Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolomic Signature in Sera of Multiple Sclerosis Patients during Pregnancy

Multiple sclerosis (MuS) is an autoimmune disease of the central nervous system characterized by neuroinflammation, neurodegeneration, and degradation of the myelin sheath. Epidemiological studies have shown that the female gender is more susceptible than the male gender to MuS development, with a female-to-male ratio of 2:1. Despite this high onset, women have a better prognosis than men, and the frequency of the relapsing phase decreases during pregnancy, while it increases soon after birth. Therefore, it is interesting to investigate hormonal fluctuations during pregnancy and whether they correlate with metabolic signatures. To gain a deeper inside into the biochemical mechanism of such a multifactorial disease, we adopted targeted metabolomics approaches for the determination of many serum metabolites in 12 pregnant women affected by MuS by mass spectrometry analysis. Our data show a characteristic hormonal fluctuation for estrogens and progesterone, as expected. They also highlight other interesting hormonal alterations for cortisol, corticosterone, 11-deoxycortisol, 4-androstene-3,17-dione, testosterone, and 17α-hydroxyprogesterone. Furthermore, a negative correlation with progesterone levels was observed for amino acids and for acylcarnitines, while an imbalance of different sphingolipids pathways was found during pregnancy. In conclusion, these data are in agreement with the characteristic clinical signs of MuS patients during pregnancy and, if confirmed, they may add an important tessera in the complex mosaic of maternal neuroprotection.
Percutaneous laser ablation for benign and malignant thyroid diseases

Minimally invasive image-guided thermal ablation is becoming increasingly common as an alternative to surgery for the treatment of benign thyroid nodules. Among the various techniques for thermal ablation, laser ablation (LA) is the least invasive, using the smallest applicators available on the market and enabling extremely precise energy deposition. However, in some cases, multiple laser fibers must be used simultaneously for the treatment of large nodules. In this review, the LA technique is described, and its main clinical applications and results are discussed and illustrated.
Low-Voltage Low-Power Integrable CMOS Circuit Implementation of Integer- and Fractional–Order FitzHugh–Nagumo Neuron Model

The low-voltage low-power sinh-domain (SD) implementations of integer- and fractional-order FitzHugh–Nagumo (FHN) neuron model have been introduced in this paper. Besides, the effect of fractional-orders on the external excitation current and dynamics of the neuron has been examined in this paper. The proposed SD designs of FHN neuron model have the benefits of: 1) low-voltage operation; 2) integrability, due to resistor-less design and the employment of only grounded components; 3) electronic tunability of performance parameters; and 4) low-power implementation due to the inherent properties of SD technique. HSPICE simulator tool and Taiwan Semiconductor Manufacturing Company, Hsinchu, Taiwan 130-nm CMOS process was used to evaluate and verify the correct functioning of the model. In addition, to experimentally verify the operation of the proposed fractional-order FHN neuron model, field-programmable analog array (FPAA) implementation of the model has been presented, and the proper functioning of the model has been verified. To the best of the authors’ knowledge, this is the first paper that describes the electronic realization of the fractional-order FHN neuron model. In addition, it is the first time that the FPAA implementation of any fractional-order neuron model has been presented.
Academic coaching and decision analysis: Ways of deciding whether to pursue an academic career

We analyzed and compared the decision-making processes underlying two approaches that academics might use to decide whether to pursue a professorship or an alternative career: academic coaching (a paid service that supports academics with career-related issues) and decision analysis (a method for applying decision theory to real-world decision problems). To this end, we conducted in-depth expert interviews with seven out of 11 academic coaches known to work in Berlin to examine empirically the career decision-making process that they use. Moreover, we demonstrate theoretically how decision analysis can be applied to an academic’s hypothetical career choice problem. A comparison of the two approaches showed that they both advise (i) structuring the decision problem by dividing it into smaller components, (ii) using the academic’s objectives to generate career alternatives, and (iii) quantifying the uncertainty of decision outcomes using subjective probabilities. Moreover, the observed differences in the way the two approaches structure the decision problem suggest ways in which they could inform each other: (i) they could make use of each other’s techniques to help academics define their objectives and generate career alternatives; (ii) academic coaching could, in addition, use decision trees (a hallmark of decision analysis) to represent the structure of the career decision problem, and use simple measurement scales to quantify how much the career options contribute to the academic’s objectives.
Predictors of Sexual Violence Across Young Women’s Relationship Histories

The goal of the current study was to identify risk factors that predict sexual intimate partner violence (IPV) victimization across young women’s relationship histories, within a socioeconomically diverse sample recruited from a university, a 2-year college, and community organizations serving low-income young women. We interviewed 148 young women aged 18 to 24 years about partner victimization (physical IPV, coercive control, and sexual IPV) within each of their relationships (up to four relationships, beginning with their first; 388 in total). We used the life history calendar to structure the interviews and obtain detailed information about each relationship, including age difference between participants and their partners, and relationship length. We used multilevel modeling to examine primary caregiver highest grade completed (an indicator of socioeconomic status [SES]), participant age, age difference, relationship length, setting, and physical IPV/coercive control as predictors of sexual IPV during their first relationship and across Relationships 1 to 4. Sexual IPV during participants’ first relationship was inversely associated with SES and age, and positively associated with physical IPV/coercive control; 2-year college and community participants reported lower rates of sexual IPV during the first relationship, compared with university participants. The trajectory of sexual IPV across Relationships 1 to 4 declined among university participants and increased among 2-year college participants; age difference and physical IPV/coercive control positively covaried with sexual IPV across Relationships 1 to 4. Low SES, young age, large age difference, and the presence of physical IPV and coercive control may be risk factors for sexual IPV victimization within adolescent relationships. Sexual violence prevention and intervention approaches should incorporate these risk factors, and be designed to reach an increasingly socioeconomically diverse population across a variety of settings, to be effective.
Organ‐on‐chip models: Implications in drug discovery and clinical applications

Before a lead compound goes through a clinical trial, preclinical studies utilize two‐dimensional (2D) in vitro models and animal models to study the pharmacodynamics and pharmacokinetics of that lead compound. However, these current preclinical studies may not accurately represent the efficacy and safety of a lead compound in humans, as there has been a high failure rate of drugs that enter clinical trials. All of these failures and the associated costs demonstrate a need for more representative models of human organ systems for screening in the preclinical phase of drug development. In this study, we review the recent advances in in vitro modeling including three‐dimensional (3D) organoids, 3D microfabrication, and 3D bioprinting for various organs including the heart, kidney, lung, gastrointestinal tract (intestine–gut–stomach), liver, placenta, adipose, retina, bone, and brain as well as multiorgan models. The availability of organ‐on‐chip models provides a wealth of opportunities to understand the pathogenesis of human diseases and provide a potentially better model to screen a drug, as these models utilize a dynamic 3D environment similar to the human body. Although there are limitations of organ‐on‐chip models, the emergence of new technologies have refined their capability for translational research as well as precision medicine.
Adaptive Synchronization of Reaction–Diffusion Neural Networks and Its Application to Secure Communication

This paper is mainly concerned with the synchronization problem of reaction–diffusion neural networks (RDNNs) with delays and its direct application in image secure communications. An adaptive control is designed without a sign function in which the controller gain matrix is a function of time. The synchronization criteria are established for an error model derived from master–slave models through solving the set of linear matrix inequalities derived by constructing the suitable novel Lyapunov–Krasovskii functional candidate, Green’s formula, and Wirtinger’s inequality. If the proposed sufficient conditions are satisfied, then the global asymptotic synchronization of the error model is guaranteed. The numerical illustrations are provided to demonstrate the validity of the derived synchronization criteria. In addition, the role of system parameters is picturized through the chaotic nature of RDNNs and those unprecedented solutions is utilized to promote better security of image transactions. As is evident, the enhancement of image encryption algorithm is designed with two levels, namely, image watermarking and diffusion process. The contributions of this paper are discussed as concluding remarks.
Very late onset post-transplant diffuse large B cell lymphoma in a liver transplant recipient with hepatitis B

Rationale: Post transplantation lymphoproliferative disorder (PTLD) is a rare but severe complication. Epstein-Barr virus (EBV) is considered an important pathogen for PTLD and EBV deoxyribonucleic acid (DNA) load is widely monitored to detect PTLD early. Hepatitis B virus (HBV) infection is rarely reported to be related with PTLD. We report a case of EBV negative (EBV−), HBV positive (HBV+) diffuse large B cell lymphoma in a patient 12 years after liver transplantation. Patient concerns and diagnosis: A 52-year-old man complained of worsening appetite, abdominal distension, and pruritus. Abdominal computed tomography (CT) detected a huge retroperitoneal mass and pathology of the fine needle biopsy established the diagnosis of diffuse large B cell lymphoma. Virology showed active hepatitis B viral duplication and EBV DNA was negative. Intervention: Treatment modalities for this patient included: reduction and subsequent cessation of immunosuppression; antiviral therapy for HBV with entecavir and adefovir; conventional chemotherapy consisting of cyclophosphamide, epirubicin, vindesine, and prednisone, followed by radiotherapy. He achieved complete remission (CR) and was kept on entecavir treatment afterwards. Outcomes: He has been in remission for 2 years. Lessons: HBV infection might have played some role in this very late onset EBV− PTLD patient. Therefore, HBV serology and HBV load should be monitored during the follow-up of HBV surface antigen positive (HBsAg+) transplant recipients and life-long antiviral therapy is required.
HDAC6 differentially regulates autophagy in stem-like versus differentiated cancer cells

ABSTRACT Cancer stem-like cells (CSCs), a small population of pluripotent cells residing within heterogeneous tumor mass, remain highly resistant to various chemotherapies as compared to the differentiated cancer cells. It is being postulated that CSCs possess unique molecular mechanisms, such as autophagic homeostasis, that allow CSCs to withstand the therapeutic assaults. Here we demonstrate that HDAC6 inhibition differentially modulates macroautophagy/autophagy in CSCs as compared to that of differentiated cancer cells. Using human and murine CSC models and differentiated cells, we show that the inhibition or knockdown (KD) of HDAC6 decreases CSC pluripotency by downregulating major pluripotency factors POU5F1, NANOG and SOX2. This decreased HDAC6 expression increases ACTB, TUBB3 and CSN2 expression and promotes differentiation in CSCs in an apoptosis-independent manner. Mechanistically, HDAC6 KD in CSCs decreases pluripotency by promoting autophagy, whereas the inhibition of pluripotency via retinoic acid treatment, POU5F1 or autophagy-related gene (ATG7 and ATG12) KD in CSCs decreases HDAC6 expression and promotes differentiation. Interestingly, HDAC6 KD-mediated CSC growth inhibition is further enhanced in the presence of autophagy inducers Tat-Beclin 1 peptide and rapamycin. In contrast to the results observed in CSCs, HDAC6 KD in differentiated breast cancer cells downregulates autophagy and increases apoptosis. Furthermore, the autophagy regulator p-MTOR, upstream negative regulators of p-MTOR (TSC1 and TSC2) and downstream effectors of p-MTOR (p-RPS6KB and p-EIF4EBP1) are differentially regulated in CSCs versus differentiated cancer cells following HDAC6 KD. Overall these data identify the differential regulation of autophagy as a molecular link behind the differing chemo-susceptibility of CSCs and differentiated cancer cells.
The Application of the RMT-test on the High-frequency Price Time Series

A new tool to measure the degree of randomness of a given sequence, named as the RMT-test, is introduced and applied on machine-generated random numbers as well as real-world data sequences. The tool consists of two parts: the qualitative evaluation that is aimed to visualize the degree of randomness, and the quantitative evaluation that is aimed to distinguish subtle differences of randomness among highly random sequences based on moment analysis, in which the moments of the actual eigenvalue distributions of the correlation matrix to the corresponding theoretical expression derived by the random matrix theory. The RMT-test is applied to solve practical problems by comparing the randomness of real data, such as the output of cryptographic hash functions MD5 and SHA-1, and high-frequency time series of stock prices. It is found that the stock of higher randomness tends to perform better than the stock of lower randomness in the following time period.
Effect of Pain Severity on Executive Function Decline in Community-Dwelling Older Adults

Objective: The purpose of this study was to explore the reciprocal relationship between pain severity and executive function in community-dwelling older adults. Method: In this prospective cohort study, 64 Japanese community-dwelling older adults aged 60 years or older (mean age 72.8 years; women, 68.8%) were analyzed. Pain severity was assessed by self-reported questionnaire while executive function was assessed by the Trail Making Test at baseline and at 1-year follow-up assessment. A mixed effect model was conducted to analyze the effect of baseline executive function on change in pain severity and effect of baseline pain severity on change in executive function. Results: The effect of baseline Trail Making Test on change in pain severity was not significant. On the contrary, the effect of high baseline pain severity on the decline in set shifting (Trail Making Test Part B) was significant even after adjustment with age, sex, years of education, depressive symptoms, and analgesic drug use. Conclusion: Higher baseline pain severity was associated with greater executive function decline in community-dwelling older adults. Executive function decline due to severe pain should be considered as well as pain itself.
Common data elements (CDEs) for preclinical epilepsy research: Introduction to CDEs and description of core CDEs. A TASK3 report of the ILAE/AES joint translational task force

Common data elements (CDEs) are becoming more common as more areas of preclinical research have generated CDEs. Herein we provide an overview of the progress to date in generating CDEs for preclinical epilepsy research. Currently there are CDEs that have been developed for Physiology (in vivo), Behavior, Pharmacology, and Electroencephalography (EEG). Together the CDEs and methodologic considerations associated with these CDEs are laid out in consecutive manuscripts published in Epilepsia Open, each describing CDEs for their respective topic area. In addition to the overview of progress for the 4 subjects, core characteristics (Core CDEs) are described and explained. Data collection using a case report form (CRF) is described, and considerations that are involved in using the CDEs and CRFs are discussed.
Reasoning Dimensions Underlying Science Achievement: The Case of Performance Assessment

Snow argued for multidimensional science achievement in the National Education Longitudinal Study of 1988 (NELS:88) along dimensions of basic knowledge and reasoning, spatial-mechanical reasoning, and quantitative science. We focused the generality of these reasoning dimensions in other multiple-choice tests and performance assessments. Confirmatory factor analyses retrieved the 3 dimensions for a test composed of NELS:88, the Third International Mathematics and Science Study (TIMSS) and the National Assessment of Educational Progress (NAEP) multiple-choice items, and the NELS:88 items alone. We used the latter because factor correlations were lower. We administered 3 reasoning-dimension-linked performance assessments to a subsample of 35 students from the main study. Performance assessments correlated moderately with each other and NELS:88 reasoning scores; the 2 methods partially converged on the dimensions. Performance scores scattered across multiple-choice scores due to the broad reasoning and knowledge spectrum tapped. Findings are tentative; larger samples and cognitive studies of reasoning and knowledge might shed light on convergence.
NNWarp: Neural Network-Based Nonlinear Deformation

NNWarp is a highly re-usable and efficient neural network (NN) based nonlinear deformable simulation framework. Unlike other machine learning applications such as image recognition, where different inputs have a uniform and consistent format (e.g., an array of all the pixels in an image), the input for deformable simulation is quite variable, high-dimensional, and parametrization-unfriendly. Consequently, even though the neural network is known for its rich expressivity of nonlinear functions, directly using an NN to reconstruct the force-displacement relation for general deformable simulation is nearly impossible. NNWarp obviates this difficulty by partially restoring the force-displacement relation via warping the nodal displacement simulated using a simplistic constitutive model–the linear elasticity. In other words, NNWarp yields an incremental displacement fix per mesh node based on a simplified (therefore incorrect) simulation result other than synthesizing the unknown displacement directly. We introduce a compact yet effective feature vector including geodesic, potential and digression to sort training pairs of per-node linear and nonlinear displacement. NNWarp is robust under different model shapes and tessellations. With the assistance of deformation substructuring, one NN training is able to handle a wide range of 3D models of various geometries. Thanks to the linear elasticity and its constant system matrix, the underlying simulator only needs to perform one pre-factorized matrix solve at each time step, which allows NNWarp to simulate large models in real time.
SSHeW study protocol: does slip resistant footwear reduce slips among healthcare workers? A randomised controlled trial

Introduction Slips, trips and falls are common causes of injuries in the workplace. It is estimated that in Great Britain, nearly 1 million days are taken off work due to these injuries. There is some evidence to suggest this accident burden could be reduced by the use of slip resistant footwear. This protocol describes a multicentre trial investigating the effectiveness and cost-effectiveness of slip resistant footwear to prevent slips in National Health Service (NHS) staff working in clinical, general or catering environments. Methods and analysis A two-arm, randomised controlled trial conducted within England, with 4400 NHS staff, aged 18 years and above, who adhere to a dress code policy and work in a clinical, catering or general hospital environment. Participants will be randomised 1:1 to the intervention or waiting list control group. The intervention group will be offered a pair of 5-star GRIP rated slip resistant footwear. The control group will be offered the footwear at the end of the trial. The primary outcome is the incidence rate of self-reported slips in the workplace over a 14-week period, as reported via weekly text messages. Secondary outcomes include: time to first slip/fall, proportion of participants who slip and fall over 14 weeks and incidence rate of falls resulting from and not resulting from a slip in the workplace over 14 weeks. An economic evaluation will assess cost-effectiveness, in terms of cost per quality-adjusted life year gained. A nested qualitative study will explore the acceptability of the footwear and compliance. Ethics and dissemination This protocol received a favourable ethical opinion from the University of York, Department of Health Sciences Research Governance Committee. The trial results will be published in peer-reviewed journals and at conferences. A summary of the findings will be made available to participants. Trial registration number ISRCTN33051393; Pre results.
Speech-language pathologists in paediatric palliative care: a Delphi study protocol

Background Given the dearth of literature and no clinical practice guidelines written for speech-language pathologists (SLPs) working in paediatric palliative care (PPC), a need has been identified to explore the scope of clinical practice and strategies used by SLPs. Objective This study aims to undertake an international investigation into the role and scope of practice of SLPs working in PPC to develop consensus-driven ‘Recommendations for Speech-Language Pathologists in Paediatric Palliative Care Teams’ (ReSP3CT). Methods A modified Delphi process will be used to synthesise consensus-based statements from SLPs in six different countries about their role and practice working in PPC. Initially, preliminary survey data will be collected from SLPs to obtain demographic and caseload information. Respondents will then be invited to participate in an in-depth interview to explore common and unique themes that emerge from the online survey. Participants from the interview will then ‘opt-in’ to become Delphi panel members and receive questionnaires comprising statements for agreement over multiple rounds. Statements will be based on common themes that arise from the literature review, survey and interview data. The Delphi process for each statement will stop if statements achieve ≥ 70 % agreement and an IQR of ≤ 1 (maximum of five rounds). Conclusion This is the first study to investigate the role and practice of SLPs in PPC across internationally accepted scope of practice areas. The study will use existing frameworks for statistical analysis and a mixed-methods approach to aid in the synthesis of statements/recommendations for international consensus.