Anthonyabdi2726

The potential of big data to support businesses has been demonstrated in financial services, manufacturing, and telecommunications. Here, we report on efforts to enter a new data era in plant breeding by collecting genomic and phenotypic information from 12,858 wheat genotypes representing 6575 single-cross hybrids and 6283 inbred lines that were evaluated in six experimental series for yield in field trials encompassing ~125,000 plots. Integrating data resulted in twofold higher prediction ability compared with cases in which hybrid performance was predicted across individual experimental series. Our results suggest that combining data across breeding programs is a particularly appropriate strategy to exploit the potential of big data for predictive plant breeding. This paradigm shift can contribute to increasing yield and resilience, which is needed to feed the growing world population.The southern boundary (SB) of the Antarctic Circumpolar Current, the southernmost extent of the upper overturning circulation, regulates the Antarctic thermal conditions. The SB's behavior remains unconstrained because it does not have a clear surface signature. Revisited hydrographic data from off East Antarctica indicate full-depth warming from 1996 to 2019, concurrent with an extensive poleward shift of the SB subsurface isotherms (>50 km), which is most prominent at 120°E off the Sabrina Coast. The SB shift is attributable to enhanced upper overturning circulation and a depth-independent frontal shift, generally accounting for 30 and 70%, respectively. Thirty years of oceanographic data corroborate the overall and localized poleward shifts that are likely controlled by continental slope topography. Numerical experiments successfully reproduce this locality and demonstrate its sensitivity to mesoscale processes and wind forcing. The poleward SB shift under intensified westerlies potentially induces multidecadal warming of Antarctic shelf water.Anisogamy, the size difference between small male and large female gametes, is known to enable selection for sexual dimorphism and behavioral differences between sexes. Nevertheless, even isogamous species exhibit molecular asymmetries between mating types, which are known to ensure their self-incompatibility. Here, we show that different properties of the pheromones secreted by the MATa and MATα mating types of budding yeast lead to asymmetry in their behavioral responses during mating in mixed haploid populations, which resemble behavioral asymmetries between gametes in anisogamous organisms. MATa behaves as a random searcher that is stimulated in proportion to the fraction of MATα partner cells within the population, whereas MATα behaves as a short-range directional distance sensor. Mathematical modeling suggests that the observed asymmetric responses can enhance efficiency of mating and might thus provide a selective advantage. Our results demonstrate that the emergence of asymmetric mating behavior did not require anisogamy-based sexual selection.Molecular evolutionary time scales are expected to predate the fossil evidence, but, particularly for major evolutionary radiations, they can imply extremely protracted stem lineages predating the origin of living clades, leading to claims of systematic overestimation of divergence times. We use macroevolutionary birth-death models to describe the range of total-group and crown-group ages expected under constant rates of speciation and extinction. We extend current predictions on origination times for crown- and total-groups, and extinction of stem-groups, demonstrating that there is broad variance in these predictions. Under constant rates of speciation and extinction, we show that the distribution of expected arthropod total-group ages is consistent with molecular clock estimates. The fossil record cannot be read literally, and our results preclude attempts to interpret the antiquity of clades based on the co-occurrence of stem- and crown-representatives.Genome-embedded ribonucleotides arrest replicative DNA polymerases (Pols) and cause DNA breaks. Whether mammalian DNA repair Pols efficiently use template ribonucleotides and promote RNA-templated DNA repair synthesis remains unknown. We find that human Polθ reverse transcribes RNA, similar to retroviral reverse transcriptases (RTs). Polθ exhibits a significantly higher velocity and fidelity of deoxyribonucleotide incorporation on RNA versus DNA. learn more The 3.2-Å crystal structure of Polθ on a DNA/RNA primer-template with bound deoxyribonucleotide reveals that the enzyme undergoes a major structural transformation within the thumb subdomain to accommodate A-form DNA/RNA and forms multiple hydrogen bonds with template ribose 2'-hydroxyl groups like retroviral RTs. Last, we find that Polθ promotes RNA-templated DNA repair in mammalian cells. These findings suggest that Polθ was selected to accommodate template ribonucleotides during DNA repair.Does contact across social groups influence sociopolitical behavior? This question is among the most studied in the social sciences with deep implications for the harmony of diverse societies. Yet, despite a voluminous body of scholarship, evidence around this question is limited to cross-sectional surveys that only measure short-term consequences of contact or to panel surveys with small samples covering short time periods. Using advances in machine learning that enable large-scale linkages across datasets, we examine the long-term determinants of sociopolitical behavior through an unprecedented individual-level analysis linking contemporary political records to the 1940 U.S. Census. These linked data allow us to measure the exact residential context of nearly every person in the United States in 1940 and, for men, connect this with the political behavior of those still alive over 70 years later. We find that, among white Americans, early-life exposure to black neighbors predicts Democratic partisanship over 70 years later.Skin cancer is one of the most common types of cancer in the United States and worldwide. Topical products are effective for treating cancerous skin lesions when surgery is not feasible. However, current topical products induce severe irritation, light-sensitivity, burning, scaling, and inflammation. Using hyaluronic acid (HA), we engineered clinically translatable polymer-drug conjugates of doxorubicin and camptothecin termed, DOxorubicin and Camptothecin Tailored at Optimal Ratios (DOCTOR) for topical treatment of skin cancers. When compared to the clinical standard, Efudex, DOCTOR exhibited high cancer-cell killing specificity with superior safety to healthy skin cells. In vivo studies confirmed its efficacy in treating cancerous lesions without irritation or systemic absorption. When tested on patient-derived primary cells and live-skin explants, DOCTOR killed the cancer with a selectivity as high as 21-fold over healthy skin tissue from the same donor. Collectively, DOCTOR provides a safe and potent option for treating skin cancer in the clinic.The current opioid epidemic warrants a better understanding of genetic and environmental factors that contribute to opioid addiction. Here we report an increased prevalence of vitamin D (VitD) deficiency in patients diagnosed with opioid use disorder and an inverse and dose-dependent association of VitD levels with self-reported opioid use. We used multiple pharmacologic approaches and genetic mouse models and found that deficiencies in VitD signaling amplify exogenous opioid responses that are normalized upon restoration of VitD signaling. Similarly, physiologic endogenous opioid analgesia and reward responses triggered by ultraviolet (UV) radiation are repressed by VitD signaling, suggesting that a feedback loop exists whereby VitD deficiency produces increased UV/endorphin-seeking behavior until VitD levels are restored by cutaneous VitD synthesis. This feedback may carry the evolutionary advantage of maximizing VitD synthesis. However, unlike UV exposure, exogenous opioid use is not followed by VitD synthesis (and its opioid suppressive effects), contributing to maladaptive addictive behavior.Currently, high-throughput approaches are lacking in the isolation of antibodies with functional readouts beyond simple binding. This situation has impeded the next generation of cancer immunotherapeutics, such as bispecific T cell engager (BiTE) antibodies or agonist antibodies against costimulatory receptors, from reaching their full potential. Here, we developed a highly efficient droplet-based microfluidic platform combining a lentivirus transduction system that enables functional screening of millions of antibodies to identify potential hits with desired functionalities. To showcase the capacity of this system, functional antibodies for CD40 agonism with low frequency ( less then 0.02%) were identified with two rounds of screening. Furthermore, the versatility of the system was demonstrated by combining an anti-Her2 × anti-CD3 BiTE antibody library with functional screening, which enabled efficient identification of active anti-Her2 × anti-CD3 BiTE antibodies. The platform could revolutionize next-generation cancer immunotherapy drug development and advance medical research.The role of juxtaposition of activating and inhibitory receptors in signal inhibition of cytotoxic lymphocytes remains strongly debated. The challenge lies in the lack of tools that allow simultaneous spatial manipulation of signaling molecules. To circumvent this, we produced a nanoengineered multifunctional platform with molecular-scale spatial control of ligands, which was applied to elucidate KIR2DL1-mediated inhibition of NKG2D signaling-receptors of natural killer cells. This platform was conceived by bimetallic nanodot patterning with molecular-scale registry, followed by a ternary functionalization with distinct moieties. We found that a 40-nm gap between activating and inhibitory ligands provided optimal inhibitory conditions. Supported by theoretical modeling, we interpret these findings as a consequence of the size mismatch and conformational flexibility of ligands in their spatial interaction. This highly versatile approach provides an important insight into the spatial mechanism of inhibitory immune checkpoints, which is essential for the rational design of future immunotherapies.

Patients with diabetes mellitus are risk of premature death. In this study, we developed a machine learning-driven predictive risk model for all-cause mortality among patients with type 2 diabetes mellitus using multiparametric approach with data from different domains.

This study used territory-wide data of patients with type 2 diabetes attending public hospitals or their associated ambulatory/outpatient facilities in Hong Kong between January 1, 2009 and December 31, 2009. The primary outcome is all-cause mortality. The association of risk variables and all-cause mortality was assessed using Cox proportional hazards models. Machine and deep learning approaches were used to improve overall survival prediction and were evaluated with fivefold cross validation method.

A total of 273 678 patients (mean age 65.4±12.7 years, male 48.2%, median follow-up 142 (IQR=106-142) months) were included, with 91 155 deaths occurring on follow-up (33.3%; annualized mortality rate 3.4%/year; 2.7 million patient-years). Multivariate Cox regression found the following significant predictors of all-cause mortality age, male gender, baseline comorbidities, anemia, mean values of neutrophil-to-lymphocyte ratio, high-density lipoprotein-cholesterol, total cholesterol, triglyceride, HbA1c and fasting blood glucose (FBG), measures of variability of both HbA1c and FBG.