Miracle-dz/UniFAR-FTUs huggingface dataset:
Disease-Modifying Antirheumatic Drug Use and Its Effect on Long-term Opioid Use in Patients With Rheumatoid Arthritis

Background/Objectives The prevalence of chronic pain is high in patients with rheumatoid arthritis (RA), increasing the risk for opioid use. The objective of this study was to assess disease-modifying antirheumatic drug (DMARD) use and its effect on long-term opioid use in patients with RA. Methods This cohort study included Medicare beneficiaries with diagnosis of RA who received at least 30-day consecutive prescription of opioids in 2017 (n = 23,608). The patients were grouped into non-DMARD and DMARD users, who were further subdivided into regimens set forth by the American College of Rheumatology. The outcome measured was long-term opioid use in 2018 defined as at least 90-day consecutive prescription of opioids. Dose and duration of opioid use were also assessed. A multivariable model identifying factors associated with non-DMARD use was also performed. Results Compared with non-DMARD users, the odds of long-term opioid use were significantly lower among DMARD users (odds ratio, 0.89; 95% confidence interval, 0.83–0.95). All regimens except non–tumor necrosis factor biologic + methotrexate were associated with lower odds of long-term opioid use relative to non-DMARD users. The mean total morphine milligram equivalent, morphine milligram equivalent per day, and total days of opioid use were lower among DMARD users compared with non-DMARD users. Older age, male sex, Black race, psychiatric and medical comorbidities, and not being seen by a rheumatologist were significantly associated with non-DMARD use. Conclusion Disease-modifying antirheumatic drug use was associated with lower odds of long-term opioid use among RA patients with baseline opioid prescription. Factors associated with non-DMARD use represent a window of opportunity for intervention to improve pain-related quality of life in patients living with RA.
Prevalence of nowhere analytic functions

We say that f is analytic at x0 if T (f, x0) converges to f on an open neighbourhood of x0. If this is not the case, we say that f has a singularity at x0. A function with a singularity at each point of an interval is called nowhere analytic on the interval. Several examples of infinitely differentiable nowhere analytic functions exist and generic results have already been obtained ([2, 3, 5, 6, 7]). This question of genericity can also be treated using the concept of prevalence, introduced by Hunt, Sauer and Yorke ([4]). In the talk, we show that the set of nowhere analytic functions is prevalent in C∞([0, 1]). More precise results are obtained using Gevrey classes ([1]). This study is then extended to the classes of quasi-analytic functions.
Recent updates in therapeutic approach using tolvaptan for autosomal dominant polycystic kidney disease

As a genetic disease, there has been a long-standing effort to identify therapeutic options for autosomal dominant polycystic kidney disease (ADPKD). Following the development of tolvaptan, a vasopressin 2 receptor antagonist, the treatment strategy for ADPKD patients with rapid disease progression has been changed with a disease-targeted approach. Tolvaptan showed significant efficacy in preserving kidney function and reducing the total kidney volume (TKV) growth rate. These effects were especially pronounced in patients with more severe clinical phenotypes, such as higher TKV and rapidly declining kidney function. Despite the therapeutic effects of tolvaptan, aquaretic symptoms are unavoidable side effects related to the mechanism of the drug and are also directly related to the quality of life. A shared decision-making process could be a valuable strategy for reducing the incidence of side effects and improving medication adherence. Herein, we aimed to review overall clinical trials for applying tolvaptan and suggest important factors during the shared decision-making process.
CD4 Effector TCR Avidity for Peptide on APC Determines the Level of Memory Generated.

Initial TCR affinity for peptide Ag is known to impact the generation of memory; however, its contributions later, when effectors must again recognize Ag at 5-8 d postinfection to become memory, is unclear. We examined whether the effector TCR affinity for peptide at this "effector checkpoint" dictates the extent of memory and degree of protection against rechallenge. We made an influenza A virus nucleoprotein (NP)-specific TCR transgenic mouse strain, FluNP, and generated NP-peptide variants that are presented by MHC class II to bind to the FluNP TCR over a broad range of avidity. To evaluate the impact of avidity in vivo, we primed naive donor FluNP in influenza A virus-infected host mice, purified donor effectors at the checkpoint, and cotransferred them with the range of peptides pulsed on activated APCs into second uninfected hosts. Higher-avidity peptides yielded higher numbers of FluNP memory cells in spleen and most dramatically in lung and draining lymph nodes and induced better protection against lethal influenza infection. Avidity determined memory cell number, not cytokine profile, and already impacted donor cell number within several days of transfer. We previously found that autocrine IL-2 production at the checkpoint prevents default effector apoptosis and supports memory formation. Here, we find that peptide avidity determines the level of IL-2 produced by these effectors and that IL-2Rα expression by the APCs enhances memory formation, suggesting that transpresentation of IL-2 by APCs further amplifies IL-2 availability. Secondary memory generation was also avidity dependent. We propose that this regulatory pathway selects CD4 effectors of highest affinity to progress to memory.
Threshold optimization according to the restricted Bayes criterion in decentralized detection problems

In this paper, the restricted Bayes approach is studied in a decentralized detection problem. All decisions on which the hypothesis is true are made by local sensors through conditionally independent observations. Then these decisions are transmitted to the fusion center for thenal decision. In the conventional approach, all thresholds of local sensors and the fusion center are considered as deterministic variables and optimized according to the given criterion for given test statistics of local sensors and the fusion center. In this paper, it is shown that setting thresholds as random variables instead of deterministic ones can improve the performance according to the restricted Bayes criterion. It is proved that optimal random thresholds are dependent on each other, and the probability density function of each one consists of at most two point masses. Two methods for the implementation of this scheme are proposed. A necessary and sufficient condition for improvability of the conventional approach through replacing optimal deterministic thresholds by optimal random ones is derived. Finally, theoretical results are investigated through simulations.
Die Möglichkeiten der Phytotherapie bei entzündlichen Hautkrankheiten

Zusammenfassung In den letzten Jahren wurden einige neue pflanzliche Arzneimittel, Medizinprodukte und Hautpflegemittel für die topische Behandlung von entzündlichen Hauterkrankungen entwickelt. Besonders gut belegt ist die Wirksamkeit von Inhaltsstoffen aus dem Süßholz bei der atopischen Dermatitis und von Indigo-Extrakten bei der Psoriasis. Ein neuer vielversprechender Therapieansatz zur äußerlichen Behandlung einer geschädigten Hautbarriere sind Bitterstoffe, die an Bitterstoff-Rezeptoren der Haut binden und die Keratin- und Lipidsynthese der Keratinozyten anregen. Weitere pflanzliche Wirkstoffe für die Behandlung von Rosazea und Akne vulgaris werden ebenfalls besprochen, wie z. B. Extrakte aus dem Grüntee, der Blutwurz oder dem Hopfen.
Numerical simulation of microfluidic mixing

This report describes the mixing of fluids in microchannels, both in steady state, and for time dependent systems. A dimensionless parameter describing the mixing in steady state is found and the influence of channel obstacles versus channel height is examined. An AC potential is applied to the fluid in a time dependant simulation and the effect on mixing is studied as a function of frequency, fluidic velocity and spatial modulation of the AC potential.
Monitoring Valence with Facial EMG Sensors using Machine Learning

Affective Computing is an essential field of study with many impactful applications, from remote solutions for timely detection and improved management of mental health to improved human-computer interaction in the physical world and the metaverse. In this study, we explore the usage of a novel facial mask equipped with seven surface electromyography (sEMG) sensors to monitor subjective valence. We collected data from 30 participants who watched 20 affective videos (five exciting videos, five positive videos, five neutral videos, and five negative videos). The sensor data was filtered, and EMG features were extracted, including statistical and frequency-based features. The exploratory analysis indicated that the activations of the muscles associated with positive affect (left/right orbicularis and left/right zygomaticus) increased during positive periods compared to negative ones. Similarly, the activation of the corrugator muscle (related to negative affect) was increased during negative periods. This trend was also confirmed by the SHAP analysis performed on a machine-learning model for classifying 3-class valence (negative, neutral, and positive). On the test data of five unseen participants, the model achieved an accuracy of 63% and an F1-score of 49%. The class imbalance seemed to be one of the more significant challenges the ML models faced. The results confirmed the relationship between sEMG sensing and subjective valence but also showed that monitoring valence in real-time is challenging and requires more advanced approaches.
WellComp 2022: Fifth International Workshop on Computing for Well-Being

With the advancements in ubiquitous computing, ubicomp technology has deeply spread into our daily lives, including office work, home and house-keeping, health management, transportation, or even urban living environments. Furthermore, beyond the initial metrics commonly applied in computing, such as “efficiency” and “productivity”, the benefits that people (users) get from well-being-aware ubiquitous technology have been greatly emphasized in the recent years. Through the fifth “WellComp” (Computing for Well-being) workshop, we will discuss and debate the contribution of ubiquitous computing towards users’ well-being covering both physical, mental, and social wellness (and the combinations thereof), from the viewpoints of various different layers of computing. Organized by a diverse international team of ubicomp researchers, WellComp 2022 will bring together researchers and practitioners from both academia and industry to explore versatile topics related to well-being and ubiquitous computing.
EmoTracer: A Wearable Physiological and Psychological Monitoring System With Multi-modal Sensors

The monitoring of physical and mental health has been the focus of attention. At the same time, with the advancement of wearable sensors and information acquisition technology, there is no longer any satisfaction with the centralized, fixed-point traditional physiological indicator collection methods. Physiological indicator monitoring systems based on portable devices and mobile collection are gradually becoming a priority for research. Based on these needs, we present a wearable human physiological indicator monitoring system called EmoTracer. Through the self-developed and well-designed wearable collection device, body temperature, blood oxygen, heart rate and electrical skin signals are transmitted to the mobile terminal via Bluetooth communication; the mobile terminal then stores and calculates the data and displays the changes in physiological indicators in a visualized form in real-time. At the same time, we conducted an emotion recognition experiment (N = 10) based on our device, which can reach an average accuracy of 91.23%, making a preliminary exploration in the direction of emotion perception.
Enhancing the Future Impact of Six Sigma Management

Abstract Though Six Sigma has proven to be an effective framework for performance improvement in a wide variety of industries for many years, the future development of Six Sigma needs to be explored. In this paper, we briefly review the background and development of Six Sigma and suggest ways to enhance and extend the effectiveness of Six Sigma in the coming years. We propose the future development of Six Sigma from three perspectives: strategy, integration and innovation. Some challenges are addressed for Six Sigma’s spreading to service systems. Research shows that when Six Sigma becomes more pervasive and inclusive, it will offer opportunities for excellence in performance in the production of goods and services in a wide variety of businesses.
Excerpt of ToothSonic: Earable Authentication via Acoustic Toothprint

Earables (ear wearable) are rapidly emerging as a new platform to enable a variety of personal applications. The traditional authentication methods thus become less applicable and inconvenient for earables due to their limited input interface. Earables, however, often feature rich around the head sensing capability that can be leveraged to capture new types of biometrics. In this work, we propose ToothSonic that leverages the toothprint-induced sonic effect produced by a user performing teeth gestures for user authentication. In particular, we design several representative teeth gestures that can produce effective sonic waves carrying the information of the toothprint. To reliably capture the acoustic toothprint, it leverages the occlusion effect of the ear canal and the inward-facing microphone of the earables. It then extracts multi-level acoustic features to represent the intrinsic acoustic toothprint for authentication. The key advantages of ToothSonic are that it is suitable for earables and is resistant to various spoofing attacks as the acoustic toothprint is captured via the private teeth-ear channel of the user that is unknown to others. Our preliminary studies with 20 participants show that ToothSonic achieves 97% accuracy with only three teeth gestures.
Dating ancient humans splits by estimating Poisson rates from mitochondrial DNA parity samples

We tackle the problem of estimating species divergence times, given a genome sequence from each species and a large known phylogenetic tree with a known structure (typically from one of the species). The number of transitions at each site from the first sequence to the other is assumed to be Poisson distributed, and only the parity of the number of transitions is observed. The detailed phylogenetic tree contains information about the transition rates in each site. We use this formulation to develop and analyze multiple estimators of the divergence between the species. To test our methods, we use mtDNA substitution statistics from the well-established Phylotree as a baseline for data simulation such that the substitution rate per site mimics the real-world observed rates. We evaluate our methods using simulated data and compare them to the Bayesian optimizing software BEAST2, showing that our proposed estimators are accurate for a wide range of divergence times and significantly outperform BEAST2. We then apply the proposed estimators on Neanderthal, Denisovan, and Chimpanzee mtDNA genomes to better estimate their TMRCA (Time to Most Recent Common Ancestor) with modern humans and find that their TMRCA is sub-stantially later, compared to values cited recently in the literature.
Whither unisensory olfactory cortex: processing of visual and auditory stimuli in olfactory cortex, independently of odor associations

Primary sensory cortices process atypical sensory objects in some conditions, which brings into question their presumed sensory specificity. Whether this atypical sensory processing originates from true atypical sensory processing or from cross-modal associations to objects is not known. Visual/auditory objects typically have strong reciprocal associations; hence, it is difficult to address this question in these modalities. Here, we instead use the olfactory system as a model system. We show that even in total absence of any odor reference, the posterior piriform cortex (PPC; odor object processing) is activated by both sounds and pictures of objects. This activation is independent of the objects’ odor associations, thereby demonstrating that the activity is not due to cross-modal associations. In the anterior piriform cortex (APC; low-level odor processing) we found activation by sounds, again independent of odor associations. Analogously, we found clear cross-modal effects in visual and auditory brain regions: Pictures activated higher-level auditory cortex and caused a decreased signal in primary auditory cortex, whereas sounds activated primary visual cortex and caused a decreased signal in higher-level visual cortex. Our findings demonstrate an atypical sensory processing that is independent of cross-modal associations in olfactory cortices and contribute to a more nuanced view of modality specificity in olfactory, auditory, and visual cortices.
Collagen and actin network mediate antiviral immunity against Orsay in C. elegans intestinal cells

C. elegans is a free-living nematode that is widely used as a small animal model for studying fundamental biological processes and disease mechanisms. Since the discovery of the Orsay virus in 2011, C. elegans also holds the promise of dissecting virus-host interaction networks and innate antiviral immunity pathways in an intact animal. Orsay primarily targets the worm intestine, causing enlarged intestinal lumen as well as visible changes to infected cells such as liquefaction of cytoplasm and rearrangement of the terminal web. Previous studies of Orsay identified that C. elegans is able to mount antiviral responses by DRH-1/RIG-I mediated RNA interference and Intracellular Pathogen Response, a uridylyltransferase that destabilizes viral RNAs by 3′ end uridylation, and ubiquitin protein modifications and turnover. To comprehensively search for novel antiviral pathways in C. elegans, we performed genome-wide RNAi screens by bacterial feeding using existing bacterial RNAi libraries covering 94% of the entire genome. Out of the 106 antiviral genes identified, we investigated those in three new pathways: collagens, actin remodelers, and epigenetic regulators. By characterizing Orsay infection in RNAi and mutant worms, our results indicate that collagens likely form a physical barrier in intestine cells to inhibit viral infection by preventing Orsay entry. Furthermore, evidence suggests that the intestinal actin (act-5), which is regulated by actin remodeling proteins (unc-34, wve-1 and wsp-1), a Rho GTPase (cdc-42) and chromatin remodelers (nurf-1 and isw-1), also provides antiviral immunity against Orsay possibly through another physical barrier presented as the terminal web.
Contrasting walking styles map to discrete neural substrates in the mouse brainstem

Walking is a slow gait which is particularly adaptable to meet internal or external needs and is prone to maladaptive alterations that lead to gait disorders. Alterations can affect speed, but also style (the way one walks). While slowed speed may signify the presence of a problem, style represents the hallmark essential for clinical classification of gait disorders. However, it has been challenging to objectively capture key stylistic features while uncovering neural substrates driving these features. Here we revealed brainstem hotspots that drive strikingly different walking styles by employing an unbiased mapping assay that combines quantitative walking signatures with focal, cell type specific activation. We found that activation of inhibitory neurons that mapped to the ventromedial caudal pons induced slow motion-like style. Activation of excitatory neurons that mapped to the ventromedial upper medulla induced shuffle-like style. Contrasting shifts in walking signatures distinguished these styles. Activation of inhibitory and excitatory neurons outside these territories or of serotonergic neurons modulated walking speed, but without walking signature shifts. Consistent with their contrasting modulatory actions, hotspots for slow-motion and shuffle-like gaits preferentially innervated different substrates. These findings lay the basis for new avenues to study mechanisms underlying (mal)adaptive walking styles and gait disorders. Graphical abstract
Immune heterogeneity in cardiovascular diseases from a single-cell perspective

A variety of immune cell subsets occupy different niches in the cardiovascular system, causing changes in the structure and function of the heart and vascular system, and driving the progress of cardiovascular diseases (CVDs). The immune cells infiltrating the injury site are highly diverse and integrate into a broad dynamic immune network that controls the dynamic changes of CVDs. Due to technical limitations, the effects and molecular mechanisms of these dynamic immune networks on CVDs have not been fully revealed. With recent advances in single-cell technologies such as single-cell RNA sequencing, systematic interrogation of the immune cell subsets is feasible and will provide insights into the way we understand the integrative behavior of immune populations. We no longer lightly ignore the role of individual cells, especially certain highly heterogeneous or rare subpopulations. We summarize the phenotypic diversity of immune cell subsets and their significance in three CVDs of atherosclerosis, myocardial ischemia and heart failure. We believe that such a review could enhance our understanding of how immune heterogeneity drives the progression of CVDs, help to elucidate the regulatory roles of immune cell subsets in disease, and thus guide the development of new immunotherapies.
Stephen Massey: a career in visual neuroscience

This review is a memoir by Dr. Stephen C. Massey’s longtime collaborator, Dr. Stephen L. Mills, and written, for the most part, in the first person. It also serves as an introduction to the virtual festschrift to celebrate Dr. Massey’s retirement. and. The references cited here are only a few of the highlights of Dr. Massey’s distinguished career. A complete list is found here: https://pubmed.ncbi. nlm.nih. gov/? term=massey+sc+%28retina+or+photoreceptors%29&sort=date.
Scientometric analysis of lipid metabolism in breast neoplasm: 2012–2021

Introduction: In recent years, more and more studies have proved that lipid metabolism plays an essential role in breast cancer’s proliferation and metastasisand also has a specific significance in predicting survival. Methods: This paper collected data from 725 publications related to lipid metabolism in breast neoplasm from 2012 to 2021 through the Web of Science Core Collection database. Bibliometrix, VOSviewer, and CiteSpace were used for the scientometrics analysis of countries, institutions, journals, authors, keywords, etc. Results: The number of documents published showed an increasing trend, with an average annual growth rate of 14.49%. The United States was the most productive country (n = 223, 30.76%). The journals with the largest number of publications are mostly from developed countries. Except for the retrieved topics, “lipid metabolism” (n = 272) and “breast cancer” (n = 175), the keywords that appeared most frequently were “expression” (n = 151), “fatty-acid synthase” (n = 78), “growth” (n = 72), “metabolism” (n = 67) and “cells“ (n = 66). Discussion: These findings and summaries help reveal the current research status and clarify the hot spots in this field.