Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of seven pollens on life table parameters of Neoseiulus cucumeris (Acari: Phytoseiidae)

Abstract In some integrated pest management programs, different pollens are used as alternative or supplementary food sources for rearing of the generalist predatory mites. The aim of this study was to determine the performance of the predatory mite Neoseiulus cucumeris (Oudemans) (Acari: Phytoseiidae) on pollen of seven plant species including Panicum miliaceum, Punica granatum, Eruca sativa, Chenopodium album, Chaenomeles cathayensis, Datura stramonium, Caesalpinia gilliesii as a food source. All experiments were conducted at 25±1°C, 65±5% RH and 16:8 h (L:D) photoperiod. Age-stage, two-sex life table method was used for data analysis to take into account the variable developmental rate among individuals as well as stage differentiation. The predatory mite was able to survive to adult and reproduce on all pollen grains tested. The shortest pre-adult period was shown on P. granatum pollen. The intrinsic rate of increase (r) was between 0.162 to -0.097 day -1, which was observed on D. stramonium and P. miliaceum, respectively. The longest total lifespan of females, highest intrinsic rate of increase, finite rate of increase (λ) and net reproductive rate (R0) were recorded on the D. stramonium pollen, while the shortest mean generation time (T) was on the P. granatum pollen. According to the results, in the absence or shortage of the main prey in the environment, the pollen of D. stramonium can be suggested as an alternative or supplementary food for N. cucumeris.
Morphological ontogeny of Graptoppia granadaensis sp. nov. (Acari, Oribatida, Oppiidae), and comments on Graptoppia Balogh

Abstract The morphological ontogeny of Graptoppia granadaensis S. et A. Seniczak sp. nov. is described and illustrated, based on the instars obtained from laboratory cultures. The adults of this species were collected from spruce litter (Picea sp.) in the Campus of University of Science in Granada, Spain. These adults are the most similar to that of G. tanaitica Karppinen et Poltavskaja, 1990, but differ from it by having fewer spines on the bothridial seta. In laboratory cultures, G. granadaensis fed on deciduous and pine litter and small parts of pine cones, overgrown by mycelium. The juveniles of this species are unpigmented, with soft body, covered with microtuberculate cerotegument. The larva has 12 pairs of gastronotal setae, including h3, the nymphs have 15 pairs; all setae are smooth and mostly short. In the juveniles, seta d coupled to proper solenidia is present on genua I–III and tibiae II–IV.
Evaluation of race/ethnicity-specific survival machine learning models for Hispanic and Black patients with breast cancer

Objectives Survival machine learning (ML) has been suggested as a useful approach for forecasting future events, but a growing concern exists that ML models have the potential to cause racial disparities through the data used to train them. This study aims to develop race/ethnicity-specific survival ML models for Hispanic and black women diagnosed with breast cancer to examine whether race/ethnicity-specific ML models outperform the general models trained with all races/ethnicity data. Methods We used the data from the US National Cancer Institute’s Surveillance, Epidemiology and End Results programme registries. We developed the Hispanic-specific and black-specific models and compared them with the general model using the Cox proportional-hazards model, Gradient Boost Tree, survival tree and survival support vector machine. Results A total of 322 348 female patients who had breast cancer diagnoses between 1 January 2000 and 31 December 2017 were identified. The race/ethnicity-specific models for Hispanic and black women consistently outperformed the general model when predicting the outcomes of specific race/ethnicity. Discussion Accurately predicting the survival outcome of a patient is critical in determining treatment options and providing appropriate cancer care. The high-performing models developed in this study can contribute to providing individualised oncology care and improving the survival outcome of black and Hispanic women. Conclusion Predicting the individualised survival outcome of breast cancer can provide the evidence necessary for determining treatment options and high-quality, patient-centred cancer care delivery for under-represented populations. Also, the race/ethnicity-specific ML models can mitigate representation bias and contribute to addressing health disparities.
Investigating the risks of cardiovascular disease among premenopausal women using oral contraceptive: a protocol for a systematic review and meta-analysis

Introduction The use of oral contraceptives (OCs) is linked to an increased risk of cardiovascular diseases (CVDs) in women of reproductive age. CVD remain one of the top causes of death worldwide, with at least three-quarters of deaths occurring in low-income and middle-income nations. The impact of various types of combined oral contraceptive (COC) on several modifiable risk factors associated with CVDs in premenopausal women is inconsistent regardless of genetic mutations. The aim of this systematic review will be to provide a comprehensive synthesis of the available evidence on the impact of COC usage on modifiable risk factors associated with CVDs and assess ethnic and geographic disparities in the reported prevalence of CVD. Methods and analysis This systematic review protocol was prepared in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses Protocols 2015 statement. An extensive search on the Embase, MEDLINE and Cochrane Library will be conducted from inception until. Two reviewers will independently screen for eligible studies using a predefined criterion. The risk of bias and quality of included studies will be assessed using the modified Downs and Black’s checklist. Whereas the overall quality of included studies will be assessed using the Grading of Recommendations, Assessment, Development and Evaluation assessment tool. Ethics and dissemination This is a review of existing studies and will not require ethical approval. The findings will be disseminated through peer-reviewed publication. The use of OC and the risk of CVDs including arterial and venous thrombosis remain a major concern among women of reproductive age. Thus, given the impact of COCs on the risk variables linked with CVDs, this review may provide an insight and assistance during COC use. PROSPERO registration number CRD42020216169.
Differentiating stages of functional vision loss from glaucoma using the Disc Damage Likelihood Scale and cup:disc ratio

Background Glaucoma staging is critical for treatment planning but has rarely been tested in severe/end-stage disease. We compared the performance of the Disc Damage Likelihood Scale (DDLS) and cup:disc ratio (CDR) using a functional glaucoma staging system (GSS) as the reference standard. Methods Post hoc analysis of a randomised controlled trial at the Eye Department of Kilimanjaro Christian Medical Centre, Tanzania. Eligible participants (aged ≥18 years) with open-angle glaucoma, intraocular pressure (IOP) of >21 mm Hg, were randomised to timolol 0.5% eye drops or selective laser trabeculoplasty. Fundoscopy established vertical and horizontal CDRs and DDLS. Visual acuity and static visual fields were graded (GSS). The study used area under the receiver operating characteristic (AROC) curves and Spearman’s rank correlation coefficients to compare staging systems. Logistic regression with generalised estimating equations determined risk factors of functional severe/end-stage glaucoma. Results 382 eyes (201 participants) were evaluated; 195 (51%) had severe or end-stage glaucoma; mean IOP was 26.7 (SD 6.9) mm Hg. DDLS yielded an AROC of 0.90 (95% CI 0.87 to 0.93), vertical cup:disc ratio (vCDR) of 0.88 (95% CI 0.85 to 0.91, p=0.048) for identifying severe/end-stage disease. Correlation coefficients comparing GSS to DDLS and vCDRs were 0.73 and 0.71, respectively. Advanced structural stages, vision impairment, higher IOP and less financial resources were risk factors of functional severe/end-stage glaucoma. Conclusion This study indicates that both structural staging systems can differentiate severe/end-stage glaucoma from less severe disease, with a moderate advantage of DDLS over CDR. Clinical examination of the optic disc plays an important role in addition to functional assessment when managing severe/end-stage glaucoma.
Ebola virus disrupts the inner blood-retinal barrier by induction of vascular endothelial growth factor in pericytes

Ebola virus (EBOV) causes severe hemorrhagic fever in humans with high mortality. In Ebola virus disease (EVD) survivors, EBOV persistence in the eyes may break through the inner blood–retinal barrier (iBRB), leading to ocular complications and EVD recurrence. However, the mechanism by which EBOV affects the iBRB remains unclear. Here, we used the in vitro iBRB model to simulate EBOV in retinal tissue and found that Ebola virus-like particles (EBO-VLPs) could disrupt the iBRB. Cytokine screening revealed that EBO-VLPs stimulate pericytes to secrete vascular endothelial growth factor (VEGF) to cause iBRB breakdown. VEGF downregulates claudin-1 to disrupt the iBRB. Ebola glycoprotein is crucial for VEGF stimulation and iBRB breakdown. Furthermore, EBO-VLPs caused iBRB breakdown by stimulating VEGF in rats. This study provides a mechanistic insight into that EBOV disrupts the iBRB, which will assist in developing new strategies to treat EBOV persistence in EVD survivors.
Detection of Offensive Language and ITS Severity for Low Resource Language

Continuous proliferation of hate speech in different languages on social media has drawn significant attention from researchers in the past decade. Detecting hate speech is indispensable irrespective of the scale of use of language, as it inflicts huge harm on society. This work presents a first resource for classifying the severity of hate speech in addition to classifying offensive and hate speech content. Current research mostly limits hate speech classification to its primary categories, such as racism, sexism, and hatred of religions. However, hate speech targeted at different protected characteristics also manifests in different forms and intensities. It is important to understand varying severity levels of hate speech so that the most harmful cases of hate speech may be identified and dealt with earlier than the less harmful ones. In this work, we focus on detecting offensive speech, hate speech, and multiple levels of hate speech in the Urdu language. We investigate three primary target categories of hate speech: religion, racism, and national origin. We further divide these categories into levels based on the severity of hate conveyed. The severity levels are referred to as symbolization, insult, and attribution. A corpus comprising more than 20,000 tweets against the corresponding hate speech categories and severity levels is collected and annotated. A comprehensive experimentation scheme is applied using traditional as well as deep learning–based models to examine their impact on hate speech detection. The highest macro-averaged F-score yielded for detecting offensive speech is 86% while the highest F-scores for detecting hate speech with respect to ethnicity, national origin, and religious affiliation are 80%, 81%, and 72%, respectively. This shows that results are very encouraging and would provide a lead towards further investigation in this domain.
High HIV and syphilis prevalence among female sex workers and sexually exploited adolescents in Nimule town at the border of South Sudan and Uganda

HIV prevalence among the general population in South Sudan, the world’s newest country, is estimated at 2.9% and in Nimule, a town at the border with Uganda, it is estimated at 7.5%. However, there is limited data describing the HIV epidemic among female sex workers and sexually exploited adolescents (FSW/SEA) in the country. This study was conducted using a respondent-driven sampling (RDS) among FSW/SEA aged ≥15 years in January-February 2017 who sold or exchanged sex in the last six months in Nimule. Consenting participants were administered a questionnaire and tested for HIV according to the national algorithm. Syphilis testing was conducted using SD BIOLINE Syphilis 3.0 and Rapid Plasma Reagin for confirmation. Data were analyzed in SAS and RDS-Analyst and weighted results are presented. The 409 FSW/SEA participants with a median age of 28 years (IQR 23–35) and a median age of 23 years (IQR 18–28) when they entered the world of sex work, were enrolled in the Eagle survey. Nearly all (99.2%) FSW/SEA lacked comprehensive knowledge of HIV though almost half (48.5%) talked to a peer educator or outreach worker about HIV in the last 30 days. More than half (55.3%) were previously tested for HIV. Only 46.4% used a condom during their last vaginal or anal sexual act with a client. One in five (19.8%) FSW/SEA experienced a condom breaking during vaginal or anal sex in the last six months HIV prevalence was 24.0% (95% CI: 19.4–28.5) and 9.2% (95% CI: 6.5–11.9) had active syphilis. The multivariable analysis revealed the association between HIV and active syphilis (aOR: 6.99, 95% CI: 2.23–21.89). HIV and syphilis prevalence were higher among FSW/SEA in Nimule than the general population in the country and Nimule. Specifically, the HIV prevalence was eight times higher than the general population. Our findings underscore the importance of providing HIV and syphilis testing for FSW/SEA in conjunction with comprehensive combination prevention, including comprehensive HIV information, promotion of condom use, and availing treatment services for both HIV and syphilis.
A Multi-Level Consistency Network for High-Fidelity Virtual Try-On

The 2D virtual try-on task aims to transfer a target clothing image to the corresponding region of a person image. Although an extensive amount of research has been conducted due to its immense applications, this task still remains a great challenge to handle some complicated issues (e.g., non-rigid shapes, large occlusions and arbitrary poses). To this end, we propose a novel network with structural and textural consistency-preserving mechanism for producing high-fidelity try-on images. Specifically, we first generate the semantic layout of a clothing-agnostic person to obtain the segmentation map, which is used as the transforming conditions of the target clothes. Based on a recurrent network structure, the transform lookup is performed to iteratively update a dense flow. Then, we adopt a thin-plate-spline-based warping method to estimate the coarse offset flow for all key-point positions. Guided by this sparse flow, a multi-scale deformable convolution module is designed to further iteratively predict the fine offsets for densely sampled positions, by which the clothing item and person shape can be accurately aligned. Finally, we develop a refinement module to effectively fuse the global and local features, which can render accurate geometric structures of the body parts and maintain texture sharpness of the clothes. Extensive experiments on benchmark datasets demonstrate that our method outperforms other state-of-the-art methods in terms of quantitative and qualitative try-on results. The code is available on: https://github.com/TJU-WEIHAO/MLCN.
The application of machine learning to predict high-cost patients: A performance-comparison of different models using healthcare claims data

Our aim was to predict future high-cost patients with machine learning using healthcare claims data. We applied a random forest (RF), a gradient boosting machine (GBM), an artificial neural network (ANN) and a logistic regression (LR) to predict high-cost patients in the following year. Therefore, we exploited routinely collected sickness funds claims and cost data of the years 2016, 2017 and 2018. Various specifications of each algorithm were trained and cross-validated on training data (n = 20,984) with claims and cost data from 2016 and outcomes from 2017. The best performing specifications of each algorithm were selected based on validation dataset performance. For performance comparison, selected models were applied to unforeseen data with features of the year 2017 and outcomes of the year 2018 (n = 21,146). The RF was the best performing algorithm measured by the area under the receiver operating curve (AUC) with a value of 0.883 (95% confidence interval (CI): 0.872–0.893) on test data, followed by the GBM (AUC = 0.878; 95% CI: 0.867–0.889). The ANN (AUC = 0.846; 95% CI: 0.834–0.857) and LR (AUC = 0.839; 95% CI: 0.826–0.852) were significantly outperformed by the GBM and the RF. All ML algorithms and the LR performed ´good´ (i.e. 0.9 > AUC ≥ 0.8). We were able to develop machine learning models that predict high-cost patients with ‘good’ performance facilitating routinely collected sickness fund claims and cost data. We found that tree-based models performed best and outperformed the ANN and LR.
Light and temperature regulate m6A-RNA modification to regulate growth in plants

N6-methyladenosine is a highly dynamic, abundant mRNA modification which is an excellent potential mechanism for fine tuning gene expression. Plants adapt to their surrounding light and temperature environment using complex gene regulatory networks. The role of m6A in controlling gene expression in response to variable environmental conditions has so far been unexplored. Here, we map the transcriptome-wide m6A landscape under various light and temperature environments. Identified m6A-modifications show a highly specific spatial distribution along transcripts with enrichment occurring in 5’UTR regions and around transcriptional end sites. We show that the position of m6A modifications on transcripts might influence cellular transcript localization and the presence of m6A-modifications is associated with alternative polyadenylation, a process which results in multiple RNA isoforms with varying 3’UTR lengths. RNA with m6A-modifications exhibit a higher preference for shorter 3’UTRs. These shorter 3’UTR regions might directly influence transcript abundance and localization by including or excluding cis-regulatory elements. We propose that environmental stimuli might change the m6A landscape of plants as one possible way of fine tuning gene regulation through alternative polyadenylation and transcript localization.
Apical expansion of calvarial osteoblasts and suture patency is dependent on graded fibronectin cues

The skull roof, or calvaria, is comprised of interlocking plates of bone. Premature suture fusion (craniosynostosis, CS) or persistent fontanelles are common defects in calvarial development. Although some of the genetic causes of these disorders are known, we lack an understanding of the instructions directing the growth and migration of progenitors of these bones, which may affect the suture patency. Here, we identify graded expression of Fibronectin (FN1) protein in the mouse embryonic cranial mesenchyme (CM) that precedes the apical expansion of calvarial osteoblasts. Syndromic forms of CS exhibit dysregulated FN1 expression, and we find FN1 expression is altered in a mouse CS model as well. Conditional deletion of Fn1 in CM causes diminished frontal bone expansion by altering cell polarity and shape. To address how osteoprogenitors interact with the observed FN1 prepattern, we conditionally ablate Wasl/N-Wasp to disrupt F-actin junctions in migrating cells, impacting lamellipodia and cell-matrix interaction. Neural crest-targeted deletion of Wasl results in a diminished actin network and reduced expansion of frontal bone primordia similar to conditional Fn1 mutants. Interestingly, defective calvaria formation in both the Fn1 and Wasl mutants occurs without a significant change in proliferation, survival, or osteogenesis. Finally, we find that CM-restricted Fn1 deletion leads to premature fusion of coronal sutures. These data support a model of FN1 as a directional substrate for calvarial osteoblast migration that may be a common mechanism underlying many cranial disorders of disparate genetic etiologies.
The emergence of goblet inflammatory or ITGB6hi nasal progenitor cells determines age-associated SARS-CoV-2 pathogenesis

Children infected with SARS-CoV-2 rarely progress to respiratory failure, but the risk of mortality in infected people over 85 years of age remains high, despite vaccination and improving treatment options. Here, we take a comprehensive, multidisciplinary approach to investigate differences in the cellular landscape and function of paediatric (<11y), adult (30- 50y) and elderly (>70y) nasal epithelial cells experimentally infected with SARS-CoV-2. Our data reveal that nasal epithelial cell subtypes show different tropism to SARS-CoV-2, correlating with age, ACE2 and TMPRSS2 expression. Ciliated cells are a viral replication centre across all age groups, but a distinct goblet inflammatory subtype emerges in infected paediatric cultures, identifiable by high expression of interferon stimulated genes and truncated viral genomes. In contrast, infected elderly cultures show a proportional increase in ITGB6hi progenitors, which facilitate viral spread and are associated with dysfunctional epithelial repair pathways. Graphical Abstract
Anti-CRISPR AcrIIC5 is a dsDNA mimic that inhibits type II-C Cas9 effectors by blocking PAM recognition

Anti-CRISPR proteins are encoded by phages to inhibit the CRISPR-Cas systems of the hosts. AcrIIC5 inhibits several naturally high-fidelity type II-C Cas9 enzymes, including orthologs from Neisseria meningitidis (Nme1Cas9) and Simonsiella muelleri (SmuCas9). Here, we solve the structure of AcrIIC5 in complex with Nme1Cas9 and sgRNA. We show that AcrIIC5 adopts a novel fold to mimic the size and charge distribution of double-stranded DNA, and uses its negatively charged grooves to bind and occlude the protospacer adjacent motif (PAM) binding site in the target DNA cleft of Cas9. AcrIIC5 is positioned into the crevice between the WED and PI domains of Cas9, and one end of the anti-CRISPR interacts with the phosphate lock loop and a linker between the RuvC and BH structural domains. We employ biochemical and mutational analyses to build a model for AcrIIC5’s mechanism of action, and identify residues on both the anti-CRISPR and Cas9 that are important for their interaction and inhibition. Together, the structure and mechanism of AcrIIC5 reveal convergent evolution among disparate anti-CRISPR proteins that use a DNA-mimic strategy to inhibit diverse CRISPR-Cas surveillance complexes, and provide new insights into a tool for potent inhibition of type II-C Cas9 orthologs.