Miracle-dz/UniFAR-FTUs huggingface dataset:
Preliminary Clinical Experience of Molnupiravir to Prevent Progression of COVID-19 in Kidney Transplant Recipients

Background. Recently, different therapeutic lines have been tried in the initial stage of the disease of COVID-19, including remdesivir and molnupiravir. There is scarce evidence on the efficacy and safety of molnupiravir in kidney transplant recipients (KTRs). Methods. ingle-center prospective cohort study‚ all adult KTRs diagnosed with COVID-19 and treated with molnupiravir or remdesivir from January to April 2022 were included. Results. Nine KTRs with SARS-CoV-2 (Omicron variant) infection and mild symptoms received molnupiravir in an outpatient basis and were compared with a cohort of similar patients treated with remdesivir (n = 7). Three patients in the molnupiravir cohort were in the early posttransplant period and received a basiliximab (n = 2) or antithymocite globulin–based induction (n = 1). One of the patients had been treated with methylprednisolone bolus and antithymocite globulin for an episode of acute rejection in the previous months. They were all vaccinated with mRNA vaccines‚ and all but 1 had serological response. Only one of the patients experienced clinical worsening despite molnupiravir treatment and developed pneumonia requiring hospital admission. None of the patients suffered adverse effects attributed to molnupiravir‚ and no adjustment of tacrolimus dose was needed. None of the patients treated with remdesivir progressed in COVID-19 severity. Conclusions. Our study suggests that KTRs with SARS-CoV-2 infection under treatment with molnupiravir have a good clinical evolution with a probable lower risk for hospitalization and no adverse effects. At the renal level, molnupiravir was well tolerated, with no evidence of nephrotoxicity secondary to the drug nor interactions with the immunosuppressive therapy.
Hospital‐diagnosed sleep disorders and incident dementia: a nationwide observational cohort study

Several smaller, community‐based studies have suggested a link between sleep disorders and dementia with a focus on sleep as a modifiable risk factor for dementia. Studies on neurodegenerative diseases are prone to reverse causation, and few studies have examined the association with long follow‐up time. Our aim was to explore the possible association between sleep disorders and late‐onset dementia in an entire population.
New Perspectives on Antimicrobial Agents: Maribavir

Maribavir was approved by the U.S. Food and Drug Administration in November 2021 for the treatment of adult and pediatric patients with post-transplant cytomegalovirus (CMV) infection/disease that is refractory to treatment (with or without genotypic resistance) with ganciclovir, valganciclovir, cidofovir, or foscarnet. ABSTRACT Maribavir was approved by the U.S. Food and Drug Administration in November 2021 for the treatment of adult and pediatric patients with post-transplant cytomegalovirus (CMV) infection/disease that is refractory to treatment (with or without genotypic resistance) with ganciclovir, valganciclovir, cidofovir, or foscarnet. Maribavir is an oral benzimidazole riboside with potent and selective multimodal anti-CMV activity. It utilizes a novel mechanism of action which confers activity against CMV strains that are resistant to traditional anti-CMV agents, and also offers a more favorable safety profile relative to the dose-limiting side effects of previously available therapies. Maribavir was initially studied as an agent for CMV prophylaxis in solid organ and hematopoietic stem cell recipients, but initial phase III trials failed to meet clinical efficacy endpoints. It has been more recently studied as a therapeutic agent at higher doses for refractory-resistant (R-R) CMV infections with favorable outcomes. After an overview of maribavir’s chemistry and clinical pharmacology, this review will summarize clinical efficacy, safety, tolerability, and resistance data associated with maribavir therapy.
The Impact of Parental Presence Restrictions on Canadian Parents in the NICU During COVID-19: A National Survey

The purpose of this research was to explore parental perspectives on the impact of parent restrictions imposed in response to the COVID-19 pandemic across Canadian Neonatal Intensive Care Units (NICUs). A co-designed online survey was conducted targeting parents (n = 235) of infants admitted to a Canadian NICU from March 1, 2020, until March 5, 2021. Parents completed the survey from 38 Canadian NICUs. Large variation in the severity of policies regarding parental presence was reported. Most respondents (68.9%) were classified as experiencing high restrictions, with one or no support people allowed in the NICU, and felt that policies were less easy to understand, felt less valued and respected, and found it more challenging to access medicine or health care. Parents reported gaps in care related to self-care, accessibility, and mental health outcomes. There is significant variation in parental restrictions implemented across Canadian NICUs. National guidelines are needed to support consistent and equitable care practices.
Functional RG flow of the effective Hamiltonian action

After a brief review of the definition and properties of the quantum effective Hamiltonian action we describe its renormalization flow by a functional RG equation. This equation can be used for a non-perturbative quantization and study also of theories with bare Hamiltonians which are not quadratic in the momenta. As an example the vacuum energy and gap of quantum mechanical models are computed. Extensions of this framework to quantum field theories are discussed. In particular one possible Lorentz covariant approach for simple scalar field theories is developed. Fermionic degrees of freedom, being naturally described by a first order formulation, can be easily accommodated in this approach.
Long-distance association of topological boundaries through nuclear condensates

Significance The cellular mechanisms organizing chromosomal architecture in the eukaryotic genome are not yet well understood. Here, based on our demonstration that chemical disruption of nuclear condensate assembly weakens the insulation properties of a specific subset (∼20%) of topologically associated domain (TAD) boundaries, we were able to reveal that these boundary elements are characterized by high transcriptional activity, striking spatial clustering, and an augmented presence of long-distance/interchromosomal interactions between transcription units widely expressed in diverse cell types (i.e., boundary-associated “housekeeping” genes), thus providing insights into the physical basis for TAD-boundary establishment. Therefore, these results support a model whereby transcription contributes to chromatin compartmentalization and hierarchical genome organization, potentially through the association of transcriptional condensates with membraneless nuclear organelles.
Antitumour effects of a solid lipid nanoparticle loaded with gemcitabine and oxaliplatin on the viability, apoptosis, autophagy, and Hsp90 of ovarian cancer cells

Abstract The present study aimed to explore the sensitising capability of the anticancer agents, gemcitabine (GEM) and oxaliplatin (OXA), encapsulated in a novel SLN (GEM:OXA-SLN) against the ovarian cancer cell lines. A novel SLN, prepared using hot homogenisation by mixing phosphatidylcholine, cholesterol, tween 80, and oleic acid, was characterised using Transmission Electron Microscope and zetasizer. The anticancer activities and the underlying molecular mechanisms of GEM:OXA-SLN were investigated. The average z-diameter of the homogeneous spherical GEM:OXA-SLN was (70.33 ± 0.70) nm with zeta potential (–7.69 ± 0.61) mV. GEM:OXA-SLN significantly inhibited the viability of ovarian cancer cells in a dose-dependent manner within 24 h. It also triggered the induction of autophagy cellular death, suppression of multidrug resistance efflux pump and inhibition of heat shock protein (Hsp90). The encapsulation of GEM and OXA in SLN improved the efficacy of the drugs and diminished the ovarian cancer cell’s resistance.
Automatic grading for Arabic short answer questions using optimized deep learning model

Auto-grading of short answer questions is considered a challenging problem in the processing of natural language. It requires a system to comprehend the free text answers to automatically assign a grade for a student answer compared to one or more model answers. This paper suggests an optimized deep learning model for grading short-answer questions automatically by using various sizes of datasets collected in the Science subject for students in seventh grade in Egypt. The proposed system is a hybrid approach that optimizes a deep learning technique called LSTM (Long Short Term Memory) with a recent optimization algorithm called a Grey Wolf Optimizer (GWO). The GWO is employed to optimize the LSTM by selecting the best dropout and recurrent dropout rates of LSTM hyperparameters rather than manual choice. Using GWO makes the LSTM model more generalized and can also avoid the problem of overfitting in forecasting the students’ scores to improve the learning process and save instructors’ time and effort. The model’s performance is measured in terms of the Root Mean Squared Error (RMSE), the Pearson correlation coefficient, and R-Square. According to the simulation results, the hybrid GWO with the LSTM model ensured the best performance and outperformed the classical LSTM model and other compared models such that it had the highest Pearson correlation coefficient value, the lowest RMSE value, and the best R square value in all experiments, but higher training time than the traditional deep learning model.
Pregnancy and malaria: the perfect storm

Purpose of review Malaria in pregnancy continues to exert a toll on pregnant women and their offspring. Recent findings The burden of Plasmodium falciparum infection is especially large in Africa, and new data show lasting effects of maternal infection on the infant's neurocognitive development. Elsewhere, P. vivax infection causes relapsing infections that are challenging to prevent. Infection in first trimester of pregnancy is an area of increasing focus, and its adverse effects on pregnancy outcome are increasingly recognised. First-trimester infection is common and frequently acquired prior to conception. Although newer rapid diagnostic tests still have limited sensitivity, they may be useful in detection of early pregnancy malaria for treatment. Artemisinin-based combination therapies are efficacious in later pregnancy but have yet to be recommended in first trimester because of limited safety data. In Africa, intermittent preventive treatment in pregnancy (IPTp) with monthly sulfadoxine-pyrimethamine improves pregnancy outcomes, but sulfadoxine-pyrimethamine resistance is worsening. The alternative, IPTp with dihydroartemisinin-piperaquine, has greater antimalarial efficacy, but does not appear to improve pregnancy outcomes, because sulfadoxine-pyrimethamine has poorly understood nonmalarial benefits on birthweight. Summary Novel IPTp regimens must be combined with interventions to strengthen protection from malaria infection acquired before and in early pregnancy.
Mechanistic details of CRISPR-associated transposon recruitment and integration revealed by cryo-EM

Significance CRISPR-associated transposons (CASTs) show tremendous promise for genome engineering yet remain poorly understood. Here, we present the cryo-electron microscopy structure of the transposase (TnsB) from the V-K CAST element from Scytonema hofmanni (ShCAST). We determine the molecular mechanism of TnsB recruitment to the target site (via the AAA+ regulator TnsC) and the structural details of the TnsB transposase. This TnsB structure reveals architectural similarities to MuA, but also key structural differences that are significant for understanding CAST transposition. Importantly, we highlight a base-flipping mechanism for stabilizing the 5′ end of the transposon, potentially to ensure the fidelity of synaptic complex assembly. The structures presented here provide a direct target for rational, structure-guided design strategies and re-engineering of CAST elements.
Stability and Change in Subjective, Psychological, and Social Well-Being: A Latent State-Trait Analysis of Mental Health Continuum–Short Form in Korea and the Netherlands

Abstract Mental well-being consists of hedonic/subjective, psychological, and social dimensions. Research has yet to determine how much of the variance in these three dimensions is stable or variable over time. This study used data from South Korea (N = 338) and the Netherlands (N = 2,094) to answer this question. Data were collected over a period of approximately 14 months in Korea (four time points) and 10 months in the Netherlands (four time points). The study used the Mental Health Continuum–Short Form (MHC–SF) to measure dimensions of well-being and the Multi-Trait Multi-State model for data analysis. Results showed a moderate degree of stability for the three dimensions, with the proportion of stable variance ranging from 51% to 61% (M = 58%). Item-level analysis provided more detailed insights into item stability, which helped clarify some of the concept-level results. Despite the large differences between Korea and the Netherlands in cultural values and well-being, estimates of stability and change were quite similar across the two countries. However, some modest cross-cultural differences were also found. The study provides insights that can help researchers and practitioners in the selection or construction of well-being items for various research and practical settings.
Probabilistic Neural–Symbolic Models With Inductive Posterior Constraints

Neural–symbolic models provide a powerful tool to tackle complex visual reasoning tasks by combining symbolic program execution for reasoning and deep representation learning for visual recognition. A probabilistic formulation of such models with stochastic latent variables can obtain an interpretable and legible reasoning system with less supervision. However, it is still nontrivial to generate reasonable symbolic structures without the guidance of domain knowledge, since it generally involves an optimization problem with both continuous and discrete variables. Despite the challenges, the interpretability of such symbolic structures provides an interface to regularize their generation by domain knowledge. In this article, we propose to incorporate the available domain knowledge into the learning process of probabilistic neural–symbolic (PNS) models via posterior constraints that directly regularize the structure posterior. In this way, our model is able to identify a middle point where the structure generation process mainly learns from data but also selectively borrows information from domain knowledge. We further present inductive reasoning where the posterior constraints can be automatically reweighted to handle noisy annotations. The experimental results show that our method achieves state-of-the-art performance on major abstract reasoning datasets and enjoys good generalization capability and data efficiency.
Deliberating enhanced weathering: Public frames, iconic ecosystems and the governance of carbon removal at scale

Meeting goals for ‘net zero’ emissions may require the removal of previously emitted carbon dioxide from the atmosphere. One proposal, enhanced rock weathering, aims to speed up the weathering processes of rocks by crushing them finely and spreading them on agricultural land. Public perceptions of enhanced rock weathering and its wider social and environmental implications will be a critical factor determining its potential; we use six 2-day deliberative workshops in England, Wales and Illinois to understand public views. Consideration of enhanced rock weathering deployment in tropical countries led participants to frame it from a social justice perspective, which had been much less prevalent when considering Western agricultural contexts, and generated assumptions of increased scale, which heightened concerns about detrimental social and environmental impacts. Risk perceptions relating to ‘messing with nature’ became amplified when participants considered enhanced rock weathering in relation to ‘iconic’ environments such as the oceans and rainforest.
Simultaneous UBVRI observations of the cataclysmic variable AE Aquarii: temperature and mass of fireballs

We report simultaneous multicolour observations in 5 bands (UBVRI) of the flickering variability of the cataclysmic variable AE Aqr. Our aim is to estimate the parameters (colours, temperature, size) of the fireballs that produce the optical flares. The observed rise time of the optical flares is in the interval 220 - 440 sec. We estimate the dereddened colours of the fireballs: (U-B)_0 in the range 0.8-1.4, (B-V)_0 ~ 0.03-0.24, (V-I)_0 ~ 0.26-0.78. We find for the fireballs a temperature in the range 10000 - 25000 K, mass (7-90). 10^{19} g, size (3-7). 10^9 cm (using a distance of d=86 pc). These values refer to the peak of the flares observed in UBVRI bands. The data are available upon request from the authors.
Group Sparsity Mixture Model and Its Application on Image Denoising

Prior learning is a fundamental problem in the field of image processing. In this paper, we conduct a detailed study on (1) how to model and learn the prior of the image patch group, which consists of a group of non-local similar image patches, and (2) how to apply the learned prior to the whole image denoising task. To tackle the first problem, we propose a new prior model named Group Sparsity Mixture Model (GSMM). With the bilateral matrix multiplication, the GSMM can model both the local feature of a single patch and the relation among non-local similar patches, and thus it is very suitable for patch group based prior learning. This is supported by the parameter analysis which demonstrates that the learned GSMM successfully captures the inherent strong sparsity embodied in the image patch group. Besides, as a mixture model, GSMM can be used for patch group classification. This makes the image denoising method based on GSMM capable of processing patch groups flexibly. To tackle the second problem, we propose an efficient and effective patch group based image denoising framework, which is plug-and-play and compatible with any patch group prior model. Using this framework, we construct two versions of GSMM based image denoising methods, both of which outperform the competing methods based on other prior models, e.g., Field of Experts (FoE) and Gaussian Mixture Model (GMM). Also, the better version is competitive with the state-of-the-art model based method WNNM with about $\times 8$ faster average running speed.
Polarization imaging of the galactic emission at 1420 MHz-the Canadian Galactic Plane Survey

The Canadian Galactic Plane Survey (CGPS) is providing images of total intensity and polarized emission at 1420 MHz with arcminute angular resolution over the region 75°<l<145°, −3.5°<b<5.5°. Small-scale structure, attributed to Faraday-rotation effects, is detected over almost the entire survey area. Data are presented for the range 83°<l<95°. Here the polarization features lie in the Local arm, at distances less than 2 kpc.
COMPARISON OF ANTIEMETIC EFFECT OF GRANISETRON AND PALONOSETRON IN PATIENTS UNDERGOING THYROIDECTOMY: A PROSPECTIVE, RANDOMIZED, DOUBLE-BLIND STUDY.

Background: Postoperative nausea and vomiting (PONV) is the second most frequent postoperative complaint after pain. The 5-hydroxytryptamine type-3 antagonists have proven a particularly valuable addition to the armamentarium against PONV. Granisetron has been very popular drug in this class for its efficacy and patient tolerability. Palonosetron is a second-generation 5-HT 3 antagonist that has recently been approved for prophylaxis against PONV. It has unique structural, pharmacological and clinical properties that distinguish it from other agents in its class. This study compared the effects of intravenous granisetron and palonosetron administered five minutes before induction of anaesthesia in preventing postoperative nausea and vomiting (PONV) in patients undergoing thyroidectomy. Methods: 120 female patients of physical status ASA-I & ASA-II, 25-50 years of age, posted for elective thyroidectomy were enrolled in the study and randomly divided into two groups (group - G and group-P). Patients in group - G received 2.5 mg of granisetron and group - P received 0.075 mg of palonosetron intravenously five minutes before induction of anesthesia according to group assignment by an anesthesiologist not involved in the study. Incidence of nausea and vomiting, severity of nausea and vomiting, need for rescue anti emetics and side effects if any were evaluated at 0-2 hours, 2-24 hours and 24-48 hours after surgery. Results: The incidence of PONV during 24-48 hours postoperative period was lower in palonosetron group than in granisetron group (8.33% vs 31.66%, p-value=0.001) and was statistically significant however no differences were observed between the two groups at 0-2 hours and 2-24 hours. The severity of nausea and vomiting was significantly lower in the palonosetron group as compared to granisetron group at all study intervals. The number of patients requiring anti-emetics was statistically insignificant between the two groups at 0-2 hours and 2-24 hours postoperatively. However, the difference was statistically significant (p-value=0.025) at 24-48 hours postoperatively with 11 patients (18.33%) requiring rescue anti-emetics in group-G (Granisetron) and 2 patients (3.33%) in group-P (Palonosetron). Total number of rescue anti-emetics used in both the groups during 0-48 hours was 28, out of which 22(78.57%) were used in group-G (Granisetron) and 6 (21.43%) used in group-P (Palonosetron). Conclusions: From our study, we concluded that palonosetron is more effective than granisetron for antiemetic prophylaxis in patients undergoing thyroidectomy under general anesthesia.
The t-value, the nucleolus and the core for a subclass of games

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