Miracle-dz/UniFAR-FTUs huggingface dataset:
Blockade of Adenosine A2A Receptor Protects Photoreceptors after Retinal Detachment by Inhibiting Inflammation and Oxidative Stress

Purpose Adenosine A2A receptor (A2AR) signaling is neuroprotective in some retinal damage models, but its role in neuronal survival during retinal detachment (RD) is unclear. We tested the hypothesis that A2AR antagonist ZM241385 would prevent photoreceptor apoptosis by inhibiting retinal inflammation and oxidative stress after RD. Methods The A2AR antagonist ZM241385 was delivered daily to C57BL/6J mice for three days at a dose (3 mg/kg, i.p.) starting 2 hours prior to creating RD. A2AR expression, microglia proliferation and reactivity, glial fibrillary acidic protein (GFAP) accumulation, IL-1β expression, and reactive oxygen species (ROS) production were evaluated with immunofluorescence. Photoreceptor TUNEL was analyzed. Results A2AR expression obviously increased and accumulated in microglia and Müller cells in the retinas after RD. The A2AR antagonist ZM241385 effectively inhibited retinal microglia proliferation and reactivity, decreased GFAP upregulation and proinflammatory cytokine IL-1β expression of Müller cells, and suppressed ROS overproduction, resulting in attenuation of photoreceptor apoptosis after RD. Conclusions The A2AR antagonist ZM241385 is an effective suppressor of microglia proliferation and reactivity, gliosis, neuroinflammation, oxidative stress, and photoreceptor apoptosis in a mouse model of RD. This suggests that A2AR blockade may be an important therapeutic strategy to protect photoreceptors in RD and other CNS diseases that share a common etiology.
Occurrence, inter-annual variability and zooplankton-predation impact of the invasive ctenophore Mnemiopsis leidyi and the native jellyfish Aurelia aurita in Limfjorden (Denmark) in 2010 and 2011

In 2007, the invasive ctenophore Mnemiopsis leidyi was observed for the first time in Limfjorden (Denmark) where it exhibited mass occurrence in late summer while the indigenous and usually dominating common jellyfish, Aurelia aurita, was nearly absent. Both species were further studied in 2008 and 2009 and it was found that the additional predation pressure by M. leidyi caused the zooplankton stocks to be severely depressed. Here, we report on the population dynamics and predation impact of M. leidyi and A. aurita in Limfjorden in 2010 and 2011. In 2010, M. leidyi was observed in Limfjorden for the first time in August with the highest density and largest size in the central parts (Skive Fjord). The estimated half-life of zooplankton (copepods) was only important in Skive Fjord in mid August 2010 when the jointpredation impact of A. aurita and M. leidyi was 2.3 d. In 2011, no M. leidyi were observed on the first cruise (3 August), while during the second cruise (17 November) it was observed in large numbers. The western most location (Veno Bugt) was dominated by large sized (≤ 60 mm) M. leidyi, while the average size decreased towards the central parts of the fjord-system. The proportion of cydippid larvae increased from west to the central parts thus suggesting rapid reproduction and population-size expansion. The bio-volumes of ctenophores were highest in the central part with 85 ml m -3 in Logstor Bredning, which may be compared to the greatest mean bio-volume of about 184 ml m -3 observed in the Black Sea in 1989 when the zooplankton and fish stocks collapsed. Analysis of available hydrographic data and model calculations indicates that re-invasion of M. leidyi from the North Sea seeded the autumn population in Limfjorden in mid-September.
The influence of emergent and submerged macrophyte beds on ciliate communities in a shallow lake

Abstract Relationships between ciliates and the presence of emergent and submerged vegetation were studied in a shallow lake in eastern Poland. Samples were collected in zones of Phragmites, Typha, Batrachium, Elodea, Stratiotes and from the open water zone. The abundance and biomass of ciliates were significantly higher at sites with structurally most complex plants than in the open water or sparsely vegetated sites. The redundancy analysis indicated that bacterial abundance and total organic carbon were the most influential variables that determine the distribution of ciliates. However, chlorophyll a and Ptot have a lesser influence on the distribution of these microorganisms. Based on differences in macrophyte structure, two groups of habitats with similar patterns of size-related ciliate distribution were distinguished. The first group consisted of three vegetation zones of sparse stem structure and the open water zone, the second group comprised submerged macrophyte species, which were more complex.
Use of Big Data and Machine Learning Methods in the Monitoring and Evaluation of Digital Health Programs in India: An Exploratory Protocol

Background Digital health programs, which encompass the subsectors of health information technology, mobile health, electronic health, telehealth, and telemedicine, have the potential to generate “big data. ” Objective Our aim is to evaluate two digital health programs in India—the maternal mobile messaging service (Kilkari) and the mobile training resource for frontline health workers (Mobile Academy). We illustrate possible applications of machine learning for public health practitioners that can be applied to generate evidence on program effectiveness and improve implementation. Kilkari is an outbound service that delivers weekly gestational age–appropriate audio messages about pregnancy, childbirth, and childcare directly to families on their mobile phones, starting from the second trimester of pregnancy until the child is one year old. Mobile Academy is an Interactive Voice Response audio training course for accredited social health activists (ASHAs) in India. Methods Study participants include pregnant and postpartum women (Kilkari) as well as frontline health workers (Mobile Academy) across 13 states in India. Data elements are drawn from system-generated databases used in the routine implementation of programs to provide users with health information. We explain the structure and elements of the extracted data and the proposed process for their linkage. We then outline the various steps to be undertaken to evaluate and select final algorithms for identifying gaps in data quality, poor user performance, predictors for call receipt, user listening levels, and linkages between early listening and continued engagement. Results The project has obtained the necessary approvals for the use of data in accordance with global standards for handling personal data. The results are expected to be published in August/September 2019. Conclusions Rigorous evaluations of digital health programs are limited, and few have included applications of machine learning. By describing the steps to be undertaken in the application of machine learning approaches to the analysis of routine system-generated data, we aim to demystify the use of machine learning not only in evaluating digital health education programs but in improving their performance. Where articles on analysis offer an explanation of the final model selected, here we aim to emphasize the process, thereby illustrating to program implementors and evaluators with limited exposure to machine learning its relevance and potential use within the context of broader program implementation and evaluation. International Registered Report Identifier (IRRID) DERR1-10.2196/11456
Alzheimer’s Disease, Inflammation, and the Role of Antioxidants

The World Health Organization refers to Alzheimer’s disease (AD) as a global health priority. As the average age of the world’s population is increasing, so too is the rate of AD. There are an estimated 47 million people globally who have been diagnosed with AD dementia, and researchers have yet to figure out the root cause. All misfolded aggregate proteins that are involved in neurodegenerative disorders (amyloid-β, Huntington’s tau, α-synuclein) induce oxidative stress. It is that oxidative stress that leads to inflammation and, in conjunction with amyloid protein and tau hyperphosphorylation, progresses to and exacerbates AD. The consumption of antioxidants and nutrients, specifically vitamin E, caffeine, and turmeric, may slow the progression of AD and can be found in a wide variety of dietary foods. This review explores the role of inflammation on AD, the antioxidants that can potentially combat it, and future directions of how the treatment of the disease can be better understood.
Effect of Yucca Saponin on Urease Activity and Development of Ascites in Broiler Chickens

The study was conducted to ascertain the effect of "Norponin 200 Liquid" on urease activity and development of ascites in broiler chickens. Two commercial broiler rations were prepared containing 2810 Kcal/kg metabolizable energy and 20 % crude protein starter and 2900 Kcal/kg metabolizable energy and 18.50 % crude protein, finisher ration. 240 chicks were divided into four groups i.e. A, B, C and D, respectively. Each group had 60 birds and groups were further subdivided into 6 replicates having 10 birds each. Each group offered different concentrations of Norponin 200 Liquid. Group A was control group i.e. without medication. Groups B, C and D were offered 2.5, 5.0 and 7.5 ml Norponin 200 liquid/100 liter of drinking water, respectively. The data regarding feed consumption, weight gain, FCR, urease activity inside the intestine and in the excreta, mortality and economics were recorded. It was concluded that group D offered Norponin 200 Liquid at 7.50 ml/100 liter of drinking water had comparatively better results than groups B and C offered 2.5 ml and 5.0 ml Norponin 200 liquid/100 liter of drinking water and control group A.
Insecticidal effects of essential oils of Pelargonium graveolens and Cymbopogon citratus on Sitophilus zeamais (Motsch.)

The evaluation of the effect of essential oils of Pelargonium graveolens andCymbopogon citratus on maize weevil (Sitophilus zeamais) has assigned the most significant insecticidal activity against it with a maximum mortality rate of 100%. The essential oils were found to have high contact and ingestion toxicity than fumigant / respiratory poison. This is evident from 90% mortality of weevils that come in contact or ingest contaminated food and only 40% when inhaled. This observation clarifies that the non volatile active components are more efficient than the volatile compounds of these essential oils. The insecticidal activity was more intense but short for higher concentrations of these oils and low and long-lasting for average concentrations. In fact, insecticidal activity decreased with the concentration of essential oils and varnishes with very small concentrations (from a dilution of 1/80 in our case) while it decreased with an increase in contact distance. The statistical results showed that the difference between the insecticidal activity of essential oils of P. graveolens (geranium) and C. citratus (lemongrass) was not significant in the three tests. Given that the weevil is the most devastating insect of maize (post-harvest), this study showed that these essential oils can serve, in one way or another, as a means of conserving maize corns for a longer time. Key words: Cymbopogon citratus, Pelargonium graveolens, essential oils, insecticidal activity, Sitophilus zeamais.
LSRepair: Live Search of Fix Ingredients for Automated Program Repair

Automated program repair (APR) has extensively been developed by leveraging search-based techniques, in which fix ingredients are explored and identified in different granularities from a specific search space. State-of-the approaches often find fix ingredients by using mutation operators or leveraging manually-crafted templates. We argue that the fix ingredients can be searched in an online mode, leveraging code search techniques to find potentially-fixed versions of buggy code fragments from which repair actions can be extracted. In this study, we present an APR tool, LSRepair, that automatically explores code repositories to search for fix ingredients at the method-level granularity with three strategies of similar code search. Our preliminary evaluation shows that code search can drive a faster fix process (some bugs are fixed in a few seconds). LSRepair helps repair 19 bugs from the Defects4J benchmark successfully. We expect our approach to open new directions for fixing multiple-lines bugs.
High thermal acclimation potential of both photosynthesis and respiration in two lowland Plantago species in contrast to an alpine congeneric

Thermal acclimation of photosynthesis and respiration can enable plants to maintain near constant rates of net CO2 exchange, despite experiencing sustained changes in daily average temperature. In this study, we investigated whether the degree of acclimation of photosynthesis and respiration of mature leaves differs among three congeneric Plantago species from contrasting habitats [two fast‐growing lowland species (Plantago major and P. lanceolata), and one slow‐growing alpine species (P. euryphylla)]. In addition to investigating some mechanisms underpinning variability in photosynthetic acclimation, we also determined whether leaf respiration in the light acclimates to the same extent as leaf respiration in darkness, and whether acclimation reestablishes the balance between leaf respiration and photosynthesis. Three growth temperatures were provided: constant 13, 20, or 27°C. Measurements were made at five temperatures (6–34°C). Little acclimation of photosynthesis and leaf respiration to growth temperature was exhibited by P. euryphylla. Moreover, leaf masses per area (LMA) were similar in 13°C‐grown and 20°C‐grown plants of the alpine species. In contrast, growth at 13°C increased LMA in the two lowland species; this was associated with increased photosynthetic capacity and rates of leaf respiration (both in darkness and in the light). Alleviation of triose phosphate limitation and increased capacity of electron transport capacity relative to carboxylation were also observed. Such changes demonstrate that the lowland species cold‐acclimated. Light reduced the short‐term temperature dependence (i.e. Q10) of leaf respiration in all three species, irrespective of growth temperature. Collectively, our results highlight the tight coupling that exists between thermal acclimation of photosynthetic and leaf respiratory metabolism (both in darkness and in the light) in Plantago. If widespread among contrasting species, such coupling may enable modellers to assume levels of acclimation in one parameter (e.g. leaf respiration) where details are only known for the other (e.g. photosynthesis).
Purification and Characterization of Pisum Seed Trypsin Inhibitors

Seed trypsin inhibitors have been purified from Pisum. Three groups of inhibitor were separated using column chromatography, whereas non-denaturing activity gels showed that five inhibitors could be distinguished. N-terminal sequence data obtained for two purified inhibitors showed that these belong to the Bowman-Birk class of inhibitors. Partial purification and characterization of a protease with in vitro trypsin-like activity from Pisum seed protein preparations indicated that this endogenous protease is not inhibited by any of the fractionated inhibitors.
Herd immunity thresholds for SARS-CoV-2 estimated from unfolding epidemics

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads, the susceptible subpopulation declines causing the rate at which new infections occur to slow down. Variation in individual susceptibility or exposure to infection exacerbates this effect. Individuals that are more susceptible or more exposed tend to be infected and removed from the susceptible subpopulation earlier. This selective depletion of susceptibles intensifies the deceleration in incidence. Eventually, susceptible numbers become low enough to prevent epidemic growth or, in other words, the herd immunity threshold is reached. Here we fit epidemiological models with inbuilt distributions of susceptibility or exposure to SARS-CoV-2 outbreaks to estimate basic reproduction numbers (R_0) alongside coefficients of individual variation (CV) and the effects of containment strategies. Herd immunity thresholds are then calculated as 1-(1/R_0 )^(1/((1+CV^2 ) )) or 1-(1/R_0 )^(1/((1+2CV^2 ) )), depending on whether variation is on susceptibility or exposure. Our inferences result in herd immunity thresholds around 10-20%, considerably lower than the minimum coverage needed to interrupt transmission by random vaccination, which for R_0 higher than 2.5 is estimated above 60%. We emphasize that the classical formula, 1-1/R_0 , remains applicable to describe herd immunity thresholds for random vaccination, but not for immunity induced by infection which is naturally selective. These findings have profound consequences for the governance of the current pandemic given that some populations may be close to achieving herd immunity despite being under more or less strict social distancing measures.
m-Nonparallel support vector machine for pattern classification

In this paper, we propose a novel nonparallel hyperplane classifier, named m-nonparallel support vector machine (m-NPSVM), for binary classification. Based on our recently proposed method, i.e., nonparallel support vector machine (NPSVM), which has been proved superior to the twin support vector machines, m-NPSVM is param- eterized by the quantity m to let ones effectively control the number of support vectors. By combining the m-support vector classification and the m-support vector regression together to construct the primal problems, m-NPSVM inherits the advantages of m-support vector machine so that enables us to eliminate one of the other free parameters of the NPSVM: the accuracy parameter e and the regulariza- tion constant C. We describe the algorithm, give some theoretical results concerning the meaning and the choice of m, and also report the experimental results on lots of data sets to show the effectiveness of our method.
Geographical reconstruction of the SARS‐CoV‐2 outbreak in Lombardy (Italy) during the early phase

The first identification of autochthonous transmission of SARS‐CoV‐2 in Italy was documented by the Laboratory of Clinical Microbiology, Virology and Bioemergencies of L. Sacco Hospital (Milano, Italy) on 20th February 2020 in a 38 years old male patient, who was found positive for pneumonia at the Codogno Hospital. Thereafter Lombardy has reported the highest prevalence of COVID‐19 cases in the country, especially in Milano, Brescia and Bergamo provinces. The aim of this study was to assess the potential presence of different viral clusters belonging to the six main provinces involved in Lombardy COVID‐19 cases in order to highlight peculiar province‐dependent viral characteristics. A phylogenetic analysis was conducted on 20 full length genomes obtained from patients addressing to several Lombard hospitals from February 20th to April 4th, 2020, aligned with 41 Italian viral genome assemblies available on GISAID database as of 30th March, 2020: two main monophyletic clades, containing 8 and 53 isolates, respectively, were identified. Noteworthy, Bergamo isolates mapped inside the small clade harbouring M gene D3G mutation. The molecular clock analysis estimated a cluster divergence approximately one month before the first patient identification, supporting the hypothesis that different SARS‐CoV‐2 strains had spread worldwide at different times, but their presence became evident only in late February along with Italian epidemic emergence. Therefore, this epidemiological reconstruction suggests that virus initial circulation in Lombardy was ascribable to multiple introduction. The phylogenetic reconstruction robustness, however, will be improved when more genomic sequences are available, in order to guarantee a complete epidemiological surveillance.
Relative contributions of family history and a polygenic risk score on COPD and related outcomes: COPDGene and ECLIPSE studies

Introduction: Family history is a risk factor for chronic obstructive pulmonary disease (COPD). We previously developed a COPD risk score from genome-wide genetic markers (polygenic risk score, or PRS). Whether the PRS and family history provide complementary or redundant information for predicting COPD and related outcomes is unknown. Methods: We assessed the predictive capacity of family history and PRS on COPD and COPD-related outcomes in European ancestry subjects from the COPDGene and ECLIPSE studies. We also performed interaction and mediation analyses. Results: In COPDGene, family history and PRS were significantly associated with COPD in a single model (PFamHx = 1.6e-12; PPRS = 5.0e-92). Similar trends were seen in ECLIPSE. Area-under-the-receiver-operator-characteristic-curves (AUCs) for family history, PRS, and the combined predictors for COPD were 0.752, 0.798, and 0.803, respectively. The AUC for a model containing both family history and the PRS was significantly higher than models with PRS (p = 0.00035) or family history (p = 6.1e-29) alone. Both family history and PRS were significantly associated with BODE, SGRQ, and multiple measures of quantitative emphysema and airway thickness. There was a weakly positive interaction between family history and the PRS under the additive, but not the multiplicative scale (RERI = 0.48, p=0.04). Mediation analysis found 16.5% of the effect of family history on risk for COPD was mediated through the PRS [95% CI: 9.4%-24.3%]. Conclusion: Family history and the PRS provide complementary information for predicting COPD and related outcomes. Future studies can address the impact of obtaining both measures in clinical practice.
Serum Anion Gap Is Associated with All-Cause Mortality among Critically Ill Patients with Congestive Heart Failure

Background: Congestive heart failure (CHF) is a complex clinical syndrome, with high morbidity and mortality. Serum anion gap (SAG) has been known to be associated with the severity of various cardiovascular diseases. However, the role of SAG indicators in CHF is unclear. Methods and results: A retrospective analysis of data from MIMIC-III v1.4 was conducted in critically ill patients with CHF. Clinical information of each patient, including demographic data, comorbidities, vital signs, scores, and laboratory indicators, were successfully obtained. Cox proportional hazards models were performed to determine the relationship between SAG and mortality in CHF patient, the consistency of which was further verified by subgroup analysis. Results: A total of 7426 subjects met the inclusion criteria. In multivariate analysis, after adjusting for age, gender, ethnicity, and other potential confounders, higher SAG was significantly related to an increase in 30-day and 90-day all-cause mortality of critically ill patients with CHF compared with lower SAG (tertile3 vs tertile1: adjusted HR, 95% CI: 1.74, 1.46-2.08; 1.53, 1.32-1.77). In subgroup analysis, the association between SAG and all-cause mortality present similarities in most strata. Conclusion: SAG at admission can be a promising predictor of all-cause mortality in critically ill patients with CHF.