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Science is humanity's best insurance against threats from nature, but it is a fragile enterprise that must be nourished and protected. The preponderance of scientific evidence indicates a natural origin for SARS-CoV-2. Yet, the theory that SARS-CoV-2 was engineered in and escaped from a lab dominates media attention, even in the absence of strong evidence. We discuss how the resulting anti-science movement puts the research community, scientific research, and pandemic preparedness at risk.

Rare-earth iron garnets (REIGs) are the benchmark systems for magnonics, including the longitudinal spin Seebeck effect (LSSE). While most research has focused on single-crystalline REIGs on complimentary garnet substrates, moving to more, cost-effective complementary metal-oxide semiconductor (CMOS)-compatible substrates is important to integrate REIG thin films with existing technology. In this regard, we grow a 130 nm-thick polycrystalline gadolinium iron garnet (GdIG) film on the Si/SiO2 substrate and investigate the temperature-dependent LSSE. Interestingly, the polycrystalline GdIG film exhibits perpendicular magnetic anisotropy (PMA) at room temperature which is induced by tensile in-plane (IP)-strain originating from the thermal-expansion mismatch between the GdIG film and the substrate during rapid thermal annealing. Further, a spin-reorientation transition from the out-of-plane IP direction below TS = 180 K is observed. Additionally, the film reveals a magnetic compensation temperature, T Comp , of ≈240 K. The LSSE voltage not only demonstrates a sign-inversion around T Comp , but also shows noticeable changes around T S. As compared to a single-crystalline GdIG film, the lower LSSE voltage for the polycrystalline GdIG is attributed to the higher effective magnetic anisotropy and enhanced magnon scattering at the grain boundaries. Our study not only paves the way for the cost-effective growth of CMOS-compatible REIG-based systems with PMA for magnonic memory and information processing applications, but also highlights the fact that the spincaloritronic and spin-insulatronic properties of the polycrystalline REIGs follow those of their single-crystalline counterparts with reduced spin-to-charge conversion efficiency through LSSE which can be tuned further by controlling the average gran size and interface engineering. [ABSTRACT FROM AUTHOR]

Accurate assessment and effective feedback are crucial for cultivating learners' abilities of collaborative problem‐solving and critical thinking in online inquiry‐based discussions. Based on quantitative content analysis (QCA), there has been a methodological evolvement from descriptive statistics to sequential mining and to network analysis for mining coded discourse data. Epistemic network analysis (ENA) has recently gained increasing recognition for modelling and visualizing the temporal characteristics of online discussions. However, due to methodological restraints, some valuable information regarding online discussion dynamics remains unexplained, including the directionality of connections between theoretical indicators and the trajectory of thinking development. Guided by the community of inquiry (CoI) model, this study extended generic ENA by incorporating directional connections and stanza‐based trajectory tracking. By examining the proposed extensions with discussion data of an online learning course, this study first verified that the extensions are comparable with QCA, indicating acceptable assessment validity. Then, the directional ENA revealed that two‐way connections between CoI indicators could vary over time and across groups, reflecting different discussion strategies. Furthermore, trajectory tracking effectively detected and visualized the fine‐grained progression of thinking. At the end, we summarize several research and practical implications of the ENA extensions for assessing the learning process.Practitioner notesWhat is already known about this topicAssessment and feedback are crucial for cultivating collaborative problem‐solving and critical thinking in online inquiry‐based discussions.Cognitive presence is an important construct describing the progression of thinking in online inquiry‐based discussions.Epistemic network analysis is gaining increasing recognition for modelling the temporal characteristics of online inquiries.What this paper addsDirectional connections between discourses can reflect different online discussion strategies of groups and individuals.A pair of connected discourses coded with the community of inquiry model can have different meanings depending on their temporal order.A trajectory tracking approach can uncover the fine‐grained progression of thinking in online inquiry‐based discussions.Implications for practice and/or policyBesides the occurrences of individual discourses, examining the meanings of directional co‐occurrences of discourses in online discussions is worthwhile.Groups and individuals can employ different discussion strategies and follow diverse paths to thought development.Developmental assessment is crucial for understanding how participants achieve specific outcomes and providing adaptive feedback. [ABSTRACT FROM AUTHOR]

Protein kinase function and interactions with drugs are controlled in part by the movement of the DFG and ɑC-Helix motifs that are related to the catalytic activity of the kinase. Small molecule ligands elicit therapeutic effects with distinct selectivity profiles and residence times that often depend on the active or inactive kinase conformation(s) they bind. Modern AI-based structural modeling methods have the potential to expand upon the limited availability of experimentally determined kinase structures in inactive states. Here, we first explored the conformational space of kinases in the PDB and models generated by AlphaFold2 (AF2) and ESMFold, two prominent AI-based protein structure prediction methods. Our investigation of AF2's ability to explore the conformational diversity of the kinome at various multiple sequence alignment (MSA) depths showed a bias within the predicted structures of kinases in DFG-in conformations, particularly those controlled by the DFG motif, based on their overabundance in the PDB. We demonstrate that predicting kinase structures using AF2 at lower MSA depths explored these alternative conformations more extensively, including identifying previously unobserved conformations for 398 kinases. Ligand enrichment analyses for 23 kinases showed that, on average, docked models distinguished between active molecules and decoys better than random (average AUC (avgAUC) of 64.58), but select models perform well (e.g., avgAUCs for PTK2 and JAK2 were 79.28 and 80.16, respectively). Further analysis explained the ligand enrichment discrepancy between low- and high-performing kinase models as binding site occlusions that would preclude docking. The overall results of our analyses suggested that, although AF2 explored previously uncharted regions of the kinase conformational space and select models exhibited enrichment scores suitable for rational drug discovery, rigorous refinement of AF2 models is likely still necessary for drug discovery campaigns. Author summary: Greater abundance of kinase structural data in inactive conformations, currently lacking in structural databases, would improve our understanding of how protein kinases function, and expand drug discovery and development for this important family of therapeutic targets. Modern approaches utilizing artificial intelligence and machine learning, like AlphaFold2 and ESMFold, have potential for efficiently capturing novel protein conformations. We provide evidence for a bias within AlphaFold2 and ESMFold to predict structures of kinases in their active states, similar to their overrepresentation in the PDB. We show that lowering the multiple sequence alignment depth used in the AlphaFold2 algorithm can help explore the kinase conformational space more broadly. Through a series of quantitative and visual analyses of the models, we also offer a critique of AlphaFold2-generated models, highlighting their potential utility in drug discovery, but also underscoring the need for further refinement to enhance their suitability for rational drug design. Furthermore, many of the high-quality and high-enriching models we make available may represent starting points for novel drug discovery campaigns. [ABSTRACT FROM AUTHOR]

The article proposes the replacement of trade-motivated aspects of software intellectual property (IP) law with expanded trade regulation. Topics discussed include software innovation law, online software innovation incentives, disruptive innovation like cloning, limited protection for software interfaces such as the misappropriation doctrine, removal of redundant protection of software implementations, and the cases of the social media app Instagram and generative artificial intelligence.

Obesity-induced insulin resistance (IR) is known to influence hepatic cytokines (hepatokines), including fibroblast growth factor (FGF-21), fetuin-A, and chemerin. This study aimed to investigate the association between hepatokines and markers of endothelial dysfunction and vascular reactivity in obese adolescents. A total of 45 obese adolescents were categorized into three groups based on glucose tolerance: normal glucose tolerance (NGT), prediabetes (PD), and type 2 diabetes (T2D). We examined the relationships between FGF-21, fetuin-A, and chemerin with endothelial markers (plasminogen activator inhibitor-1 [PAI-1], intercellular adhesion molecule-1 [ICAM-1], and vascular cell adhesion marker-1 [VCAM-1]) and vascular surrogates (brachial artery reactivity testing [BART] and peak reactive hyperemia [PRH]). Obese adolescents (age 16.2±1.2 years; 62 % female, 65 % Hispanic) with NGT (n=20), PD (n=14), and T2D (n=11) had significant differences between groups in BMI; waist-hip ratio (p=0.05), systolic BP (p=0.008), LDL-C (p=0.02), PAI-1 (p<0.001). FGF-21 pg/mL (mean±SD: NGT vs. PD vs. T2D 54±42; 266±286; 160±126 p=0.006) and fetuin-A ng/mL (266±80; 253±66; 313±50 p=0.018), were significantly different while chemerin ng/mL (26±5; 31±10; 28±2) did not significantly differ between the groups. Positive correlations were found between chemerin and both PAI-1 (r=0.6; p=0.05) and ICAM-1 (r=0.6; p=0.05), FGF-21 and PAI-1 (r=0.6; p<0.001), and fetuin-A with TNFα (r=−0.4; p=0.05). Negative correlations were found between chemerin and PRH (r= −0.5; p=0.017) and fetuin-A and PRH (r=−0.4; p=0.05). In our cohort, IR predicted higher FGF-21 levels suggesting a linear relationship may exist between the two parameters. Hepatokines can augment alterations in the microvascular milieu in obese adolescents as demonstrated by their associations with the markers PAI-1, ICAM-1, and PRH. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Plain Language Summary The use of electronic health record (EHR) data for research is limited by a lack of structure and a standard data model. The objective of the ICAREdata (Integrating Clinical Trials and Real‐World Endpoints Data) project was to structure key research data elements in EHRs using a minimal Common Oncology Data Elements (mCODE) data model to extract and transmit data.The ICAREdata project captured two EHR data elements essential to clinical trials: cancer disease status and treatment plan change. The project was implemented in clinical sites participating in Alliance for Clinical Trials in Oncology trials. Data were extracted from EHRs and sent by secure Fast Healthcare Interoperability Resource messaging (a standard for exchanging EHRs) to a database. Selected elements were compared with corresponding data from the trial's electronic data capture (EDC) system, Medidata Rave.By December 2023, data were extracted and transmitted from 10 sites for 35 patients, involving 367 clinical encounters across 15 clinical trials. Data through March 2023 demonstrated that concordance for the elements treatment plan change and cancer disease status was 79% and 34%, respectively. When disease evaluation was reported by both EHR and EDC (n = 15), there was 87% agreement on cancer disease status.Documentation, extraction, and aggregation of structured data elements in EHRs using mCODE and ICAREdata methods is feasible in multi‐institutional cancer clinical trials. EDC as a reference data set allowed assessment of the completeness of EHR data capture. Future initiatives will focus on elements with shared definitions in clinical and research environments and efficient workflows. Clinical trials use electronic case report forms to report data, and data must be manually entered on these forms, which is costly and time consuming. ICAREdata methods use structured, organized data from clinical trials that can be more easily shared instead having to enter free text into electronic health records. Clinical trials use electronic case report forms to report data, and data must be manually entered on these forms, which is costly and time consuming.ICAREdata methods use structured, organized data from clinical trials that can be more easily shared instead having to enter free text into electronic health records. [ABSTRACT FROM AUTHOR]

Science is humanity's best insurance against threats from nature, but it is a fragile enterprise that must be nourished and protected. The preponderance of scientific evidence indicates a natural origin for SARS-CoV-2. Yet, the theory that SARS-CoV-2 was engineered in and escaped from a lab dominates media attention, even in the absence of strong evidence. We discuss how the resulting anti-science movement puts the research community, scientific research, and pandemic preparedness at risk., Competing Interests: T.D. is on the Board of Directors, Burroughs Wellcome Fund, and is an Editor for the Annual Review of Virology. P.D. receives funding from Moderna. K.F. has substantial financial interest in Vir Biotechnology, Inc., and is cofounder of the company and is coinventor of patents licensed to Vir and receives compensation for consulting. The potential conflict of interest has been reviewed and managed by OHSU. S.G. has done legal consulting on the origins of the pandemic. A.L.G. reports central testing contracts from Pfizer, Novavx, Sanofi, Abbott, Hologic, Cephid, and Quidel and has research support from Gilead. A.M. is scientific founder of Thylacine Biotherapeutics. G.A.S. is President of Thyreos, Inc. Most authors receive funding from the National Institutes of Health and other funding agencies.