Miracle-dz/UniFAR-FTUs huggingface dataset:
Nematode biomass changes along an elevational gradient are trophic group dependent but independent of body size

Aboveground, large and higher trophic‐level organisms often respond more strongly to environmental changes than small and lower trophic‐level organisms. However, whether this trophic or size‐dependent sensitivity also applies to the most abundant animals, microscopic soil‐borne nematodes, remains largely unknown. Here, we sampled an altitudinal transect across the Tibetan Plateau and applied a community‐weighted mean (CWM) approach to test how differences in climatic and edaphic properties affect nematode CWM biomass at the level of community, trophic group and taxon mean biomass within trophic groups. We found that climatic and edaphic properties, particularly soil water‐related properties, positively affected nematode CWM biomass, with no overall impact of altitude on nematode CWM biomass. Higher trophic‐level omnivorous and predatory nematodes responded more strongly to climatic and edaphic properties, particularly to temperature, soil pH, and soil water content than lower trophic‐level bacterivorous and fungivorous nematodes. However, these differences were likely not (only) driven by size, as we did not observe significant interactions between climatic and edaphic properties and mean biomasses within trophic groups. Together, our research implies a stronger, size‐independent trophic sensitivity of higher trophic‐level nematodes compared with lower trophic‐level ones. Therefore, our findings provide new insights into the mechanisms underlying nematode body size structure in alpine grasslands and highlight that traits independent of size need to be found to explain increased sensitivity of higher trophic‐level nematodes to climatic and edaphic properties, which might affect soil functioning.
Defining drivers of under-immunization and vaccine hesitancy in refugee and migrant populations

Abstract Background/objective Some refugee and migrant populations globally showed lower uptake of COVID-19 vaccines and are also considered to be an under-immunized group for routine vaccinations. These communities may experience a range of barriers to vaccination systems, yet there is a need to better explore drivers of under-immunization and vaccine hesitancy in these mobile groups. Methods We did a global rapid review to explore drivers of under-immunization and vaccine hesitancy to define strategies to strengthen both COVID-19 and routine vaccination uptake, searching MEDLINE, Embase, Global Health PsycINFO and grey literature. Qualitative data were analysed thematically to identify drivers of under-immunization and vaccine hesitancy, and then categorized using the ‘Increasing Vaccination Model’. Results Sixty-three papers were included, reporting data on diverse population groups, including refugees, asylum seekers, labour migrants and undocumented migrants in 22 countries. Drivers of under-immunization and vaccine hesitancy pertaining to a wide range of vaccines were covered, including COVID-19 (n = 27), human papillomavirus (13), measles or Measles-mumps-rubella (MMR) (3), influenza (3), tetanus (1) and vaccination in general. We found a range of factors driving under-immunization and hesitancy in refugee and migrant groups, including unique awareness and access factors that need to be better considered in policy and service delivery. Acceptability of vaccination was often deeply rooted in social and historical context and influenced by personal risk perception. Conclusions These findings hold direct relevance to current efforts to ensure high levels of global coverage for a range of vaccines and to ensure that marginalized refugee and migrant populations are included in the national vaccination plans of low-, middle- and high-income countries. We found a stark lack of research from low- and middle-income and humanitarian contexts on vaccination in mobile groups. This needs to be urgently rectified if we are to design and deliver effective programmes that ensure high coverage for COVID-19 and routine vaccinations.
Epidemiology and drug susceptibility of nontuberculous mycobacteria (NTM) in Italy in 2016-2020.

INTRODUCTION Nontuberculous mycobacteria (NTM) are environmental mycobacteria which may cause pulmonary and extrapulmonary diseases. These organisms are difficult to treat due to their intrinsic drug-resistance. In Italy, no major nationwide study on NTM epidemiology and drug susceptibility was performed. METHODS Data on the epidemiology of 7,469 NTM clinical isolates identified in Italy in 2016-2020 and on the minimum inhibitory concentrations (MICs) of 1,506 of these strains were analysed. RESULTS Overall, 63 species were identified in 42 hospital laboratories located in 16 out of 20 regions, with Mycobacterium avium complex (MAC) being the most frequently isolated, followed by M. gordonae, M. xenopi, M. abscessus. The MICs of 12 drugs for MAC, M. xenopi, M. kansasii, M. abscessus, M. fortuitum and M. chelonae were interpreted for clinical significance (susceptible, intermediate, resistant) based on the guidelines published by the Clinical and Laboratory Standards Institute in November 2018. CONCLUSIONS Our data are in line with other nationwide studies and may be of value for further update of microbiological and clinical guidelines.
Functional recovery after ischemic stroke: Impact of different sleep health parameters

Sleep disturbances after ischaemic stroke include alterations of sleep architecture, obstructive sleep apnea, restless legs syndrome, daytime sleepiness and insomnia. Our aim was to explore their impacts on functional outcomes at month 3 after stroke, and to assess the benefit of continuous positive airway pressure in patients with severe obstructive sleep apnea. Ninety patients with supra‐tentorial ischaemic stroke underwent clinical screening for sleep disorders and polysomnography at day 15 ± 4 after stroke in a multisite study. Patients with severe obstructive apnea (apnea–hypopnea index ≥ 30 per hr) were randomized into two groups: continuous positive airway pressure‐treated and sham (1:1 ratio). Functional independence was assessed with the Barthel Index at month 3 after stroke in function of apnea–hypopnea index severity and treatment group. Secondary objectives were disability (modified Rankin score) and National Institute of Health Stroke Scale according to apnea–hypopnea index. Sixty‐one patients (71.8 years, 42.6% men) completed the study: 51 (83.6%) had obstructive apnea (21.3% severe apnea), 10 (16.7%) daytime sleepiness, 13 (24.1%) insomnia, 3 (5.7%) depression, and 20 (34.5%) restless legs syndrome. Barthel Index, modified Rankin score and Stroke Scale were similar at baseline and 3 months post‐stroke in the different obstructive sleep apnea groups. Changes at 3 months in those three scores were similar in continuous positive airway pressure versus sham‐continuous positive airway pressure patients. In patients with worse clinical outcomes at month 3, mean nocturnal oxygen saturation was lower whereas there was no association with apnea–hypopnea index. Poorer outcomes at 3 months were also associated with insomnia, restless legs syndrome, depressive symptoms, and decreased total sleep time and rapid eye movement sleep.
How does linguistic context influence word learning?

Abstract While there are well-known demonstrations that children can use distributional information to acquire multiple components of language, the underpinnings of these achievements are unclear. In the current paper, we investigate the potential pre-requisites for a distributional learning model that can explain how children learn their first words. We review existing literature and then present the results of a series of computational simulations with Vector Space Models, a type of distributional semantic model used in Computational Linguistics, which we evaluate against vocabulary acquisition data from children. We focus on nouns and verbs, and we find that: (i) a model with flexibility to adjust for the frequency of events provides a better fit to the human data, (ii) the influence of context words is very local, especially for nouns, and (iii) words that share more contexts with other words are harder to learn.
Exact solution for a two-dimensional KDV-Burgers-type equation with nonlinear terms of any order

In this paper, we study a two-dimensional Burgers--Korteweg-de Vries-type equation with higher-order nonlinearities. A class of solitary wave solution is obtained by means of the Divisor Theorem which is based on the ring theory of commutative algebra. Our result indicates that the presentation of traveling wave solution in [J. Phys. A (Math. Gen.) 35 (2002) 8253--8265] is incorrect; an explanation as to why this is so is given.
The Current Limitations and Advanced Analysis of Hemodynamic Study of Cerebral Aneurysms

Among the various perspectives on cerebrovascular diseases, hemodynamic analysis—which has recently garnered interest—is of great help in understanding cerebrovascular diseases. Computational fluid dynamics (CFD) analysis has been the primary hemodynamic analysis method, and studies on cerebral aneurysms have been actively conducted. However, owing to the intrinsic limitations of the analysis method, the role of wall shear stress (WSS), the most representative parameter, remains controversial. High WSS affects the formation of cerebral aneurysms; however, no consensus has been reached on the role of WSS in the growth and rupture of cerebral aneurysms. Therefore, this review aimed to briefly introduce the up-to-date results and limitations made through CFD analysis and to inform the need for a new hemodynamic analysis method.
Provider perspectives on antiretroviral therapy adherence among psychiatric inpatients in Botswana

Background: Optimal adherence to antiretroviral therapy (ART) is crucial for the effective management of HIV. Mental disorders often co-occur with HIV infection which often compromises ART adherence. Little is known about ART adherence in psychiatric settings in sub-Saharan Africa. Aims: This study aimed at exploring the health care providers’ perspectives on ART adherence among psychiatric inpatients. The study further assessed the facilitators and strategies enhancing ART adherence in hospitalised psychiatric patients. Methods: In-depth interviews were conducted with 25 health care providers at the Sbrana Psychiatric Hospital in Botswana. Interviews were focused on barriers and facilitators to psychiatric inpatients’ adherence to ART, and strategies and recommendations to support adherence. Data were manually analysed using a thematic analysis approach. Results: Key barriers were lack of insight, HIV-related stigma, lack of HIV-related knowledge, antiretroviral side effects and delays in re-initiating ART. Facilitators of ART adherence included motivation to be discharged from the hospital, fear of being sick, peer support, longer duration of hospitalisation, good provider-patient relationships, good diet, privacy and confidentiality and a single-tablet regimen. Health care providers described the various strategies currently used to support adherence, including directly observed therapy and family support, and recommended potential approaches to enhance psychiatric inpatient adherence to ART, including the use of injectable antiretrovirals and the introduction of halfway house centres. Conclusions: Findings from this study revealed unique insights into the numerous factors that influence ART adherence among psychiatric inpatients, and underscore the need to implement tailored strategies to support ART adherence in this population with complex health needs.
DTCM: Joint Optimization of Dark Enhancement and Action Recognition in Videos

Recognizing human actions in dark videos is a useful yet challenging visual task in reality. Existing augmentation-based methods separate action recognition and dark enhancement in a two-stage pipeline, which leads to inconsistently learning of temporal representation for action recognition. To address this issue, we propose a novel end-to-end framework termed Dark Temporal Consistency Model (DTCM), which is able to jointly optimize dark enhancement and action recognition, and force the temporal consistency to guide downstream dark feature learning. Specifically, DTCM cascades the action classification head with the dark augmentation network to perform dark video action recognition in a one-stage pipeline. Our explored spatio-temporal consistency loss, which utilizes the RGB-Difference of dark video frames to encourage temporal coherence of the enhanced video frames, is effective for boosting spatio-temporal representation learning. Extensive experiments demonstrated that our DTCM has remarkable performance: 1) Competitive accuracy, which outperforms the state-of-the-arts on the ARID dataset by 2.32% and the UAVHuman-Fisheye dataset by 4.19% in accuracy, respectively; 2) High efficiency, which surpasses the current most advanced method (Chen et al., 2021) with only 6.4% GFLOPs and 71.3% number of parameters; 3) Strong generalization, which can be used in various action recognition methods (e.g., TSM, I3D, 3D-ResNext-101, Video-Swin) to promote their performance significantly.
How does obstructive sleep apnea alter cerebral hemodynamics?

Abstract Study Objectives We aimed to characterize the cerebral hemodynamic response to obstructive sleep apnea/hypopnea events, and evaluate their association to polysomnographic parameters. The characterization of the cerebral hemodynamics in obstructive sleep apnea (OSA) may add complementary information to further the understanding of the severity of the syndrome beyond the conventional polysomnography. Methods Severe OSA patients were studied during night sleep while monitored by polysomnography. Transcranial, bed-side diffuse correlation spectroscopy (DCS) and frequency‐domain near-infrared diffuse correlation spectroscopy (NIRS-DOS) were used to follow microvascular cerebral hemodynamics in the frontal lobes of the cerebral cortex. Changes in cerebral blood flow (CBF), total hemoglobin concentration (THC), and cerebral blood oxygen saturation (StO2) were analyzed. Results We considered 3283 obstructive apnea/hypopnea events from sixteen OSA patients (Age (median, interquartile range) 57 (52‐64.5); females 25%; AHI (apnea‐hypopnea index) 84.4 (76.1‐93.7)). A biphasic response (maximum/minimum followed by a minimum/maximum) was observed for each cerebral hemodynamic variable (CBF, THC, StO2), heart rate and peripheral arterial oxygen saturation (SpO2). Changes of the StO2 followed the dynamics of the SpO2, and were out of phase from the THC and CBF. Longer events were associated with larger CBF changes, faster responses and slower recoveries. Moreover, the extrema of the response to obstructive hypopneas were lower compared to apneas (p < .001). Conclusions Obstructive apneas/hypopneas cause profound, periodic changes in cerebral hemodynamics, including periods of hyper- and hypo-perfusion and intermittent cerebral hypoxia. The duration of the events is a strong determinant of the cerebral hemodynamic response, which is more pronounced in apnea than hypopnea events.
What nature has to offer: Opportunities for immuno-oncology

Recent rapid development of cancer therapy has come about with the paradigm shift from the traditional goal of targeting cancer cells themselves, to reprograming the immune tumor microenvironment. Accumulating evidence shows that compounds that target epigenetic regulation, called epidrugs, play a crucial role in mediating the immunogenicity of cancer cells and in reshaping antitumor immunity. A large body of literature has recognized natural compounds as epigenetic modulators for their immunomodulatory effects and anticancer potential. Unifying our understanding of the role of these biologically active compounds in immuno-oncology may open new avenues for more effective cancer therapies. In this review, we explore how natural compounds modulate the epigenetic machinery to shape antitumor immune response, highlighting the promise offered by the Mother Nature that could be exploited therapeutically to improve outcomes for cancer patients.
Hygrothermal Effects on the Nonlinear Bending of Shear Deformable Laminated Plates

The influence of hygrothermal effects on the nonlinear bending of shear deformable laminated plates subjected to a uniform or sinusoidal load is investigated using a micro-to-micromechanical analytical model. The material properties of the composite are affected by the variation of temperature and mositure, and are based on a micromechanical model of a laminate. The governing equations of a laminated plate are based on Reddy's higher-order shear deformation plate theory with von Karman-type kinematic nonlinearity, and including hygrothermal effects. A perturbation technique is employed to determine the load-deflection and load-bending moment curves. The numerical illustrations concern nonlinear bending behavior of antisymmetric angle-ply and symmetric cross-ply laminated plates under different sets of environmental conditions. The results presented show the effects of temperature rise, the degree of moisture concentration, and fiber volume fraction on the nonlinear bending behavior of the plate.
A rare cause of intellectual disability: Novel mutations of NFIX gene in two patients with clinical features of Marshall–Smith syndrome and Malan syndrome

Marshall–Smith syndrome (MSS) and Malan syndrome (MS) are both allelic disorders caused by mutations in the NFIX gene. MS is characterized by overgrowth, intellectual disability, distinctive facial features, and accelerated skeletal maturation. On the other hand, clinical features of MSS consist of advanced bone age, dysmorphic features, intellectual disability, and failure to thrive at birth. In this study, we presented the clinical and molecular findings of two different patients with MS and MSS as a rare cause of intellectual disability and reported two novel variants in the NFIX gene. NFIX gene sequencing revealed a novel heterozygous c.1287delC (p.G430Vfs*34) mutation in patient 1 whose clinical diagnosis was compatible with Marshall–Smith syndrome, and in the second patient, physical features consistent with Malan syndrome, was detected a heterozygous one nucleotide duplication, c.303dupC (pCys102LeufsTer17).
Targeting the cGAS-STING pathway as an inflammatory crossroad in coronavirus disease 2019 (COVID-19)

Abstract Context and objective The emerging pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has imposed significant mortality and morbidity on the world. An appropriate immune response is necessary to inhibit SARS-CoV-2 spread throughout the body. Results During the early stages of infection, the pathway of stimulators of interferon genes (STING), known as the cGAS-STING pathway, has a significant role in the induction of the antiviral immune response by regulating nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and Interferon regulatory factor 3 (IRF3), two key pathways responsible for proinflammatory cytokines and type I IFN secretion, respectively. Discussion During the late stages of COVID-19, the uncontrolled inflammatory responses, also known as cytokine storm, lead to the progression of the disease and poor prognosis. Hyperactivity of STING, leading to elevated titers of proinflammatory cytokines, including Interleukin-I (IL-1), IL-4, IL-6, IL-18, and tissue necrosis factor-α (TNF-α), is considered one of the primary mechanisms contributing to the cytokine storm in COVID-19. Conclusion Exploring the underlying molecular processes involved in dysregulated inflammation can bring up novel anti-COVID-19 therapeutic options. In this article, we aim to discuss the role and current studies targeting the cGAS/STING signaling pathway in both early and late stages of COVID-19 and COVID-19-related complications and the therapeutic potential of STING agonists/antagonists. Furthermore, STING agonists have been discussed as a vaccine adjuvant to induce a potent and persistent immune response.
Non-asymptotic System Identification for Linear Systems with Nonlinear Policies

This paper considers a single-trajectory system identification problem for linear systems under general nonlinear and/or time-varying policies with i.i. d. random excitation noises. The problem is motivated by safe learning-based control for constrained linear systems, where the safe policies during the learning process are usually nonlinear and time-varying for satisfying the state and input constraints. In this paper, we provide a non-asymptotic error bound for least square estimation when the data trajectory is generated by any nonlinear and/or time-varying policies as long as the generated state and action trajectories are bounded. This significantly generalizes the existing non-asymptotic guarantees for linear system identification, which usually consider i.i. d. random inputs or linear policies. Interestingly, our error bound is consistent with that for linear policies with respect to the dependence on the trajectory length, system dimensions, and excitation levels. Lastly, we demonstrate the applications of our results by safe learning with robust model predictive control and provide numerical analysis.
A geometrical framework for thinking about proteins

We present a model, based on symmetry and geometry, for proteins. Using elementary ideas from mathematics and physics, we derive the geometries of discrete helices and sheets. We postulate a compatible solvent-mediated emergent pairwise attraction that assembles these building blocks, while respecting their individual symmetries. Instead of seeking to mimic the complexity of proteins, we look for a simple abstraction of reality that yet captures the essence of proteins. We employ analytic calculations and detailed Monte Carlo simulations to explore some consequences of our theory. The predictions of our approach are in accord with experimental data. Our framework provides a rationalization for understanding the common characteristics of proteins. Our results show that the free energy landscape of a globular protein is pre-sculpted at the backbone level, sequences and functionalities evolve in the fixed backdrop of the folds determined by geometry and symmetry, and that protein structures are unique in being simultaneously characterized by stability, diversity, and sensitivity. Statement for broader audience We present a simple geometrical model of a chain, which captures the essential features of globular proteins, and explore its consequences. Our model marries the ideas of Kepler, of objects touching each other, and Pauling, of hydrogen bonds providing scaffolding for helices and sheets. We suggest a poking potential for a chain, whose deployment yields the correct structures of both helices and sheets, while promoting the assembly of the building blocks into the tertiary structure.