Rapid Whole Genome Characterization of High-Risk Pathogens Using Long-Read Sequencing to Identify Potential Healthcare Transmission.

Objective: Routine use of whole genome sequencing (WGS) has been shown to help identify transmission of pathogens causing healthcare-associated infections (HAIs). However, the current gold standard of short-read, Illumina-based WGS is labor and time-intensive. In light of recent improvements in long-read Oxford Nanopore Technologies (ONT) sequencing, we sought to establish a low resource utilization approach capable of providing accurate WGS-based comparisons of HAI pathogens within a time frame allowing for infection prevention and control (IPC) interventions. Methods: WGS was prospectively performed on antimicrobial-resistant pathogens at increased risk of potential healthcare transmission using the ONT MinION sequencer with R10.4.1 flow cells and Dorado basecalling algorithm. Potential transmission was assessed via Ridom SeqSphere+ for core genome multilocus sequence typing and MINTyper for reference-based core genome single nucleotide polymorphisms using previously published cut-off values. The accuracy of our ONT pipeline was determined relative to Illumina-based WGS data generated from the same genomic DNA sample. Results: Over a six-month period, 242 bacterial isolates from 216 patients were sequenced by a single operator. Compared to the Illumina gold-standard data, our ONT pipeline achieved a Q score of 60 for assembled genomes, even with a coverage rate of as low as 40X. The mean time from initiating DNA extraction to complete genetic analysis was 2 days (IQR 2-3.25 days). We identified five potential transmission clusters comprising 21 isolates (8.7% of all sequenced strains). Combining ONT WGS data with epidemiological data, >70% (15/21) of the isolates originated from patients with potential healthcare transmission links. Conclusions: Via a stand-alone ONT pipeline, we detected potentially transmitted HAI pathogens rapidly and accurately, aligning closely with epidemiological data. Our low-resource method has the potential to assist in the efficient detection and deployment of preventative measures against HAI transmission.

Paradoxical SERCA dysregulation contributes to atrial fibrillation in a model of diet-induced obesity.

Obesity is a major risk factor for atrial fibrillation (AF) the most common serious cardiac arrhythmia, but the molecular mechanisms underlying diet-induced AF remain unclear. In this study, we subjected mice to a chronic high-fat diet and acute sympathetic activation ('two-hit' model) to study the mechanisms by which diet-induced obesity promotes AF. Surface electrocardiography revealed that diet-induced obesity and sympathetic activation synergize during intracardiac tachypacing to induce AF. At the cellular level, diet-induced obesity and acute adrenergic stimulation facilitate the formation of delayed afterdepolarizations in atrial myocytes, implicating altered Ca2+ dynamics as the underlying cause of AF. We found that diet-induced obesity does not alter the expression of major Ca2+-handling proteins in atria, including the sarcoplasmic reticulum Ca2+-ATPase (SERCA), a major component of beat-to-beat Ca2+ cycling in the heart. Paradoxically, obesity reduces phospholamban phosphorylation, suggesting decreased SERCA activity, yet atrial myocytes from obese mice showed a significantly increased Ca2+ transient amplitude and SERCA-mediated Ca2+ uptake. Adrenergic stimulation further increases the Ca2+ transient amplitude but does not affect Ca2+ reuptake in atrial myocytes from obese mice. Transcriptomics analysis showed that a high-fat diet prompts upregulation of neuronatin, a protein that has been implicated in obesity and is known to stimulate SERCA activity. We propose a mechanism in which obesity primes SERCA for paradoxical activation, and adrenergic stimulation facilitates AF conversion through a Ca2+-induced Ca2+ release gain in atrial myocytes. Overall, this study links obesity, altered Ca2+ signaling, and AF, and targeting this mechanism may prove effective for treating obesity-induced AF.

Do ChatGPT and Gemini Provide Appropriate Recommendations for Pediatric Orthopaedic Conditions?

BACKGROUND: Artificial intelligence (AI), and in particular large language models (LLMs) such as Chat Generative Pre-Trained Transformer (ChatGPT) and Gemini have provided additional resources for patients to research the management of healthcare conditions, for their own edification and the advocacy in the care of their children. The accuracy of these models, however, and the sources from which they draw conclusions, have been largely unstudied in pediatric orthopaedics. This research aimed to assess the reliability of machine learning tools in providing appropriate recommendations for the care of common pediatric orthopaedic conditions. METHODS: ChatGPT and Gemini were queried using plain language generated from the American Academy of Orthopaedic Surgeons (AAOS) Clinical Practice Guidelines (CPGs) listed on the Pediatric Orthopedic Society of North America (POSNA) web page. Two independent reviewers assessed the accuracy of the responses, and chi-square analyses were used to compare the 2 LLMs. Inter-rater reliability was calculated via Cohen's Kappa coefficient. If research studies were cited, attempts were made to assess their legitimacy by searching the PubMed and Google Scholar databases. RESULTS: ChatGPT and Gemini performed similarly, agreeing with the AAOS CPGs at a rate of 67% and 69%. No significant differences were observed in the performance between the 2 LLMs. ChatGPT did not reference specific studies in any response, whereas Gemini referenced a total of 16 research papers in 6 of 24 responses. 12 of the 16 studies referenced contained errors and either were unable to be identified (7) or contained discrepancies (5) regarding publication year, journal, or proper accreditation of authorship. CONCLUSION: The LLMs investigated were frequently aligned with the AAOS CPGs; however, the rate of neutral statements or disagreement with consensus recommendations was substantial and frequently contained errors with citations of sources. These findings suggest there remains room for growth and transparency in the development of the models which power AI, and they may not yet represent the best source of up-to-date healthcare information for patients or providers.

Iatrogenic Intraoperative Fracture in Patients With Osteogenesis Imperfecta.

BACKGROUND: Osteogenesis imperfecta (OI) is a genetic defect in collagen type I, phenotypically characterized by bony fragility and a propensity to high rates of childhood fracture. Fragility fractures in patients with OI have been reported with routine hospital care. In addition, there is a nonzero rate of iatrogenic fracture during orthopaedic surgery directly related to the technical steps of the procedure itself. The rate of this latter has never been explicitly investigated. METHODS: A review of all patients at a single OI referral center was conducted, including all patients with a diagnosis of OI seen between 2013 and 2023, inclusive. All patients who underwent orthopaedic surgery of any kind were reviewed, and clinical and radiographic details of all procedures were extracted. Among the details examined were the OI subtype, surgery details, any implants used, intraoperative and hospital stay complications, modified Clavien-Dindo classification of complications, and ultimate outcome. RESULTS: Eleven of 60 patients experienced an unplanned, iatrogenic intraoperative fracture during orthopaedic surgery (11/60 = 18.3%). This comprised 15 fractures among 356 total orthopaedic surgical episodes (15/356 = 4.2%). All but one fracture occurred on the operative long bone segment, all were a direct result of surgical steps, and 11 of 15 fractures occurred in the femur. Most fractures were secondary to the removal, insertion, or exchange of intramedullary implants in the lower extremity (11 of 15 fractures), most often the femur. Thirteen of 15 injuries were classified as modified Clavien-Dindo II or III, requiring modification of postop rehabilitation, additional treatments, or surgical intervention (87%). Overall, iatrogenic fracture was the most common intraoperative complication experienced in the cohort. CONCLUSIONS: Iatrogenic fracture during orthopaedic surgery for patients with OI is not uncommon. A sizeable minority of patients with OI undergoing orthopaedic surgery will experience unplanned fractures, most commonly in the femur, and care is altered in most instances. The risk of intraoperative fracture can be discussed with families of children with OI as part of informed consent and shared decision-making. LEVEL OF EVIDENCE: Level IV-retrospective cohort series.

International Headache Society global practice recommendations for the acute pharmacological treatment of migraine.

BACKGROUND: In an effort to improve migraine management around the world, the International Headache Society (IHS) has here developed a list of practical recommendations for the acute pharmacological treatment of migraine. The recommendations are categorized into optimal and essential, in order to provide treatment options for all possible settings, including those with limited access to migraine medications. METHODS: An IHS steering committee developed a list of clinical questions based on practical issues in the management of migraine. A selected group of international senior and junior headache experts developed the recommendations, following expert consensus and the review of available national and international headache guidelines and guidance documents. Following the initial search, a bibliography of twenty-one national and international guidelines was created and reviewed by the working group. RESULTS: A total of seventeen questions addressing different aspects of acute migraine treatment have been outlined. For each of them we provide an optimal recommendation, to be used whenever possible, and an essential recommendation to be used when the optimal level cannot be attained. CONCLUSION: Adoption of these international recommendations will improve the quality of acute migraine treatment around the world, even where pharmacological options remain limited.

O-glycosylation of IgA1 and the pathogenesis of an autoimmune disease IgA nephropathy.

IgA nephropathy is a kidney disease characterized by deposition of immune complexes containing abnormally O-glycosylated IgA1 in the glomeruli. Specifically, some O-glycans are missing galactose that is normally ß1,3-linked to N-acetylgalactosamine of the core 1 glycans. These galactose-deficient IgA1 glycoforms are produced by IgA1-secreting cells due to a dysregulated expression and activity of several glycosyltransferases. Galactose-deficient IgA1 in the circulation of patients with IgA nephropathy is bound by IgG autoantibodies and the resultant immune complexes can contain additional proteins, such as complement C3. These complexes, if not removed from the circulation, can enter the glomerular mesangium, activate the resident mesangial cells, and induce glomerular injury. In this review, we briefly summarize clinical and pathological features of IgA nephropathy, review normal and aberrant IgA1 O-glycosylation pathways, and discuss the origins and potential significance of natural anti-glycan antibodies, namely those recognizing N-acetylgalactosamine. We also discuss the features of autoantibodies specific for galactose-deficient IgA1 and the characteristics of pathogenic immune complexes containing IgA1 and IgG. In IgA nephropathy, kidneys are injured by IgA1-containing immune complexes as innocent bystanders. Most patients with IgA nephropathy progress to kidney failure and require dialysis or transplantation. Moreover, most patients after transplantation experience a recurrent disease. Thus, a better understanding of the pathogenetic mechanisms is needed to develop new disease-specific treatments.

Probiotic therapy modulates the brain-gut-liver microbiota axis in a mouse model of traumatic brain injury.

The interplay between gut microbiota and host health is crucial for maintaining the overall health of the body and brain, and it is even more crucial how changes in the bacterial profile can influence the aftermath of traumatic brain injury (TBI). We studied the effects of probiotic treatment after TBI to identify potential changes in hepatic lipid species relevant to brain function. Bioinformatic analysis of the gut microbiota indicated a significant increase in the Firmicutes/Bacteroidetes ratio in the probiotic-treated TBI group compared to sham and untreated TBI groups. Although strong correlations between gut bacteria and hepatic lipids were found in sham mice, TBI disrupted these links, and probiotic treatment did not fully restore them. Probiotic treatment influenced systemic glucose metabolism, suggesting altered metabolic regulation. Behavioral tests confirmed memory improvement in probiotic-treated TBI mice. While TBI reduced hippocampal mRNA expression of CaMKII and CREB, probiotics reversed these effects yet did not alter BDNF mRNA levels. Elevated pro-inflammatory markers TNF-α and IL1-ß in TBI mice were not significantly affected by probiotic treatment, pointing to different mechanisms underlying the probiotic benefits. In summary, our study suggests that TBI induces dysbiosis, alters hepatic lipid profiles, and preemptive administration of Lactobacillus helveticus and Bifidobacterium longum probiotics can counter neuroplasticity deficits and memory impairment. Altogether, these findings highlight the potential of probiotics for attenuating TBI's detrimental cognitive and metabolic effects through gut microbiome modulation and hepatic lipidomic alteration, laying the groundwork for probiotics as a potential TBI therapy.

Gene transfer of human cardiomyopathy ß-MyHC mutant R403Q directly alters intact cardiac myocyte calcium homeostasis and causes hyper-contractility.

The R403Q mutation of human cardiac ß-myosin heavy chain was the first missense mutation of a sarcomeric protein identified as being causal for hypertrophic cardiomyopathy (HCM), in humans. The direct effect of the R403Q mutant myosin on intracellular calcium homeostasis and contractility is not fully known. Here we have used in vitro gene transfer of the R403Q mutant human ß-myosin to study its direct effects on single intact adult cardiac myocyte contractility and calcium homeostasis. In the first experiments, adult cardiac myocytes transduced with the R403Q mutant myosin recombinant viral vectors were compared to myocytes transduced with wild-type human ß-myosin (wtMYH7). Efficiency of gene transfer was high in both groups (>98%) and the degree of stoichiometric myofilament incorporation of either the mutant or normal myosin was comparable at ∼40% in quiescent myocytes in primary culture. Sarcomere structure and cellular morphology were unaffected by R403Q myosin expression and myofilament incorporation. Functionally, in electrically paced cardiac myocytes, the R403Q mutant myosin caused a significant increase in intracellular calcium concentration and myocyte hyper-contractility. At the sub-cellular myofilament level, the mutant myosin increased the calcium sensitivity of steady state isometric tension development and increased isometric cross-bridge cycling kinetics. R403Q myocytes became arrhythmic after ß-adrenergic stimulation with spontaneous calcium transients and contractions in between electrical stimuli. These results indicate that human R403Q mutant myosin directly alters myofilament function and intracellular calcium cycling. Elevated calcium levels may provide a trigger for the ensuing hypertrophy and susceptibility to arrhythmia that are characteristic of HCM.

Elevated serum neurologic biomarker profiles after cardiac arrest in a porcine model.

Introduction: Swine exhibit cerebral cortex mitochondrial dysfunction and neuropathologic injury after hypoxic cardiac arrest treated with hemodynamic-directed CPR (HD-CPR) despite normal Cerebral Performance Category scores. We analyzed the temporal evolution of plasma protein biomarkers of brain injury and inflammatory cytokines, as well as cerebral cortical mitochondrial injury and neuropathology for five days following pediatric asphyxia-associated cardiac arrest treated with HD-CPR. Methods: One-month-old swine underwent asphyxia associated cardiac arrest, 10-20 min of HD-CPR (goal SBP 90 mmHg, coronary perfusion pressure 20 mmHg), and randomization to post-ROSC survival duration (24, 48, 72, 96, 120 h; n = 3 per group) with standardized post-resuscitation care. Plasma neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and cytokine levels were collected pre-injury and 1, 6, 24, 48, 72, 96, and 120 h post-ROSC. Cerebral cortical tissue was assessed for: mitochondrial respirometry, mass, and dynamic proteins; oxidative injury; and neuropathology. Results: Relative to pre-arrest baseline (9.4 pg/ml [6.7-12.6]), plasma NfL was increased at all post-ROSC time points. Each sequential NfL measurement through 48 h was greater than the previous value {1 h (12.7 pg/ml [8.4-14.6], p = 0.01), 6 h (30.9 pg/ml [17.7-44.0], p = 0.0004), 24 h (59.4 pg/ml [50.8-96.1], p = 0.0003) and 48 h (85.7 pg/ml [61.9-118.7], p = 0.046)}. Plasma GFAP, inflammatory cytokines or cerebral cortical tissue measurements were not demonstrably different between time points. Conclusions: In a swine model of pediatric cardiac arrest, plasma NfL had an upward trajectory until 48 h post-ROSC after which it remained elevated through five days, suggesting it may be a sensitive marker of neurologic injury following pediatric cardiac arrest.

The headache research priorities: Research goals from the American Headache Society and an international multistakeholder expert group.

OBJECTIVE: To identify and disseminate research priorities for the headache field that should be areas of research focus during the next 10 years. BACKGROUND: Establishing research priorities helps focus and synergize the work of headache investigators, allowing them to reach the most important research goals more efficiently and completely. METHODS: The Headache Research Priorities organizing and executive committees and working group chairs led a multistakeholder and international group of experts to develop headache research priorities. The research priorities were developed and reviewed by clinicians, scientists, people with headache, representatives from headache organizations, health-care industry representatives, and the public. Priorities were revised and finalized after receiving feedback from members of the research priorities working groups and after a public comment period. RESULTS: Twenty-five research priorities across eight categories were identified: human models, animal models, pathophysiology, diagnosis and management, treatment, inequities and disparities, research workforce development, and quality of life. The priorities address research models and methods, development and optimization of outcome measures and endpoints, pain and non-pain symptoms of primary and secondary headaches, investigations into mechanisms underlying headache attacks and chronification of headache disorders, treatment optimization, research workforce recruitment, development, expansion, and support, and inequities and disparities in the headache field. The priorities are focused enough that they help to guide headache research and broad enough that they are widely applicable to multiple headache types and various research methods. CONCLUSIONS: These research priorities serve as guidance for headache investigators when planning their research studies and as benchmarks by which the headache field can measure its progress over time. These priorities will need updating as research goals are met and new priorities arise.

The impact of headache intensity on speech in participants with migraine and acute post-traumatic headache.

BACKGROUND: Slower speaking rates and higher pause rates are found in individuals with migraine or post-traumatic headache during headache compared to when headache-free. We aimed to determine whether headache intensity influences the speaking rate and pause rate of participants with migraine or acute post-traumatic headache (aPTH) following mild traumatic brain injury (mTBI). METHODS: Using a speech elicitation tool, participants with migraine, aPTH, and healthy controls (HC) submitted speech samples over a period of 3 months. Speaking and pause rates were calculated when participants were headache-free and when they had mild or moderate headache. In this observational study, speaking and pause rates in participants with migraine and aPTH were compared to HC, controlling for age, sex, and days since mTBI (participants with aPTH only). RESULTS: A total of 2902 longitudinal speech samples from 13 individuals with migraine (mean age = 33.5, SD = 6.6; 12 females/1 male), 43 individuals with aPTH (mean age = 44.4, SD = 13.5; 28 females/15 males), and 56 HC (mean age = 40.8, SD = 13.0; 36 females/20 males) were collected. There was no difference in speaking rate between HC and the combined headache cohort of participants (migraine and aPTH) when they had headache freedom or a mild headache. When participants had moderate intensity headache, their speaking rate was significantly slower compared to that of HC and compared to their speaking rate during mild headache intensity or headache freedom. For the combined headache cohort of participants, pause rates were significantly higher when they had headache freedom or had a headache of mild or moderate intensity relative to HC. Compared to participants' pause rate during headache freedom, their pause rate was significantly higher during mild and moderate headache intensity. Participants with aPTH had significantly slower speaking rates compared to participants with migraine during headache freedom, mild headache intensity, and moderate headache intensity. Participants with aPTH had significantly higher pause rates compared to participants with migraine when experiencing moderate headache intensity. DISCUSSION: For both aPTH and migraine, more severe headache pain was associated with higher pause rates and slower speaking rates, suggesting that speaking rate and pause rate could serve as objective biomarkers for headache-related pain. Slower speaking rate in participants with aPTH could reflect additional consequences of TBI-related effects on motor control and speech production.

Novel High-tech, Low-cost Ventilation for Military Use, Mass Casualty Incidents, Stockpiling, and Underserved Communities.

INTRODUCTION: Despite the significant need for mechanical ventilation in- and out-of-hospital, mechanical ventilators remain inaccessible in many instances because of cost or size constraints. Mechanical ventilation is especially critical in trauma scenarios, but the impractical size and weight of standard mechanical ventilators restrict first responders from carrying them in medical aid bags, leading to reliance on imprecise manual bag-mask ventilation. This is particularly important in combat-related injury, where airway compromise and respiratory failure are leading causes of preventable death, but medics are left without necessary mechanical ventilation. To address the serious gaps in mechanical ventilation accessibility, we are developing an Autonomous, Modular, and Portable Ventilation platform (AMP-Vent) suitable for austere environments, prolonged critical care, surgical applications, mass casualty incidents, and stockpiling. The core system is remarkably compact, weighing <2.3 kg, and can fit inside a shoebox (23.4 cm × 17.8 cm × 10.7 cm). Notably, this device is 65% lighter than standard transport ventilators and astoundingly 96% lighter than typical intensive care unit ventilators. Beyond its exceptional portability, AMP-Vent can be manufactured at less than one-tenth the cost of conventional ventilators. Despite its reduced size and cost, the system's functionality is uncompromised. The core system is equipped with closed-loop sensors and advanced modes of ventilation (pressure-control, volume-control, and synchronized intermittent mandatory ventilation), enabling quality care in a portable form factor. The current prototype has undergone preliminary preclinical testing and optimization through trials using a breathing simulator (ASL 5000) and in a large animal model (swine). This report aims to introduce a novel ventilation system and substantiate its promising performance through evidence gathered from preclinical studies. MATERIALS AND METHODS: Lung simulator testing was performed using the ASL 5000, in accordance with table 201.105 "pressure-control inflation-type testing" from ISO 80601-2-12:2020. Following simulations, AMP-Vent was tested in healthy 10-kg female domestic piglets. The Children's Hospital of Philadelphia Institutional Animal Care and Use Committee approved all animal procedures. Swine received 4-min blocks of alternating ventilation, where AMP-Vent and a conventional anesthesia ventilator (GE AISYS CS2) were used to titrate to varied end-tidal carbon dioxide (EtCO2) goals with the initial ventilator switching for each ascending target (35, 40, 45, 50, 55 mmHg). RESULTS: During ASL 5000 simulations, AMP-Vent exhibited consistent performance under varied conditions, maintaining a coefficient of variation of 2% or less within each test. In a large animal study, AMP-Vent maintained EtCO2 and SpO2 targets with comparable performance to a conventional anesthesia ventilator (GE AISYS CS2). Furthermore, the comparison of minute ventilation (Ve) distributions between the conventional anesthesia ventilator and AMP-Vent at several EtCO2 goals (35, 40, 45, 50, and 55 mmHg) revealed no statistically significant differences (p = 0.46 using the Kruskal-Wallis rank sum test). CONCLUSIONS: Preclinical results from this study highlight AMP-Vent's core functionality and consistent performance across varied scenarios. AMP-Vent sets a benchmark for portability with its remarkably compact design, positioning it to revolutionize trauma care in previously inaccessible medical scenarios.

Advancing toward precision migraine treatment: Predicting responses to preventive medications with machine learning models based on patient and migraine features.

OBJECTIVE: To develop machine learning models using patient and migraine features that can predict treatment responses to commonly used migraine preventive medications. BACKGROUND: Currently, there is no accurate way to predict response to migraine preventive medications, and the standard trial-and-error approach is inefficient. METHODS: In this cohort study, we analyzed data from the Mayo Clinic Headache database prospectively collected from 2001 to December 2023. Adult patients with migraine completed questionnaires during their initial headache consultation to record detailed clinical features and then at each follow-up to track preventive medication changes and monthly headache days. We included patients treated with at least one of the following migraine preventive medications: topiramate, beta-blockers (propranolol, metoprolol, atenolol, nadolol, timolol), tricyclic antidepressants (amitriptyline, nortriptyline), verapamil, gabapentin, onabotulinumtoxinA, and calcitonin gene-related peptide (CGRP) monoclonal antibodies (mAbs) (erenumab, fremanezumab, galcanezumab, eptinezumab). We pre-trained a deep neural network, "TabNet," using 145 variables, then employed TabNet-embedded data to construct prediction models for each medication to predict binary outcomes (responder vs. non-responder). A treatment responder was defined as having at least a 30% reduction in monthly headache days from baseline. All model performances were evaluated, and metrics were reported in the held-out test set (train 85%, test 15%). SHapley Additive exPlanations (SHAP) were conducted to determine variable importance. RESULTS: Our final analysis included 4260 patients. The responder rate for each medication ranged from 28.7% to 34.9%, and the mean time to treatment outcome for each medication ranged from 151.3 to 209.5 days. The CGRP mAb prediction model achieved a high area under the receiver operating characteristics curve (AUC) of 0.825 (95% confidence interval [CI] 0.726, 0.920) and an accuracy of 0.80 (95% CI 0.70, 0.88). The AUCs of prediction models for beta-blockers, tricyclic antidepressants, topiramate, verapamil, gabapentin, and onabotulinumtoxinA were: 0.664 (95% CI 0.579, 0.745), 0.611 (95% CI 0.562, 0.682), 0.605 (95% CI 0.520, 0.688), 0.673 (95% CI 0.569, 0.724), 0.628 (0.533, 0.661), and 0.581 (95% CI 0.550, 0.632), respectively. Baseline monthly headache days, age, body mass index (BMI), duration of migraine attacks, responses to previous medication trials, cranial autonomic symptoms, family history of headache, and migraine attack triggers were among the most important variables across all models. A variable could have different contributions; for example, lower BMI predicts responsiveness to CGRP mAbs and beta-blockers, while higher BMI predicts responsiveness to onabotulinumtoxinA, topiramate, and gabapentin. CONCLUSION: We developed an accurate prediction model for CGRP mAbs treatment response, leveraging detailed migraine features gathered from a headache questionnaire before starting treatment. Employing the same methods, the model performances for other medications were less impressive, though similar to the machine learning models reported in the literature for other diseases. This may be due to CGRP mAbs being migraine-specific. Incorporating medical comorbidities, genomic, and imaging factors might enhance the model performance. We demonstrated that migraine characteristics are important in predicting treatment responses and identified the most crucial predictors for each of the seven types of preventive medications. Our results suggest that precision migraine treatment is feasible.

Application of Artificial Intelligence in the Headache Field.

PURPOSE OF REVIEW: Headache disorders are highly prevalent worldwide. Rapidly advancing capabilities in artificial intelligence (AI) have expanded headache-related research with the potential to solve unmet needs in the headache field. We provide an overview of AI in headache research in this article. RECENT FINDINGS: We briefly introduce machine learning models and commonly used evaluation metrics. We then review studies that have utilized AI in the field to advance diagnostic accuracy and classification, predict treatment responses, gather insights from various data sources, and forecast migraine attacks. Furthermore, given the emergence of ChatGPT, a type of large language model (LLM), and the popularity it has gained, we also discuss how LLMs could be used to advance the field. Finally, we discuss the potential pitfalls, bias, and future directions of employing AI in headache medicine. Many recent studies on headache medicine incorporated machine learning, generative AI and LLMs. A comprehensive understanding of potential pitfalls and biases is crucial to using these novel techniques with minimum harm. When used appropriately, AI has the potential to revolutionize headache medicine.

Antibiotic treatment induces microbiome dysbiosis and reduction of neuroinflammation following traumatic brain injury in mice.

Background: The gut microbiome is linked to brain pathology in cases of traumatic brain injury (TBI), yet the specific bacteria that are implicated are not well characterized. To address this gap, in this study, we induced traumatic brain injury (TBI) in male C57BL/6J mice using the controlled cortical impact (CCI) injury model. After 35 days, we administered a broad-spectrum antibiotics (ABX) cocktail (ampicillin, gentamicin, metronidazole, vancomycin) through oral gavage for 2 days to diminish existing microbiota. Subsequently, we inflicted a second TBI on the mice and analyzed the neuropathological outcomes five days later. Results: Longitudinal analysis of the microbiome showed significant shifts in the diversity and abundance of bacterial genera during both acute and chronic inflammation. These changes were particularly dramatic following treatment with ABX and after the second TBI. ABX treatment did not affect the production of short-chain fatty acids (SCFA) but did alter intestinal morphology, characterized by reduced villus width and a lower count of goblet cells, suggesting potential negative impacts on intestinal integrity. Nevertheless, diminishing the intestinal microbiome reduced cortical damage, apoptotic cell density, and microglial/macrophage activation in the cortical and thalamic regions of the brain. Conclusions: Our findings suggest that eliminating colonized gut bacteria via broad-spectrum ABX reduces neuroinflammation and enhances neurological outcomes in TBI despite implications to gut health.

The complete pathway for co-transcriptional mRNA maturation within a large protein of a non-segmented negative-strand RNA virus.

Non-segmented negative-strand (NNS) RNA viruses, such as rabies, Nipah and Ebola, produce 5'-capped and 3'-polyadenylated mRNAs resembling higher eukaryotic mRNAs. Here, we developed a transcription elongation-coupled pre-mRNA capping system for vesicular stomatitis virus (VSV, a prototypic NNS RNA virus). Using this system, we demonstrate that the single-polypeptide RNA-dependent RNA polymerase (RdRp) large protein (L) catalyzes all pre-mRNA modifications co-transcriptionally in the following order: (i) 5'-capping (polyribonucleotidylation of GDP) to form a GpppA cap core structure, (ii) 2'-O-methylation of GpppA into GpppAm, (iii) guanine-N7-methylation of GpppAm into m7GpppAm (cap 1), (iv) 3'-polyadenylation to yield a poly(A) tail. The GDP polyribonucleotidyltransferase (PRNTase) domain of L generated capped pre-mRNAs of 18 nucleotides or longer via the formation of covalent enzyme-pre-mRNA intermediates. The single methyltransferase domain of L sequentially methylated the cap structure only when pre-mRNAs of 40 nucleotides or longer were associated with elongation complexes. These results suggest that the formation of pre-mRNA closed loop structures in elongation complexes via the RdRp and PRNTase domains followed by the RdRp and MTase domains on the same polypeptide is required for the cap 1 formation during transcription. Taken together, our findings indicate that NNS RNA virus L acts as an all-in-one viral mRNA assembly machinery.

Chassis-based fiber-coupled optical probe design for reproducible quantitative diffuse optical spectroscopy measurements.

Advanced optical neuromonitoring of cerebral hemodynamics with hybrid diffuse optical spectroscopy (DOS) and diffuse correlation spectroscopy (DCS) methods holds promise for non-invasive characterization of brain health in critically ill patients. However, the methods' fiber-coupled patient interfaces (probes) are challenging to apply in emergent clinical scenarios that require rapid and reproducible attachment to the head. To address this challenge, we developed a novel chassis-based optical probe design for DOS/DCS measurements and validated its measurement accuracy and reproducibility against conventional, manually held measurements of cerebral hemodynamics in pediatric swine (n = 20). The chassis-based probe design comprises a detachable fiber housing which snaps into a 3D-printed, circumferential chassis piece that is secured to the skin. To validate its reproducibility, eight measurement repetitions of cerebral tissue blood flow index (BFI), oxygen saturation (StO2), and oxy-, deoxy- and total hemoglobin concentration were acquired at the same demarcated measurement location for each pig. The probe was detached after each measurement. Of the eight measurements, four were acquired by placing the probe into a secured chassis, and four were visually aligned and manually held. We compared the absolute value and intra-subject coefficient of variation (CV) of chassis versus manual measurements. No significant differences were observed in either absolute value or CV between chassis and manual measurements (p > 0.05). However, the CV for BFI (mean ± SD: manual, 19.5% ± 9.6; chassis, 19.0% ± 10.8) was significantly higher than StO2 (manual, 5.8% ± 6.7; chassis, 6.6% ± 7.1) regardless of measurement methodology (p<0.001). The chassis-based DOS/DCS probe design facilitated rapid probe attachment/re-attachment and demonstrated comparable accuracy and reproducibility to conventional, manual alignment. In the future, this design may be adapted for clinical applications to allow for non-invasive monitoring of cerebral health during pediatric critical care.

Mitochondrial antioxidants abate SARS-COV-2 pathology in mice.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection inhibits mitochondrial oxidative phosphorylation (OXPHOS) and elevates mitochondrial reactive oxygen species (ROS, mROS) which activates hypoxia-inducible factor-1alpha (HIF-1α), shifting metabolism toward glycolysis to drive viral biogenesis but also causing the release of mitochondrial DNA (mtDNA) and activation of innate immunity. To determine whether mitochondrially targeted antioxidants could mitigate these viral effects, we challenged mice expressing human angiotensin-converting enzyme 2 (ACE2) with SARS-CoV-2 and intervened using transgenic and pharmacological mitochondrially targeted catalytic antioxidants. Transgenic expression of mitochondrially targeted catalase (mCAT) or systemic treatment with EUK8 decreased weight loss, clinical severity, and circulating levels of mtDNA; as well as reduced lung levels of HIF-1α, viral proteins, and inflammatory cytokines. RNA-sequencing of infected lungs revealed that mCAT and Eukarion 8 (EUK8) up-regulated OXPHOS gene expression and down-regulated HIF-1α and its target genes as well as innate immune gene expression. These data demonstrate that SARS-CoV-2 pathology can be mitigated by catalytically reducing mROS, potentially providing a unique host-directed pharmacological therapy for COVID-19 which is not subject to viral mutational resistance.

A history of abuse is associated with more severe migraine- and pain-related disability: Results from the American Registry for Migraine Research.

BACKGROUND: Prior studies have established an association between a history of abuse and more severe migraine presentation. OBJECTIVES: This cross-sectional, observational study of a clinic-based migraine population used validated measures to elucidate migraine-specific and migraine-related burdens among patients with a history of abuse. METHODS: Patients with migraine (n = 866) from the American Registry for Migraine Research self-reported if they had a history of emotional, physical, and/or sexual abuse and completed questionnaires assessing migraine-related burden: Migraine Disability Assessment, Subjective Cognitive Impairment Scale for Migraine Attacks, Work Productivity and Activity Impairment, Patient-Reported Outcomes Measurement Information System Pain Interference, Patient Health Questionnaire-2, and Generalized Anxiety Disorder-7. Migraine-related burden in patients with versus without a history of abuse was compared. Subsequently, a mediation analysis evaluated the impact of depression and anxiety symptoms in the relationship between abuse history and migraine burden. RESULTS: A history of abuse was reported by 36.5% (n = 316/866) of participants. After controlling for patient age, sex, years lived with headache, and headache frequency, a history of abuse was significantly associated with more severe migraine-related disability. The combined burden of depression and anxiety symptoms mediated the relationship. CONCLUSION: A history of abuse is associated with greater migraine-related disability. Future studies should determine if identification and management of the psychological and physical sequelae of abuse reduce migraine burden.

Graph-based self-supervised learning for repeat detection in metagenomic assembly.

Repetitive DNA (repeats) poses significant challenges for accurate and efficient genome assembly and sequence alignment. This is particularly true for metagenomic data, where genome dynamics such as horizontal gene transfer, gene duplication, and gene loss/gain complicate accurate genome assembly from metagenomic communities. Detecting repeats is a crucial first step in overcoming these challenges. To address this issue, we propose GraSSRep, a novel approach that leverages the assembly graph's structure through graph neural networks (GNNs) within a self-supervised learning framework to classify DNA sequences into repetitive and non-repetitive categories. Specifically, we frame this problem as a node classification task within a metagenomic assembly graph. In a self-supervised fashion, we rely on a high-precision (but low-recall) heuristic to generate pseudo-labels for a small proportion of the nodes. We then use those pseudo-labels to train a GNN embedding and a random forest classifier to propagate the labels to the remaining nodes. In this way, GraSSRep combines sequencing features with predefined and learned graph features to achieve state-of-the-art performance in repeat detection. We evaluate our method using simulated and synthetic metagenomic datasets. The results on the simulated data highlight our GraSSRep's robustness to repeat attributes, demonstrating its effectiveness in handling the complexity of repeated sequences. Additionally, our experiments with synthetic metagenomic datasets reveal that incorporating the graph structure and the GNN enhances our detection performance. Finally, in comparative analyses, GraSSRep outperforms existing repeat detection tools with respect to precision and recall.