Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatiotemporal characteristics of lower back muscle fatigue during a ten minutes endurance test at 50% upper body weight in healthy inactive, endurance, and strength trained subjects

In modern developed societies, heavy physical demands are decreasing and getting replaced by longer periods of static, low-exertion activities such as sitting or standing. To counteract this lack of physical activity, more and more people are engaging in physical activity through exercise and training. Virtually opposite training modalities are endurance and strength. We asked if back muscle endurance capacity is influenced by training mode. 38 healthy male subjects (age range 19–31 years, mean age 22.6 years) were investigated: sedentary (Control, n = 12), endurance trained (ET, n = 13), and strength trained participants (ST, n = 13). They underwent a ten-minutes isometric extension task at 50% of their upper body weight. Surface EMG was measured in the low-back region utilizing quadratic 4*4 monopolar electrode montages per side. Relative amplitude and mean frequency changes were analysed with respect to electrode position and group during the endurance task. Eight ST subjects failed to complete the endurance task. Relative amplitude and frequency changes were largest in the ST group, followed by Control and ET groups (amplitude: F 6.389, p 0.004, frequency: F 11.741, p<0.001). Further, independent of group largest amplitude increase was observed for the most upper and laterally positioned electrodes. Mean frequency changes showed no systematic spatial distribution pattern. Although, in the light of an aging population, strength training has its merits our results question the functional suitability of frequent and isolated high-impact strength training for everyday endurance requirements like doing the dishes. Fatigue related amplitude elevations are systematically distributed in the back region, showing least fatigue signs for the most caudal and medial, i.e. the lumbar paravertebral region.
Constant mean curvature surfaces and loop groups.

In this paper we Start from the observation that formally the Frenet equations of cmc surfaces in i? (and thus the Solutions to the sinh-Gordon equation) can be obtained from a loop group via a natural Riemann-Hilbert Splitting. The first goal of this paper is to consider Banach loop groups and show that the corresponding cmc surfaces (equivalently, Solutions to the sinh-Gordon equation) form Banach manifolds ^(r, R)9 where 0 < r ̂ l ^ R. This is done in the first three chapters. In §4 we discuss the vector fields un(co) and t^(co) considered by Pinkall and Sterling in [10]. We show that they correspond to a hierarchy of vector fields naturally associated with the loop groups and the Riemann-Hilbert Splitting occurring in our approach. Finally, in § 5 we show that all real finite type Solutions are contained in the union of our Banach manifolds £f(r, R). In particular, every cmc torus in AP is contained in some ! (r, R).
Splicing of branchpoint-distant exons is promoted by Cactin, Tls1 and the ubiquitin-fold-activated Sde2

Abstract Intron diversity facilitates regulated gene expression and alternative splicing. Spliceosomes excise introns after recognizing their splicing signals: the 5′-splice site (5′ss), branchpoint (BP) and 3′-splice site (3′ss). The latter two signals are recognized by U2 small nuclear ribonucleoprotein (snRNP) and its accessory factors (U2AFs), but longer spacings between them result in weaker splicing. Here, we show that excision of introns with a BP-distant 3′ss (e.g. rap1 intron 2) requires the ubiquitin-fold-activated splicing regulator Sde2 in Schizosaccharomyces pombe. By monitoring splicing-specific ura4 reporters in a collection of S. pombe mutants, Cay1 and Tls1 were identified as additional regulators of this process. The role of Sde2, Cay1 and Tls1 was further confirmed by increasing BP–3′ss spacings in a canonical tho5 intron. We also examined BP-distant exons spliced independently of these factors and observed that RNA secondary structures possibly bridged the gap between the two signals. These proteins may guide the 3′ss towards the spliceosome's catalytic centre by folding the RNA between the BP and 3′ss. Orthologues of Sde2, Cay1 and Tls1, although missing in the intron-poor Saccharomyces cerevisiae, are present in intron-rich eukaryotes, including humans. This type of intron-specific pre-mRNA splicing appears to have evolved for regulated gene expression and alternative splicing of key heterochromatin factors.
Structure of the HOPS tethering complex, a lysosomal membrane fusion machinery

Lysosomes are essential for cellular recycling, nutrient signaling, autophagy, and pathogenic bacteria and viruses invasion. Lysosomal fusion is fundamental to cell survival and requires HOPS, a conserved heterohexameric tethering complex. On the membranes to be fused, HOPS binds small membrane-associated GTPases and assembles SNAREs for fusion, but how the complex fulfills its function remained speculative. Here, we used cryo-electron microscopy to reveal the structure of HOPS. Unlike previously reported, significant flexibility of HOPS is confined to its extremities, where GTPase binding occurs. The SNARE-binding module is firmly attached to the core, therefore, ideally positioned between the membranes to catalyze fusion. Our data suggest a model for how HOPS fulfills its dual functionality of tethering and fusion and indicate why it is an essential part of the membrane fusion machinery.
AQDS Activates Extracellular Synergistic Biodetoxification of Copper and Selenite via Altering the Coordination Environment of Outer-Membrane Proteins.

The biotransformation of heavy metals in the environment is usually affected by co-existing pollutants like selenium (Se), which may lower the ecotoxicity of heavy metals, but the underlying mechanisms remain unclear. Here, we shed light on the pathways of copper (Cu2+) and selenite (SeO32-) synergistic biodetoxification by Shewanella oneidensis MR-1 and illustrate how such processes are affected by anthraquinone-2,6-disulfonate (AQDS), an analogue of humic substances. We observed the formation of copper selenide nanoparticles (Cu2-xSe) from synergistic detoxification of Cu2+ and SeO32- in the periplasm. Interestingly, adding AQDS triggered a fundamental transition from periplasmic to extracellular reaction, enabling 14.7-fold faster Cu2+ biodetoxification (via mediated electron transfer) and 11.4-fold faster SeO32- detoxification (via direct electron transfer). This is mainly attributed to the slightly raised redox potential of the heme center of AQDS-coordinated outer-membrane proteins that accelerates electron efflux from the cells. Our work offers a fundamental understanding of the synergistic detoxification of heavy metals and Se in a complicated environmental matrix and unveils an unexpected role of AQDS beyond electron mediation, which may guide the development of more efficient environmental remediation and resource recovery biotechnologies.
Improving Delivery of Cardiovascular Disease Preventive Services in Small-to-Medium Primary Care Practices

Background: The EvidenceNOW initiative provided smaller primary care practices with external support interventions to implement quality improvement strategies focused on cardiovascular disease prevention. This manuscript reports effectiveness of EvidenceNOW interventions in improving quality metrics. Methods: Seven regional Cooperatives delivered external support interventions (practice facilitation, health information technology support to assist with audit and feedback, performance benchmarking, learning collaboratives, and establishing community linkages) to 1278 smaller primary care practices. Outcomes included proportion of eligible patients meeting Centers for Medicaid and Medicare Services-specified ABCS metrics, that is, Aspirin for those at risk of ischemic vascular disease; achieving target Blood pressure among hypertensives; prescribing statin for those with elevated Cholesterol, diabetes, or increased cardiovascular disease risk; and screening for Smoking and providing cessation counseling. An event study compared prepost changes in outcomes among intervention practices and a difference-in-differences design compared intervention practices to 688 external comparison practices. Results: Mean baseline outcomes ranged from 61.5% (cholesterol) to 64.9% (aspirin). In the event study, outcomes improved significantly (aspirin: +3.39 percentage points, 95% CI, 0.61–6.17; blood pressure: +1.59, 95% CI, 0.12–3.06; cholesterol: +4.43, 95% CI, 0.33–8.53; smoking: +7.33, 95% CI, 4.70–9.96). Difference-in-differences estimates were similar in magnitude but statistically significant for smoking alone. Preintervention trends were significant for smoking, but parallel-trends tests were not significant. Conclusions: EvidenceNOW Cooperatives improved cardiovascular prevention quality metrics among small and medium sized primary care practices across the US. While estimated improvements were small, they reflected average changes across a large and diverse sample of practices.
Eukaryotic mRNA decapping factors: molecular mechanisms and activity

Decapping is the enzymatic removal of 5′ cap structures from mRNAs in eukaryotic cells. Cap structures normally enhance mRNA translation and stability, and their excision commits an mRNA to complete 5′–3′ exoribonucleolytic digestion and generally ends the physical and functional cellular presence of the mRNA. Decapping plays a pivotal role in eukaryotic cytoplasmic mRNA turnover and is a critical and highly regulated event in multiple 5′–3′ mRNA decay pathways, including general 5′–3′ decay, nonsense‐mediated mRNA decay (NMD), AU‐rich element‐mediated mRNA decay, microRNA‐mediated gene silencing, and targeted transcript‐specific mRNA decay. In the yeast Saccharomyces cerevisiae, mRNA decapping is carried out by a single Dcp1‐Dcp2 decapping enzyme in concert with the accessory activities of specific regulators commonly known as decapping activators or enhancers. These regulatory proteins include the general decapping activators Edc1, 2, and 3, Dhh1, Scd6, Pat1, and the Lsm1‐7 complex, as well as the NMD‐specific factors, Upf1, 2, and 3. Here, we focus on in vivo mRNA decapping regulation in yeast. We summarize recently uncovered molecular mechanisms that control selective targeting of the yeast decapping enzyme and discuss new roles for specific decapping activators in controlling decapping enzyme targeting, assembly of target‐specific decapping complexes, and the monitoring of mRNA translation. Further, we discuss the kinetic contribution of mRNA decapping for overall decay of different substrate mRNAs and highlight experimental evidence pointing to the functional coordination and physical coupling between events in mRNA deadenylation, decapping, and 5′–3′ exoribonucleolytic decay.
Complete Genome Sequence of Rhodococcus sp. Strain 9, Isolated from Contaminated Australian Groundwater

Here, we report the 7.7-Mbp genome sequence of Rhodococcus sp. strain 9, which was isolated from Australian groundwater contaminated with phenols and trichloroethylene. This strain has previously been shown to efficiently degrade p-nitrophenol and high-molecular-weight polycyclic aromatic hydrocarbons (PAHs). ABSTRACT Here, we report the 7.7-Mbp genome sequence of Rhodococcus sp. strain 9, which was isolated from Australian groundwater contaminated with phenols and trichloroethylene. This strain has previously been shown to efficiently degrade p-nitrophenol and high-molecular-weight polycyclic aromatic hydrocarbons (PAHs).
Deletion of a previously uncharacterized lipoprotein lirL confers resistance to an inhibitor of type II signal peptidase in Acinetobacter baumannii

Significance Inhibiting bacterial lipoprotein biosynthesis in Enterobacteriaceae is an attractive antibacterial strategy to target multidrug resistance, and mechanisms of resistance to prolipoprotein signal peptidase (LspA) inhibitors in Escherichia coli are relatively well understood. In contrast, it has been challenging to understand the mechanisms of resistance to LspA inhibitors in Acinetobacter baumannii due to the substantially lower inhibitor potencies and the lack of a homologous lpp gene. By increasing the antibacterial potency of the LspA inhibitor, globomycin, against wild-type A. baumannii, we were able to examine resistance to LspA inhibitors, resulting in the identification of a previously uncharacterized highly abundant lipoprotein, LspA inhibitor resistance lipoprotein. This study reveals insights into resistance mechanisms of A. baumannii against inhibitors of bacterial lipoprotein biosynthesis.
Slowing and switching of light in semiconductor quantum wells

After light became a part of the telecommunication system, the manipulation of light, especially the control of the speed of light, became a focus of research. By using the different approaches of the interaction between light and matter, there have been many successful attempts to slow down the speed of light, even to several meters per second. In the first part of my thesis, I studied pulse propagation in absorptive media (GaAs/AlGaAs multiple quantum well structures-MQWs) to gain insight into the linear interaction between matter and light. Systematic and fundamental measurements of pulse propagation in GaAs/AlGaAs multiple quantum well structures will be presented. These measurements are simulated by treating MQWs as a slab. These measurements and simulations will be compared while using a newly introduced general formalism. In the second part of my thesis, I will present another aspect of manipulating light: all–optical switching. Eric Gansen demonstrated all-optical switching in GaAs/AlGaAs MQWs at cryogenic temperatures. I will demonstrate that the same design of all-optical switch, which is based on polarized virtual carriers, can work without any serious loss of performance at near-room temperatures. Another material used in all-optical switches is Bragg-spaced-quantum-well structures (BSQWs) which are grown by molecular beam epitaxy. The growth of BSQW is challenging because of the associated unusually long growth times. In the last part of this dissertation, I will discuss the challenges involved in MBE growth of 210 period long GaAs/InGaAs BSQWs. By presenting basic characterization measurements of the
Pairing Symmetry, Phase diagram and Edge Modes in Topological Fulde-Ferrell-Larkin-Ovchinnikov Phase

The realizations of spin-orbit coupling in cold atoms lead to a burst of research activities in the searching of topological matters in ultracold atom systems. The very recent theoretical predictions show that topological Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) superfluids can be realized with proper spin-orbit coupling and Zeeman fields. In this work, a comprehensive understanding of the pairing symmetry, phase diagram and the edge modes in this new topological matter are presented. The momentum of the Cooper pairs plays the role of renormalizing the in-plane Zeeman field and chemical potential. The in-plane Zeeman field and finite momentum pairing induce asymmetry to the effective $p$-wave pairing, apart from a small fraction of higher orbital components. The phase diagram is composed by different phases, which are determined by the topology and band gap nature of the superfluids. Especially, the gapped and gapless topological FFLO phase have totally different finite size effect. These novel features show that the spin-orbit coupled cold atoms provides an important platform in realizing topological matters which may not be materialized with solids.
Wnt5a/b-catenin axis is involved in the downregulation of AT2 lineage by PAI-1.

Failure to regenerate injured alveoli functionally and promptly causes a high incidence of fatality in COVID-19. How elevated plasminogen activator inhibitor-1 (PAI-1) regulates the lineage of alveolar type 2 (AT2) cells for re-alveolarization has not been studied. This study aimed to examine the role of PAI-1-Wnt5a-β catenin cascades in AT2 fate. Dramatic reduction in AT2 yield was observed in Serpine1Tg mice. Elevated PAI-1 level suppressed organoid number, development efficiency, and total surface area in vitro. Anti-PAI-1 neutralizing antibody restored organoid number, proliferation and differentiation of AT2 cells, and β-catenin level in organoids. Both Wnt5a and Box5 altered the lineage of AT2 cells. This study demonstrates that elevated PAI-1 regulates AT2 proliferation and differentiation via the Wnt5a/β catenin cascades. PAI-1 could serve as autocrine signaling for lung injury repair.
Convergence of cascade algorithms

A nonstationary cascade algorithm for the nonstationary re-(cid:12)nement equation (cid:8) k (x) = jMj P j2ZZ s h k+1 (j)(cid:8) k+1 (Mx (cid:0) j); x 2 IR s ; is an iterative process, (cid:8) k;n (x) = jMj P j2ZZ s h k+1 (j)(cid:8) k+1;n(cid:0)1 (Mx(cid:0) j); that generates a family of sequences of vector functions (cid:8) k;n 2 L 2 (IR s ) r ; k;n = 0;1;:::; from an initial sequence of vectors (cid:8) k;0 2 L 2 (IR 2 ) r ; where each h k is a (cid:12)nitely supported sequence of r(cid:2)r matrices, and M is an s(cid:2)s dilation matrix, i.e. an integer matrix with all eigenvalues of modulus > 1 and det(M) (cid:21) 2: We assume that as k ! 1; h k ! h which de(cid:12)nes an ideal or stationary re(cid:12)nement equation (cid:8)(x) = jMj P j2ZZ s h(j)(cid:8)(Mx(cid:0)j): The corresponding cascade algorithm, ~ (cid:8)n(x) = jMj P j2ZZ s h(j) ~ (cid:8) n(cid:0)1 (Mx(cid:0)j); generates a sequence of vector functions ~ (cid:8)n from an initial vector ~ (cid:8) 0 2 L 2 (IR s ) r : The spectrum of the associated transition operator, Tb(j) := jMj P k P ` h(k)b(2j (cid:0)`)h(k(cid:0)`) (cid:3) ; de(cid:12)ned on sequences of r(cid:2)r matrices, plays an important role in the convergence of the nonstationary as well as the ideal cascade algorithms. This paper surveys results on various forms of convergence of cascade algorithms, from the scalar case in one dimen-sion, s = r = 1 and M = (2); to the latest developments on nonstationary cascade algorithms. Even in the scalar case in one dimension some of the results presented are new.
Linear Mixed Model Analysis of Polygenic Hazard Score on Verbal Memory Decline in Alzheimer’s Disease

Background Alzheimer’s disease (AD) is a chronic, progressive, degenerative disease characterized by cognitive dysfunction, including verbal memory loss. Studies were lacking in examining the longitudinal effect of polygenic hazard score on the Rey Auditory Verbal Learning Test–Delayed Total (AVDELTOT) score (a common measure of verbal memory). A key step in analyzing longitudinal changes in cognitive measures using a linear mixed model (LMM) is choosing a suitable covariance structure. Objectives The study aims to determine the association between the polygenic hazard score and the AVDELTOT score accounting for repeated measures (the covariance structure). Methods The AVDELTOT scores were collected at baseline, 12 months, 24 months, 36 months, and 48 months from 283 participants with AD, 347 with cognitive normal, and 846 with mild cognitive impairment in the Alzheimer’s Disease Neuroimaging Initiative. The Bayesian information criterion statistic was used to select the best covariance structure from 10 covariance structures in longitudinal analysis of AVDELTOT scores. The multivariable LMM was used to investigate the effect of polygenic hazard score status (low vs. medium vs. high) on changes in AVDELTOT scores while adjusted for age, gender, education, APOE-ε4 genotype, and baseline Mini-Mental State Examination score. Results One-way analysis of variance revealed significant differences in AVDELTOT scores, Mini-Mental State Examination scores, and polygenic hazard scores among AD diagnoses at baseline. Bayesian information criterion favored the compound symmetry covariance structure in the LMM analysis. Using the multivariate LMM, the APOE-ε4 allele and high polygenic hazard score value was significantly associated with AVDELTOT declines. Significant polygenic hazard score status by follow-up visit interactions was discovered. Conclusion Our findings provide the first evidence of the effect of polygenic hazard score status and APOE-ε4 allele on declines in verbal memory in people with AD.
Predicting Depression in Patients With Knee Osteoarthritis Using Machine Learning: Model Development and Validation Study

Background Knee osteoarthritis (OA) is the most common form of OA and a leading cause of disability worldwide. Chronic pain and functional loss secondary to knee OA put patients at risk of developing depression, which can also impair their treatment response. However, no tools exist to assist clinicians in identifying patients at risk. Machine learning (ML) predictive models may offer a solution. We investigated whether ML models could predict the development of depression in patients with knee OA and examined which features are the most predictive. Objective The primary aim of this study was to develop and test an ML model to predict depression in patients with knee OA at 2 years and to validate the models using an external data set. The secondary aim was to identify the most important predictive features used by the ML algorithms. Methods Osteoarthritis Initiative Study (OAI) data were used for model development and external validation was performed using Multicenter Osteoarthritis Study (MOST) data. Forty-two features were selected, which denoted routinely collected demographic and clinical data such as patient demographics, past medical history, knee OA history, baseline examination findings, and patient-reported outcome measures. Six different ML classification models were trained (logistic regression, least absolute shrinkage and selection operator [LASSO], ridge regression, decision tree, random forest, and gradient boosting machine). The primary outcome was to predict depression at 2 years following study enrollment. The presence of depression was defined using the Center for Epidemiological Studies Depression Scale. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and F1 score. The most important features were extracted from the best-performing model on external validation. Results A total of 5947 patients were included in this study, with 2969 in the training set, 742 in the test set, and 2236 in the external validation set. For the test set, the AUC ranged from 0.673 (95% CI 0.604-0.742) to 0.869 (95% CI 0.824-0.913), with an F1 score of 0.435 to 0.490. On external validation, the AUC varied from 0.720 (95% CI 0.685-0.755) to 0.876 (95% CI 0.853-0.899), with an F1 score of 0.456 to 0.563. LASSO modeling offered the highest predictive performance. Blood pressure, baseline depression score, knee pain and stiffness, and quality of life were the most predictive features. Conclusions To our knowledge, this is the first study to apply ML classification models to predict depression in patients with knee OA. Our study showed that ML models can deliver a clinically acceptable level of performance (AUC>0.7) in predicting the development of depression using routinely available demographic and clinical data. Further work is required to address the class imbalance in the training data and to evaluate the clinical utility of the models in facilitating early intervention and improved outcomes.