a suggestive QTL in females for slope of BLE on distal Chromosome 18 (LOD = 4.1; p = 0.055; 1.5‐LOD: 23–35 cM). Future studies will use BXD‐RI strains to fine map loci and support candidate gene nomination for gene editing.
Silver(I)‐N‐heterocyclic carbene complexes challenge cancer; evaluation of their anticancer properties and in silico studies

Because of the continuous need for efficient therapeutic agents against various kinds of cancers and infectious diseases, the pharmaceutical industry has to find new candidates and strategies to develop novel and efficient drugs. They increasingly use computational tools in R&D stages for screening extensive sets of drug candidates before starting pre‐clinical and clinical trials. N‐Heterocyclic carbenes (NHCs) can be evaluated as good drug candidates because they offer both anti‐cancer and anti‐inflammatory features with their general low‐toxicity profiles. To date, different kinds of NHCs (Cu, Co, Ni, Au, Ag, Ru, etc.) have been synthesized and their therapeutic uses has been shown. Here, we have reviewed the recent studies focused on Ag(I)‐NHC complexes and their anti‐cancer activities. Also, existing examples of the usage of density functional theory and structure–activity relationship have been evaluated.
Production of Flexible Transparent Conducting Films of Self‐Fused Nanowires via One‐Step Supersonic Spraying

Scalable and economical manufacturing of flexible transparent conducting films (TCF) is a key barrier to widespread adoption of low‐cost flexible electronics. Here, a simple, robust, and scalable method of flexible TCF formation using supersonic kinetic spraying is demonstrated. Silver nanowire (AgNW) suspensions are sprayed at supersonic speed to produce self‐sintered films of AgNWs on flexible substrates. These films display remarkably low sheet resistance, <10 Ω sq−1, combined with high transmittance, >90%. These electrically conducting, transparent, and flexible coatings can be deposited over a 100 cm2 area in ≈30 s. Theoretical analysis reveals the underlying physical mechanism behind self‐sintering, showing that self‐sintering is enabled by the high velocity of impact in supersonic spraying.
Discovering unknown human and mouse transcription factor binding sites and their characteristics from ChIP-seq data

Significance Transcription factor binding sites (TFBSs) are essential for gene regulation, but the majority of TFBSs remain unknown. To discover new TFBSs, we developed a computational pipeline to analyze human and mouse ChIP-seq (chromatin immunoprecipitation followed by sequencing) data. We found that the number of motif occurrences in ChIP-seq peaks is a highly effective quality-control criterion. Analyzing 1,089 human (101 mouse) TF experiments, we inferred 2,058 (163) motifs, including 487 previously unreported motifs, revealing predicted TFBS enrichment in promoters, particularly near transcription start sites. However, some TFs have TFBSs enriched in intergenic regions, including enhancers. We found frequent interactions between TFs, with a higher frequency of tethered binding than cobinding. This study provides many previously unreported TFBSs and describes their biological features. Transcription factor binding sites (TFBSs) are essential for gene regulation, but the number of known TFBSs remains limited. We aimed to discover and characterize unknown TFBSs by developing a computational pipeline for analyzing ChIP-seq (chromatin immunoprecipitation followed by sequencing) data. Applying it to the latest ENCODE ChIP-seq data for human and mouse, we found that using the irreproducible discovery rate as a quality-control criterion resulted in many experiments being unnecessarily discarded. By contrast, the number of motif occurrences in ChIP-seq peak regions provides a highly effective criterion, which is reliable even if supported by only one experimental replicate. In total, we obtained 2,058 motifs from 1,089 experiments for 354 human TFs and 163 motifs from 101 experiments for 34 mouse TFs. Among these motifs, 487 have not previously been reported. Mapping the canonical motifs to the human genome reveals a high TFBS density ±2 kb around transcription start sites (TSSs) with a peak at −50 bp. On average, a promoter contains 5.7 TFBSs. However, 70% of TFBSs are in introns (41%) and intergenic regions (29%), whereas only 12% are in promoters (−1 kb to +100 bp from TSSs). Notably, some TFs (e.g., CTCF, JUN, JUNB, and NFE2) have motifs enriched in intergenic regions, including enhancers. We inferred 142 cobinding TF pairs and 186 (including 115 completely) tethered binding TF pairs, indicating frequent interactions between TFs and a higher frequency of tethered binding than cobinding. This study provides a large number of previously undocumented motifs and insights into the biological and genomic features of TFBSs.
Left Ventricular Response to Cardiac Resynchronization Therapy: Insights From Hemodynamic Forces Computed by Speckle Tracking

Aims: Despite continuous efforts in improving the selection process, the rate of non-responders to cardiac resynchronization therapy (CRT) remains high. Recent studies on intraventricular blood flow suggested that the alignment of hemodynamic forces (HDFs) may be a reproducible biomarker of mechanical dyssynchrony. We aimed to explore the relationship between pacing-induced realignment of HDFs and positive response to CRT. Methods and results: We retrospectively analyzed 38 patients from the CRT database of our institution fulfilling the inclusion criteria for HDFs-related echocardiographic assessment early pre and post CRT implantation, with available mid-term follow-up (≥ 6 months) evaluation. Standard echocardiographic and deformation parameters early pre and post CRT implantation were integrated with the measurement of HFDs through novel methods based on speckle-tracking analysis. At midterm follow-up 71% of patients were classified as responders (reduction of Left Ventricular Systolic Volume Indexed ≥ 15%). Patients did not display significant changes between close evaluations pre and post-implant in terms of ejection fraction and strain metrics. A significant reduction of the ratio between the amplitudes of transversal and longitudinal force components was found. The variation of this ratio strongly correlates (R2 =0.60) with Left Ventricular (LV) end-systolic volume variation at mid-term follow up. Conclusion: Pacing-induced realignment of HDFs is associated with CRT efficacy at follow up. These preliminary results claim for dedicated prospective clinical studies testing the potential impact of HDFs study for patient selection and pacing optimization in CRT.
Electrochemical Model-Based State of Charge and State of Health Estimation of Lithium-Ion Batteries

Vehicle electrification continues to be a key topic of interest for automotive manufacturers, in an effort to reduce the usage of fossil fuel energy and improve vehicle efficiency. Lithium-ion batteries are currently the technology of choice for hybrid and electric vehicles due to their decreasing cost and improved power and energy density over traditional lead-acid or nickel-metal-hydride batteries. In particular, batteries with composite electrodes have seen increased use in automotive applications due to their ability to balance energy density, power density, and cost by adjusting the amount of each material within the electrode. However, this improved performance introduces new challenges to ensure the battery pack operates safely, reliably, and durably. The vehicle’s battery management system (BMS) is designed to meet these challenges, in part, by estimating the battery state of charge (SOC) and state of health (SOH). Knowledge of SOC allows the BMS to predict the available instantaneous power while ensuring the battery is operating within safe limits. As batteries age, they lose capacity and the ability to deliver power. Therefore, tracking the battery SOH is necessary to maintain accurate estimates of SOC and power throughout the battery life and give an accurate miles-to-empty metric to the driver. Recently, increased attention has been given to electrochemical models for SOC and SOH estimation, over traditional circuit models. Electrochemical models based on first principles have the potential to more accurately predict cell performance, as well as provide more information about the internal battery states. State of health estimation algorithms that do not use electrochemical-based models may have more
Resting‐state functional connectivity of the human hippocampus in periadolescent children: Associations with age and memory performance

The hippocampus is necessary for declarative (relational) memory, and the ability to form hippocampal‐dependent memories develops through late adolescence. This developmental trajectory of hippocampal‐dependent memory could reflect maturation of intrinsic functional brain networks, but resting‐state functional connectivity (rs‐FC) of the human hippocampus is not well‐characterized for periadolescent children. Measuring hippocampal rs‐FC in periadolescence would thus fill a gap, and testing covariance of hippocampal rs‐FC with age and memory could inform theories of cognitive development. Here, we studied hippocampal rs‐FC in a cross‐sectional sample of healthy children (N = 96; 59 F; age 9–15 years) using a seed‐based approach, and linked these data with NIH Toolbox measures, the Picture‐Sequence Memory Test (PSMT) and the List Sorting Working Memory Test (LSWMT). The PSMT was expected to rely more on hippocampal‐dependent memory than the LSWMT. We observed hippocampal rs‐FC with an extensive brain network including temporal, parietal, and frontal regions. This pattern was consistent with prior work measuring hippocampal rs‐FC in younger and older samples. We also observed novel, regionally specific variation in hippocampal rs‐FC with age and hippocampal‐dependent memory but not working memory. Evidence consistent with these findings was observed in a second, validation dataset of similar‐age healthy children drawn from the Philadelphia Neurodevelopment Cohort. Further, a cross‐dataset analysis suggested generalizable properties of hippocampal rs‐FC and covariance with age and memory. Our findings connect prior work by describing hippocampal rs‐FC and covariance with age and memory in typically developing periadolescent children, and our observations suggest a developmental trajectory for brain networks that support hippocampal‐dependent memory.
Leveraging Artificial Intelligence to Improve Chronic Disease Care: Methods and Application to Pharmacotherapy Decision Support for Type-2 Diabetes Mellitus

Abstract Objectives Artificial intelligence (AI), including predictive analytics, has great potential to improve the care of common chronic conditions with high morbidity and mortality. However, there are still many challenges to achieving this vision. The goal of this project was to develop and apply methods for enhancing chronic disease care using AI. Methods Using a dataset of 27,904 patients with diabetes, an analytical method was developed and validated for generating a treatment pathway graph which consists of models that predict the likelihood of alternate treatment strategies achieving care goals. An AI-driven clinical decision support system (CDSS) integrated with the electronic health record (EHR) was developed by encapsulating the prediction models in an OpenCDS Web service module and delivering the model outputs through a SMART on FHIR (Substitutable Medical Applications and Reusable Technologies on Fast Healthcare Interoperability Resources) web-based dashboard. This CDSS enables clinicians and patients to review relevant patient parameters, select treatment goals, and review alternate treatment strategies based on prediction results. Results The proposed analytical method outperformed previous machine-learning algorithms on prediction accuracy. The CDSS was successfully integrated with the Epic EHR at the University of Utah. Conclusion A predictive analytics-based CDSS was developed and successfully integrated with the EHR through standards-based interoperability frameworks. The approach used could potentially be applied to many other chronic conditions to bring AI-driven CDSS to the point of care.
An ECG method for positioning the tip of a PICC in “mirror people” with dextrocardia: A case report

Intracavitary electrocardiogram (ECG) has been widely used for PICC tip positioning in patients with a normal left heart. However, there is little information about using ECG for PICC insertion in patients with mirror dextrocardia. We report a 70-year-old stomach cancer patient with mirror dextrocardia admitted to our vascular access center for four Fr silicon Groshong PICC insertion. We successfully performed an ultrasound-guided modified Seldinger technique for insertion. First, the usual standardized ECG technique was used for tip positioning, and it failed. Then, we changed the procedure slightly, using the opposite electrode connections (RA: the first intercostal space of the midline of the left clavicle; LA: the first intercostal space of the midline of the right clavicle; and LL: the inferior margin of the right costal arch) to obtain an evident P-wave change to guide catheter placement in this case. We confirm that we can use the opposite electrodes to obtain an apparent P-wave for locating the catheter tip in patients with mirror dextrocardia.
Perturbed Microbiota/Immune Homeostasis in Multiple Sclerosis

Objective Based on animal models and human studies, there is now strong suspicion that host/microbiota mutualism in the context of gut microbial dysbiosis could influence immunity and multiple sclerosis (MS) evolution. Our goal was to seek evidence of deregulated microbiota-induced systemic immune responses in patients with MS. Methods We investigated gut and systemic commensal-specific antibody responses in healthy controls (n = 32), patients with relapsing-remitting MS (n = 30), and individuals with clinically isolated syndromes (CISs) (n = 15). Gut microbiota composition and diversity were compared between controls and patients by analysis of 16S ribosomal ribonucleic acid (rRNA) sequencing. Autologous microbiota and cultivable bacterial strains were used in bacterial flow cytometry assays to quantify autologous serum IgG and secretory IgA responses to microbiota. IgG-bound bacteria were sorted by flow cytometry and identified using 16S rRNA sequencing. Results We show that commensal-specific gut IgA responses are drastically reduced in patients with severe MS, disease severity being correlated with the IgA-coated fecal microbiota fraction (r = −0.647, p < 0.0001). At the same time, IgA-unbound bacteria elicit qualitatively broad and quantitatively increased serum IgG responses in patients with MS and CIS compared with controls (4.1% and 2.5% vs 1.9%, respectively, p < 0.001). Conclusions Gut and systemic microbiota/immune homeostasis are perturbed in MS. Our results argue that defective IgA responses in MS are linked to a breakdown of systemic tolerance to gut microbiota leading to an enhanced triggering of systemic IgG immunity against gut commensals occurring early in MS.
Experienced racism, attachment and the risk of offending among Dutch Caribbean women

Abstract Dutch Caribbean-born women form one of the largest female ethnic minority groups in the Netherlands and are overrepresented in Dutch crime statistics. Experienced racism has been shown to weaken bonds to society and has been linked to (female) offending among African Americans. In the Netherlands and across the Caribbean research on experienced racism and offending is scarce. The current study examines the relationship between self-reported offending, weakened attachments and experienced racism among 328 Dutch Caribbean-born women. Results show that more experienced racism is related to both weakened attachments as to higher rates of self-reported offending across the life course.
Accurate Determination and Comprehensive Evaluation of Heavy Metals in Different Soils from Jilin Province in Northeast China

Abstract To provide technical support and theoretical guarantee for the prevention and control of soil heavy metal pollution, the main types of topsoil and parent material in Jilin Province were systematically collected, accurately tested by atomic fluorescence spectrometry and inductively coupled plasma mass spectrometry, and comprehensively evaluated through five indexes. By principal component analysis, it was initially judged that there were 2 or 3 major heavy metal sources in topsoil, which could be attributed to the parent material, soil-forming process, and/or anthropogenic factor. The pH of surface soil mainly depended on its parent material, and changed to a certain extent during its formation. The contents of heavy metals As, Hg, Cd, Cr, Cu, Ni, Pb, and Zn in surface soils were both significantly influenced by parent materials and soil-forming processes. Here the geo-accumulation index calculated by corresponding background value of parent material was more suitable for pollution assessment than the other four indexes, and the heavy metal contamination degree in each type of soil basically followed the order: Hg > Cd > Cu, Pb, Zn, As > Cr, Ni. Furthermore, the heavy metal contamination level in the types of soils was ranked as follows: cambisol, phaeozem > podzol, planosol > chernozem. The health risk assessment indicated that the soil in the study area had no significant carcinogenic or non-carcinogenic risks. Excluding the influence of parent material and soil-formation process, the comprehensive evaluation of soil heavy metal pollution will be more reasonable.