Miracle-dz/UniFAR-FTUs huggingface dataset:
Review of Clinical Research Informatics

Summary Objectives: Clinical Research Informatics (CRI) declares its scope in its name, but its content, both in terms of the clinical research it supports—and sometimes initiates—and the methods it has developed over time, reach much further than the name suggests. The goal of this review is to celebrate the extraordinary diversity of activity and of results, not as a prize-giving pageant, but in recognition of the field, the community that both serves and is sustained by it, and of its interdisciplinarity and its international dimension. Methods: Beyond personal awareness of a range of work commensurate with the author’s own research, it is clear that, even with a thorough literature search, a comprehensive review is impossible. Moreover, the field has grown and subdivided to an extent that makes it very hard for one individual to be familiar with every branch or with more than a few branches in any depth. A literature survey was conducted that focused on informatics-related terms in the general biomedical and healthcare literature, and specific concerns (“artificial intelligence”, “data models”, “analytics”, etc.) in the biomedical informatics (BMI) literature. In addition to a selection from the results from these searches, suggestive references within them were also considered. Results: The substantive sections of the paper—Artificial Intelligence, Machine Learning, and “Big Data” Analytics; Common Data Models, Data Quality, and Standards; Phenotyping and Cohort Discovery; Privacy: Deidentification, Distributed Computation, Blockchain; Causal Inference and Real-World Evidence—provide broad coverage of these active research areas, with, no doubt, a bias towards this reviewer’s interests and preferences, landing on a number of papers that stood out in one way or another, or, alternatively, exemplified a particular line of work. Conclusions: CRI is thriving, not only in the familiar major centers of research, but more widely, throughout the world. This is not to pretend that the distribution is uniform, but to highlight the potential for this domain to play a prominent role in supporting progress in medicine, healthcare, and wellbeing everywhere. We conclude with the observation that CRI and its practitioners would make apt stewards of the new medical knowledge that their methods will bring forward.
Dengue Virus Serotype 4 Is Responsible for the Outbreak of Dengue in East Java City of Jember, Indonesia

Outbreaks of dengue virus (DENV) in Indonesia have been mainly caused by the DENV serotype-1; -2; or -3. The DENV-4 was the least-reported serotype in Indonesia during the last five decades. We recently conducted a molecular epidemiology study of dengue in the Jember regency, East Java province, Indonesia. Dengue is endemic in the region and outbreaks occur annually. We investigated the clinical characteristics and etiology of dengue-like febrile illness in this regency to understand the disease dynamics. A total of 191 patients with clinical symptoms similar to dengue were recruited during an 11-month study in 2019–2020. Children accounted for the majority of cases and dengue burden was estimated in 41.4% of the cases based on NS1 antigen, viral RNA, and IgG/IgM antibody detection with the majority (73.4%) being primary infections. Secondary infection was significantly associated with a higher risk of severe dengue manifestation. All four DENV serotypes were detected in Jember. Strikingly, we observed the predominance of DENV-4, followed by DENV-3, DENV-1, and DENV-2. Genotype determination using Envelope gene sequence revealed the classification into Genotype I, Cosmopolitan Genotype, Genotype I, and Genotype II for DENV-1, -2, -3, and -4, respectively. The predominance of DENV-4 in Jember may be associated with a new wave of DENV infections and spread in a non-immune population lacking a herd-immunity to this particular serotype.
Conventional and Non-Conventional Roles of Non-Muscle Myosin II-Actin in Neuronal Development and Degeneration

Myosins are motor proteins that use chemical energy to produce mechanical forces driving actin cytoskeletal dynamics. In the brain, the conventional non-muscle myosin II (NMII) regulates actin filament cytoskeletal assembly and contractile forces during structural remodeling of axons and dendrites, contributing to morphology, polarization, and migration of neurons during brain development. NMII isoforms also participate in neurotransmission and synaptic plasticity by driving actin cytoskeletal dynamics during synaptic vesicle release and retrieval, and formation, maturation, and remodeling of dendritic spines. NMIIs are expressed differentially in cerebral non-neuronal cells, such as microglia, astrocytes, and endothelial cells, wherein they play key functions in inflammation, myelination, and repair. Besides major efforts to understand the physiological functions and regulatory mechanisms of NMIIs in the nervous system, their contributions to brain pathologies are still largely unclear. Nonetheless, genetic mutations or deregulation of NMII and its regulatory effectors are linked to autism, schizophrenia, intellectual disability, and neurodegeneration, indicating non-conventional roles of NMIIs in cellular mechanisms underlying neurodevelopmental and neurodegenerative disorders. Here, we summarize the emerging biological roles of NMIIs in the brain, and discuss how actomyosin signaling contributes to dysfunction of neurons and glial cells in the context of neurological disorders. This knowledge is relevant for a deep understanding of NMIIs on the pathogenesis and therapeutics of neuropsychiatric and neurodegenerative diseases.
Time to Next Treatment as a Meaningful Endpoint for Trials of Primary Cutaneous Lymphoma

Time to next treatment (TTNT) is an emerging endpoint in clinical studies of primary cutaneous T-cell lymphomas (CTCL), with utility as a surrogate marker for the “duration of clinical benefit”. TTNT provides a highly clinically meaningful endpoint that uniquely reflects not only the duration of treatment efficacy on disease and symptom control, but also incorporates the patient experience by accounting for patient compliance and tolerance to the studied therapy(s). Given the distinct challenges of pin-pointing the exact date of progression in patients with multi-compartmental CTCL, TTNT overcomes many of the shortcomings of conventional, disease-focused, clinical endpoints in primary CTCL research. Although widely accepted in clinical research for numerous other incurable malignancies, TTNT currently lacks a standardised definition. In this paper, we describe the value of TTNT as a clinical endpoint, review the applications of TTNT in primary CTCL research, and propose a standardised definition of TTNT to be applied in future clinical research of primary CTCL therapies.
Evaluating the Use of LAST 2-Tiered Nomenclature and Its Impact on Reporting Cervical Lesions in a Population-Based Cancer Registry.

BACKGROUND Since 2012, the Lower Anogenital Squamous Terminology (LAST) Project recommended a 2-tiered nomenclature, low-grade and high-grade squamous intraepithelial lesion (LSIL and HSIL), to replace the 3-tiered cervical intraepithelial neoplasia (CIN) system for HPV-associated lesions. Prior to 2019, preinvasive cervical lesions classified as CIN3, severe dysplasia, carcinoma in situ (CIS), and adenocarcinoma in situ (AIS) were considered reportable to the Louisiana Tumor Registry for a CIN3 project funded by the Centers for Disease Control and Prevention (CDC); but lesions classified exclusively as high-grade/HSIL based on the 2-tiered system were not considered reportable. Due to the terminology changes, we wanted to know whether pre-2019 reportable criteria need to be modified to capture all reportable precancerous cervical cases diagnosed in 2019 forward. OBJECTIVES To evaluate the utilization of LAST 2-tiered classification, low-grade and high-grade squamous intraepithelial lesion, and p16 immunohistochemistry (IHC) testing on cervical biopsy/surgical specimens, assess the search criteria needed to identify high-grade lesions for the CDC-funded CIN3 project, and assess the impact of underreporting cervical lesions caused by terminology changes. METHODS An equal number of abnormal/precancerous and normal cervical findings from biopsy pathology reports received in 2015 were randomly selected by an artificial intelligence (AI) search engine developed by Artificial Intelligence in Medicine Inc (AIM) using pre2019 search criteria. Selected pathology reports were reflagged for the reportability by AIM audit software based on 2019 search criteria and manually reviewed for the use of reportable terms including CIN3, severe dysplasia, CIS, AIS, highgrade/HSIL terminology, and CIN2 or CIN2-3 with positive p16 IHC testing. Cohen's kappa statistic was used to assess the agreement between AIM auto-coding and manual review. Positive predictive values (PPV) and sensitivity tests were computed to evaluate the reportable terms. RESULTS Six out of 9 surveyed laboratories used 2-tiered terminology on cervical biopsy pathology reports and 7 performed p16 IHC tests. Of 1,974 randomly selected reports from 5 laboratories, 987 were flagged as precancer by AI using pre-2019 search criteria. After adding the high-grade/HSIL term into pre-2019 search criteria, precancerous reports increased by 29%. After manual review, 41.6% of these cases were reportable precancerous cervical cases with a PPV of 0.65 (95% CI, 0.62-0.67) and 13.6% had p16 IHC performed. CONCLUSIONS Both the 2-tiered and 3-tiered nomenclature are needed to ensure complete identification of all reportable high-grade cervical lesions.
Energy Efficiency in RF Energy Harvesting-Powered Distributed Antenna Systems for the Internet of Things

This paper studies a distributed antenna system (DAS) network with radio frequency (RF) energy harvesting (EH) technology where the distributed antenna ports (DAPs) transmit energy and information to multiple users simultaneously. The time division multiple access (TDMA) protocol is adopted, so for each time slot is allowed to receive information, while the rest of the users harvest energy. In order to maximize the system energy efficiency (EE), subject to the EH requirements and data rate requirements of the users, the transmission time and power assignment are jointly optimized. In order to deal with this non-convex problem, based on Dinkelbach theory and the block-coordinate descent (BCD) scheme, an efficient algorithm is designed to obtain the global optimal solution. Then, simulation results are presented to show that the proposed method achieves much higher system EE compared with benchmark methods. With the increase of the user’s minimum information rate, the system EE decreases rapidly.
Environmental Methamphetamine Exposures and Health Effects in 25 Case Studies

The clandestine manufacture and use of methamphetamine can result in contamination of residential properties. It is understood that this contamination remains in homes for a significant period, however there are a lack of data available to understand the health effects of exposure to environmental methamphetamine contamination (third-hand exposure). Our study collected information from 63 individuals in 25 separate case studies where the subjects had unwittingly suffered third-hand exposure to methamphetamine from former manufacture, use, or both. Data included environmental contamination data, information on subjects’ health effects, and evidence of exposure using hair analysis. This study identified a range of health effects that occur from residing in these properties, including behavioural effects or issues, sleep issues, respiratory effects, skin and eye effects, and headaches. Methamphetamine was detected in hair samples from some individuals, including children. The exposures and concomitant reported health effects covered a wide range of environmental methamphetamine levels in the properties, including low levels close to the current Australian guideline of 0.5 µg methamphetamine/100 cm2. There were no discernible differences between health effects from living in properties contaminated from former manufacture or use. This study demonstrates that residing in these properties can represent a serious public health risk.
Electrical Conduction Characteristic of a 2D MXene Device with Cu/Cr2C/TiN Structure Based on Density Functional Theory

The electronic structure and the corresponding electrical conductive behavior of the Cu/Cr2C/TiN stack were assessed according to a newly developed first-principle model based on density functional theory. Using an additional Cr2C layer provides the metal-like characteristic of the Cu/Cr2C/TiN stack with much larger electrical conduction coefficients (i.e., mobility, diffusivity, and electrical conductivity) than the conventional Ag/Ti3C2/Pt stack due to the lower activation energy. This device is therefore capable of offering faster switching speeds, lower programming voltage, and better stability and durability than the memristor device with conventional Ti3C2 MXene.
Effects of a 14-Day High-Intensity Shock Microcycle in High-Level Ice Hockey Players' Fitness

Abstract Brocherie, F, Perez, J, and Guilhem, G. Effects of a 14-day high-intensity shock microcycle in high-level ice hockey players' fitness. J Strength Cond Res 36(8): 2247–2252, 2022—Elite athletes face congested schedules with increased competition frequency and restricted time for training periods. Therefore, time is lacking to design long-term sport-specific block periodization. This study aimed to investigate the effects of adding a 14-day off-ice high-intensity training (HIT) shock microcycle to the usual training content of the pre-season preparation of high-level male ice hockey players' fitness. Fourteen players were randomly assigned to off-ice HIT (n = 7) or usual pre-season training (control, n = 7). For the HIT group, additional off-ice training content included 2 sessions of repeated-maximal resistance training, 2 sessions of repeated-sprint training, and 2 sessions of high-intensity intermittent training. Control group performed equal number of off-ice sessions using traditional strength and conditioning training. Off-ice Yo-Yo intermittent recovery test level 2 (YYIR2) and on-ice repeated-sprint ability test (RSA) were conducted before (pre-test) and 3 days after the intervention (post-test). Statistical significance was set at p < 0.05. Significant group × time interactions were found for off-ice YYIR2 performance (p < 0.05) and on-ice RSA-cumulated skating time (RSATT; p < 0.05). Compared with pre-test, off-ice YYIR2 distance covered significantly increased (from 708.6 ± 97.2 to 885.7 ± 118.7 m, p < 0.01; +25.8 ± 16.9%, p < 0.05) and on-ice RSATT significantly decreased (from 28.35 ± 0.87 to 28.14 ± 0.84 seconds; −1.7 ± 2.1%, both p < 0.05)] for HIT group. No significant pre-test to post-test changes were found for the control group (+2.7 ± 20.0% for YYIR2 and +0.9 ± 2.2% for RSATT). The implementation of a 14-day shock microcycle (including 6 HIT sessions) significantly improved fitness performance in high-level male ice hockey players. Such HIT block periodization offers a promising way to deal with congested schedules.
PPARδ and FOXO1 Mediate Palmitate-Induced Inhibition of Muscle Pyruvate Dehydrogenase Complex and CHO Oxidation, Events Reversed by Electrical Pulse Stimulation

The mechanisms behind the reduction in muscle pyruvate dehydrogenase complex (PDC)-controlled carbohydrate (CHO) oxidation during chronic high-fat dietary intake are poorly understood, as is the basis of CHO oxidation restoration during muscle contraction. C2C12 myotubes were treated with (300 μM) palmitate or without (control) for 16 h in the presence and absence of electrical pulse stimulation (EPS, 11.5 V, 1 Hz, 2 ms). Compared to control, palmitate reduced cell glucose uptake (p < 0.05), PDC activity (p < 0.01), acetylcarnitine accumulation (p < 0.05) and glucose-derived mitochondrial ATP production (p < 0.01) and increased pyruvate dehydrogenase kinase isoform 4 (PDK4) (p < 0.01), peroxisome proliferator-activated receptor alpha (PPARα) (p < 0.01) and peroxisome proliferator-activated receptor delta (PPARδ) (p < 0.01) proteins, and reduced the whole-cell p-FOXO1/t-FOXO1 (Forkhead Box O1) ratio (p < 0.01). EPS rescued palmitate-induced inhibition of CHO oxidation, reflected by increased glucose uptake (p < 0.01), PDC activity (p < 0.01) and glucose-derived mitochondrial ATP production (p < 0.01) compared to palmitate alone. EPS was also associated with less PDK4 (p < 0.01) and PPARδ (p < 0.01) proteins, and lower nuclear p-FOXO1/t-FOXO1 ratio normalised to the cytoplasmic ratio, but with no changes in PPARα protein. Collectively, these data suggest PPARδ, and FOXO1 transcription factors increased PDK4 protein in the presence of palmitate, which limited PDC activity and flux, and blunted CHO oxidation and glucose uptake. Conversely, EPS rescued these metabolic events by modulating the same transcription factors.
An Innovative Concept for a Multivariate Plausibility Assessment of Simultaneously Recorded Data

Simple Summary Benefiting from technical progress, it is nowadays easy to collect huge amounts of data using computerized sensor-based acquisition systems for both research and practical applications. However, such data often contain technology-related errors that are difficult to distinguish from physiologically extreme observations and thus can impair the quality of the data and also the statistical analysis. To tackle this, an innovative procedure for a multivariate plausibility assessment was developed to discriminate observations of simultaneously recorded traits between ‘physiologically normal’, ‘physiologically extreme’ or ‘implausible’ cases. To evaluate the performance and applicability, it was tested on a comprehensive data set collected from 10 commercial dairy farms. The added value of the developed method can be summarized as the ability to improve the quality of huge data sets with complex structure by distinguishing implausible observations from observations indicating physiological extreme conditions. The underlying concept can be applied to future data collections in science as well as in agricultural practice with regard to precision livestock farming. Abstract The aim of this work was to develop an innovative multivariate plausibility assessment (MPA) algorithm in order to differentiate between ‘physiologically normal’, ‘physiologically extreme’ and ‘implausible’ observations in simultaneously recorded data. The underlying concept is based on the fact that different measurable parameters are often physiologically linked. If physiologically extreme observations occur due to disease, incident or hormonal cycles, usually more than one measurable trait is affected. In contrast, extreme values of a single trait are most likely implausible if all other traits show values in a normal range. For demonstration purposes, the MPA was applied on a time series data set which was collected on 100 cows in 10 commercial dairy farms. Continuous measurements comprised climate data, intra-reticular pH and temperature, jaw movement and locomotion behavior. Non-continuous measurements included milk yield, milk components, milk mid-infrared spectra and blood parameters. After the application of the MPA, in particular the pH data showed the most implausible observations with approximately 5% of the measured values. The other traits showed implausible values up to 2.5%. The MPA showed the ability to improve the data quality for downstream analyses by detecting implausible observations and to discover physiologically extreme conditions even within complex data structures. At this stage, the MPA is not a fully developed and validated management tool, but rather corresponds to a basic concept for future works, which can be extended and modified as required.
Design of Wearable EEG Devices Specialized for Passive Brain–Computer Interface Applications

Owing to the increased public interest in passive brain–computer interface (pBCI) applications, many wearable devices for capturing electroencephalogram (EEG) signals in daily life have recently been released on the market. However, there exists no well-established criterion to determine the electrode configuration for such devices. Herein, an overall procedure is proposed to determine the optimal electrode configurations of wearable EEG devices that yield the optimal performance for intended pBCI applications. We utilized two EEG datasets recorded in different experiments designed to modulate emotional or attentional states. Emotion-specialized EEG headsets were designed to maximize the accuracy of classification of different emotional states using the emotion-associated EEG dataset, and attention-specialized EEG headsets were designed to maximize the temporal correlation between the EEG index and the behavioral attention index. General purpose electrode configurations were designed to maximize the overall performance in both applications for different numbers of electrodes (2, 4, 6, and 8). The performance was then compared with that of existing wearable EEG devices. Simulations indicated that the proposed electrode configurations allowed for more accurate estimation of the users’ emotional and attentional states than the conventional electrode configurations, suggesting that wearable EEG devices should be designed according to the well-established EEG datasets associated with the target pBCI applications.
In Vitro Degradation of Electrospun Poly(Lactic-Co-Glycolic Acid) (PLGA) for Oral Mucosa Regeneration

Poly(lactic-co-glycolic acid) (PLGA) has been used in the field of tissue engineering as a scaffold due to its good biocompatibility, biodegradability and mechanical strength. With the aim to explore the degradability of PLGA electrospun nonwoven structures for oral mucosa tissue engineering applications, non-irradiated and gamma irradiated nonwovens were immersed in three different solutions, in which simulated body fluid (SBF) and artificial saliva are important for future oral mucosa tissue engineering. The nonwovens were immersed for 7, 15 and 30 days in SBF, culture media (DMEM) and artificial saliva at 37 °C. Before immersion in the solutions, the dosage of 15 kGy was applied for sterilization in one assay and compared with non-irradiated samples at the same timepoints. Samples were characterized using different techniques such as scanning electron microscopy (SEM), differential scanning calorimetric (DSC) and gel permeation chromatography (GPC) to evaluate the nonwoven degradation and Fourier-transform infrared spectroscopy (FTIR) to evaluate the chain scissions. Our results showed that PLGA nonwovens were constituted by semicrystalline fibers with moderate degradation properties up to thirty days. The non-irradiated samples exhibited slower kinetics of degradation than irradiated nonwovens. For immersion times longer than 7 days in the three different solutions, the mean diameter of irradiated fibers stayed in the same range, but significantly different from the control sample. On non-irradiated samples, the degradation kinetics was slower and the plateau in the diameter value was only attained after 30 days of immersion in the fluids. Plasticization (fluid absorption into the fiber structure) occurred in the bulk material, as confirmed by a decrease in Tg observed by DSC analyses of non-irradiated and irradiated nonwovens, in comparison with the respective controls. In addition, artificial saliva showed a higher capacity of influencing PLGA crystallization than SBF and DMEM. FTIR analyses showed typical PLGA chemical functional groups changes. These results will be important for future application of those PLGA electrospun nonwovens for oral mucosa regeneration.