Miracle-dz/UniFAR-FTUs huggingface dataset:
Surveillance Study of Acute Neurological Manifestations among 439 Egyptian Patients with COVID-19 in Assiut and Aswan University Hospitals

Background: COVID-19 can be accompanied by acute neurological complications of both central and peripheral nervous systems (CNS and PNS). In this study, we estimate the frequency of such complications among hospital inpatients with COVID-19 in Assiut and Aswan university hospitals. Materials and Methods: We screened all patients with suspected COVID-19 admitted from 1 June to 10 August 2020 to the university hospitals of Assiut and Aswan in Upper Egypt. Clinical and laboratory tests, CT/MRI of the chest and brain, and neurophysiology study were performed for each patient if indicated. Results: 439 patients had confirmed/probable COVID-19; neurological manifestations occurred in 222. Of these, 117 had acute neurological disease and the remainder had nonspecific neuropsychiatric symptoms such as headache, vertigo, and depression. The CNS was affected in 75 patients: 55 had stroke and the others had convulsions (5), encephalitis (6), hypoxic encephalopathy (4), cord myelopathy (2), relapse of multiple sclerosis (2), and meningoencephalitis (1). The PNS was affected in 42 patients: the majority had anosmia and ageusia (31) and the others had Guillain-Barré syndrome (4), peripheral neuropathy (3), myasthenia gravis (MG, 2), or myositis (2). Fever, respiratory symptoms, and headache were the most common general symptoms. Hypertension, diabetes mellitus, and ischemic heart disease were the most common comorbidities in patients with CNS affection. Conclusion: In COVID-19, both the CNS and PNS are affected. Stroke was the most common complication for CNS, and anosmia and/or ageusia were common for PNS diseases. However, there were 6 cases of encephalitis, 2 cases of spinal cord myelopathy, 2 cases of MG, and 2 cases of myositis.
Transmission routes of SARS-CoV-2 among healthcare workers of a French university hospital in Paris, France: a case-control study

In this case-control study on 564 healthcare workers of a university hospital in Paris (France), contacts without protection with COVID-19 patients or with colleagues were associated with infection with SARS-CoV-2, while working in a COVID-dedicated unit, using public transportation and having children kept in childcare facilities were not.
Genome-wide association study meta-analysis identifies three novel loci for circulating anti-Müllerian hormone levels in women

Anti-Mullerian hormone (AMH) is expressed by antral stage ovarian follicles in women. Consequently, circulating AMH levels are detectable until menopause. Variation in age-specific AMH levels has been associated with breast cancer and polycystic ovary syndrome (PCOS), amongst other diseases. Identification of genetic variants underlying variation in AMH levels could provide clues about the physiological mechanisms that explain these AMH-disease associations. To date, only one variant in MCM8 has been identified to be associated with circulating AMH levels in women. We aimed to identify additional variants for AMH through a GWAS meta-analysis including data from 7049 premenopausal women of European ancestry, which more than doubles the sample size of the largest previous GWAS. We identified four loci associated with AMH levels at p < 5x10-8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41, and CDCA7. The strongest signal was a missense variant in the AMH gene (rs10417628). Most prioritized genes at the other three identified loci were involved in cell cycle regulation. Genetic correlation analyses indicated a strong positive correlation among SNPs for AMH levels and for age at menopause (rg= 0.82, FDR=0.003). Exploratory Mendelian randomization analyses did not support a causal effect of AMH on breast cancer or PCOS risk, but should be interpreted with caution as they may be underpowered and the validity of genetic instruments could not be extensively explored. In conclusion, we identified a variant in the AMH gene and three other loci that may affect circulating AMH levels in women.
Identification of metabolomics biomarkers for type 2 diabetes: triangulating evidence from longitudinal and Mendelian randomization analyses

The number of people affected by Type 2 Diabetes Mellitus (T2DM) is close to half a billion and is on a sharp rise, representing a major and growing public health burden. As the case for many other complex diseases, early diagnosis is key to prevent irreversible end-organ damages. However, given its mild initial symptoms, T2DM is often diagnosed several years after its onset, leaving half of diabetic individuals undiagnosed. While several classical clinical and genetic biomarkers have been identified, improving early diagnosis by exploring other kinds of omics data remains crucial. In this study, we have combined longitudinal data from two population-based cohorts CoLaus and DESIR (comprising in total 493 incident cases vs 1360 controls) to identify new or confirm previously implicated metabolomic biomarkers predicting T2DM incidence more than five years ahead of clinical diagnosis. Our longitudinal data have shown robust evidence for valine, leucine, carnitine and glutamic acid being predictive of future conversion to T2DM, and also confirmed to be causal by 2-sample Mendelian randomisation (based on independent data). Interestingly, for valine and leucine a strong reverse causal effect was detected, indicating that the genetic predisposition to T2DM may trigger early changes of these metabolites, which appear well-before any clinical symptoms. These findings indicate that molecular traits linked to the genetic basis of T2DM may be particularly promising early biomarkers.
A tipping point in cancer-immune dynamics leads to divergent immunotherapy responses and hampers biomarker discovery

Background Predicting treatment response or survival of cancer patients remains challenging in immuno-oncology. Efforts to overcome these challenges focus, among others, on the discovery of new biomarkers. Despite advances in cellular and molecular approaches, only a limited number of candidate biomarkers eventually enter clinical practice. Methods A computational modeling approach based on ordinary differential equations was used to simulate the fundamental mechanisms that dictate tumor-immune dynamics and to investigate its implications on responses to immune checkpoint inhibition (ICI) and patient survival. Using in silico biomarker discovery trials, we revealed fundamental principles that explain the diverging success rates of biomarker discovery programs. Results Our model shows that a tipping point—a sharp state transition between immune control and immune evasion—induces a strongly non-linear relationship between patient survival and both immunological and tumor-related parameters. In patients close to the tipping point, ICI therapy may lead to long-lasting survival benefits, whereas patients far from the tipping point may fail to benefit from these potent treatments. Conclusion These findings have two important implications for clinical oncology. First, the apparent conundrum that ICI induces substantial benefits in some patients yet completely fails in others could be, to a large extent, explained by the presence of a tipping point. Second, predictive biomarkers for immunotherapy should ideally combine both immunological and tumor-related markers, as a patient’s distance from the tipping point can typically not be reliably determined from solely one of these. The notion of a tipping point in cancer-immune dynamics helps to devise more accurate strategies to select appropriate treatments for patients with cancer.
Growth of respiratory droplets in cold and humid air

The ambient conditions surrounding liquid droplets determine their growth or shrinkage. However, the precise fate of a liquid droplet expelled from a respiratory puff as dictated by its surroundings and the puff itself has not yet been fully quantified. From the view of airborne disease transmission, such as SARS-CoV-2, knowledge of such dependencies are critical. Here we employ direct numerical simulations (DNS) of a turbulent respiratory vapour puff and account for the mass and temperature exchange with respiratory droplets and aerosols. In particular, we investigate how droplets respond to different ambient temperatures and relative humidity (RH) by tracking their Lagrangian statistics. We reveal and quantify that in cold and humid environments, as there the respiratory puff is supersaturated, expelled droplets can first experience significant growth, and only later followed by shrinkage, in contrast to the monotonic shrinkage of droplets as expected from the classical view by William F. Wells (1934). Indeed, cold and humid environments diminish the ability of air to hold water vapour, thus causing the respiratory vapour puff to super-saturate. Consequently, the super-saturated vapour field drives the growth of droplets that are caught and transported within the humid puff. To analytically predict the likelihood for droplet growth, we propose a model for the axial RH based on the assumption of a quasi-stationary jet. Our model correctly predicts super-saturated RH conditions and is in good quantitative agreement with our DNS. Our results culminate in a temperature-RH map that can be employed as an indicator for droplet growth or shrinkage.
UDC: 544.13 ULTRAFAST ELECTRON CRYSTALLOGRAPHY AND NANOCRYSTALL OGRAPHY: FOR CHEMISTRY, BIOLOGY AND MATERIALS SCIENCE. PART II. ULTRAFAST ELECTRON NANOCRYSTALLOGRAPHY

В статье описан метод сверхбыстрой электронной нанокристаллографии ‒ конкретной реализации метода сверхбыстрой электронной кристаллографии, оптимизированной для высокочувствительного и высокоэффективного сбора данных при исследовании наноструктур с высоким временным разрешением, от пико до фемтосекунд. Эти достижения открыли новые возможности для изучения когерентной структурной динамики наночастиц. Наноструктуры характеризуются рядом необычных свойств по сравнению с их объемными аналогами. Прежде всего, это связано с проявлением квантоворазмерного эффекта и относительно большого числа структурных единиц наночастицы, находящихся на ее поверхности. Одной из структурных особенностей является возникновение так называемых нанокристаллических структурных типов, которые имеют тенденцию к образованию замкнутых оболочек, и связаны с появлением магических чисел в распределении размеров. Морфология и параметры решетки нанокристаллов сильно зависят от подложки и модификации поверхности, что приводит к сжатию и образованию границ двойников из-за релаксации поверхностных деформаций. Статья описывает эксперимент сверхбыстрой электронной нанокристаллографии, теорию метода и анализ данных, а также процедуру пробоподготовки поверхности подложки и образцов при исследовании методом UEnC. Представленные примеры включают результаты изучения структурной динамики конденсированной фазы, поверхностей и нанокристаллов, дина-
Scared Straight or Scared to Death? Fatalism in Response to Disease Risks

This paper tests a model in which responses to disease risks can be “fatalistic”: higher risk beliefs can lead to more risk-taking rather than less. This occurs because high risk beliefs raise the perceived chance that you are already infected, lowering the marginal cost of risk-taking. I test for fatalism by randomly providing information about the true (low) average risk of HIV transmission in Malawi. Just as the model predicts, the treatment causes sexual activity to rise slightly on average but decline sharply for people with high initial risk beliefs—especially those with high baseline levels of sexual activity. JEL Codes: D81, D83, I12
Phase II Clinical trial for Evaluation of BCG as potential therapy for COVID-19

Bacillus Calmette Guerin (BCG) is widely used in national vaccination programs worldwide. It is accepted that BCG alleviates both pathogen and allergy induced respiratory diseases that could also include Covid-19. To investigate this possibility, we randomly assigned 60 Covid-19 patients, after admission to the hospital with pneumonia and requirement for oxygen therapy in a 1:1 ratio to receive either a single adult dose of intradermal BCG or normal saline with concomitant standard of care (SoC) medications. Primary endpoints were favorable prognosis of Covid-19 as deduced from resolution of pneumonia, viremia and secondary outcome were enumeration of ICU admissions, duration thereof and mortalities. Results Both primary and secondary endpoints were significantly improved in the BCG+SoC group. This could be seen from reduction in oxygen requirement due to Covid-19 associated pneumonia decreasing from day 3-4, improved radiological resolution from day 7-15. There were a total of 6 (10%) adverse events in the study of which 2 deaths and 4 ICU admissions were in SoC group (1 ICU admission culminated in death of the subject) and in contrast only 1 ICU admission in the BCG+SoC group. While there was an increase in Covid-19 specific IgG levels in the BCG+SoC group, there was no evidence of BCG induced cytokine storm in this group. Four patients showed localized inflammatory response at the injection site in the BCG+SoC group. Conclusions BCG+SoC administration resulted in a significantly higher percentage of patients with favorable outcomes than did SoC. A third of the patients were naive for childhood BCG vaccination. This mimicked elderly patients in countries with no universal vaccination policy for BCG. No BCG related adversity was seen in this group. The study shows that BCG is a safe, cost-effective treatment that can be introduced as a standard of care in patients with moderate Covid-19 that can reduce requirement of oxygen supplemented beds and disease burden in low resource countries, with additional long-term benefits of reducing risk for tuberculosis.
Rapid Memory Reactivation at Movie Event Boundaries Promotes Episodic Encoding

Segmentation of continuous experience into discrete events is driven by rapid fluctuations in encoding stability at context shifts (i.e., event boundaries), yet the mechanisms underlying the online formation of event memories are poorly understood. We investigated the neural per-time point spatial similarity patterns of the scalp electrophysiological (EEG) activity of 30 human participants (male and female) watching a 50 min movie and found that event boundaries triggered the rapid reinstatement of the just-encoded movie event EEG patterns. We also found that the onset of memory reinstatement at boundary onset was accompanied by a left-lateralized anterior negative ERP effect, which likely reflects the detection of a shift in the narrative structure of the movie. A data-driven approach based on Hidden Markov modeling allowed us to detect event boundaries as shifts between stable patterns of brain EEG activity during encoding, and to identify their reactivation during a free recall task. These results provide the first neurophysiological underpinnings for how the memory systems segment a continuous long stream of experience into episodic events. SIGNIFICANCE OF STATEMENT Memory for specific episodic events are the building blocks of our autobiographical memory. However, it is still unclear how the memory systems structure the unfolding experience into discrete event units that can be understood and remembered at the long-term. Here, we show that the detection of context shifts, or event boundaries, during a 50 min movie viewing triggers the rapid memory reactivation of the just-encoded event to promote its successful encoding into long-term memory. By finding that memory reactivation, a neural mechanism critical for episodic memory formation and consolidation, takes place under these ecologically valid experimental circumstances, our results provide valuable insights into how the brain shapes the ongoing experience into episodic memories in the real-life.
Innate immunity plays a key role in controlling viral load in COVID-19: mechanistic insights from a whole-body infection dynamics model

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a pathogen of immense public health concern. Efforts to control the disease have only proven mildly successful, and the disease will likely continue to cause excessive fatalities until effective preventative measures (such as a vaccine) are developed. It is important to better understand SARS-CoV-2 pathogenesis and population susceptibility to infection in order to develop effective disease management strategies. To this end, physiologically relevant mathematical modeling can provide a robust in silico tool to understand COVID-19 pathophysiology and the in vivo dynamics of SARS-CoV-2. Guided by ACE2-tropism (ACE2 receptor dependency of the virus for infection) of the virus, and by incorporating cellular-scale viral dynamics and innate and adaptive immune response, we have developed a multiscale mechanistic model for simulating the time-dependent evolution of viral load distribution in susceptible organs of the body. Following calibration with in vivo and clinical data, we used the model to simulate viral load progression in a virtual patient with varying degrees of compromised immune status. Further, to understand the effects of physiological factors and underlying conditions on viral load dynamics, we conducted global sensitivity analysis of model parameters and ranked them for their significance in governing clearance of viral load from the body. Antiviral drug therapy, interferon therapy, and their combination was simulated to study the effects on viral load kinetics of SARS-CoV-2. The model highlights the importance of innate immunity (interferons and resident macrophages) in controlling viral load, and the significance of timing when initiating therapy following infection.
Therapeutic efficacy of Honey and Nigella sativa against COVID-19: A multi-center randomized controlled clinical trial (HNS-COVID-PK)

BACKGROUND: COVID-19 has caused havoc across the globe since, no specific treatment exists for this disease, thus, far. Hence, there is an urgent need to find an effective treatment to mitigate this scourge. Honey and Nigella sativa are two natural substances with anti-inflammatory, anti-viral, anti-microbial and immune modulating properties. They could be potentially beneficial in these patients. METHODS: We conducted an add-on, randomized, open label, placebo-controlled clinical trial using parallel group design. This was a multi-centered study with superiority framework conducted in RT-PCR confirmed COVID-19 patients showing moderate or severe disease. All patients receiving standard care were randomized into treatment and control groups. In the treatment arm, patients received HNS (honey plus Nigella sativa) in predefined doses for up to 13 days. The primary outcome measures (time taken for alleviation of symptoms, viral clearance and clinical status improvement on day 6) outcomes were assessed. RESULTS: Of 1046 patients testing positive for the SARS-CoV-2, 210 showing moderate and 103 showing severe disease were randomized into treatment and control groups as per inclusion criteria. In the moderate cases, 107 were assigned to the HNS group and 103 to the control group. Among 103 severe cases, 50 were assigned to the HNS group and 53 to the control group. In the moderate and severe cases, the HNS treatment was associated with a normalized median symptoms alleviation time reduction of 3 and 7 days (HR: 6.11; 95% CI: 4.23-8.84 and HR: 4.04; 95% CI, 2.46-6.64) respectively. The HNS treatment in both groups were further associated with 4 days earlier reduction in median viral clearance time (Moderate HR: 5.53; 95% CI: 3.76-8.14) and Severe HR: 4.32; 95% CI: 2.62-7.13). Moreover, in the intention-to-treat analysis, the HNS groups led to a lower (better) clinical score on day 6 with resumption of normal activity among 63.6% of the moderate (OR: 0.07; 95% CI: 0.03-0.13) and 28% of severe cases (OR: 0.03; 95% CI: 0.01-0.09). Furthermore, a significant (14.87%) reduction (OR: 0.18; 95% CI: 0.02-0.92) in mortality was observed in the HNS arm. No difference in adverse effects were seen between the HNS and control arms. CONCLUSIONS: A significant reduction in in the severity of disease, the time taken for viral clearance and mortality was observed with HNS treatment in COVID-19 patients. HNS represents a safe, effective, over the counter and affordable therapy for this pandemic essentially lowering health care burden. It can be used alone or in combination with other expensive treatments and give an additive effect. Hence, the potential of HNS against COVID-19 should be explored in future larger studies. (Funded by Smile Welfare Organization, Shaikh Zayed Medical Complex and Services Institute of Medical Sciences; NIH Clinical Trial Register number: NCT04347382.)
The Interplay between Maternal Smoking and Genes in Offspring Birth Weight

It is well-established that both the child's genetic endowments as well as maternal smoking during pregnancy impact offspring birth weight. In this paper we move beyond the nature versus nurture debate by investigating the interaction between genetic endowments and this critical prenatal environmental exposure (maternal smoking) in determining birth weight. We draw on longitudinal data from the Avon Longitudinal Study of Parents and Children (ALSPAC) study and replicate our results using data from the UK Biobank. Genetic endowments of the children are proxied with a polygenic score that is constructed based on the results of the most recent genome wide association study of birth weight. We instrument the maternal decision to smoke during pregnancy with a genetic variant (rs1051730) located in the nicotine receptor gene CHRNA3. This genetic variant is associated with the number of cigarettes consumed daily, and we present evidence that this is plausibly the only channel through which the maternal genetic variant affects the child's birth weight. Additionally, we deal with the misreporting of maternal smoking by using measures of cotinine, a biomarker of nicotine, collected from the mother's urine during their pregnancy. We confirm earlier findings that genetic endowments as well as maternal smoking during pregnancy significantly affects the child's birth weight. However, we do not find evidence of meaningful interactions between genetic endowments and an adverse fetal environment, suggesting that the child's genetic predisposition cannot cushion the damaging effects of maternal smoking.
Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent

Expectation maximization (EM) is the default algorithm for fitting probabilistic models with missing or latent variables, yet we lack a full understanding of its non-asymptotic convergence properties. Previous works show results along the lines of “EM converges at least as fast as gradient descent” by assuming the conditions for the convergence of gradient descent apply. This approach is not only loose, in that it does not capture that EM can make more progress than a gradient step, but the assumptions fail to hold for textbook examples of EM like Gaussian mixtures. In this work, we show that for the common setting of exponential family distributions, viewing EM as a mirror descent algorithm leads to convergence rates in Kullback-Leibler (KL) divergence and how the KL divergence is related to first-order stationarity via Bregman divergences. In contrast to previous works, the analysis is invariant to the choice of parametrization and holds with minimal assumptions. We also show applications of these ideas to local linear (and superlinear) convergence rates, generalized EM, and non-exponential family distributions.