Miracle-dz/UniFAR-FTUs huggingface dataset:
Preliminary Assessment of a Microwave System to Detect Contrast Enhancing Agents

This paper presents a preliminary study of the impact of potential contrast enhancing agents on a 2-port microwave imaging system. To this end, we have conducted microwave measurements inside a dual cylindrical tank, comprised of an outer and inner cylinder filled with high and low loss liquids, respectively. A third smaller cylinder inside the low loss filled tank represents a target. The target materials consisted of safflower oil, water, PEGylated zinc oxide nanoparticles dispersed in water, and saline with varying concentrations of salt. To benchmark our experimental results, we have also performed accurate numerical simulations of the system under three target scenarios: safflower oil, water, and PEGylated zinc oxide suspension. Our results show that the difference in received signal strength in scenarios with and without PEGylated zinc oxide nanoparticles in our 2-port system was comparable to measurement error. However, with the use of varying concentrations of saline solutions as a target, we have observed a significant difference in received signal strength.
A no-regret generalization of hierarchical softmax to extreme multi-label classification

Extreme multi-label classification (XMLC) is a problem of tagging an instance with a small subset of relevant labels chosen from an extremely large pool of possible labels. Large label spaces can be efficiently handled by organizing labels as a tree, like in the hierarchical softmax (HSM) approach commonly used for multi-class problems. In this paper, we investigate probabilistic label trees (PLTs) that have been recently devised for tackling XMLC problems. We show that PLTs are a no-regret multi-label generalization of HSM when precision@$k$ is used as a model evaluation metric. Critically, we prove that pick-one-label heuristic---a reduction technique from multi-label to multi-class that is routinely used along with HSM---is not consistent in general. We also show that our implementation of PLTs, referred to as extremeText (XT), obtains significantly better results than HSM with the pick-one-label heuristic and XML-CNN, a deep network specifically designed for XMLC problems. Moreover, XT is competitive to many state-of-the-art approaches in terms of statistical performance, model size and prediction time which makes it amenable to deploy in an online system.
Cortical Brain Stimulation with Endovascular Electrodes

Electrical stimulation of neural tissue and recording of neural activity are the bases of emerging prostheses and treatments for spinal cord injury, stroke, sensory deficits, and drug-resistant neurological disorders. Safety and efficacy are key aspects for the clinical acceptance of therapeutic neural stimulators. The cortical vasculature has been shown to be a safe site for implantation of electrodes for chronically recording neural activity, requiring no craniotomy to access high-bandwidth, intracranial EEG. This work presents the first characterization of endovascular cortical stimulation measured using cortical subdural surface recordings. Visual stimulation was used to verify electrode viability and cortical activation was compared with electrically evoked activity. Due to direct activation of the neural tissue, the latency of responses to electrical stimulation was shorter than for that of visual stimulation. We also found that the center of neural activation was different for visual and electrical stimulation indicating an ability of the stentrode to provide localized activation of neural tissue.
Regulation of Nuclear Factor Kappa-Light-Chain-Enhancer of Activated B Cells (NF-κβ) in Inflammatory Bowel Diseases

Inflammatory bowel diseases (IBD), encompassing both Crohn Disease (CD) and ulcerative colitis (UC) are globally prevalent diseases, impacting children of all ages. The hallmark of IBD is a perturbed immune system that leads to continuous inflammation in the gut and challenges optimal treatment. Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κβ), a nuclear transcription factor, plays a major role in gut homeostasis and contributes significantly toward a balanced, homeostatic immune system. Dysregulation in the NF-κβ pathway and factors that regulate it lead to a state of uncontrolled inflammation and altered immunity, as typically observed in IBD. Levels of proinflammatory cytokines that are regulated through NF-κβ are increased in both CD and UC. Genes known to activate NF-κβ, such as, Nucleotide-binding oligomerization domain-containing protein 2 (NOD2) and Interleukin 23 (IL-23), are associated with IBD. Factors involved in inhibition of NF-κβ, such as A20 and TOLLIP, are also affected in IBD, resulting in failed inflammation suppression/regulation. NOD-2 and A20 have specifically been found to be strongly associated with pediatric IBD. Gut commensals are known to exert anti-inflammatory activities toward NF-κβ and can have a potential role in attenuating inflammation that likely occurs due to microbial dysbiosis in IBD. Failure to terminate/downregulate NF-κβ signaling results in chronic inflammation in IBD. Well-regulated control of inflammation in children with IBD can help better control the disease and suppress immune responses. Better understanding of factors that control NF-κβ can potentially lead toward discovering targeted therapeutic interventions for IBD. Suppression of NF-κβ can be achieved through many modalities including anti-sense oligonucleotides (ASOs), siRNA (small interfering RNA), factors regulating NF-κβ, and microbes. This review focuses on the role of NF-κβ, especially in pediatric IBD, and potential therapeutic venues for attenuating NF-κβ-induced inflammation.
Machine Learning in Human Olfactory Research

Abstract The complexity of the human sense of smell is increasingly reflected in complex and high-dimensional data, which opens opportunities for data-driven approaches that complement hypothesis-driven research. Contemporary developments in computational and data science, with its currently most popular implementation as machine learning, facilitate complex data-driven research approaches. The use of machine learning in human olfactory research included major approaches comprising 1) the study of the physiology of pattern-based odor detection and recognition processes, 2) pattern recognition in olfactory phenotypes, 3) the development of complex disease biomarkers including olfactory features, 4) odor prediction from physico-chemical properties of volatile molecules, and 5) knowledge discovery in publicly available big databases. A limited set of unsupervised and supervised machine-learned methods has been used in these projects, however, the increasing use of contemporary methods of computational science is reflected in a growing number of reports employing machine learning for human olfactory research. This review provides key concepts of machine learning and summarizes current applications on human olfactory data.
Comparison of hemodynamic parameters that can predict an aneurysmal rupture: 20 patient-specific models experiment

Hemodynamic analysis of cerebral aneurysms is widely performed to understand the mechanism of aneurysmal rupture. Computational fluid dynamics (CFD) studies have suggested that several hemodynamic parameters are associated with such ruptures. However, a number of factors remain to be addressed to correlate these parameters with aneurysmal ruptures, especially under analytical conditions. Specifically, CFD analysis is often performed with rigid wall models due to computational cost limitations. Here, to evaluate the effects of the deformation of the aneurysmal wall, experimental flow measurement with elastic models under pulsating conditions was conducted using three-dimensional particle image velocimetry (3D PIV). By analyzing 20 patient-specific, elastic, silicone aneurysm models, the hemodynamic parameters of ruptured and unruptured aneurysms were statistically compared to identify the variables that can effectively predict an aneurysmal rupture. Our analyses yielded three parameters (average wall shear stress ratio, in-phase deviation ratio, and pressure difference) which could effectively predict an aneurysmal rupture. These results suggested that measurement of wall shear stress (WSS) at both the aneurysm dome and parent artery is important and that pressure difference can also be a potential indicator of aneurysmal rupture.
Prediction of Ion Channels and their Types from Protein Sequences: Comprehensive Review and Comparative Assessment.

BACKGROUND Ion channels are a large and growing protein family. Many of them are associated with diseases, and consequently, they are targets for over 700 drugs. Discovery of new ion channels is facilitated with computational methods that predict ion channels and their types from protein sequences. However, these methods were never comprehensively compared and evaluated. OBJECTIVE We offer first-of-its-kind comprehensive survey of the sequence-based predictors of ion channels. We describe eight predictors that include five methods that predict ion channels, their types, and four classes of the voltage-gated channels. We also develop and use a new benchmark dataset to perform comparative empirical analysis of the three currently available predictors. RESULTS While several methods that rely on different designs were published, only a few of them are currently available and offer a broad scope of predictions. Support and availability after publication should be required when new methods are considered for publication. Empirical analysis shows strong performance for the prediction of ion channels and modest performance for the prediction of ion channel types and voltage-gated channel classes. We identify a substantial weakness of current methods that cannot accurately predict ion channels that are categorized into multiple classes/types. CONCLUSION Several predictors of ion channels are available to the end users. They offer practical levels of predictive quality. Methods that rely on a larger and more diverse set of predictive inputs (such as PSIONplus) are more accurate. New tools that address multi-label prediction of ion channels should be developed.
Remnant Lipoprotein Cholesterol and Cardiovascular and Cerebrovascular Events in Patients with Non-Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) is characterized by an atherogenic dyslipidaemia and an increased cardiovascular risk. Remnant lipoprotein cholesterol (RLP-C) is emerging as a novel cardiovascular risk factor, but its predictive value in patients with NAFLD is unknown. We investigated factors affecting RLP-C levels, and the association with major adverse cardiovascular and cerebrovascular events (MACCE) in NAFLD. A prospective observational cohort study was carried out including 798 unselected patients with cardio-metabolic diseases screened by ultrasound for the presence of NAFLD. Fasting RLP-C (mg/dL) was calculated as total cholesterol—(HDL (high-density lipoprotein) + LDL (low-density-lipoprotein)). Primary endpoint of the follow-up study was a combined endpoint of MACCE. Patients with NAFLD (79.2%) had higher median fasting RLP-C in comparison to those without (27.0 vs. 20.0 mg/dL, respectively p < 0.001). Metabolic syndrome, NAFLD, age above median, and female sex were independently associated to fasting RLP-C above the median. In patients with NAFLD, values of RLP-C were associated with liver disease severity, as shown by the increasing value of RLP-C across tertiles of aspartate aminotransferase (AST) (p = 0.002) and gamma-glutamyl transpeptidase (GGT) (p < 0.001). Furthermore, levels of RLP-C and Hamaguchi score, were significantly correlated (r = 0.193, p < 0.001). During a median follow-up of 32 months (interquartile range: 14.2–51.7, 1700 person-years), 41 MACCE (2.41%/year) were registered in 596 NAFLD patients. The rate of events was higher in NAFLD patients with RLP-C above the median compared to those below (log-rank test p = 0.040). Age (hazard ratio (HR) 1.039, 95% confidence interval (CI), 1.005–1.074, p = 0.024), previous cardiovascular events (HR 2.210, 95% CI, 1.052–4.643, p = 0.036), female sex (HR 0.454, 95% CI, 0.208–0.989, p = 0.047) and RLP-C above the median (HR 2.202, 95% CI, 1.132–4.285, p = 0.020) were associated with MACCE. In conclusion, we found that NAFLD was independently associated with higher circulating RLP-C, and that high RLP-C levels were predictive of MACCE in patients with NAFLD.
Autism spectrum disorder (ASD) in girls. Co-occurring psychopathology. Sex differences in clinical manifestation.

OBJECTIVES The study aims to define the differences in clinical manifestation among adolescent girls and boys with autism spectrum disorder (ASD). METHODS The study group consisted of 15 adolescent girls and 16 adolescent boys with diagnosis of autismor Asperger syndrome and their parents. Adolescents were assessed with ADOS (Autism Diagnostic Observation Schedule, Polish adaptation of the assessment), algorithms of ADOS and ADOS-2 (revised version) were compared. Structured interview was conducted with parents, they fulfilled AQ (Autism Quotient), ASAS (Australian Scale for Asperger Syndrome), GQ-ASC (Girls' Questionnaire for Autism Spectrum Conditions). Medical records were analyzed. Results were analyzed using statistical methods. RESULTS Patients were assessed with ADOS Module 4. Results indicated statistically significant differences between ASD girls and ASD boys in communication section, both verbal and gestures. The mean scores of AQ for ASD girls and ASD boys were M = 33.0 and M=30.9, and of ASAS M =57% and M =61% respectively. ASD girls had more psychiatric hospitalisations than ASD boys (60% vs. 31%), and they were more often treated with antidepressants (67% vs. 31%), anxiolytics (20% vs. 6%), mood stabilizers (40% vs. 19%). ASD boys were more often treated with psychotropic medications (50% vs. 47%) and stimulants (44% vs. 20%) than ASD girls. CONCLUSIONS ASD girls are at risk of receiving non-spectrum classification in ADOS or ADOS-2 while their developmental history and clinical manifestation confirm ASD. Clinical data suggests that ASD girls present more abnormalities in sensory profile. ASD girls are at greater risk for developing anxiety, depression, suicidal ideation, and for psychiatric hospitalization. ASD boys appear to be at greater risk for co-occurring ADHD, OCD and tics.
They’re Doing What? A Brief Paper on Service Use and Attitudes in ASD Community-Based Agencies

ABSTRACT This brief article examines the community services delivered to youth with autism spectrum disorder (ASD) in a Southern Californian city as a way to better understand ASD service provision and service attitudes. Specific goals of the study were to identify the services being delivered within the area, and how the use, perceived evidence, and value attached to these services mapped onto recent systematic ASD service reviews. Forty-six providers completed the ASD Strategies and Interventions Survey (ASD-SIS), which consisted of 21 treatment strategies and 22 interventions packages commonly used with children with ASD. Participants: (1) indicated each treatment strategy and intervention package they use, and (2) rated the perceived evidence and value of each treatment strategy and intervention package they endorsed using. Results demonstrated that a variety of treatment strategies and intervention packages, both with and without an established evidence base, were reportedly being delivered to youth with ASD through community-based agencies. Additionally, a large number of providers reported not knowing the evidence of many treatment strategies and intervention packages. Finally, although no relationship was found between evidence base and use, perceived evidence, and value for treatment strategies, providers reported significantly higher use, perceived evidence, and value for established intervention packages. Results demonstrate the need to more effectively disseminate strategies that can support providers in selecting services to deliver to youth with ASD, and underscore the need to better understand the community service landscape on a larger scale.
MiR‐448‐5p inhibits TGF‐β1‐induced epithelial‐mesenchymal transition and pulmonary fibrosis by targeting Six1 in asthma

MicroRNAs (miRNAs) are small yet versatile gene tuners that regulate a variety of cellular processes, including cell growth and proliferation. The aim of this study was to explore how miR‐448‐5p affects airway remodeling and transforming growth factor‐β1 (TGF‐β1)‐stimulated epithelial‐mesenchymal transition (EMT) by targeting Sine oculis homeobox homolog 1 (Six1) in asthma. Asthmatic mice models with airway remodeling were induced with ovalbumin solution. MiRNA expression was evaluated using quantitative real‐time polymerase chain reaction. Transfection studies of bronchial epithelial cells were performed to determine the target genes. A luciferase reporter assay system was applied to identify whether Six1 is a target gene of miR‐448‐5p. In the current study, we found that miR‐448‐5p was dramatically decreased in lung tissues of asthmatic mice and TGF‐β1‐stimulated bronchial epithelial cells. In addition, the decreased level of miR‐448‐5p was closely associated with the increased expression of Six1. Overexpression of miR‐448‐5p decreased Six1 expression and, in turn, suppressed TGF‐β1‐mediated EMT and fibrosis. Next, we predicted that Six1 was a potential target gene of miR‐448‐5p and demonstrated that miR‐448‐5p could directly target Six1. An SiRNA targeting Six1 was sufficient to suppress TGF‐β1‐induced EMT and fibrosis in 16HBE cells. Furthermore, the overexpression of Six1 partially reversed the protective effect of miR‐448‐5p on TGF‐β1‐mediated EMT and fibrosis in bronchial epithelial cells. Taken together, the miR‐448‐5p/TGF‐β1/Six1 link may play roles in the progression of EMT and pulmonary fibrosis in asthma.
Altered Levels of Long NcRNAs Meg3 and Neat1 in Cell And Animal Models Of Huntington’s Disease

ABSTRACT Altered expression levels of protein-coding genes and microRNAs have been implicated in the pathogenesis of Huntington’s disease (HD). The involvement of other ncRNAs, especially long ncRNAs (lncRNA), is being realized recently and the related knowledge is still rudimentary. Using small RNA sequencing and PCR arrays we observed perturbations in the levels of 12 ncRNAs in HD mouse brain, eight of which had human homologs. Of these, Meg3, Neat1, and Xist showed a consistent and significant increase in HD cell and animal models. Transient knock-down of Meg3 and Neat1 in cell models of HD led to a significant decrease of aggregates formed by mutant huntingtin and downregulation of the endogenous Tp53 expression. Understanding Meg3 and Neat1 functions in the context of HD pathogenesis is likely to open up new strategies to control the disease.
Molecular and Microbiological Insights on the Enrichment Procedures for the Isolation of Petroleum Degrading Bacteria and Fungi

Autochthonous bioaugmentation, by exploiting the indigenous microorganisms of the contaminated environment to be treated, can represent a successful bioremediation strategy. In this perspective, we have assessed by molecular methods the evolution of bacterial and fungal communities during the selective enrichment on different pollutants of a soil strongly polluted by mixtures of aliphatic and polycyclic hydrocarbons. Three consecutive enrichments were carried out on soil samples from different soil depths (0–1, 1–2, 2–3 m), and analyzed at each step by means of high-throughput sequencing of bacterial and fungal amplicons biomarkers. At the end of the enrichments, bacterial and fungal contaminants degrading strains were isolated and identified in order to (i) compare the composition of enriched communities by culture-dependent and culture-independent molecular methods and to (ii) obtain a collection of hydrocarbon degrading microorganisms potentially exploitable for soil bioremediation. Molecular results highlighted that for both bacteria and fungi the pollutant had a partial shaping effect on the enriched communities, with paraffin creating distinct enriched bacterial community from oil, and polycyclic aromatic hydrocarbons generally overlapping; interestingly neither the soil depth or the enrichment step had significant effects on the composition of the final enriched communities. Molecular analyses well-agreed with culture-dependent analyses in terms of most abundant microbial genera. A total of 95 bacterial and 94 fungal strains were isolated after selective enrichment procedure on different pollutants. On the whole, isolated bacteria where manly ascribed to Pseudomonas genus followed by Sphingobacterium, Bacillus, Stenothrophomonas, Achromobacter, and Serratia. As for fungi, Fusarium was the most abundant genus followed by Trichoderma and Aspergillus. The species comprising more isolates, such as Pseudomonas putida, Achromobacter xylosoxidans and Ochromobactrum anthropi for bacteria, Fusarium oxysporum and Fusarium solani for fungi, were also the dominant OTUs assessed in Illumina.
Suicide and Youth: Risk Factors

Suicide occurs more often in older than in younger people, but is still one of the leading causes of death in late childhood and adolescence worldwide. This not only results in a direct loss of many young lives, but also has disruptive psychosocial and adverse socio-economic effects. From the perspective of public mental health, suicide among young people is a main issue to address. Therefore we need good insight in the risk factors contributing to suicidal behavior in youth. This mini review gives a short overview of the most important risk factors for late school-age children and adolescents, as established by scientific research in this domain. Key risk factors found were: mental disorders, previous suicide attempts, specific personality characteristics, genetic loading and family processes in combination with triggering psychosocial stressors, exposure to inspiring models and availability of means of committing suicide. Further unraveling and knowledge of the complex interplay of these factors is highly relevant with regard to the development of effective prevention strategy plans for youth suicide.