Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Prenatal Exposure to Alcohol and Smoking on Fetal Heart Rate and Movement Regulation

Negative associations of prenatal tobacco and alcohol exposure (PTE and PAE) on birth outcomes and childhood development have been well documented, but less is known about underlying mechanisms. A possible pathway for the adverse fetal outcomes associated with PTE and PAE is the alteration of fetal autonomic nervous system development. This study assessed PTE and PAE effects on measures of fetal autonomic regulation, as quantified by heart rate (HR), heart rate variability (SD-HR), movement, and HR-movement coupling in a population of fetuses at ≥ 34 weeks gestational age. Participants are a subset of the Safe Passage Study, a prospective cohort study that enrolled pregnant women from clinical sites in Cape Town, South Africa, and the Northern Plains region, United States. PAE was defined by six levels: no alcohol, low quit early, high quit early, low continuous, moderate continuous, and high continuous; while PTE by 4 levels: no smoking, quit early, low continuous, and moderate/high continuous. Linear regression analyses of autonomic measures were employed controlling for fetal sex, gestational age at assessment, site, maternal education, household crowding, and depression. Analyses were also stratified by sleep state (1F and 2F) and site (South Africa, N = 4025, Northern Plains, N = 2466). The final sample included 6491 maternal-fetal-dyad assessed in the third trimester [35.21 ± 1.26 (mean ± SD) weeks gestation]. PTE was associated with a decrease in mean HR in state 2F, in a dose dependent fashion, only for fetuses of mothers who continued smoking after the first trimester. In state 1F, there was a significant increase in mean HR in fetuses whose mother quit during the first trimester. This effect was driven by the Norther Plains cohort. PTE was also associated with a significant reduction in fetal movement in the most highly exposed group. In South Africa a significant increase in mean HR both for the high quit early and the high continuous group was observed. In conclusion, this investigation addresses a critical knowledge gap regarding the relationship between PTE and PAE and fetal autonomic regulation. We believe these results can contribute to elucidating mechanisms underlying risk for adverse outcomes.
Information silos distort biomedical research

Information silos have been an oft-maligned feature of scientific research for introducing a bias towards knowledge that is produced within a scientist’s own community. The vastness of the scientific literature has been commonly blamed for this phenomenon, despite recent improvements in information retrieval and text mining. Its actual negative impact on scientific progress, however, has never been quantified. This analysis attempts to do so by exploring its effects on biomedical discovery, particularly in the discovery of relations between diseases, genes and chemical compounds. Results indicate that the probability that two scientific facts will enable the discovery of a new fact depends on how far apart these two facts were published within the scientific landscape. In particular, the probability decreases exponentially with the citation distance. Thus, the direction of scientific progress is distorted based on the location in which each scientific fact is published, representing a path-dependent bias in which originally closely-located discoveries drive the sequence of future discoveries. To counter this bias, scientists should open the scope of their scientific work with modern computational approaches.
CRISPR-Cas9 Screen Reveals PSMB3 Contributes to Gliomagenesis Through Proteasome-Dependent and Independent Mechanisms

Glioblastoma (GBM) is the most common adult malignant brain tumor, with a median survival of 21 months and a 100% recurrence rate. Even though many of the critical oncogenic drivers for GBM have been identified, the basis of gliomagenesis is still under investigation. To identify novel genes that contribute to GBM progression, we performed a genome-wide CRISPR-Cas9 knockout screen. We identified four previously unstudied genes – PSMB3, CHCHD4, SPDYE5, HSPA1 – which had elevated expression in cancer and demonstrated a significant positive correlation with respect to GBM growth and patient survival in vivo and patient datasets. Furthermore, overexpression of PSMB3 and HSPA5 in neural stem cells resulted in transformation to a cancer phenotype. Further investigation of PSMB3, a subunit of the proteasome, allowed us to identify both ubiquitin-mediated and non-ubiquitin-mediated mechanisms of oncogenesis. Ultimately, the data from our CRISPR screens suggests that these genes drive tumor progression, making them promising therapeutic targets for GBM.
PRMT7 ablation stimulates anti-tumor immunity and sensitizes melanoma to immune checkpoint blockade

Despite the success of immune checkpoint inhibitor (ICI) therapy in different cancers, resistance and relapses are frequent. Thus, combination therapies are expected to enhance response rates and overcome resistance to ICIs. Herein, we report that combining protein arginine methyltransferase 7 (PRMT7) inhibition with ICIs triggers a strong anti-tumor T cell immunity and restrains tumor growth in vivo by increasing tumor immune cell infiltration. Consistently, TCGA database analysis showed an inverse correlation between PRMT7 expression and T cell infiltration in human melanomas. Mechanistically, we show that PRMT7 has a two-prong effect on melanoma tumor immunity. On one hand, it serves as a coactivator of IRF-1 for PD-L1 expression by upregulating promoter H4R3me2s levels in melanoma cells. Next, PRMT7 prevents repetitive element expression to avoid intracellular dsRNA accumulation or ‘viral mimicry’. PRMT7 deletion resulted in increased endogenous retroviral elements (ERVs), dsRNA, and genes implicated in interferon activation, antigen presentation and chemokine signaling. Our findings identify PRMT7 as factor used by melanoma to evade anti-tumor immunity and define the therapeutic potential of PRMT7 alone or in combination with PD-(L)1 blockade to enhance ICI efficiency.
Natural variations in reproductive timing of brood size and X-chromosome nondisjunction in Caenorhabditis elegans

Reproductive timing underlies self-sperm production and X-chromosome nondisjunction rate in Caenorhabditis elegans. These traits can be measured as brood size and male-production rate, and brood size decreases and male-production rate increases as worms age. These phenotypic changes occur simultaneously; however, whether these changes share common underlying genetic architectures still remains unclear. To enhance our understanding of reproductive timing in C. elegans, we measured and compared these two reproductive timing-related traits of 96 wild strains during early, late and total reproductive periods. We found that the two traits exhibited natural phenotypic variation with few outliers and a similar reproductive timing pattern as previous reports. The brood size and the male-production rate were not genetically correlated, implying that they might have different genetic architectures and that meiosis quality can be maintained despite increased progeny-production in the late reproductive period caused by more self-sperm. We also identified loci and candidate genetic variants significantly associated with male-production rate in the late and total reproductive periods. Our results provide an insight into life history traits in wild C. elegans strains.
Sex change in aquarium systems establishes the New Zealand spotty wrasse (Notolabrus celidotus) as a temperate model species for the investigation of sequential hermaphroditism

The stunning sexual transformation commonly triggered by age, size or social context in some fishes is one of the best examples of phenotypic plasticity thus far described. To date our understanding of this process is dominated by studies on a handful of subtropical and tropical teleosts, often in wild settings because sex change has been challenging to achieve in captivity. Here we have established the protogynous New Zealand spotty wrasse, Notolabrus celidotus, as a temperate model for the experimental investigation of sex change. Captive fish were induced to change sex using either aromatase inhibition or manipulation of social groups. Complete transition from female to male occurred over 60 days and time-series sampling was used to quantify changes in hormone production, gene expression and gonadal cellular anatomy using radioimmunoassay, nanoString nCounter mRNA and histological analyses, respectively. Early-stage decreases in plasma 17β-estradiol (E2) concentrations or gonadal aromatase (cyp19a1a) expression were not detected in spotty wrasse, despite these being commonly associated with the onset of sex change in subtropical and tropical protogynous (female-to-male) hermaphrodites. In contrast, expression of the masculinising factor amh (anti-Müllerian hormone) increased during early sex change, implying a potential role as a proximate trigger for masculinisation. Expression of male-related genes responsible for androgen production cyp11c1 and hsd11b2 increased from mid sex change. Gonadal expression of the glucocorticoid and mineralocorticoid receptors nr3c1 and nr3c2, putative mediators of the stress hormone cortisol, increased in late stages of sex change. Collectively, these data provide a foundation for the spotty wrasse as a temperate teleost model to study sex change and cell fate in vertebrates.The spotty wrasse, Notolabrus celidotus, is a new temperate model for the study of vertebrate sex change, this work characterises endocrine and genetic markers based on laboratory induced sex change.
The decomposition of konyaite: importance in CO2 fixation in mine tailings

Abstract The sodium-magnesium hydrated double salt konyaite, Na2Mg(SO4)2·5H2O, has been studied by single-crystal X-ray diffraction and thermogravimetry on synthetic samples and by quantitative X-ray diffraction utilizing the Rietveld method on natural samples from the Mount Keith mine, Western Australia. Konyaite crystallizes in space group P21/c, with the cell parameters: a = 5.7594(10), b = 23.914(4), c = 8.0250(13) Å, β = 95.288(9)º, V = 1100.6(3) Å3 and Z = 4. The crystal structure has been refined to R1 = 3.41% for 2155 reflections [Fo>4σ(Fo)] and 6.44% for all 3061 reflections, with all atoms located. Quantitative phase analysis utilizing the Rietveld method was undertaken on five samples of konyaite-bearing mine tailings from the Mount Keith Nickel Mine, Western Australia. Konyaite was found to decompose over time and after 22 months had transformed to other sulphate and amorphous phases. Blödite did not increase in any of the samples indicating that konyaite may not always transform to blödite. Over the same time frame, synthetic konyaite completely decomposed to a mixture of thenardite (Na2SO4), hexahydrite (MgSO4·6H2O), blödite (Na2Mg(SO4)2·4H2O) and löweite (Na12Mg7(SO4)13). Detection of konyaite and other Mg-rich sulphates is important in terms of CO2 fixation. Magnesium bound to sulphate mineral phases reduces the overall potential of tailings piles to lock up atmospheric carbon in Mg carbonates, such as hydromagnesite. Amorphous sulphates are also highly reactive and may contribute to acid mine drainage if present in large quantities, and may dissolve carbonate phases which have already sequestered carbon.
Identification of muscle weakness in older adults from normalized lower and upper limbs strength

Introduction: Weakness is a natural age-related condition meaning the loss of muscle strength that impairs older adults mobility and quality of life. Because the relationship between muscle strength and body-size variables is non-linear, weakness is misclassified in older adults with extreme body size (e.g., light, short, heavy, or tall). This misclassification can be overcome using the allometric approach. Objectives: To propose cut-off points for older adults weakness for upper and lower limbs muscle strength normalized by body size with the ratio standard and allometric scaling. Methods: Ninety-four community-dwelling older adults (69.1% women) were assessed for 49 body-size variables (anthropometry, body composition and body indexes), handgrip strength (HGS), one maximum repetition measurement for knee extensors (1RMknee extensors), isokinetic knee extension peak torque at 60 degrees per second (knee extensionPT), and six-minute walk test (6MWT). Ratio standard (muscle strength/body size) and allometric scaling (muscle strength/body size^b; when b is the allometric exponent) were applied for body-size variables that significantly were correlated with HGS, 1RMknee extensors and knee extensionPT. Cut-off points were computed based on ROC curve and Youden index. When there was mobility limitation (6MWT<400m) cut-off were computed according to sex. Results: Absolute HGS, 1RMknee extensors and knee extensionPT cut-off points were not adequate because they were associated with body size (r>0.30). But it was corrected with muscle strength normalization according to body size-variables: HGS (n=1); 1RMknee extensors (n=24) and knee extensionPT (n=24). The best cut-off points, with the highest area under the curve (AUC), were found after normalization for men: HGS/forearm circumference (1.33 kg/cm, AUC=0.74), 1RMknee extensors/triceps skinfold (4.22 kg/mm, AUC=0.81), and knee extensionPT/body mass*height^0.43 (13.0 Nm/kg*m0.43, AUC=0.94); and for women: HGS/forearm circumference (1.04 kg/cm, AUC=0.70), 1RMknee extensors/body mass (0.54 kg/kg, AUC=0.76); and knee extensionPT/body mass^0.72 (3.14 Nm/kg0.72; AUC=0.82). Conclusion: Normalization removes the effect of extreme body size on muscle strength and improves the accuracy to identify weakness at population level, reducing the risk of false-positive cases.
Predictors of COVID-19 vaccination uptake and reasons for decline of vaccination: a systematic review

Background: Various COVID-19 vaccines with proven safety and effectiveness are available now but vaccine hesitancy remains a public threat. COVID-19 vaccines uptake appears to have an essential role in the successful control of the COVID-19 pandemic. Objective: To examine predictors of COVID-19 vaccination uptake and reasons for decline of vaccination. Methods: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines for this systematic review. We searched Medline, PubMed, Web of Science, Scopus, ProQuest, CINAHL, and a pre-print service (medRxiv) from inception to July 12, 2021. We used the following key-words: vaccin*, COVID-19, and uptake. We included all types of studies (quantitative, qualitative, and mixed methods) reporting COVID-19 vaccination uptake. The review protocol was registered with PROSPERO (CRD42021267460). Results: Twelve studies met the inclusion and exclusion criteria. COVID-19 vaccination uptake ranged from 28.6% to 98% in the general population, while among healthcare workers ranged from 33.3% to 94.5%, and among patients ranged from 36% to 80%. The main predictors of COVID-19 vaccination uptake were male gender, white race, older age, higher socioeconomic status, higher self-perceived COVID-19 vulnerability, increased information about COVID-19 vaccines, and chronic illness. The most important reasons for decline of vaccination were concerns about the safety and effectiveness of vaccines, illness, medication, pregnancy, fertility, breastfeeding, religious reasons, ethical reasons, previous COVID-19 diagnosis, self-estimation that COVID-19 is not a severe disease, and limited knowledge about the vaccines. Conclusions: Several factors affect COVID-19 vaccination uptake, while various reasons affect people decision to refuse to take a COVID-19 vaccine. These findings are essential to further enhance our understanding of COVID-19 vaccination uptake and design specific interventions. Given the high prevalence of COVID-19 vaccine hesitancy, our findings have major implications for the delivery of COVID-19 vaccination programmes in the public with special attention to people who are undecided or unlikely to take a COVID-19 vaccine.
IGS-CMAES: A Two-Stage Optimization for Ground Deformation and DEM Error Estimation in Time Series InSAR Data

Interferometric synthetic aperture radar (InSAR) has become an increasingly recognized remote sensing technology for earth surface monitoring. Slow and subtle terrain displacements can be estimated using time-series InSAR (TSInSAR) data. However, a substantial increase in the availability of exclusive time series data necessitates the development of more efficient and effective algorithms. Research in these areas is usually carried out by solving complicated optimization problems, which is very computationally expensive and time-consuming. This work proposes a two-stage black-box optimization framework to jointly estimate the average ground deformation rate and terrain digital elevation model (DEM) error. The method performs an iterative grid search (IGS) to acquire coarse candidate solutions, and then a covariance matrix adaptive evolution strategy (CMAES) is adopted to obtain the final local results. The performance of our method is evaluated using both simulated and real datasets. Both quantitative and qualitative comparisons using different optimizers support the reliability and effectiveness of our work. The proposed IGS-CMAES achieves higher accuracy with a significantly fewer number of objective function evaluations than other established algorithms. It offers the possibility for wide-area monitoring, where high precision and real-time processing is essential.
Evaluation of RGB and Multispectral Unmanned Aerial Vehicle (UAV) Imagery for High-Throughput Phenotyping and Yield Prediction in Barley Breeding

With advances in plant genomics, plant phenotyping has become a new bottleneck in plant breeding and the need for reliable high-throughput plant phenotyping techniques has emerged. In the face of future climatic challenges, it does not seem appropriate to continue to solely select for grain yield and a few agronomically important traits. Therefore, new sensor-based high-throughput phenotyping has been increasingly used in plant breeding research, with the potential to provide non-destructive, objective and continuous plant characterization that reveals the formation of the final grain yield and provides insights into the physiology of the plant during the growth phase. In this context, we present the comparison of two sensor systems, Red-Green-Blue (RGB) and multispectral cameras, attached to unmanned aerial vehicles (UAV), and investigate their suitability for yield prediction using different modelling approaches in a segregating barley introgression population at three environments with weekly data collection during the entire vegetation period. In addition to vegetation indices, morphological traits such as canopy height, vegetation cover and growth dynamics traits were used for yield prediction. Repeatability analyses and genotype association studies of sensor-based traits were compared with reference values from ground-based phenotyping to test the use of conventional and new traits for barley breeding. The relative height estimation of the canopy by UAV achieved high precision (up to r = 0.93) and repeatability (up to R2 = 0.98). In addition, we found a great overlap of detected significant genotypes between the reference heights and sensor-based heights. The yield prediction accuracy of both sensor systems was at the same level and reached a maximum prediction accuracy of r2 = 0.82 with a continuous increase in precision throughout the entire vegetation period. Due to the lower costs and the consumer-friendly handling of image acquisition and processing, the RGB imagery seems to be more suitable for yield prediction in this study.
Remote Sensing-Based Statistical Approach for Defining Drained Lake Basins in a Continuous Permafrost Region, North Slope of Alaska

Lake formation and drainage are pervasive phenomena in permafrost regions. Drained lake basins (DLBs) are often the most common landforms in lowland permafrost regions in the Arctic (50% to 75% of the landscape). However, detailed assessments of DLB distribution and abundance are limited. In this study, we present a novel and scalable remote sensing-based approach to identifying DLBs in lowland permafrost regions, using the North Slope of Alaska as a case study. We validated this first North Slope-wide DLB data product against several previously published sub-regional scale datasets and manually classified points. The study area covered >71,000 km2, including a >39,000 km2 area not previously covered in existing DLB datasets. Our approach used Landsat-8 multispectral imagery and ArcticDEM data to derive a pixel-by-pixel statistical assessment of likelihood of DLB occurrence in sub-regions with different permafrost and periglacial landscape conditions, as well as to quantify aerial coverage of DLBs on the North Slope of Alaska. The results were consistent with previously published regional DLB datasets (up to 87% agreement) and showed high agreement with manually classified random points (64.4–95.5% for DLB and 83.2–95.4% for non-DLB areas). Validation of the remote sensing-based statistical approach on the North Slope of Alaska indicated that it may be possible to extend this methodology to conduct a comprehensive assessment of DLBs in pan-Arctic lowland permafrost regions. Better resolution of the spatial distribution of DLBs in lowland permafrost regions is important for quantitative studies on landscape diversity, wildlife habitat, permafrost, hydrology, geotechnical conditions, and high-latitude carbon cycling.
CONSTANT SLOPE IMPEDANCE FACTOR MODEL FOR PREDICTING THE SOLUTE DIFFUSION COEFFICIENT IN UNSATURATED SOIL

Solute diffusivity (ratio of diffusion coefficients in soil and free water, DS/D0) is markedly soil-type dependent. Soil texture and pore size distribution govern the threshold soil-water content (&thetas;th) where DS/D0 approaches zero as a result of discontinuous diffusion pathways. In a recent study (Soil Science 161:633-645), we suggested that &thetas;th can be predicted from the soil-water characteristic curve (SWC) based on the Campbell pore size distribution parameter, b. In this study, the &thetas;th-b expression was recalibrated based on diffusivity data for three soils (Hiroshima sand, Foulum loamy sand, and Yolo loam) measured in this study plus 20 soils reported in the literature, obtaining &thetas;th=0.020b. As the SWC is often not measured, a second &thetas;th expression that requires only knowledge of soil texture and bulk density was calibrated from measured data. A third expression, including both soil texture, bulk density, and Campbell b, was also calibrated and gave the most accurate description of &thetas;th. The solute impedance factor (ratio of diffusivity by volumetric soil-water content), f1 = DS/(&thetas; D0), was shown to increase linearly with the water content available for diffusion, &thetas;a=&thetas;−&thetas;th. The slopes of the f1-&thetas;a relations were similar for most soils and did not exhibit soil-type dependency. Based on this, a so-called constant slope impedance factor (CSIF) model to predict DS(&thetas;a)/D0 is presented. The model can be used in combination with any of the three suggested &thetas;th expressions. Combined with the soil-texture/bulk-density dependent &thetas;th expression, the model accurately predicted solute diffusivities for three independent soils for which the SWC were not known.