Miracle-dz/UniFAR-FTUs huggingface dataset:
Ab Initio Molecular Dynamics Study of Methanol-Water Mixtures under External Electric Fields

Intense electric fields applied on H-bonded systems are able to induce molecular dissociations, proton transfers, and complex chemical reactions. Nevertheless, the effects induced in heterogeneous molecular systems such as methanol-water mixtures are still elusive. Here we report on a series of state-of-the-art ab initio molecular dynamics simulations of liquid methanol-water mixtures at different molar ratios exposed to static electric fields. If, on the one hand, the presence of water increases the proton conductivity of methanol-water mixtures, on the other, it hinders the typical enhancement of the chemical reactivity induced by electric fields. In particular, a sudden increase of the protonic conductivity is recorded when the amount of water exceeds that of methanol in the mixtures, suggesting that important structural changes of the H-bond network occur. By contrast, the field-induced multifaceted chemistry leading to the synthesis of e.g., hydrogen, dimethyl ether, formaldehyde, and methane observed in neat methanol, in 75:25, and equimolar methanol-water mixtures, completely disappears in samples containing an excess of water and in pure water. The presence of water strongly inhibits the chemical reactivity of methanol.
Intensive monitoring of adverse drug reactions to antipsychotic medications in the inpatient psychiatry department of a secondary care hospital of UAE

Background: Antipsychotics are a class of medications used primarily for the treatment of psychotic disorders. However, these medications are associated with potential adverse drug reactions (ADRs). Aim: To monitor the incidence and nature of ADRs in the psychiatric inpatient department of a secondary care hospital of Ras Al Khaimah, UAE. Materials and Methods: This was an observational, prospective, noninterventional study, conducted in the psychiatric inpatient setting of a secondary care hospital. Psychiatric inpatients of all age groups and both the gender, diagnosed with any psychotic disorder, and hospitalized in the psychiatry ward and managed with at least one antipsychotic medication were included in the study. The causality, severity, and preventability of ADRs were assessed using different assessment scales. Results: Out of 170 patients, 38 patients reported at least one ADR with an incidence rate of 22.3%. The most common ADRs were weight gain 15 (29.4%) due to olanzapine, followed by pseudo-parkinsonism 11 (21.6%) due to parenteral haloperidol. Schizophrenia (18, 35.3%), followed by bipolar I disorder (10, 19.6%) was the most common condition associated with ADRs. Female gender and duration of hospital stay were found to be significant (P < 0.05) predictors of occurrence of ADRs. Conclusion: A high incidence of ADRs was observed in the inpatients of psychiatry department, especially of mild nature and probably preventable types. The study highlights the importance of intensive monitoring by pharmacists to identify high ADR risk psychiatric inpatients. To reduce the ADR risk, specific and frequent monitoring for antipsychotics is recommended such as weight and extrapyramidal symptoms.
Markers Useful in Monitoring Radiation-Induced Lung Injury in Lung Cancer Patients: A Review

In 2018, lung cancer was the most common cancer and the most common cause of cancer death, accounting for a 1.76 million deaths. Radiotherapy (RT) is a widely used and effective non-surgical cancer treatment that induces remission in, and even cures, patients with lung cancer. However, RT faces some restrictions linked to the radioresistance and treatment toxicity, manifesting in radiation-induced lung injury (RILI). About 30–40% of lung cancer patients will develop RILI, which next to the local recurrence and distant metastasis is a substantial challenge to the successful management of lung cancer treatment. These data indicate an urgent need of looking for novel, precise biomarkers of individual response and risk of side effects in the course of RT. The aim of this review was to summarize both preclinical and clinical approaches in RILI monitoring that could be brought into clinical practice. Next to transforming growth factor-β1 (TGFβ1) that was reported as one of the most important growth factors expressed in the tissues after ionizing radiation (IR), there is a group of novel, potential biomarkers—microRNAs—that may be used as predictive biomarkers in therapy response and disease prognosis.
THE SKELETAL ANATOMY AND RELATIONSHIPS OF A NEW DISCOSAURISCID SEYMOURIAMORPH FROM THE LOWER PERMIAN OF MORAVIA (CZECH REPUBLIC)

Abstract A new genus and species of seymouriamorph tetrapod from the Lower Permian deposits of the Boskovice Furrow in Moravia (Czech Republic), Spinarerpeton brevicephalum, new genus, new species, is described in detail, and its cranial reconstruction and phylogenetic position within seymouriamorphs is presented. The skeletal anatomy of Spinarerpeton allows this new taxon to be assigned to the family Discosauriscidae (together with Discosauriscus Kuhn, 1933, Makowskia Klembara, 2005, and Ariekanerpeton Ivakhnenko, 1981). It is distinguished from other ? Uppermost Carboniferous-Lower Permian seymouriamorphs, Utegenia Kuznetsov and Ivachnenko, 1981, Ariekanerpeton, Discosauriscus, Makowskia, and Seymouria Broili, 1904, by the following characters: postorbital portion of skull short; postparietal and tabular abbreviated anteroposteriorly; posterior process of jugal long; squamosal high (posterior portion of cheek deep); basioccipital wide and with anteroposteriorly long bilateral processes; exoccipital high and with slender shaft; anterior margin of iliac blade running obliquely anteroventrally to posterodorsally. A phylogenetic analysis places Spinarerpeton as the sister taxon to the Lower Permian Makowskia within the Discosauriscidae.
The Great War of Today: Modifications of CAR-T Cells to Effectively Combat Malignancies

Immunotherapy of cancer had its early beginnings in the times when the elements of the immune system were still poorly characterized. However, with the progress in molecular biology, it has become feasible to re-engineer T cells in order to eradicate tumour cells. The use of synthetic chimeric antigen receptors (CARs) helped to re-target and simultaneously unleash the cytotoxic potential of T cells. CAR-T therapy proved to be remarkably effective in cases of haematological malignancies, often refractory and relapsed. The success of this approach yielded two Food and Drug Administration (FDA) approvals for the first “living drug” modalities. However, CAR-T therapy is not without flaws. Apart from the side effects associated with the treatment, it became apparent that CAR introduction alters T cell biology and the possible therapeutic outcomes. Additionally, it was shown that CAR-T approaches in solid tumours do not recapitulate the success in the haemato-oncology. Therefore, in this review, we aim to discuss the recent concerns of CAR-T therapy for both haematological and solid tumours. We also summarise the general strategies that are implemented to enhance the efficacy and safety of the CAR-T regimens in blood and solid malignancies.
Modeling motivation for alcohol in humans using traditional and machine learning approaches

Given the significant cost of alcohol use disorder (AUD), identifying risk factors for alcohol seeking represents a research priority. Prominent addiction theories emphasize the role of motivation in the alcohol seeking process, which has largely been studied using preclinical models. In order to bridge the gap between preclinical and clinical studies, this study examined predictors of motivation for alcohol self‐administration using a novel paradigm. Heavy drinkers (n = 67) completed an alcohol infusion consisting of an alcohol challenge (target breath alcohol = 60 mg%) and a progressive‐ratio alcohol self‐administration paradigm (maximum breath alcohol 120 mg%; ratio requirements range = 20–3 139 response). Growth curve modeling was used to predict breath alcohol trajectories during alcohol self‐administration. K‐means clustering was used to identify motivated (n = 41) and unmotivated (n = 26) self‐administration trajectories. The data were analyzed using two approaches: a theory‐driven test of a‐priori predictors and a data‐driven, machine learning model. In both approaches, steeper delay discounting, indicating a preference for smaller, sooner rewards, predicted motivated alcohol seeking. The data‐driven approach further identified phasic alcohol craving as a predictor of motivated alcohol self‐administration. Additional application of this model to AUD translational science and treatment development appear warranted.
Sans Forgetica is not desirable for learning

ABSTRACT Do students learn better with material that is perceptually hard to process? While evidence is mixed, recent claims suggest that placing materials in Sans Forgetica, a perceptually difficult-to-process typeface, has positive impacts on student learning. Given the weak evidence for other similar perceptual disfluency effects, we examined the mnemonic effects of Sans Forgetica more closely in comparison to other learning strategies across three preregistered experiments. In Experiment 1, participants studied weakly related cue-target pairs with targets presented in either Sans Forgetica or with missing letters (e.g., cue: G_RL, the generation effect). Cued recall performance showed a robust effect of generation, but no Sans Forgetica memory benefit. In Experiment 2, participants read an educational passage about ground water with select sentences presented in either Sans Forgetica typeface, yellow pre-highlighting, or unmodified. Cued recall for select words was better for pre-highlighted information than an unmodified pure reading condition. Critically, presenting sentences in Sans Forgetica did not elevate cued recall compared to an unmodified pure reading condition or a pre-highlighted condition. In Experiment 3, individuals did not have better discriminability for Sans Forgetica relative to a fluent condition in an old-new recognition test. Our findings suggest that Sans Forgetica really is forgettable.
Harvesting Devices’ Heterogeneous Energy Profiles and QoS Requirements in IoT: WPT-NOMA vs BAC-NOMA

The next generation Internet of Things (IoT) exhibits a unique feature that IoT devices have different energy profiles and quality of service (QoS) requirements. In this paper, two energy and spectrally efficient transmission strategies, namely wireless power transfer assisted non-orthogonal multiple access (WPT-NOMA) and backscatter communication (Back-Com) assisted NOMA (BAC-NOMA), are proposed by utilizing this feature of IoT and employing spectrum and energy cooperation among the devices. In particular, the use of NOMA ensures that the devices with different QoS requirements can share the same spectrum, and WPT and Back-Com are employed to utilize the cooperation among the devices with different energy profiles, which avoids the use of a dedicated power beacon. Furthermore, for the proposed WPT-NOMA scheme, the application of hybrid successive interference cancelation (SIC) decoding order is also considered, and analytical results are developed to demonstrate that WPT-NOMA can avoid outage probability error floors and realize the full diversity gain. Unlike WPT-NOMA, BAC-NOMA suffers from an outage probability error floor, and the asymptotic behavior of this error floor is analyzed in the paper by applying the extreme value theory. In addition, the effect of a unique feature of BAC-NOMA, i.e., employing one device’s signal as the carrier signal for another device, is studied, and its impact on the diversity gain is revealed. Simulation results are also provided to compare the performance of the proposed strategies and verify the developed analytical results.
Ultra-Short Circulating Tumor DNA (usctDNA) in Plasma and Saliva of Non-Small Cell Lung Cancer (NSCLC) Patients

Mutations identified in the epidermal growth factor receptor (EGFR) predict sensitivity to EGFR-targeted therapy for non-small cell lung carcinoma (NSCLC). We previously reported that Electric Field-Induced Release and Measurement (EFIRM)-based liquid biopsy could detect EGFR ctDNA with >94% concordance with tissue-based genotyping. A side-by-side comparison of concordance of EFIRM and droplet digital PCR (ddPCR) for the detection of the two front-line actionable EFGR mutations was performed with paired plasma and saliva samples from 13 NSCLC patients. Deep sequencing analysis based on single-strand DNA library preparation was employed to determine the size distributions of EGFR L858R ctDNA in plasma and saliva samples. EFIRM detected both EGFR mutations with 100% sensitivity in both plasma and saliva samples, whereas ddPCR detected EGFR mutations with sensitivities of 84.6% and 15.4%, respectively. In saliva samples, the majority of EGFR L858R ctDNA fragments detected were <80 bp. Deep sequencing analysis of ctDNA enriched for the EGFR L858R mutation revealed the significant presence of EGFR L858R ctDNA as ultra-short circulating tumor DNA (usctDNA) with the size of 40–60 bp in patient plasma and saliva. Most of usctDNAs are not amplifiable with the current ddPCR assay. Further examination using cell lines and patient biofluids revealed that the majority of usctDNAs were predominately localized in the exosomal fraction. Our study revealed the abundant existence of EGFR ctDNA in the plasma and saliva of NSCLC patients is usctDNA. usctDNA is a novel type of targets for liquid biopsy that can be efficiently detected by EFIRM technology.
Review of Big Data Analytics, Artificial Intelligence and Nature-Inspired Computing Models towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing

The emergence of the 2019 novel coronavirus (COVID-19) which was declared a pandemic has spread to 210 countries worldwide. It has had a significant impact on health systems and economic, educational and social facets of contemporary society. As the rate of transmission increases, various collaborative approaches among stakeholders to develop innovative means of screening, detecting and diagnosing COVID-19’s cases among human beings at a commensurate rate have evolved. Further, the utility of computing models associated with the fourth industrial revolution technologies in achieving the desired feat has been highlighted. However, there is a gap in terms of the accuracy of detection and prediction of COVID-19 cases and tracing contacts of infected persons. This paper presents a review of computing models that can be adopted to enhance the performance of detecting and predicting the COVID-19 pandemic cases. We focus on big data, artificial intelligence (AI) and nature-inspired computing (NIC) models that can be adopted in the current pandemic. The review suggested that artificial intelligence models have been used for the case detection of COVID-19. Similarly, big data platforms have also been applied for tracing contacts. However, the nature-inspired computing (NIC) models that have demonstrated good performance in feature selection of medical issues are yet to be explored for case detection and tracing of contacts in the current COVID-19 pandemic. This study holds salient implications for practitioners and researchers alike as it elucidates the potentials of NIC in the accurate detection of pandemic cases and optimized contact tracing.
A test of the instream flow incremental methodology for underyearling rainbow trout, Salmo gairdnerii, in experimental New Zealand streams

Abstract The instream flow incremental methodology predicts the potential amount of habitat in a stream, rather than fish biomass or numbers. We introduced rainbow trout into stream channels next to the Waitaki River, South Island, New Zealand, and subsequently maintained a constant flow in these streams. The biomass of rainbow trout in individual riffles and pools of the streams was determined and related to the amount of usable area in these habitats calculated using the incremental methodology. Regardless of fish stocking density, rainbow trout biomass in late summer and early winter was not correlated with the amount of usable habitat. Users of the incremental methodology should realise that the method cannot be expected to predict fish biomass or numbers when fish are not limited by the amount of space available to them. When fish are food‐limited, as apparently occurred in our streams, relationships between usable area, fish food organisms, and fish biomass must be understood before one can predict .
Flat Foot and Postural Harmony in 6-Year-Old Caucasians: What is Their Relationship?

Objective To determine whether asymptomatic flexible flat feet show specific postural assessment with respect to neutral feet in 6-year-old children. Methods In this cross-sectional observational study, 164 subjects were observed and divided into two groups: 57 with flexible flat feet and 107 with neutral feet. A non-quantitative inspection by podoscopy and baropodometry were performed to evaluate plantar support, and a clinical examination to assess postural setting. Results The prevalence of flexible flat feet was 34.8%. The differenceinthe mean centre of pressure (CoP) between the two groups was significant (p=0.028), regarding the antero-posterior direction of CoP only. There was no significant differencein the presence of postural growth disharmony between the neutral and flat-feet groups. Conclusion The flattening of the plantar archseems to be linked to a displacement of CoP Y, more posterior in flat feet than in neutral feet; on the other hand, postural harmony in 6-year-old children during growth is not influenced by flat feet.
Recovery of Saccharomyces cerevisiae CNCM I-3856 in Vaginal Samples of Healthy Women after Oral Administration

Bacterial vaginosis and vulvovaginal candidiasis are common causes of impaired health and quality of life for women. Although antimicrobial agents remain the main strategy for the treatment of vaginal infections, their repeated use involves high rates of resistance and recurrence. Alternative approaches such as probiotics are studied. Saccharomyces cerevisiae CNCM I-3856 already demonstrated beneficial effects in experimental models of vaginal infections. This randomized, double-blind, placebo-controlled clinical study was performed to evaluate the recovery of S. cerevisiae CNCM I-3856 in vaginal samples in healthy women after oral consumption. Sixty healthy women were randomized to receive a daily dose of S. cerevisiae CNCM I-3856 or a placebo for 4 weeks. Subcultures and quantitative polymerase chain reaction (qPCR) were used to detect the strain in vaginal and stool samples. A safety assessment was carried out throughout the study. Fifty-seven women completed the study. Over the 4-week supplementation phase, S. cerevisiae CNCM I-3856 has been detected in the vaginal samples of 21% of women (n = 4/19) in the 500 mg Probiotic group and 16% of women (n = 3/19) in the 1000 mg Probiotic group. The strain was detected in the faeces of 90% of women consuming the probiotic. This is the first clinical study demonstrating the migration of yeast from intestine to vagina where it may exert its benefits.
Serum CCL22 levels decreased in parallel with disease activity in CCR4‐positive mycosis fungoides treated with mogamulizumab

Mogamulizumab is a humanized anti‐C‐C chemokine receptor type (CCR)4 antibody that shows cytotoxicity against CCR4+ lymphoma cells via antibody‐dependent cell‐mediated cytotoxicity in advanced cutaneous T cell lymphoma (CTCL) patients. The production levels of ligands for CCR4, that is, Chemokine (C‐C motif) ligand (CCL)17 and CCL22, are important for the assessment of the disease activity in CTCL patients. We evaluated the serum levels of CCL17, CCL19, CCL22, C‐X‐C motif chemokine ligand (CXCL)10, and CXCL13, which are ligands for CCR4, CCR7, CCR4, C‐X‐C Motif Chemokine Receptor (CXCR)3, and CXCR5, respectively, at baseline and 4 weeks after the administration of mogamulizumab in five patients with mycosis fungoides. The serum levels of CCL22 were significantly decreased in patients who responded to mogamulizumab, but no differences were identified in the serum levels of CCL17, CCL19, CXCL10, or CXCL13. Immunofluorescence staining revealed that the majority of CCL22‐producing cells were cluster of differentiation (CD)163+ tumor‐associated macrophages, and they were surrounded by CCR4+ CTCL cells. Our present data suggested that the serum CCL22 level may be a predictive marker of the efficacy of mogamulizumab for the treatment of CCR4+ CTCL.
Drug interactions with zidovudine phosphorylation in vitro

We have investigated the effect of a range of drugs (some commonly coadministered with zidovudine [ZDV] to human immunodeficiency virus-positive patients) on intracellular phosphorylation of ZDV by stimulated peripheral blood mononuclear cells, Molt 4 cells, and U937 cells in vitro. Of the drugs tested (azoles, antiviral agents, antibiotics, and anticancer agents), only doxorubicin and ribavirin caused inhibition of anabolite formation as measured by high-performance liquid chromatography. This in vitro approach may provide important leads to potential interactions at the phosphorylation level in patients with human immunodeficiency virus disease. It is reassuring that so many commonly administered drugs do not alter ZDV phosphorylation.
Improving Agility Using Big Data Analytics: The Role of Democratization Culture

Abstract Background: Big data analytics (BDA) is considered an enabler of organizational agility because it helps firms to sense market-based changes and improve decision making in a more informed and timely manner. However, in reality, only a handful of firms have achieved improvement in their outcomes by using BDA. To address this inconsistency, our study explores the conditions under which BDA use translates into agility. We particularly focus on organizational culture because in the pursuit of agility, culture is emphasized as a source of stability that allows firms to successfully adapt to the changing environment. Therefore, by assuming organizational culture as a contextual factor, this study examines the moderating effect of organizational culture on the link between BDA use and agility. Method: We employ a concept from data democratization called “democratization culture,” which values the willingness to share information and the acceptance of diversity. We also adopt collectivistic culture for comparison with democratization culture. Further, BDA use is decomposed into advanced and basic use based on the functions and BDA types. A model is proposed and empirically validated through survey data collected from 304 senior-level managers. Results: Our findings suggest that the moderating effects of democratization culture on agility are different depending on whether it is combined with advanced or basic BDA use. Conclusions: This study provides initial empirical evidence that contributes to the scarce research on the role of organizational culture in the link between BDA use and agility. Available at: https://aisel.aisnet. org/pajais/vol12/iss2/2/ Recommended Citation Hyun, Youyung; Kamioka, Taro; and Hosoya, Ryuichi (2020) "Improving Agility Using Big Data Analytics: The Role of Democratization Culture," Pacific Asia Journal of the Association for Information Systems: Vol. 12: Iss. 2, Article 2. DOI: 10.17705/1pais.12202 Available at: https://aisel.aisnet. org/pajais/vol12/iss2/2