ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
The failure of drug repurposing for COVID-19 as an effect of excessive hypothesis testing and weak mechanistic evidence

The current strategy of searching for an effective treatment for COVID-19 relies mainly on repurposing existing therapies developed to target other diseases. Conflicting results have emerged in regard to the efficacy of several tested compounds but later results were negative. The number of conducted and ongoing trials and the urgent need for a treatment pose the risk that false-positive results will be incorrectly interpreted as evidence for treatments' efficacy and a ground for drug approval. Our purpose is twofold. First, we show that the number of drug-repurposing trials can explain the false-positive results. Second, we assess the evidence for treatments' efficacy from the perspective of evidential pluralism and argue that considering mechanistic evidence is particularly needed in cases when the evidence from clinical trials is conflicting or of low quality. Our analysis is an application of the program of Evidence Based Medicine Plus (EBM+) to the drug repurposing trials for COVID. Our study shows that if decision-makers applied EBM+, authorizing the use of ineffective treatments would be less likely. We analyze the example of trials assessing the efficacy of hydroxychloroquine as a treatment for COVID-19 and mechanistic evidence in favor of and against its therapeutic power to draw a lesson for decision-makers and drug agencies on how excessive hypothesis testing can lead to spurious findings and how studying negative mechanistic evidence can be helpful in discriminating genuine from spurious results.
Phylogenetic placement of Turkish populations of Ixodes ricinus and Ixodes inopinatus

Studies on phylogeography and population structure of Ixodes ricinus have been carried out in Europe for decades, but the number of specimens from the Middle East included in these analyses is relatively small, despite the wide distribution of the species in this area. This study aimed to clarify the phylogenetic positions of I. ricinus from Turkey as well as to investigate the presence of Ixodes inopinatus in Anatolia. For this purpose, one mitochondrial (mt 16S rDNA) and one nuclear gene (defensin) were used to generate molecular data from I. ricinus samples, which were collected from 17 locations across the species' distributional range in Turkey. Bayesian inference was used to investigate phylogenetic relationships. Globally, the mt 16S rDNA lineages correspond to the lineages revealed by defensin; I. ricinus and I. inopinatus sequences clustered separately. However, a discordant genetic pattern was observed between the phylogenetic position of turkish I. ricinus revealed by nuclear versus mitochondrial genes. All Turkish haplotypes of mt 16SrDNA clustered with I. ricinus samples from Europe, which might be the result of extensive gene flow between populations of Europe and the Middle East. On the other hand, a sample from Thrace Region grouped within I. inopinatus clade. Thus, the occurrence of I. inopinatus in Turkey was demonstrated for the first time using molecular data. Moreover, four individuals were found to be heterozygous for the defensin. The potential evolutionary processes that underlie this observed discrepancy between the phylogenetic trees of two genes have been discussed.
White Light Emission Through Downconversion of Terbium and Europium Doped CeF3 Nanophosphors

CeF3 nanophosphors have been extensively investigated in recent years for lighting and numerous bio-applications. Downconversion emissions in CeF3:Eu(3+)/Tb(3+) phosphors were studied with the objective of attaining a white light emitting composition, by means of a simple co-precipitation method. The material was characterized by X-ray Diffraction (XRD), Transmission Electron Microscopy (TEM), Fourier Transform Infrared Spectroscopy (FT-IR) and Photoluminescence (PL). Uniformly distributed nanoparticles were obtained with an average particle size range of 8-10 nm. Various studies were undertook utilizing different doping concentrations and respective fluorescence studies were carried out to optimize dopant concentrations while achieving maximum luminescence intensity. From PL results, it was observed that the efficient energy transfers from the donor to the acceptor ions. Different concentrations of Tb(3+), Eu(3+) were doped in order to achieve a white light emitting phosphor for UV-based Light Emitting Diodes (LEDs). The nanoparticles showed characteristic emission of respective dopants (Eu(3+), Tb(3+)) when excited at the 4f → 5d transition of Ce(3+). The chromaticity coordinates for CeF3 doped with Eu(3+) and Tb(3+) were calculated and an emission very close to white light was observed.
A Linear Encoding Approach to Index Assignment in Lossy Source-Channel Coding

We present a general scheme for the lossy transmission of a source with arbitrary statistics through a noisy channel under the mean-square error fidelity criterion. Our approach is based on transform coding, scalar quantization of the transform coefficients and linear encoding of the quantization indices. Entropy coding and channel coding are merged into a single linear encoding function, such that the "catastrophic" behavior of conventional entropy coding is avoided and the full power of modern coding techniques and iterative "Belief-Propagation" decoding can be exploited. We show that this approach is asymptotically optimal in the limit of large block length, for arbitrary source statistics and binary-input output-symmetric channel. In the practical regime of finite block length and low decoding complexity, we show, through the explicit construction of codes for the lossy transmission of digital images over a binary symmetric channel, that our approach yields significant improvements with respect to previously proposed channel-optimized quantization schemes and also with respect to the conventional concatenation of state-of-the art image coding with state-of-the art channel coding. Although our constructive example focuses on a special case, the approach is general and can be applied to other classes of sources of practical interest.
Methylation patterns within 5'-UTR of DAT1 gene as a function of allelic 3'-UTR variants and their maternal or paternal origin: May these affect the psychopathological phenotypes in children? An explorative study

Psychopathological symptoms such as depression/anxiety vs attention or aggression problems, in children, have been associated to altered expression of the DAT1/SLC6A3 gene. Inheriting specific 9- or 10-repeat VNTR alleles could modify the pattern of methylation in the CpGs islands at the 5'-UTR of the DAT1 gene. Through accurate recruitment at primary schools, we ended up with four subgroups of children: 9/9 and 10/10 homozygous; 9/10 heterozygous born from 9/10 mothers and 10/10 fathers (called heM); 9/10 heterozygous born from 10/10 mothers and 9/10 fathers (called heF). (Epi)genetical changes were found to be in relation to internalizing and externalizing symptoms: compared to other genotypes, our 9/9 children exhibited mainly internalizing symptoms, while 10/10 genotype was previously associated with ADHD severity. We found that 10/10 children bear 5'-UTR motifs showing a CpGs 1-2-3-5 unity with anticorrelated CpG 6, while 9/9 children showed rather a demethylated CpG 1 linked to demethylated CpG 6. We found two different patterns between heMs and heFs: a feature of heM children is in CpGs 1-3 methylated pattern with CpGs 2, 5 and 6 demethylated together, supporting a "split" unitary destiny. Within the heF children, the status for CpGs 3 + 6 remained opposite, yet pattern of (de)methylation was not well defined. The prevailing one between inherited parental alleles may somewhat influence the motif destiny of heterozigous children. Present work aimed to identify novel epigenetic biomarkers, to be exploited as fairly indicators of children's psychopathological vulnerability.
Pseudomonas fitomaticsae sp. nov., isolated at Marimurtra Botanical Garden in Blanes, Catalonia, Spain

In the framework of the research project called fitomatics, we have isolated and characterized a bacterial plant-endophyte from the rhizomes of Iris germanica, hereafter referred to as strain FIT81T. The bacterium is Gram negative, rod-shaped with lophotrichous flagella, and catalase- and oxidase-positive. The optimal growth temperature of strain FIT81T is 28 °C, although it can grow within a temperature range of 4-32 °C. The pH growth tolerance ranges between pH 5 and 10, and it tolerates 4% (w/v) NaCl. A 16S rRNA phylogenetic analysis positioned strain FIT81T within the genus Pseudomonas, and multilocus sequence analysis revealed that Pseudomonas gozinkensis IzPS32dT, Pseudomonas glycinae MS586T, Pseudomonas allokribbensis IzPS23T, 'Pseudomonas kribbensis' 46-2 and Pseudomonas koreensis PS9-14T are the top five most closely related species, which were selected for further genome-to-genome comparisons, as well as for physiological and chemotaxonomic characterization. The genome size of strain FIT81T is 6 492 796 base-pairs long, with 60.6 mol% of G+C content. Average nucleotide identity and digital DNA-DNA hybridization analyses yielded values of 93.6 and 56.1%, respectively, when the FIT81T genome was compared to that of the closest type strain P. gozinkensis IzPS32dT. Taken together, the obtained genomic, physiologic and chemotaxonomic data indicate that strain FIT81T is different from its closest relative species, which lead us to suggest that it is a novel species to be included in the list of type strains with the name Pseudomonas fitomaticsae sp. nov. (FIT81T=CECT 30374T=DSM 112699T).
Long-term effectiveness and safety of omalizumab in pediatric and adult patients with moderate-to-severe inadequately controlled allergic asthma

Omalizumab is recommended as an add-on therapy in patients aged ≥6 years with inadequately controlled, moderate-to-severe persistent allergic asthma. The efficacy and safety of omalizumab treatment in allergic asthma clinical trials and its effectiveness in the real world have been reported in numerous studies. In this review, we examine clinical evidence in pediatric and adult patients with allergic asthma who received omalizumab treatment for at least 2 years, to assess its effectiveness, durability, and trajectory of response over time as well as safety. We performed a literature search from inception until March 2022 in PubMed using the keywords "omalizumab" and "allergic asthma" to retrieve articles examining the effects of omalizumab in patients with allergic asthma, aged ≥6 years. Only articles that evaluated the effectiveness of omalizumab for at least 2 years were included. Data from case reports were excluded. Our review confirmed the long-term effectiveness and safety of omalizumab, demonstrating reduced rate of exacerbations, improved lung function, asthma control, and quality of life, decreased health care resource utilization, and use of corticosteroids (oral/inhaled) with a favorable safety and tolerability profile for up to 9 years in adult patients with moderate-to-severe allergic asthma. Similar results were also observed in the pediatric population with up to 7.5 years of omalizumab treatment. This review highlights and confirms the sustained clinical benefits of omalizumab over long periods of treatment in pediatric and adult populations with allergic asthma.
Towards Fast and Optimal Grouping of Regular Expressions via DFA Size Estimation

Regular Expression (RegEx) matching, as a core operation in many network and security applications, is typically performed on Deterministic Finite Automata (DFA) to process packets at wire speed; however, DFA size is often exponential in the number of RegExes. RegEx grouping is the practical way to address DFA state explosion. Prior RegEx grouping algorithms are extremely slow and memory intensive. In this paper, we first propose DFAestimator, an algorithm that can quickly estimate DFA size for a given RegEx set without building the actual DFA. Second, we propose RegexGrouper, a RegEx grouping algorithm based on DFA size estimation. In terms of speed and memory consumption, our work is orders of magnitude more efficient than prior art because DFA size estimation is much faster and memory efficient than DFA construction. In terms of the resulting size sum of DFAs, our work is significantly more effective than prior art because we use a much finer grained quantification of the degree of interaction between two RegExes. For example, to divide the RegEx set of the L7-filter system into 7 groups, prior art uses 279.3 minutes and the resulting 7 DFAs have a total of 29047 states, whereas RegexGrouper uses 3.2 minutes and the resulting 7 DFAs have a total of 15578 states.
Timing Analysis of Tasks on Runtime Reconfigurable Processors

Real-time embedded systems need to be analyzable for timing guarantees. Despite significant scientific advances, however, timing analysis lags years behind current microarchitectures with out-of-order scheduling pipelines, several hardware threads, and multiple (shared) cache layers. To satisfy the increasing performance demands, analyzable performance features are required. We propose a novel timing analysis approach to introduce runtime reconfigurable instruction set processors as one way to escape the scarcity of analyzable performance while preserving the flexibility of the system. We introduce extensions to the state-of-the-art Integer linear programming (ILP)-based program path analysis for computing precise worst case time bounds in the presence of the widely used technique to continue processor execution during reconfiguration by emulating not yet reconfigured custom instructions (CIs) in software. We identify and safely bound a timing anomaly of runtime reconfiguration, where executing faster than worst case time during reconfiguration extends the execution time of the whole program. Stalling the processor during reconfiguration (easier to analyze but not state-of-the-art for reconfigurable processors) is not required in our approach. Finally, we show the precision of our analysis on a complex multimedia application with multiple reconfigurable CIs for several hardware parameters and give advice on how to deal with reconfiguration delay under timing guarantees.
Intergenerational Programming Increases Solid Food Consumption for Adult Day Center Attendees

We examined whether participation in intergenerational programming would impact daily food and liquid intake for adult day service center (ADSC) participants, many of whom are at risk for malnutrition and dehydration. Data came from 75 ADSC participants who, on average, attended the center for 472.32 days between 2007 and 2018. We analyzed daily data using multilevel modeling, nesting attending days within ADSC participants. On days when participants joined intergenerational programming, they consumed significantly more solid food (β = 1.54, SD = .37, p < .001), but no different liquid (β = -.16, SD = .09, p = .06), than their own average across all days they attended the ADSC. Intergenerational programming may be an effective way to support ADSCs participants' nutrition. Future research is needed to determine the longer-term health benefits of daily increases in food consumption and to explore why intergenerational programming may differentially impact eating and drinking.
Phytoremediation of nitrogen and phosphorus pollutants from glass industry effluent by using water hyacinth (Eichhornia crassipes (Mart.) Solms): Application of RSM and ANN techniques for experimental optimization

The present study aimed to assess the efficiency of the water hyacinth (Eichhornia crassipes (Mart.) Solms) plant for the reduction of nitrogen and phosphorus pollutants from glass industry effluent (GIE) as batch mode phytoremediation experiments. For this, response surface methodology (RSM) and artificial neural networks (ANN) methods were adopted to evidence the optimization and prediction performances of E. crassipes for total Kjeldahl's nitrogen (TKN) and total phosphorus (TP) removal. The control parameters, i.e., GIE concentration (0, 50, and 100%) and plant density (1, 3, and 5 numbers) were used to optimize the best reduction conditions of TKN and TP. A quadratic model of RSM and feed-forward backpropagation algorithm-based logistic model (input layer: 2 neurons, hidden layer: 10 neurons, and output layer: 1 neuron) of ANN showed good fitness results for experimental optimization. Optimization results showed that maximum reduction of TKN (93.86%) and TP (87.43%) was achieved by using 60% of GIE concentration and nearly five plants. However, coefficient of determination (R2) values showed that ANN models (TKN: 0.9980; TP: 0.9899) were superior in terms of prediction performance as compared to RSM (TKN: 0.9888; TP: 0.9868). Therefore, the findings of this study concluded that E. crassipes can be effectively used to remediate nitrogen and phosphorus loads of GIE and minimize environmental hazards caused by its unsafe disposal.
An accelerated correlation filter tracker

Recent visual object tracking methods have witnessed a continuous improvement in the state-of-the-art with the development of efficient discriminative correlation filters (DCF) and robust deep neural network features. Despite the outstanding performance achieved by the above combination, existing advanced trackers suffer from the burden of high computational complexity of the deep feature extraction and online model learning. We propose an accelerated ADMM optimisation method obtained by adding a momentum to the optimisation sequence iterates, and by relaxing the impact of the error between DCF parameters and their norm. The proposed optimisation method is applied to an innovative formulation of the DCF design, which seeks the most discriminative spatially regularised feature channels. A further speed up is achieved by an adaptive initialisation of the filter optimisation process. The significantly increased convergence of the DCF filter is demonstrated by establishing the optimisation process equivalence with a continuous dynamical system for which the convergence properties can readily be derived. The experimental results obtained on several well-known benchmarking datasets demonstrate the efficiency and robustness of the proposed ACFT method, with a tracking accuracy comparable to the start-of-the-art trackers. (C) 2020 Elsevier Ltd. All rights reserved.
Rüdin's 1916 Monograph: On the Inheritance and Primary Origin of Dementia Praecox

In 1916, Ernst Rüdin published the first modern family study in the history of psychiatric genetics, the major goal of which was to test whether the pattern of risk in the siblings of dementia praecox (DP) probands followed Mendelian expectations. He utilized systematic ascertainment of probands and multisourced diagnostic assessments of probands and relatives, applying the narrow Kraepelinian concept of DP. In a novel step, he collaborated closely with a statistical geneticist-Wilhelm Weinberg-and applied his sibling, proband, and age correction methods. In his key sample-701 sibships when neither parent had DP-the morbid risk for DP in siblings was 4.48%, much lower than 25% expected for a recessive disorder. Risk for DP was increased by alcoholism or other mental disorders in parents. Other non-DP psychoses were common in both siblings and parents of DP probands. Rüdin discussed several alternative genetic models for DP including a 2-locus recessive, incomplete penetrance, and an oligogenic model. The high rates of other psychoses and psychopathic personalities in relatives might arise, he suggested, because these disorders shared genetic risks with DP. Rüdin established that DP, when carefully studied, ran in families, did not have a simple Mendelian genetic transmission pattern, and appeared likely to be genetically related to other non-DP psychotic disorders and perhaps some kinds of psychopathic personalities. This study, the most important in Rüdin's career, should be viewed in the context of his later extensive support of and collaboration with Nazi eugenic policies.
Niche width predicts extinction from climate change and vulnerability of tropical species

Climate change may be a major threat to global biodiversity, especially to tropical species. Yet, why tropical species are more vulnerable to climate change remains unclear. Tropical species are thought to have narrower physiological tolerances to temperature, and they have already experienced a higher estimated frequency of climate-related local extinctions. These two patterns suggest that tropical species are more vulnerable to climate change because they have narrower thermal niche widths. However, no studies have tested whether species with narrower climatic niche widths for temperature have experienced more local extinctions, and if these narrower niche widths can explain the higher frequency of tropical local extinctions. Here, we test these ideas using resurvey data from 538 plant and animal species from 10 studies. We found that mean niche widths among species and the extent of climate change (increase in maximum annual temperatures) together explained most variation (>75%) in the frequency of local extinction among studies. Surprisingly, neither latitude nor occurrence in the tropics alone significantly predicted local extinction among studies, but latitude and niche widths were strongly inversely related. Niche width also significantly predicted local extinction among species, as well as among and (sometimes) within studies. Overall, niche width may offer a relatively simple and accessible predictor of the vulnerability of populations to climate change. Intriguingly, niche width has the best predictive power to explain extinction from global warming when it incorporates coldest yearly temperatures.
Semaglutide for the treatment of overweight and obesity: A review

Obesity is a chronic, relapsing disease associated with multiple complications and a substantial morbidity, mortality and health care burden. Pharmacological treatments for obesity provide a valuable adjunct to lifestyle intervention, which often achieves only limited weight loss that is difficult to maintain. The Semaglutide Treatment Effect in People with obesity (STEP) clinical trial programme is evaluating once-weekly subcutaneous semaglutide 2.4 mg (a glucagon-like peptide-1 analogue) in people with overweight or obesity. Across STEP 1, 3, 4 and 8, semaglutide 2.4 mg was associated with mean weight losses of 14.9%-17.4% in individuals with overweight or obesity without type 2 diabetes from baseline to week 68; 69%-79% of participants achieved ≥10% weight loss with semaglutide 2.4 mg (vs. 12%-27% with placebo) and 51%-64% achieved ≥15% weight loss (vs. 5%-13% with placebo). In STEP 5, mean weight loss was -15.2% with semaglutide 2.4 mg versus -2.6% with placebo from baseline to week 104. In STEP 2 (individuals with overweight or obesity, and type 2 diabetes), mean weight loss was -9.6% with semaglutide 2.4 mg versus -3.4% with placebo from baseline to week 68. Improvements in cardiometabolic risk factors, including high blood pressure, atherogenic lipids and benefits on physical function and quality of life were seen with semaglutide 2.4 mg. The safety profile of semaglutide 2.4 mg was consistent across trials, primarily gastrointestinal adverse events. The magnitude of weight loss reported in the STEP trials offers the potential for clinically relevant improvement for individuals with obesity-related diseases.