Evidence for phonon skew scattering in the spin Hall effect of platinum

\u3cp\u3eWe measure and analyze the effective spin Hall angle of platinum in the low-residual resistivity regime by second-harmonic measurements of the spin-orbit torques for a multilayer of Pt|Co|AlOx. An angular-dependent study of the torques allows us to extract the effective spin Hall angle responsible for the damping-like torque in the system. We observe a strikingly nonmonotonic and reproducible temperature dependence of the torques. This behavior is compatible with recent theoretical predictions which include both intrinsic and extrinsic (impurities and phonons) contributions to the spin Hall effect at finite temperatures.\u3c/p\u3

Statistical quality assessment and outlier detection for liquid chromatography-mass spectrometry experiments

<p>Abstract</p> <p>Background</p> <p>Quality assessment methods, that are common place in engineering and industrial production, are not widely spread in large-scale proteomics experiments. But modern technologies such as Multi-Dimensional Liquid Chromatography coupled to Mass Spectrometry (LC-MS) produce large quantities of proteomic data. These data are prone to measurement errors and reproducibility problems such that an automatic quality assessment and control become increasingly important.</p> <p>Results</p> <p>We propose a methodology to assess the quality and reproducibility of data generated in quantitative LC-MS experiments. We introduce quality descriptors that capture different aspects of the quality and reproducibility of LC-MS data sets. Our method is based on the Mahalanobis distance and a robust Principal Component Analysis.</p> <p>Conclusion</p> <p>We evaluate our approach on several data sets of different complexities and show that we are able to precisely detect LC-MS runs of poor signal quality in large-scale studies.</p

Honey Bee PTEN – Description, Developmental Knockdown, and Tissue-Specific Expression of Splice-Variants Correlated with Alternative Social Phenotypes

Phosphatase and TENsin (PTEN) homolog is a negative regulator that takes part in IIS (insulin/insulin-like signaling) and Egfr (epidermal growth factor receptor) activation in Drosophila melanogaster. IIS and Egfr signaling events are also involved in the developmental process of queen and worker differentiation in honey bees (Apis mellifera). Here, we characterized the bee PTEN gene homologue for the first time and begin to explore its potential function during bee development and adult life.Honey bee PTEN is alternatively spliced, resulting in three splice variants. Next, we show that the expression of PTEN can be down-regulated by RNA interference (RNAi) in the larval stage, when female caste fate is determined. Relative to controls, we observed that RNAi efficacy is dependent on the amount of PTEN dsRNA that is delivered to larvae. For larvae fed queen or worker diets containing a high amount of PTEN dsRNA, PTEN knockdown was significant at a whole-body level but lethal. A lower dosage did not result in a significant gene down-regulation. Finally, we compared same-aged adult workers with different behavior: nursing vs. foraging. We show that between nurses and foragers, PTEN isoforms were differentially expressed within brain, ovary and fat body tissues. All isoforms were expressed at higher levels in the brain and ovaries of the foragers. In fat body, isoform B was expressed at higher level in the nurse bees.Our results suggest that PTEN plays a central role during growth and development in queen- and worker-destined honey bees. In adult workers, moreover, tissue-specific patterns of PTEN isoform expression are correlated with differences in complex division of labor between same-aged individuals. Therefore, we propose that knowledge on the roles of IIS and Egfr activity in developmental and behavioral control may increase through studies of how PTEN functions can impact bee social phenotypes

Honey Bee PTEN – Description, Developmental Knockdown, and Tissue-Specific Expression of Splice-Variants Correlated with Alternative Social Phenotypes

Phosphatase and TENsin (PTEN) homolog is a negative regulator that takes part in IIS (insulin/insulin-like signaling) and Egfr (epidermal growth factor receptor) activation in Drosophila melanogaster. IIS and Egfr signaling events are also involved in the developmental process of queen and worker differentiation in honey bees (Apis mellifera). Here, we characterized the bee PTEN gene homologue for the first time and begin to explore its potential function during bee development and adult life.Honey bee PTEN is alternatively spliced, resulting in three splice variants. Next, we show that the expression of PTEN can be down-regulated by RNA interference (RNAi) in the larval stage, when female caste fate is determined. Relative to controls, we observed that RNAi efficacy is dependent on the amount of PTEN dsRNA that is delivered to larvae. For larvae fed queen or worker diets containing a high amount of PTEN dsRNA, PTEN knockdown was significant at a whole-body level but lethal. A lower dosage did not result in a significant gene down-regulation. Finally, we compared same-aged adult workers with different behavior: nursing vs. foraging. We show that between nurses and foragers, PTEN isoforms were differentially expressed within brain, ovary and fat body tissues. All isoforms were expressed at higher levels in the brain and ovaries of the foragers. In fat body, isoform B was expressed at higher level in the nurse bees.Our results suggest that PTEN plays a central role during growth and development in queen- and worker-destined honey bees. In adult workers, moreover, tissue-specific patterns of PTEN isoform expression are correlated with differences in complex division of labor between same-aged individuals. Therefore, we propose that knowledge on the roles of IIS and Egfr activity in developmental and behavioral control may increase through studies of how PTEN functions can impact bee social phenotypes

An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources

Division of labor in honeybees: form, function, and proximate mechanisms

Honeybees exhibit two patterns of organization of work. In the spring and summer, division of labor is used to maximize growth rate and resource accumulation, while during the winter, worker survivorship through the poor season is paramount, and bees become generalists. This work proposes new organismal and proximate level conceptual models for these phenomena. The first half of the paper presents a push–pull model for temporal polyethism. Members of the nursing caste are proposed to be pushed from their caste by the development of workers behind them in the temporal caste sequence, while middle-aged bees are pulled from their caste via interactions with the caste ahead of them. The model is, hence, an amalgamation of previous models, in particular, the social inhibition and foraging for work models. The second half of the paper presents a model for the proximate basis of temporal polyethism. Temporal castes exhibit specialized physiology and switch caste when it is adaptive at the colony level. The model proposes that caste-specific physiology is dependent on mutually reinforcing positive feedback mechanisms that lock a bee into a particular behavioral phase. Releasing mechanisms that relate colony level information are then hypothesized to disrupt particular components of the priming mechanisms to trigger endocrinological cascades that lead to the next temporal caste. Priming and releasing mechanisms for the nursing caste are mapped out that are consistent with current experimental results. Less information-rich, but plausible, mechanisms for the middle-aged and foraging castes are also presented

The Worker Honeybee Fat Body Proteome Is Extensively Remodeled Preceding a Major Life-History Transition

Honeybee workers are essentially sterile female helpers that make up the majority of individuals in a colony. Workers display a marked change in physiology when they transition from in-nest tasks to foraging. Recent technological advances have made it possible to unravel the metabolic modifications associated with this transition. Previous studies have revealed extensive remodeling of brain, thorax, and hypopharyngeal gland biochemistry. However, data on changes in the abdomen is scarce. To narrow this gap we investigated the proteomic composition of abdominal tissue in the days typically preceding the onset of foraging in honeybee workers

In the Laboratory and during Free-Flight: Old Honey Bees Reveal Learning and Extinction Deficits that Mirror Mammalian Functional Decline

Loss of brain function is one of the most negative and feared aspects of aging. Studies of invertebrates have taught us much about the physiology of aging and how this progression may be slowed. Yet, how aging affects complex brain functions, e.g., the ability to acquire new memory when previous experience is no longer valid, is an almost exclusive question of studies in humans and mammalian models. In these systems, age related cognitive disorders are assessed through composite paradigms that test different performance tasks in the same individual. Such studies could demonstrate that afflicted individuals show the loss of several and often-diverse memory faculties, and that performance usually varies more between aged individuals, as compared to conspecifics from younger groups. No comparable composite surveying approaches are established yet for invertebrate models in aging research. Here we test whether an insect can share patterns of decline similar to those that are commonly observed during mammalian brain aging. Using honey bees, we combine restrained learning with free-flight assays. We demonstrate that reduced olfactory learning performance correlates with a reduced ability to extinguish the spatial memory of an abandoned nest location (spatial memory extinction). Adding to this, we show that learning performance is more variable in old honey bees. Taken together, our findings point to generic features of brain aging and provide the prerequisites to model individual aspects of learning dysfunction with insect models

Pemetrexed plus Platinum as the First-Line Treatment Option for Advanced Non-Small Cell Lung Cancer: A Meta-Analysis of Randomized Controlled Trials

To compare the efficacy and toxicities of pemetrexed plus platinum with other platinum regimens in patients with previously untreated advanced non-small cell lung cancer (NSCLC). Methods: A meta-analysis was performed using trials identified through PubMed, EMBASE, and Cochrane databases. Two investigators independently assessed the quality of the trials and extracted data. The outcomes included overall survival (OS), progression-free survival (PFS), response rate (RR), and different types of toxicity. Hazard ratios (HRs), odds ratios (ORs) and their 95% confidence intervals (CIs) were pooled using RevMan software. Results: Four trials involving 2,518 patients with previously untreated advanced NSCLC met the inclusion criteria. Pemetrexed plus platinum chemotherapy (PPC) improved survival compared with other platinum-based regimens (PBR) in patients with advanced NSCLC (HR = 0.91, 95% CI: 0.83–1.00, p = 0.04), especially in those with non-squamous histology (HR = 0.87, 95% CI: 0.77–0.98, p = 0.02). No statistically significant improvement in either PFS or RR was found in PPC group as compared with PBR group (HR = 1.03, 95% CI: 0.94–1.13, p = 0.57; OR = 1.15, 95% CI: 0.95–1.39, p = 0.15, respectively). Compared with PBR, PPC led to less grade 3–4 neutropenia and leukopenia but more grade 3–4 nausea. However, hematological toxicity analysis revealed significant heterogeneities. Conclusion: Our results suggest that PPC in the first-line setting leads to a significant survival advantage with acceptable toxicities for advanced NSCLC patients, especially those with non-squamous histology, as compared with other PRB. PPC could be considered as the first-line treatment option for advanced NSCLC patients, especially those with non-squamous histology

Proteome changes in platelets activated by arachidonic acid, collagen, and thrombin

<p>Abstract</p> <p>Background</p> <p>Platelets are small anucleated blood particles that play a key role in the control of bleeding. Platelets need to be activated to perform their functions and participate in hemostasis. The process of activation is accompanied by vast protein reorganization and posttranslational modifications. The goal of this study was to identify changes in proteins in platelets activated by different agonists. Platelets were activated by three different agonists - arachidonic acid, collagen, and thrombin. 2D SDS-PAGE (pI 4-7) was used to separate platelet proteins. Proteomes of activated and resting platelets were compared with each other by Progenesis SameSpots statistical software; and proteins were identified by nanoLC-MS/MS.</p> <p>Results</p> <p>190 spots were found to be significantly different. Of these, 180 spots were successfully identified and correspond to 144 different proteins. Five proteins were found that had not previously been identified in platelets: protein CDV3 homolog, protein ETHE1, protein LZIC, FGFR1 oncogene partner 2, and guanine nucleotide-binding protein subunit beta-5. Using spot expression profile analysis, we found two proteins (WD repeat-containing protein 1 and mitochondrial glycerol-3-phosphate dehydrogenase) that may be part of thrombin specific activation or signal transduction pathway(s).</p> <p>Conclusions</p> <p>Our results, characterizing the differences within proteins in both activated (by various agonists) and resting platelets, can thus contribute to the basic knowledge of platelets and to the understanding of the function and development of new antiplatelet drugs.</p