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OpenAI, Google, and Microsoft have recently developed popular large language models (LLMs) with incredible clinical applications. LLMs specific to neurosurgery, such as AtlasGPT, have also been recently released. However, the comparative neurosurgical diagnostic capabilities of these models are not well studied. The aim of this study was to evaluate and compare the ability of LLMs to diagnose neurosurgical pathologies. Clinical vignettes (n = 148) extracted from a common neurosurgery case-based review textbook were stratified by subspecialty. OpenAI's ChatGPT-3.5 and ChatGPT-4, Google's Gemini, Microsoft Copilot, and AtlasGPT were prompted to provide a diagnosis: "Provide a neurosurgical diagnosis given the following history…[vignette]." Imaging was inputted for capable LLMs, and all queries were run in May 2024. Diagnoses were compared with the textbook for accuracy and errors were categorized appropriately. ChatGPT-4 was the most accurate model (74% correct), followed by AtlasGPT (63% correct), ChatGPT-3.5 (53% correct), Microsoft Copilot (48% correct), and Gemini (36% correct). Chi-square comparisons demonstrated that ChatGPT-4 was more accurate in providing clinical diagnoses than its counterparts (p = 0.005). Across all vignettes and LLMs, most errors were due to an inability to attribute a key piece of information (generally imaging data) to the diagnostic process while otherwise using logical stepwise reasoning. ChatGPT-4 offered the most accurate diagnoses when given established clinical vignettes. Adding imaging processing capabilities and relevant data significantly increased the accuracy of LLM diagnoses. LLMs can offer accurate assessments of common neurosurgical conditions but necessitate detailed prompting from clinicians. Artificial intelligence has incredible clinical potential; however, practitioners must be cautious and think critically while using them for diagnostic purposes.

The transformer architecture has revolutionized bioinformatics and driven progress in the understanding and prediction of the properties of biomolecules. To date, most biosequence transformers have been trained on single-omic data-either proteins or nucleic acids-and have seen incredible success in downstream tasks in each domain, with particularly noteworthy breakthroughs in protein structural modeling. However, single-omic pretraining limits the ability of these models to capture cross-modal interactions. Here we present OmniBioTE, the largest open-source multi-omic model trained on over 250 billion tokens of mixed protein and nucleic acid data. We show that despite only being trained on unlabeled sequence data, OmniBioTE learns joint representations mapping genes to their corresponding protein sequences. We further demonstrate that OmniBioTE achieves state-of-the-art results predicting the change in Gibbs free energy ([Formula: see text]) of the binding interaction between a given nucleic acid and protein. Remarkably, we show that multi-omic biosequence transformers emergently learn useful structural information without any a priori structural training, allowing us to predict which protein residues are most involved in the protein-nucleic acid binding interaction. Compared to single-omic controls trained with identical compute, OmniBioTE also demonstrates superior performance-per-FLOP across both multi-omic and single-omic benchmarks. Together, these results highlight the power of a unified modeling approach for biological sequences and establish OmniBioTE as a foundation model for multi-omic discovery.

Nickel-dependent enzymes catalyse incredible transformations. However, few have been discovered so far, limiting our understanding of the role of nickel in nature. Here we develop a bioinformatic pipeline to discover a family of nickel pincer mononucleotide (NPMN)-dependent enzymes with structures that are completely distinct from previously reported NPMN-dependent enzymes. We characterize one family member, NPMN-dependent hydride transferase (NphT), and find that it catalyses intermolecular hydride transfer, which we elucidate through its promiscuous disproportionation of sugars. We solve a 1.3-Å resolution crystal structure of NphT bound to NPMN and interrogate its mechanism through mutagenesis. We discover that NphT is one of many unexplored nickel enzymes within the large aldo-keto reductase superfamily, which catalyses reactions on a wide range of molecules, including secondary metabolites, sugars and drugs. This work reveals a unique enzymatic scaffold that can harness nickel, expands the known NPMN-catalysed transformations to intermolecular hydride transfer and establishes a pipeline for the discovery of distinct families of nickel-dependent enzymes.

Among the many diverse traits of insects, the most speciose and successful terrestrial animals, is an incredible range of lifespans. While some are quite long-lived, such as cicadas (years as larvae) or termite queens (decades as adults), many insects, such as mayflies (Insecta: Ephemeroptera), have exceedingly short adult lifespans that serve essentially just for mating and selecting oviposition sites, foregoing feeding to reproduce as quickly as possible. This behavior is correlated with mouthparts that are highly reduced or even absent, and the alimentary system is converted into an air-filled space, possibly non-functional for digestion. The order-wide phenomenon of the co-opted gut is found in only one other group, the twisted-wing parasites (Insecta: Strepsiptera). Here, we present micro-CT scans and volume measurements (body and alimentary air) that reveal a previously undocumented inflated alimentary system in non-feeding species from five additional insect orders: Plecoptera, Embioptera, Megaloptera, Lepidoptera, and Diptera. The association between reduction or complete loss of adult feeding and a large volume of air in the gut is statistically highly significant. The reduction of mouthparts in these taxa reflects non-feeding in adults, indicating that convergence of this trait with alimentary inflation probably has adaptive functions. We discuss several, nonexclusive ways in which an inflated alimentary system can be adaptive for adult insects.

To meet increasing energy demand, several molecules have been explored as dyes for dye-sensitized solar-cell (DSSC) applications. However, such designed cells are yet to attain a solar-power conversion efficiency (η) of more than 13%. To achieve this, new molecules should be investigated. In this work, for the first time, an antiaromatic metal-free molecule is explored for DSSC applications. We consider the antiaromatic orangarin core and load it with different donor and acceptor moieties at rationally chosen places that can enhance the absorption of sunlight. In this way, we design ten potential candidates for use as dyes in DSSCs. The photovoltaic properties, including the light-harvesting efficiency (LHE), open-circuit voltage, maximum short-circuit current density, fill factor, and η of all the designed molecules are calculated and analyzed using the state-of-the-art density functional theory and time-dependent density functional theory methods. Our study reveals that the antiaromatic nature of the core indeed increases the absorption strengths of the dyes and hence enhances the LHE and η up to an incredible value of 26%. The present study clearly demonstrates that an antiaromatic core should be explored further for DSSC application.

People in substance use disorder recovery represent a marginalized and underserved student population. Improving access to higher education for people in recovery can benefit the individual, institution, and society at large. This study explored the barriers to college applications and admissions that people in recovery face and the resources that they draw on to overcome these barriers. Semistructured interviews were completed with 17 undergraduate students in recovery at a large public university without a collegiate recovery program. Inductive thematic analysis was used to document students' experiences related to applications and admissions. Participants described barriers to higher education at multiple levels, including personal challenges (e.g., competing priorities), consequences of past use (e.g., a record of criminal legal system involvement), challenges in the social environment (e.g., substance use on campus), complex admission processes (e.g., regarding transfer credits), and stigma (i.e., anticipated, experienced, and internalized). Despite these challenges, students embodied an incredible amount of resolve. Participants were unafraid to ask for help and mobilized the resources available through their social networks. Having role models in recovery, support from faculty and staff, and flexible options for course scheduling were discussed as facilitators to higher education access. Findings highlight policies and practices that institutions of higher education can adopt to capitalize on the strengths of prospective students in recovery and promote equity and inclusivity for this underrepresented student population.

Molybdenum disulfide (MoS2)/lead sulfide (PbS) heterostructures exhibit exceptional potential because of their strong light-matter interactions and high carrier mobility. Critically, bandgap engineering can further optimize the light-absorption range for next-generation phototransistors. However, the bandgap engineering capability for MoS2/PbS heterojunctions formed by conventional transfer-after-chemical vapor deposition (CVD) fabrication is typically inherently restricted due to solely vertical interlayer coupling. Here, to realize wafer-scale bandgap-tunable MoS2/PbS phototransistors, we investigate the band structure of vertical and lateral MoS2/PbS heterojunctions via ab initio calculations and find that lateral heterojunctions in heterostructures dominate the bandgap tunability via tuning of the Type-II band alignment. To achieve wafer-scale uniformity, we investigated how plasma treatment modulates the thin-film surface energy, and the results substantially improved fabrication scaling of MoS2/PbS heterojunctions from traditional micro-scale level to an incredible 4-inch wafer-scale with near-ideal yields (97%) and enabled bandgap tunability (from 1.24 to 0.61 eV). The resulting phototransistors exhibit a maximum responsivity of 88 A/W, specific detectivity of 4.77  ×  1012 Jones, and a typical on/off ratio of 3.16  ×  107. This work establishes a pathway for developing wafer-scale bandgap-tunable optoelectronics.

Fault detection in Digital Logic Circuits is an important problem in Very Large Scale Integration (VLSI) testing especially in case of growing circuit complexity and various fault characteristics. Traditional methods tend to have a problem in the ability to accurately classify the faults with different levels of difficulty. This paper presents a new framework that combines attack inspired features from Boolean Satisfiability (SAT) with deep learning ensemble learning algorithms for holistic fault detection classification. The paper proposes a suite of novel features that are based on the SAT solver mechanics such as backtrack estimation, miter circuit complexity, distinguishing input patterns, controllability and observability metrics, and test pattern generation complexity indicators. These features represent the complex relationships between circuit structure and the fault detectability that is not modeled by these conventional approaches. The proposed stacking ensemble architecture employs Random Forest, XGBoost, LightGBM, CatBoost, Extra Trees and Histogram Gradient Boosting classifiers as its first level classifiers and a meta-learner to obtain the best classifier results. Extensive experimentation of benchmark circuits shows incredible results: 99.13% test accuracy, 99.15% precision, 99.18% recall and 99.13% F1-Score. The proposed framework performs better compared to individual state-of-the-art models by 2.66% and shows an exceptional stability with minimal overfitting gap of 0.49%. Cross validation analysis is used to verify the performance consistency (99.15% ± 0.78%) and accuracy for each class performance reaches 100%, 98.8%, and 98.5% for easy faults, medium complexity faults, and challenging faults, respectively. The results confirm the effectiveness of SAT-inspired features and advanced ensemble learning for reliable and scalable fault detection classification.

In this early career review article, we aimed to portray a sense of the important skills and knowledge obtained but more importantly the incredible ethos of collaboration and mentorship we experienced. These are attributes we have brought forward to our current roles, ensuring the patient stays at the center of service development, focusing on excellence in care and advocating for patients at a local and national level.

Notwithstanding the notable development achieved in the asymmetric and photochemical construction of spirooxindoles comprising heterocyclic compounds, constructing spirooxindoles containing carbocyclic compounds has not been extensively explored. Drawing inspiration from the incredible structural landscape and pharmaceutical activities associated with spirooxindoles, the synthesis of spirooxindoles comprising carbocyclic compounds to provide unique reactivity and activity is highly desirable. This mini-review article aims to give a brief outline of the visible-light-induced photochemical approaches established over the last decades for accessing spirooxindoles, comprising different ring-size carbocyclic scaffolds. Beyond outlining the development achieved to date, we have emphasized the reaction mechanism and highlighted the limitations associated with the reactions, providing insights for future advancement.

Our qualitative study was conducted to explore real-life experiences and challenges of caregivers and individuals with kernicterus spectrum disorder (KSD) in Northern Nigeria, where it remains a significant cause of neurological impairment. The lived experiences of affected individuals and their caregivers are largely undocumented. These stories of caregivers living with children with KSD and survivors with KSD highlight challenges and obstacles they face beyond bilirubin levels and quantitative measures. We conducted focus group discussions (FGDs; n=7), caregivers (n=54 or 6-8 per FGD) and case studies (n=4 individuals with KSD). Data were analysed using thematic analysis at three teaching hospitals in Northern Nigeria, all members of the Stop Kernicterus and Infection in Northern Nigeria+ collaborative. Caregivers with a child who had acute bilirubin encephalopathy and now has KSD and those living with KSD were interviewed. Key features identified among caregivers were remarkably limited awareness of neonatal jaundice (NNJ) and its consequences, as well as reliance on traditional remedies, resulting in delays accessing care and pervasive stigma. Caregivers reported significant physical, long-term emotional and financial burdens, while individuals with KSD faced real-life challenges with mobility, communication and social inclusion. Despite these obstacles, participants demonstrated incredible resilience and inspiring aspirations. Our study highlights the lives and stories of caregivers and individuals affected by KSD and the urgent need for public health interventions that could prevent KSD through timely access to screening, diagnosis and treatment of NNJ. For those individuals who do progress to KSD, we need not only improved care and support for caregivers but also to value their stories, insisting they not be victimised but given every opportunity to achieve their dreams and full potential.

Chimeric antigen receptor (CAR) T cells have demonstrated remarkable ability to render multiple relapsed and refractory patients into a deep and often durable remission. Since initial FDA approval of tisagenlecleucel in 2017, real-world data have shown the benefit of this therapy, even among historically complex populations, such as infants, children with Down syndrome, and those with extramedullary leukemia. Despite the success of CAR T cell therapy, nearly half of patients tend to show relapsed disease, demanding ongoing advancements. Furthermore, the incorporation of the bispecific T cell engager, blinatumomab, into B cell acute lymphoblastic leukemia (B-ALL) therapy has fundamentally shifted the treatment paradigm, calling for a reevaluation of the optimal application of CAR T cells. In this review, we describe the current usage of CAR T cells in children, adolescents, and young adults (CAYAs) with B-ALL and discuss anticipated changes to CAR T cell therapy and post-infusion management. Upfront use of blinatumomab will require novel approaches to relapsed disease, including the use of CAR T cells earlier in therapy. Limited durability of the currently approved CAR T cells will require novel constructs along with improved toxicity mitigation and refinements in post-CAR disease surveillance and therapy. While CAR T cells have made an incredible impact on the field, there is much work due to improve outcomes for CAYAs with B-ALL.

International conventions play an important role in regulating access to plant genetic resources. These regulations must balance the goal of ensuring wide access to plant genetic resources with doing this in a fair way. This is a central dilemma in achieving just transitions: how to move towards more sustainable societies in ways that are equitable and fair way. In regulations for plant genetic resources, this balance is struck with the concept of Access and Benefit Sharing (ABS). Under the bilateral system of the Nagoya Protocol, ABS requires anyone seeking access to a genetic resource to agree with the provider of that resource on what benefits will be shared. However, the lack of clarity as to what constitutes a 'benefit' has been a major stumbling block in the establishment of ABS agreements and therefore the exchange of genetic material. This article fills this gap by identifying and characterizing what types of benefits have been included in the ABS agreements established successfully under the Nagoya Protocol. We found that ABS agreements can include an incredible variety of types of monetary and non-monetary benefits, that can contribute to a wide range of different objectives, and which are not necessarily related to the benefits obtained from using the genetic resource. By providing more clarity over what benefits can be shared, this overview and characterization of benefits shared in successful ABS agreements supports the development of successful future ABS agreements. We argue that the experiences of developing Access and Benefit Sharing into a workable concept may offer valuable insights for how regulations can play a role in just transitions.