Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Binding Analysis ofN-Acetylneuraminic Acid in Bovine Serum Albumin and Human α-1 Acid Glycoprotein

The present study focuses on the determination of the biologically significant N-acetylneuraminic acid (NANA) drug binding interaction mechanism between bovine serum albumin (BSA) and human α-1 acid glycoprotein (HAG) using various optical spectroscopy and computational methods. The steady state fluorescence spectroscopy result suggests that the fluorescence intensity of BSA and HAG was quenched by NANA in a static mode of quenching. Further time-resolved emission spectroscopy measurements confirm that mode of quenching mechanism of NANA in the BSA and HAG system. The FT-IR, excitation-emission matrix and circular dichroism (CD) analysis confirms the presence of NANA in the HAG, BSA system, and fluorescence resonance energy transfer analysis shows that NANA transfers energy between the HAG and BSA system. The molecular docking result shows good binding affinity in both protein complexes, and further molecular dynamics simulations and charge distribution analysis were performed to gain more insight into the binding interaction mechanism of NANA in the HAG and BSA complex.
Functional optical coherence tomography of retinal photoreceptors

Age-related macular degeneration (AMD) is the leading cause of severe vision loss and legal blindness. It is known that retinal photoreceptors are the primary target of AMD. Therefore, a reliable method for objective assessment of photoreceptor function is needed for early detection and reliable treatment evaluation of AMD and other eye diseases such as retinitis pigmentosa that are known to cause photoreceptor dysfunctions. Stimulus-evoked intrinsic optical signal (IOS) changes promise a unique opportunity for objective assessment of physiological function of retinal photoreceptor and inner neurons. Instead of a comprehensive review, this mini-review is to provide a brief summary of our recent in vitro and in vivo optical coherence tomography (OCT) studies of stimulus-evoked IOS changes in animal retinas. By providing excellent axial resolution to differentiate individual retinal layers, depth-resolved OCT revealed rapid IOS response at the photoreceptor outer segment. The fast photoreceptor-IOS occurred almost right away (∼ 2 ms) after the onset of retinal stimulation, differentiating itself from slow IOS changes correlated with inner neural and hemodynamic changes. Further development of the functional IOS instruments and retinal stimulation protocols may provide a feasible solution to pursue clinical application of functional IOS imaging for objective assessment of human photoreceptors. Impact statement Retinal photoreceptors are the primary target of age-related macular degeneration (AMD) which is the leading cause of severe vision loss and legal blindness. An objective method for functional assessment of photoreceptor physiology can benefit early detection and better treatment evaluation of AMD and other eye diseases that are known to cause photoreceptor dysfunctions. This article summarizes in vitro study of IOS mechanisms and in vivo demonstration of IOS imaging of intact animals. Further development of the functional IOS imaging may provide a revolutionary solution to achieve objective assessment of human photoreceptors.
College Students and Eating Habits: A Study Using An Ecological Model for Healthy Behavior

Overweightness and obesity rates have increased dramatically over the past few decades and they represent a health epidemic in the United States (US). Unhealthy dietary habits are among the factors that can have adverse effects on weight status in young adulthood. The purpose of this explorative study was to use a qualitative research design to analyze the factors (barriers and enablers) that US college students perceived as influencing healthy eating behaviors. A group of Cornell University students (n = 35) participated in six semi-structured focus groups. A qualitative software, CAQDAS Nvivo11 Plus, was used to create codes that categorized the group discussions while using an Ecological Model. Common barriers to healthy eating were time constraints, unhealthy snacking, convenience high-calorie food, stress, high prices of healthy food, and easy access to junk food. Conversely, enablers to healthy behavior were improved food knowledge and education, meal planning, involvement in food preparation, and being physically active. Parental food behavior and friends’ social pressure were considered to have both positive and negative influences on individual eating habits. The study highlighted the importance of consulting college students when developing healthy eating interventions across the campus (e.g., labeling healthy food options and information campaigns) and considering individual-level factors and socio-ecological aspects in the analysis.
Respectful leadership: Reducing performance challenges posed by leader role incongruence and gender dissimilarity

We investigate how respectful leadership can help overcome the challenges for follower performance that female leaders face when working (especially with male) followers. First, based on role congruity theory, we illustrate the biases faced by female leaders. Second, based on research on gender (dis-)similarity, we propose that these biases should be particularly pronounced when working with a male follower. Finally, we propose that respectful leadership is most conducive to performance in female leader–male follower dyads compared with all other gender configurations. A multi-source field study (N = 214) provides partial support for our hypothesis. While our hypothesized effect was confirmed, respectful leadership seems to be generally effective for female leaders irrespective of follower gender, thus lending greater support in this context to the arguments of role congruity rather than gender dissimilarity.
Aerobic Fitness Level Moderates the Association Between Cannabis Use and Executive Functioning and Psychomotor Speed Following Abstinence in Adolescents and Young Adults

Abstract Objectives: The high rate of cannabis (CAN) use in emerging adults is concerning given prior research suggesting neurocognitive deficits associated with CAN use in youth. Regular CAN use downregulates endocannabinoid activity, while aerobic exercise upregulates cannabinoid receptor 1 activity and releases endocannabinoids. Here we investigate the influence of regular CAN use on neuropsychological performance, and whether aerobic fitness moderates these effects. Methods: Seventy-nine young adults (37 CAN users) aged 16–26 participated. Groups were balanced for aerobic fitness level. Exclusion criteria included: left-handedness, past-year independent Axis-I disorders, major medical/neurologic disorders, prenatal issues, or prenatal alcohol/illicit drug exposure. After 3 weeks of abstinence, participants completed a neuropsychological battery and a maximal oxygen consumption test (VO2 max). Multiple regressions tested whether past-year CAN use, VO2 max, and CAN*VO2 max interaction predicted neuropsychological performance, controlling for past-year alcohol use, cotinine, gender, and depression symptoms. Results: Increased CAN use was associated with decreased performance on working memory and psychomotor tasks. High aerobic fitness level was related to better performance on visual memory, verbal fluency, and sequencing ability. CAN*VO2 max predicted performance of psychomotor speed, visual memory, and sequencing ability. Conclusions: Following monitored abstinence, increased CAN use was associated with poorer performance in working memory and psychomotor speed. Higher aerobic fitness level moderated the impact of CAN on visual memory, executive function and psychomotor speed, as more aerobically fit CAN users demonstrated better performance relative to low-fit users. Therefore, aerobic fitness may present an affordable and efficacious method to improve cognitive functioning in CAN users. (JINS, 2019, 25, 134–145)
Produtividade e características físico-químicas dos frutos da lima ácida Tahiti sob diferentes disposições de microaspersores.

O adequado manejo de agua de irrigacao e fundamental para maximizacao da producao e melhoria da qualidade dos frutos da lima acida 'Tahiti' no semiarido. O trabalho visou avaliar a influencia de diferentes disposicoes de microaspersores, na produtividade e caracteristicas fisico-quimicas dos frutos, nos diferentes quadrantes da planta, num pomar de lima acida 'Tahiti', com quatro anos, plantada no espacamento de 5,0 x 7,0 m. O delineamento experimental foi em blocos casualizados, sendo: T1 ? um microaspersor por planta, localizado entre plantas ao longo da fileira; T2 ? um microaspersor para duas plantas, tambem ao longo da fileira; e T3 ? um microaspersor por planta, localizado a 0,3 m da planta, e seis repeticoes. Foram consideradas parcelas subdivididas, nas quais se avaliou os frutos nos quadrantes norte, sul, leste e oeste da planta. Os valores de produtividade media apresentaram diferenca significativa entre os tratamentos T2 (19.506 kg ha-1) e T1 (13.545 kg ha-1). Os frutos do T3 e T2 apresentaram teor de acido ascorbico superior aos do T1. Os valores de solidos soluveis, peso medio de frutos e acido citrico apresentaram diferencas significativas entre os quadrantes, demonstrando influencia da disposicao dos microaspersores sobre os parâmetros fisico-quimicos dos frutos da lima acida 'Tahiti', em condicoes semiaridas de cultivo.
Assaying RNA structure with LASER-Seq

Abstract Chemical probing methods are crucial to our understanding of the structure and function of RNA molecules. The majority of chemical methods used to probe RNA structure report on Watson–Crick pairing, but tertiary structure parameters such as solvent accessibility can provide an additional layer of structural information, particularly in RNA-protein complexes. Herein we report the development of Light Activated Structural Examination of RNA by high-throughput sequencing, or LASER-Seq, for measuring RNA structure in cells with deep sequencing. LASER relies on a light-generated nicotinoyl nitrenium ion to form covalent adducts with the C8 position of adenosine and guanosine. Reactivity is governed by the accessibility of C8 to the light-generated probe. We compare structure probing by RT-stop and mutational profiling (MaP), demonstrating that LASER can be integrated with both platforms for RNA structure analyses. We find that LASER reactivity correlates with solvent accessibility across the entire ribosome, and that LASER can be used to rapidly survey for ligand binding sites in an unbiased fashion. LASER has a particular advantage in this last application, as it readily modifies paired nucleotides, enabling the identification of binding sites and conformational changes in highly structured RNA.
Applicability of tumor spheroids for in vitro chemosensitivity assays

ABSTRACT Introduction: Drug screening assays employing two-dimensional (2D) cultures of cancer cells have been largely replaced by three-dimensional (3D) multicellular tumor spheroid (MCTS) models which more closely represent patient’s tumors. The predictive power of the different MCTSs depends on source of the cells, techniques of preparation, and characteristics of the aggregates. Areas covered: The preparation of MCTSs and a comparison of the spheroids assembled from permanent cancer and patient-derived cell lines in respect to the correlation of their chemosensitivity to clinical responses are discussed. Spheroids formed in in vivo in pleural effusion and blood of cancer patients are presented as interesting sources for drug screening. Expert opinion: 3D tumor models for drug screening were adopted to increase the predictive power of assays for success in clinical trials. Cell lines which form dense spheroids differ in physical properties, gene expression, and chemosensitivity from 2D cultures. Still, most of these MCTS models lack characteristics of complex tumor tissues and have not been validated for their adequacy to select clinically useful drugs. Patient-derived spheroids from pleural effusion or blood, namely tumorospheres of circulating tumor cells, are MCTS models most similar to patient’s tumors.
Machine learning in protein engineering

Machine learning-guided protein engineering is a new paradigm that enables the optimization of complex protein functions. Machine-learning methods use data to predict protein function without requiring a detailed model of the underlying physics or biological pathways. They accelerate protein engineering by learning from information contained in all measured variants and using it to select variants that are likely to be improved. In this review, we introduce the steps required to collect protein data, train machine-learning models, and use trained models to guide engineering. We make recommendations at each stage and look to future opportunities for machine learning to enable the discovery of new protein functions and uncover the relationship between protein sequence and function.
Combined supraclavicular and superficial cervical plexus block for clavicle surgery

Background Clavicle fractures occur in 35% of shoulder girdle fractures. Surgical fixation is preferred, especially in young patients for optimal functional outcomes, while nondisplaced fractures are usually treated conservatively. Case A 38-year-old male patient was admitted to the emergency services with a fracture of the left clavicle following a fall. During the preoperative evaluation, the patient requested to be awake during the surgery. Combined supraclavicular and superficial cervical plexus block was performed under ultrasound guidance without complications and the patient experienced no pain. Conclusions This technique may avoid possible complications related to interscalene brachial plexus block. Future studies are required to confirm the safety and efficacy of this approach.
The Trp64Arg Polymorphism of the β3-Adrenergic Receptor Gene: Lack of association with NIDDM and features of insulin resistance syndrome

OBJECTIVE To investigate the association of the Trp64Arg polymorphism of the β3-adrenergic receptor gene with NIDDM and the features of insulin resistance syndrome in subjects from eastern Finland. RESEARCH DESIGN AND METHODS We determined the prevalence of the Trp64Arg polymorphism of the β3-adrenergic receptor gene by restriction fragment length polymorphism analysis in 110 patients with NIDDM (54 men and 56 women, age 63 ± 1 years, BMI 30.4 ± 0.5 kg/m2), in 183 patients with features of insulin resistance syndrome (103 men and 80 women, age 44 ± 0 years, BMI 31.1 ± 0.4 kb/m2), and in 82 normoglycemic control men (age 54 ± 1 years, BMI 26.3 ± 0.4 kg/m2). RESULTS The allele frequency of the Trp64Arg polymorphism of the β3-adrenergic receptor gene was similar in patients with NIDDM, in patients with insulin resistance syndrome, and in control subjects (0.08, 0.07, and 0.07, respectively; NS). In addition, this polymorphism was not associated with low resting metabolic rate, abdominal obesity, increased lipid oxidation, hypertension, or earlier development of NIDDM as previously described. Furthermore, in 82 normoglycemic male control subjects the Trp64Arg polymorphism was not associated with insulin resistance evaluated by the euglycemic-hyperinsulinemic clamp. CONCLUSIONS The Trp64Arg polymorphism of the beta β3-adrenergic receptor gene is unlikely to be a major genetic predisposer to NIDDM or insulin resistance syndrome in subjects from eastern Finland.
What Are PWDs (People With Diabetes) Doing Online? A Netnographic Analysis

Background: Social media have become a crucial channel for patient empowerment and peer support. New qualitative research underscores the fact that this “support” transcends mental health concerns, to actually provide patients with important practical tips and tricks for diabetes self-care, and product selection/decision-making information from peers. Methods: Netnography is an emerging methodology that applies an ethnographic research approach to studying activity on the social web. Researchers embed themselves in the online environment to take an observational “deep dive” into online conversations to identify themes, sentiments, and perceptions. Using this methodology in summer 2017, a team of researchers captured and analyzed hundreds of diabetes-related posts on prominent platforms Facebook, Twitter, YouTube, Instagram, Tumblr, Pinterest, Reddit, and Quora. Results: Our team identified 6 major trends, or “life themes,” in diabetes patient social media, providing insights into patient sentiments and needs. A topology of social media channels emerged, indicating which platforms are used most often for each life theme. Conclusions: Findings indicate that social media provides a significant source not only of moral support and camaraderie, but also critical education on thriving with diabetes. Importantly, we observed strong evidence of peer influence on patients’ therapy and diabetes technology purchasing decisions.
Overcomplete Transform Learning With the  $log$  Regularizer

Transform learning has been proposed as a new and effective formulation for analysis dictionary learning, where the <inline-formula> <tex-math notation="LaTeX">$\ell _{0}$ </tex-math></inline-formula> norm or the <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> norm are generally used as sparsity constraint. The sparse solutions can be obtained by the hard thresholding or the soft thresholding. The hard thresholding is actually a greedy algorithm, which only obtains the approximate solutions; while the soft thresholding has a certain bias for the large elements. In this paper, we propose to employ the <inline-formula> <tex-math notation="LaTeX">$log$ </tex-math></inline-formula> regularizer instead of the <inline-formula> <tex-math notation="LaTeX">$\ell _{0}$ </tex-math></inline-formula> norm and the <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> norm in the overcomplete transform learning problem. Our minimization problem is nonconvex due to the <inline-formula> <tex-math notation="LaTeX">$log$ </tex-math></inline-formula> regularizer. We propose to employ a simple proximal alternating minimization method, where a closed-form solution of the <inline-formula> <tex-math notation="LaTeX">$log$ </tex-math></inline-formula> function could be obtained based on the proximal operator. Hence, an efficient and fast overcomplete transform learning algorithm is developed, which iterates based on the analysis coding stage and the transform update stage. The proposed algorithm can obtain sparser solutions and more accurate results from the theoretical analysis. Numerical experiments verify that the proposed algorithm outperforms existing transform learning approaches with the <inline-formula> <tex-math notation="LaTeX">$\ell _{0}$ </tex-math></inline-formula> norm or the <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> norm. Furthermore, the proposed algorithm is on par with the state-of-the-art image denoising algorithms.
Short-Term Intensive Insulin Therapy in Newly Diagnosed Type 2 Diabetes

OBJECTIVE —Type 2 diabetes is associated with defects in insulin secretion and insulin action. Hyperglycemia may aggravate these defects, a feature known as glucose toxicity. Previous studies have shown that acute correction of hyperglycemia in subjects with long-standing type 2 diabetes gives only short-term improvement in glycemic control after discontinuation of insulin. The current study attempts to identify any characteristics of patients with newly diagnosed type 2 diabetes (fasting glucose >11.0 mmol/l) who would have a long-term benefit, in terms of glycemic control, from a brief course of insulin therapy. RESEARCH DESIGN AND METHODS —A total of 16 subjects (52 ± 2 years old [range 36–64], BMI 30.8 ± 1.9 kg/m2) with newly diagnosed type 2 diabetes had a 2–3 week course of intensive insulin therapy that was then discontinued. RESULTS —Fasting glucose fell from 13.3 ± 0.7 to 7.0 ± 0.4 mmol/l, and this improvement was maintained at the 1-year follow-up (6.7 ± 0.3 mmol/l). The insulin area under the curve for the posttreatment oral glucose tolerance test also improved (8,251 ± 1,880 before therapy, 18,404 ± 4,040 directly after insulin therapy, and 42,368 ± 8,517 pmol · min at the 1-year follow-up). At 1 year, seven of the subjects maintained good glycemic control on diet therapy alone, eight required oral hypoglycemic agent (OHA) therapy, and one required insulin therapy. The distinguishing features of those who did not require OHA or insulin therapy were that they required less insulin during the active insulin therapy phase (0.37 ± 0.05 vs. 0.73 ± 0.07 units · kg−1 · day−1) and were able to attain a lower fasting serum glucose at the end of the period of insulin therapy (5.9 ± 0.3 vs. 7.7 ± 0.4 mmol/l). CONCLUSIONS —These results demonstrate that in newly diagnosed type 2 diabetes with elevated fasting glucose levels, a 2- to 3-week course of intensive insulin therapy can successfully lay a foundation for prolonged good glycemic control. The ease with which normoglycemia is achieved on insulin may predict those patients who can later succeed in controlling glucose levels with attention to diet alone.
Lecture Notes: Neurology, 8th edition

Edited by Lionel Ginsberg. Oxford: Oxford University Press, 2005, pp 184, £17.95 (softcover). ISBN 1405114371 What constitutes the “core knowledge” of neurology that all medical students should reasonably be expected to learn? This is a question that Lecture Notes: Neurology (LNN) and Essential Neurology (EN)—two stalwarts of the medical student library—continue to grapple with in their latest editions. EN, longer but with …
How Do We Get From Good to Great? The Need for Better Observation Studies of Creativity in Education

Without quality research using observation methods, it is difficult to understand creativity processes in action, especially in the field of education. But, what is the current state of these studies? Based on a review of 37 extant studies, we found that observation is surprisingly under-utilized, and that more rigorous observation studies of creativity processes in education are needed.
Accuracy Issues in Kalman Filtering State Estimation of Stiff Continuous-Discrete Stochastic Models Arisen in Engineering Research

This paper aims at exploring accuracy of Kalman-like filters. Its particular interest lies in estimation of stochastic systems whose drift coefficients expose a stiff behavior. The latter means that the Jacobian of the drift coefficient in such a continuous-discrete system, which is presented by an Itô-type stochastic differential equation (SDE) for modeling the plant’s dynamic behavior and a discrete-time equation for simulating its measurement process, has large eigenvalues at the solution trajectory. Here, we employ the so-called “discrete-discrete” approach, which is grounded in SDE discretization schemes, and compare the outcome accuracy of EKF-, CKF- and UKF-type methods when these are based on the Euler-Maruyama and Itô-Taylor discretizations of the strong convergence orders 0.5 and 1.5 and applied for estimating the Van der Pol oscillator and Oregonator reaction models. We evidence that state estimation errors committed in our stiff stochastic scenarios are sensitive to both the type of Kalman filtering method utilized and the SDE discretization scheme implemented. So these must be chosen carefully in accurate and robust state estimation algorithms intended for treating stiff continuous-discrete stochastic systems.