Sickle cell allele HBB-rs334(T) is associated with decreased risk of childhood Burkitt lymphoma in East Africa.

Burkitt lymphoma (BL) is an aggressive B-cell lymphoma that significantly contributes to childhood cancer burden in sub-Saharan Africa. Plasmodium falciparum, which causes malaria, is geographically associated with BL, but the evidence remains insufficient for causal inference. Inference could be strengthened by demonstrating that mendelian genes known to protect against malaria-such as the sickle cell trait variant, HBB-rs334(T)-also protect against BL. We investigated this hypothesis among 800 BL cases and 3845 controls in four East African countries using genome-scan data to detect polymorphisms in 22 genes known to affect malaria risk. We fit generalized linear mixed models to estimate odds ratios (OR) and 95% confidence intervals (95% CI), controlling for age, sex, country, and ancestry. The ORs of the loci with BL and P. falciparum infection among controls were correlated (Spearman's ρ = 0.37, p = .039). HBB-rs334(T) was associated with lower P. falciparum infection risk among controls (OR = 0.752, 95% CI 0.628-0.9; p = .00189) and BL risk (OR = 0.687, 95% CI 0.533-0.885; p = .0037). ABO-rs8176703(T) was associated with decreased risk of BL (OR = 0.591, 95% CI 0.379-0.992; p = .00271), but not of P. falciparum infection. Our results increase support for the etiological correlation between P. falciparum and BL risk.

Editorial Commentary: Large Language Models Like ChatGPT Show Promise, but Clinical Use of Artificial Intelligence Requires Physician Partnership.

Forcing ChatGPT and other large language models to perform roles reserved for physicians and other health care professionals-namely evaluation, management, and triage-poses a threat from regulatory, risk management, and professional perspectives. The clinical practice of medicine would benefit tremendously from automated administrative support with systems-based transparency and fluidity-not substitution for clinical diagnostics and decision making. ChatGPT and other large language models are not intended or authorized for clinical use, let alone to be tested or rubber stamped for this application. The best clinical use cases of artificial intelligence require physician partnership to enable personal care, minimize administrative burden, maximize efficiency, and minimize risk-without substitution of core physician tasks.

Off-the-shelf Large Language Models (LLM) Are Of Insufficient Quality To Provide Medical Treatment Recommendations, While Customization of LLMs Result In Quality Recommendations.

The content accuracy from off-the-shelf LLMs mirror the content accuracy of the unregulated Internet from which these generative artificial intelligence models are supplied. With error rates approximating 30% in terms of treatment recommendations for the management of common musculoskeletal conditions, seeking expert opinion remains paramount. However, custom LLMs represent an excellent opportunity to infuse niche, bespoke expertise from the many specialties and subspecialties within medicine. Methods of customizing these generative models broadly fall under the categories of prompt engineering, "retrieval augmented generation" (RAG) prioritizing retrieval of relevant information from a specific domain of data, "fine-tuning" a basic pre-trained model into one that is refined for healthcare-related vernacular and acronyms, and "agentic augmentation" including software that break down complex tasks into smaller ones, recruiting multiple LLMs (with or without RAG), optimizing the output, internally deciding if the response is appropriate or sufficient, and even passing on an unmet outcome to a human for supervision ("phone a friend"). Custom LLMs offer physicians and their associated organizations the rare opportunity to regain control of our profession by reestablishing authority in our increasingly digital landscape.

The Fundamentals and Applications of Wearable Sensor Devices in Sports Medicine: A Scoping Review.

PURPOSE: To (1) characterize the various forms of wearable sensor devices (WSDs) and (2) review the peer-reviewed literature of applied wearable technology within sports medicine. METHODS: A systematic search of PubMed and EMBASE databases, from inception through 2023, was conducted to identify eligible studies using WSDs within sports medicine. Data extraction was performed of study demographics and sensor specifications. Included studies were categorized by application: athletic training, rehabilitation, and research. RESULTS: In total, 43 studies met criteria for inclusion in this review. Forms of WSDs include pedometers, accelerometers, encoders (consisting of magnetometers and gyroscopes), force sensors, global positioning system trackers, and inertial measurement units. Outcome metrics include step counts; gait, limb motion, and angular positioning; foot and skin pressure; change of direction and inclination, including analysis of both body parts and athletes on a field; displacement and velocity of body segments and joints; heart rate; plethysmography; sport-specific kinematics; range of motion, symmetry, and alignment; head impact; sleep; throwing biomechanics; and kinetic and spatiotemporal running metrics. WSDs are used in athletic training to assess sport-specific biomechanics and workload with a goal of injury prevention and training optimization, as well as for rehabilitation monitoring and research such as for risk predicting and aiding diagnosis. CONCLUSIONS: WSDs enable real-time monitoring of human performance across a variety of implementations and settings, allowing collection of metrics otherwise not achievable. WSDs are powerful tools with multiple applications within athletic training, patient rehabilitation, and orthopaedic and sports medicine research. CLINICAL RELEVANCE: Wearable technology may represent the missing link to quantitatively addressing return to play and previous performance. WSDs are commercially available and portable adjuncts that allow clinicians, trainers, and individual athletes to monitor biomechanical parameters, workload, and recovery status to better contextualize personalized training, injury risk, and rehabilitation.

A Glossary of Terms in Artificial Intelligence for Healthcare.

In recent decades, artificial intelligence (AI) has infiltrated a variety of domains, including media, education, and medicine. There exists no glossary, lexicon, or reference for the uninitiated medical professional to explore the new terminology. As AI-driven technologies and applications become more available for clinical use in healthcare settings, an understanding of basic components, models, and tasks related to AI is crucial for clinical and academic appraisal. Here, we present a glossary of AI definitions that healthcare professionals can utilize to augment personal understanding of AI during this fourth industrial revolution.

Who Are the Anatomic Outliers Undergoing Total Knee Arthroplasty? A Computed Tomography-Based Analysis of the Hip-Knee-Ankle Axis Across 1,352 Preoperative Computed Tomographies Using a Deep Learning and Computer Vision-Based Pipeline.

BACKGROUND: Dissatisfaction after total knee arthroplasty (TKA) ranges from 15 to 30%. While patient selection may be partially responsible, morphological and reconstructive challenges may be determinants. Preoperative computed tomography (CT) scans for TKA planning allow us to evaluate the hip-knee-ankle axis and establish a baseline phenotypic distribution across anatomic parameters. The purpose of this cross-sectional analysis was to establish the distributions of 27 parameters in a pre-TKA cohort and perform threshold analysis to identify anatomic outliers. METHODS: There were 1,352 pre-TKA CTs that were processed. A 2-step deep learning pipeline of classification and segmentation models identified landmark images and then generated contour representations. We used an open-source computer vision library to compute measurements for 27 anatomic metrics along the hip-knee axis. Normative distribution plots were established, and thresholds for the 15th percentile at both extremes were calculated. Metrics falling outside the central 70th percentile were considered outlier indices. A threshold analysis of outlier indices against the proportion of the cohort was performed. RESULTS: Significant variation exists in pre-TKA anatomy across 27 normally distributed metrics. Threshold analysis revealed a sigmoid function with a critical point at 9 outlier indices, representing 31.2% of subjects as anatomic outliers. Metrics with the greatest variation related to deformity (tibiofemoral angle, medial proximal tibial angle, lateral distal femoral angle), bony size (tibial width, anteroposterior femoral size, femoral head size, medial femoral condyle size), intraoperative landmarks (posterior tibial slope, transepicondylar and posterior condylar axes), and neglected rotational considerations (acetabular and femoral version, femoral torsion). CONCLUSIONS: In the largest non-industry database of pre-TKA CTs using a fully automated 3-stage deep learning and computer vision-based pipeline, marked anatomic variation exists. In the pursuit of understanding the dissatisfaction rate after TKA, acknowledging that 31% of patients represent anatomic outliers may help us better achieve anatomically personalized TKA, with or without adjunctive technology.

The African mosquito-borne diseasosome: geographical patterns, range expansion and future disease emergence.

Mosquito-borne diseases (MBDs) threaten public health and food security globally. We provide the first biogeographic description of the African mosquito fauna (677 species) and the 151 mosquito-borne pathogens (MBPs) they transmit. While mosquito species richness agrees with expectations based on Africa's land surface, African arboviruses and mammalian plasmodia are more speciose than expected. Species assemblages of mosquitoes and MBPs similarly separate sub-Saharan Africa from North Africa, and those in West and Central Africa from eastern and southern Africa. Similarities between mosquitoes and MBPs in diversity and range size suggest that mosquitoes are key in delimiting the range of MBPs. With approximately 25% endemicity, approximately 50% occupying one to three countries and less than 5% occupying greater than 25 countries, the ranges of mosquitoes and MBPs are surprisingly small, suggesting that most MBPs are transmitted by a single mosquito species. Exceptionally widespread mosquito species feed on people and livestock, and most are high-altitude-windborne migrants. Likewise, widespread MBPs are transmitted among people or livestock by widespread mosquitoes, suggesting that adapting to people or livestock and to widespread mosquito species promote range expansion in MBPs. Range size may predict range expansion and emergence risk. We highlight key knowledge gaps that impede prediction and mitigation of future emergence of local and global MBDs.

Exposure to Extended Reality and Artificial Intelligence-Based Manifestations: A Primer on the Future of Hip and Knee Arthroplasty.

BACKGROUND: Software-infused services, from robot-assisted and wearable technologies to artificial intelligence (AI)-laden analytics, continue to augment clinical orthopaedics - namely hip and knee arthroplasty. Extended reality (XR) tools, which encompass augmented reality, virtual reality, and mixed reality technology, represent a new frontier for expanding surgical horizons to maximize technical education, expertise, and execution. The purpose of this review is to critically detail and evaluate the recent developments surrounding XR in the field of hip and knee arthroplasty and to address potential future applications as they relate to AI. METHODS: In this narrative review surrounding XR, we discuss (1) definitions, (2) techniques, (3) studies, (4) current applications, and (5) future directions. We highlight XR subsets (augmented reality, virtual reality, and mixed reality) as they relate to AI in the increasingly digitized ecosystem within hip and knee arthroplasty. RESULTS: A narrative review of the XR orthopaedic ecosystem with respect to XR developments is summarized with specific emphasis on hip and knee arthroplasty. The XR as a tool for education, preoperative planning, and surgical execution is discussed with future applications dependent upon AI to potentially obviate the need for robotic assistance and preoperative advanced imaging without sacrificing accuracy. CONCLUSION: In a field where exposure is critical to clinical success, XR represents a novel stand-alone software-infused service that optimizes technical education, execution, and expertise but necessitates integration with AI and previously validated software solutions to offer opportunities that improve surgical precision with or without the use of robotics and computed tomography-based imaging.

Enabling product development partnerships to bring forward the next generation of health technologies.

Over the past quarter century, product development partnerships (PDPs) have importantly brought health technologies, particularly for neglected diseases, to market for low- and middle-income countries (LMICs). With public sector financing, PDPs de-risk the gulf between where the global burden of disease falls and where paying markets exist. From fighting COVID-19 to developing novel antibiotics, the work of PDPs now extends beyond these traditional bounds. As PDPs have shepherded more health technologies to market, they are also confronting new access challenges. This article lays out 5 areas to strategically leverage the PDP model for better access to new health technologies. Making the case for enhanced support of the PDP approach will require greater transparency, as well as recognition of the contributions made by both public and private sector partners. The governance and funding of PDPs must be accountable to meeting the needs and building capacity of target beneficiaries in LMICs. To take an end-to-end approach, PDPs must work in tandem with other public sector institutions as well as local manufacturers as part of a larger innovation ecosystem. PDPs will need to keep pace with both the dynamics of diseases and markets in delivering the next generation of much needed health technologies.

Product development partnerships (PDPs) play an important role in bringing new and needed health technologies to market, particularly in low- and middle-income countries. As these products emerge from the R&D pipeline, new access challenges in paying for and delivering them in the health care system have emerged. The COVID-19 pandemic has also both stretched and tapped into this work. These developments provide a window of opportunity, both to take stock of lessons learned and of strategic opportunities to leverage the PDP model beyond its traditional bounds of neglected diseases. Greater transparency and recognition of the contributions of PDPs, accountability of governance and surety of financing, and coordination with pooled procurement and local manufacturing initiatives can build a foundation for even more impactful contributions in the future.

Longitudinal Assessment of Peripapillary Microvasculature Using Optical Coherence Tomography Angiography in Cognitively Normal Adults.

Introduction: To evaluate longitudinal peripapillary changes in cognitively normal older adults using optical coherence tomography (OCT) and OCT angiography (OCTA). Methods: Participants older than 50 years with no history of neurodegenerative disease or cognitive impairment were prospectively enrolled. OCT and OCTA images were obtained at the first visit and 2 years later. Results: The study comprised 189 eyes of 111 adults with a mean age (±SD) of 69.3 ± 5.8 years and mean follow-up of 2.1 ± 0.5 years. Woman experienced slower rate of decline than men in capillary perfusion density (0.000% ± 0.005% vs -0.002% ± 0.004%; P = .038) and retinal nerve fiber layer (RNFL) thickness (0.133 ± 1.617 µm vs -0.659 ± 1.431 µm; P = .008). At both timepoints, after controlling for sex, the capillary perfusion density (P < .001), capillary flux index (P < .001), and RNFL thickness (P = .005) were lower in older participants. The mean capillary perfusion density was higher in women than in men at both timepoints (P = .01 and P = .002, respectively), with no significant differences in the capillary flux index and RNFL thickness. Conclusions: In cognitively normal adults, there is a significant reduction in peripapillary capillary perfusion density, the capillary flux index, and RNFL thickness associated with aging beyond 50 years. Women had higher capillary perfusion density values with slower rates of change in capillary perfusion density and RNFL thickness. These values can serve as benchmarks, and variations could be suspicious for a pathologic process.

Automating Linear and Angular Measurements for the Hip and Knee After Computed Tomography: Validation of a Three-Stage Deep Learning and Computer Vision-Based Pipeline for Pathoanatomic Assessment.

Background: Variability in the bony morphology of pathologic hips/knees is a challenge in automating preoperative computed tomography (CT) scan measurements. With the increasing prevalence of CT for advanced preoperative planning, processing this data represents a critical bottleneck in presurgical planning, research, and development. The purpose of this study was to demonstrate a reproducible and scalable methodology for analyzing CT-based anatomy to process hip and knee anatomy for perioperative planning and execution. Methods: One hundred patients with preoperative CT scans undergoing total knee arthroplasty for osteoarthritis were processed. A two-step deep learning pipeline of classification and segmentation models was developed that identifies landmark images and then generates contour representations. We utilized an open-source computer vision library to compute measurements. Classification models were assessed by accuracy, precision, and recall. Segmentation models were evaluated using dice and mean Intersection over Union (IOU) metrics. Contour measurements were compared against manual measurements to validate posterior condylar axis angle, sulcus angle, trochlear groove-tibial tuberosity distance, acetabular anteversion, and femoral version. Results: Classifiers identified landmark images with accuracy of 0.91 and 0.88 for hip and knee models, respectively. Segmentation models demonstrated mean IOU scores above 0.95 with the highest dice coefficient of 0.957 [0.954-0.961] (UNet3+) and the highest mean IOU of 0.965 [0.961-0.969] (Attention U-Net). There were no statistically significant differences for the measurements taken automatically vs manually (P > 0.05). Average time for the pipeline to preprocess (48.65 +/- 4.41 sec), classify/retrieve landmark images (8.36 +/- 3.40 sec), segment images (<1 sec), and obtain measurements was 2.58 (+/- 1.92) minutes. Conclusions: A fully automated three-stage deep learning and computer vision-based pipeline of classification and segmentation models accurately localized, segmented, and measured landmark hip and knee images for patients undergoing total knee arthroplasty. Incorporation of clinical parameters, like patient-reported outcome measures and instability risk, will be important considerations alongside anatomic parameters.

Diversity, composition, altitude, and seasonality of high-altitude windborne migrating mosquitoes in the Sahel: Implications for disease transmission.

Recent studies have reported Anopheles mosquitoes captured at high-altitude (40-290 m above ground) in the Sahel. Here, we describe this migration modality across genera and species of African Culicidae and examine its implications for disease transmission and control. As well as Anopheles, six other genera-Culex, Aedes, Mansonia, Mimomyia, Lutzia, and Eretmapodites comprised 90% of the 2,340 mosquitoes captured at altitude. Of the 50 molecularly confirmed species (N = 2,107), 33 species represented by multiple specimens were conservatively considered high-altitude windborne migrants, suggesting it is a common migration modality in mosquitoes (31-47% of the known species in Mali), and especially in Culex (45-59%). Overall species abundance varied between 2 and 710 specimens/species (in Ae. vittatus and Cx. perexiguus, respectively). At altitude, females outnumbered males 6:1, and 93% of the females have taken at least one blood meal on a vertebrate host prior to their departure. Most taxa were more common at higher sampling altitudes, indicating that total abundance and diversity are underestimated. High-altitude flight activity was concentrated between June and November coinciding with availability of surface waters and peak disease transmission by mosquitoes. These hallmarks of windborne mosquito migration bolster their role as carriers of mosquito-borne pathogens (MBPs). Screening 921 mosquitoes using pan-Plasmodium assays revealed that thoracic infection rate in these high-altitude migrants was 2.4%, providing a proof of concept that vertebrate pathogens are transported by windborne mosquitoes at altitude. Fourteen of the 33 windborne mosquito species had been reported as vectors to 25 MBPs in West Africa, which represent 32% of the MBPs known in that region and include those that inflict the heaviest burden on human and animal health, such as malaria, yellow fever, dengue, and Rift Valley fever. We highlight five arboviruses that are most likely affected by windborne mosquitoes in West Africa: Rift Valley fever, O'nyong'nyong, Ngari, Pangola, and Ndumu. We conclude that the study of windborne spread of diseases by migrating insects and the development of surveillance to map the sources, routes, and destinations of vectors and pathogens is key to understand, predict, and mitigate existing and new threats of public health.

Achieving path-dependent equity for global COVID-19 vaccine allocation.

Committing to global access for COVID-19 vaccines is key to avoiding a resurgence of the pandemic. However, agreements between countries and vaccine manufacturers have undermined a globally coordinated approach, and the ongoing vaccine rollout highlights long-standing inequities in health. Yet, the surest path out of this pandemic is one toward greater equity.

Effects of lyoprotectants on long-term stability and transfection efficacy of lyophilized poly(lactide-co-glycolide)-graft-polyethylenimine/plasmid DNA polyplexes.

Aim: We investigated the effect of lyoprotectants on the long-term stability and transfection efficiency of lyophilized (Lyo.) polyplexes prepared from poly(lactide-co-glycolide)-graft-polyethylenimine (PgP) and plasmid DNA encoding green fluorescent protein (pGFP). Materials & methods: Lyo. PgP/pGFP polyplexes prepared with/without lyoprotectants were stored at -20°C over 6 months. Polyplex stability was analyzed by gel electrophoresis and heparin competition assay. Transfection efficiency and cytotoxicity were evaluated in rat glioma (C6) cells in medium containing 10% serum. Results: Lyo. PgP/pGFP polyplexes prepared with 5% sucrose as a lyoprotectant remained stable up to 6 months and retained transfection efficiency up to 4 months. Conclusion: Lyo. PgP-based polyplexes retain bioactivity during extended storage, potentially enabling transport to remote regions and less stable settings, increasing access to life-changing gene therapy.

Selective Serotonin Reuptake Inhibitors and Clozapine: Clinically Relevant Interactions and Considerations.

The monoamine hypothesis of depression attributes the symptoms of major depressive disorders to imbalances of serotonin, noradrenaline, and dopamine in the limbic areas of the brain. The preferential targeting of serotonin receptor (SERT) by selective serotonin reuptake inhibitors (SSRIs) has offered an opportunity to reduce the range of these side effects and improve patient adherence to pharmacotherapy. Clozapine remains an effective drug against treatment-resistant schizophrenia, defined as failing treatment with at least two different antipsychotic medications. Patients with schizophrenia who display a constellation of negative symptoms respond poorly to antipsychotic monotherapy. Negative symptoms include the diminution of motivation, interest, or expression. Conversely to the depressive symptomology of interest presently, supplementation of antipsychotics with SSRIs in schizophrenic patients with negative symptoms lead to synergistic improvements in the function of these patients. Fluvoxamine is one of the most potent inhibitors of CYP1A2 and can lead to an increase in clozapine levels. Similar increases in serum clozapine were detected in two patients taking sertraline. However, studies have been contradictory as well, showing no such increases, which are worrying. Clinicians should be aware that clozapine levels should be monitored with any coadministration with SSRIs.

Reserving coronavirus disease 2019 vaccines for global access: cross sectional analysis.

OBJECTIVE: To analyze the premarket purchase commitments for coronavirus disease 2019 (covid-19) vaccines from leading manufacturers to recipient countries. DESIGN: Cross sectional analysis. DATA SOURCES: World Health Organization's draft landscape of covid-19 candidate vaccines, along with company disclosures to the US Securities and Exchange Commission, company and foundation press releases, government press releases, and media reports. ELIGIBILITY CRITERIA AND DATA ANALYSIS: Premarket purchase commitments for covid-19 vaccines, publicly announced by 15 November 2020. MAIN OUTCOME MEASURES: Premarket purchase commitments for covid-19 vaccine candidates and price per course, vaccine platform, and stage of research and development, as well as procurement agent and recipient country. RESULTS: As of 15 November 2020, several countries have made premarket purchase commitments totaling 7.48 billion doses, or 3.76 billion courses, of covid-19 vaccines from 13 vaccine manufacturers. Just over half (51%) of these doses will go to high income countries, which represent 14% of the world's population. The US has reserved 800 million doses but accounts for a fifth of all covid-19 cases globally (11.02 million cases), whereas Japan, Australia, and Canada have collectively reserved more than one billion doses but do not account for even 1% of current global covid-19 cases globally (0.45 million cases). If these vaccine candidates were all successfully scaled, the total projected manufacturing capacity would be 5.96 billion courses by the end of 2021. Up to 40% (or 2.34 billion) of vaccine courses from these manufacturers might potentially remain for low and middle income countries-less if high income countries exercise scale-up options and more if high income countries share what they have procured. Prices for these vaccines vary by more than 10-fold, from $6.00 (£4.50; €4.90) per course to as high as $74 per course. With broad country participation apart from the US and Russia, the COVAX Facility-the vaccines pillar of the World Health Organization's Access to COVID-19 Tools (ACT) Accelerator-has secured at least 500 million doses, or 250 million courses, and financing for half of the targeted two billion doses by the end of 2021 in efforts to support globally coordinated access to covid-19 vaccines. CONCLUSIONS: This study provides an overview of how high income countries have secured future supplies of covid-19 vaccines but that access for the rest of the world is uncertain. Governments and manufacturers might provide much needed assurances for equitable allocation of covid-19 vaccines through greater transparency and accountability over these arrangements.