Outcomes and care quality metrics for people living with rheumatic heart disease and atrial fibrillation in Uganda.

Background: Atrial fibrillation (AF) is a common complication of rheumatic heart disease (RHD) and is challenging to treat in lower-resourced settings in which RHD remains endemic. Objective: We characterized demographics, treatment outcomes, and factors leading to care retention for participants with RHD and AF in Uganda. Methods: We conducted a retrospective analysis of the Uganda national RHD registry between June 2009 and May 2018. Participants with AF or atrial flutter were included. Demographics, survival, and care metrics were compared with participants without AF. Multivariable logistic regression was used to identify factors associated with retention in care among participants with AF. Results: A total of 1530 participants with RHD were analyzed and 293 (19%) had AF. The median age was 24 (interquartile range 14-38) years. Mortality was similar in both groups (adjusted hazard ratio 1.183, P = .77) over a median follow-up of 203 (interquartile range 98-275) days. A total of 79% of AF participants were prescribed anticoagulation, and 43% were aware of their target international normalized ratio. Retention in care was higher in participants with AF (18% vs 12%, P < .01). Factors associated with decreased retention in care include New York Heart Association functional class III/IV (adjusted odds ratio [OR] 0.48, 95% confidence interval [CI] 0.30-0.76) and distance to nearest health center (adjusted OR 0.94, 95% CI 0.90-0.99). Anticoagulation prescription was associated with enhanced care retention (adjusted OR 1.86, 95% CI 1.24-2.79). Conclusion: Participants with RHD and AF in Uganda do not experience higher mortality than those without AF. Anticoagulation prescription rates are high. Although retention in care is poor among RHD participants, those with concurrent AF are more likely to be retained.

Promoting Growth in Behavioral Neurology: A Path Forward.

Behavioral neurology & neuropsychiatry (BNNP) is a field that seeks to understand brain-behavior relationships, including fundamental brain organization principles and the many ways that brain structures and connectivity can be disrupted, leading to abnormalities of behavior, cognition, emotion, perception, and social cognition. In North America, BNNP has existed as an integrated subspecialty through the United Council for Neurologic Subspecialties since 2006. Nonetheless, the number of behavioral neurologists across academic medical centers and community settings is not keeping pace with increasing clinical and research demand. In this commentary, we provide a brief history of BNNP followed by an outline of the current challenges and opportunities for BNNP from the behavioral neurologist's perspective across clinical, research, and educational spheres. We provide a practical guide for promoting BNNP and addressing the shortage of behavioral neurologists to facilitate the continued growth and development of the subspecialty. We also urge a greater commitment to recruit trainees from diverse backgrounds so as to dismantle persistent obstacles that hinder inclusivity in BNNP-efforts that will further enhance the growth and impact of the subspecialty. With rapidly expanding diagnostic and therapeutic approaches across a range of conditions at the intersection of neurology and psychiatry, BNNP is well positioned to attract new trainees and expand its reach across clinical, research, and educational activities.

Optimal timing of hip and knee arthroplasty after bariatric surgery: A systematic review.

Background: Obesity is a risk factor for the development of osteoarthritis and contributes to the increasing demand for total joint arthroplasty (TJA). Because a lower preoperative weight decreases the risk of complications after TJA, and because bariatric surgery (BS) can reduce weight and comorbidity burden, orthopedic surgeons often recommend BS prior to TJA in patients with obesity. However, the optimal timing of TJA after BS in terms of complications, revisions and dislocations is unknown. Methods: PubMed, Embase and Cochrane CENTRAL databases were systematically searched for any type of study reporting rates of complications, revisions and dislocations in patients who had TJA after BS. The included studies' quality was assessed using the Newcastle-Ottawa Scale. Results: Out of the 16 studies eligible for review, eight registry-based retrospective studies of high to moderate quality compared different time periods between BS and TJA and overall their results suggest little differences in complication rates. The remaining eight retrospective studies evaluated only one time period and had moderate to poor quality. Overall, there were no clear differences in outcomes after TJA for the different time frames between BS and TJA. Conclusion: The results of this systematic review suggest that there is limited and insufficient high-quality evidence to determine the optimal timing of TJA after BS in terms of the rates of complications, revisions and dislocations. Given this lack of evidence, timing of TJA after BS will have to be decided by weighing the individual patients' risk factors against the expected benefits of TJA.

Genome-Wide Association Study of Treatment-Resistant Depression: Shared Biology With Metabolic Traits.

OBJECTIVE: Treatment-resistant depression (TRD) occurs in roughly one-third of all individuals with major depressive disorder (MDD). Although research has suggested a significant common variant genetic component of liability to TRD, with heritability estimated at 8% when compared with non-treatment-resistant MDD, no replicated genetic loci have been identified, and the genetic architecture of TRD remains unclear. A key barrier to this work has been the paucity of adequately powered cohorts for investigation, largely because of the challenge in prospectively investigating this phenotype. The objective of this study was to perform a well-powered genetic study of TRD. METHODS: Using receipt of electroconvulsive therapy (ECT) as a surrogate for TRD, the authors applied standard machine learning methods to electronic health record data to derive predicted probabilities of receiving ECT. These probabilities were then applied as a quantitative trait in a genome-wide association study of 154,433 genotyped patients across four large biobanks. RESULTS: Heritability estimates ranged from 2% to 4.2%, and significant genetic overlap was observed with cognition, attention deficit hyperactivity disorder, schizophrenia, alcohol and smoking traits, and body mass index. Two genome-wide significant loci were identified, both previously implicated in metabolic traits, suggesting shared biology and potential pharmacological implications. CONCLUSIONS: This work provides support for the utility of estimation of disease probability for genomic investigation and provides insights into the genetic architecture and biology of TRD.

Study of Changes in Serum Alkaline Phosphatase Level during Postmenopausal Period of Women in Bangladesh.

The study was designed to evaluate the serum alkaline phosphatase level may be altered in postmenopausal women. This case-control study was carried out in the Department of the Biochemistry, Mymensingh Medical College, Bangladesh from January 2015 to December 2015. The subjects were selected on the basis of inclusion and exclusion criteria by purposive (non-random) method. This study included 50 postmenopausal women as case. The results were compared with 50 apparently healthy pre-menopausal women as control. All statistical analysis was done by SPSS windows package. The values were expressed as Mean±SD. Statistical significance of difference between two groups was evaluated by using student's unpaired t-test. Serum alkaline phosphatase level was analyzed. Serum alkaline phosphatase was determined by using colorimetric method. The mean value of serum alkaline phosphatase was 325.56±76.79 U/L respectively in Group B (Case) and 136.50±76.50 U/L respectively in Group A (Control). The level of serum alkaline phosphatase was significantly increased in Group B (Case). Menopause has an effect on serum alkaline phosphatase which leads to increased risk of development of osteoporosis. This study may facilated the clinicians and gynaecologists to update their knowledge in regard to serum alkaline phosphatase level of women associated with menopause.

Psychiatric Symptoms, Treatment Uptake, and Barriers to Mental Health Care Among US Adults With Post-COVID-19 Condition.

Importance: Psychiatric symptoms are reportedly common among adults with post-COVID-19 condition (PCC). However, nationally representative data regarding symptom prevalence, treatment uptake, and barriers to care are needed to inform the development of care models. Objectives: To evaluate the prevalence of psychiatric symptoms in US adults with PCC compared with those without PCC and assess treatment uptake and cost-related barriers to treatment. Design, Setting, and Participants: Data from the 2022 National Health Interview Survey (NHIS), a nationally representative US cross-sectional survey, were analyzed between October 2023 and February 2024. Exposure: Current PCC, defined as new symptoms following SARS-CoV-2 infection lasting more than 3 months and ongoing at the time of interview. Main Outcomes and Measures: Depression symptoms were evaluated by the Patient Health Questionnaire-8 and anxiety symptoms were assessed using the General Anxiety Disorder-7 instrument. Participants were classified as having received treatment if they received mental health counseling or therapy or medications for mental health. Sleep difficulties, cognitive difficulties, disabling fatigue, and cost-related barriers were assessed from additional NHIS questions. Results: Of the 25 122 participants representing approximately 231 million US adults (median [IQR] age, 46 [32-61] years; 49.8% male and 50.2% female participants), a weighted prevalence (wPr) of 3.4% (95% CI, 3.1%-3.6%) had current PCC. Compared with other US adults, participants with current PCC were more likely to have depression symptoms (wPr, 16.8% vs 7.1%; adjusted odds ratio [AOR], 1.96; 95% CI, 1.51-2.55), anxiety symptoms (wPr, 16.7% vs 6.3%; AOR, 2.21; 95% CI, 1.53-3.19), sleep difficulties (wPr, 41.5% vs 22.7%; AOR 1.95; 95% CI, 1.65-2.29), cognitive difficulties (wPr, 35.0% vs 19.5%; AOR, 2.04; 95% CI, 1.66-2.50), and disabling fatigue (wPr, 4.0% vs 1.6%; AOR, 1.85; 95% CI, 1.20-2.86). Among participants who had depression or anxiety symptoms, those with PCC had a similar likelihood of not having received treatment (wPr, 28.2% vs 34.9%; AOR, 1.02; 95% CI, 0.66-1.57). However, participants with current PCC were more likely to report a cost-related barrier to accessing mental health counseling or therapy (wPr, 37.2% vs 23.3%; AOR, 2.05; 95% CI, 1.40-2.98). Conclusions and Relevance: The findings of this study suggest that people with PCC have a higher prevalence of psychiatric symptoms than other adults but are more likely to experience cost-related barriers to accessing therapy. Care pathways for PCC should consider prioritizing mental health screening and affordable treatment.

Frequency tunable magnetostatic wave filters with zero static power magnetic biasing circuitry.

A single tunable filter simplifies complexity, reduces insertion loss, and minimizes size compared to frequency switchable filter banks commonly used for radio frequency (RF) band selection. Magnetostatic wave (MSW) filters stand out for their wide, continuous frequency tuning and high-quality factor. However, MSW filters employing electromagnets for tuning consume excessive power and space, unsuitable for consumer wireless applications. Here, we demonstrate miniature and high selectivity MSW tunable filters with zero static power consumption, occupying less than 2 cc. The center frequency is continuously tunable from 3.4 GHz to 11.1 GHz via current pulses of sub-millisecond duration applied to a small and nonvolatile magnetic bias assembly. This assembly is limited in the area over which it can achieve a large and uniform magnetic field, necessitating filters realized from small resonant cavities micromachined in thin films of Yttrium Iron Garnet. Filter insertion loss of 3.2 dB to 5.1 dB and out-of-band third order input intercept point greater than 41 dBm are achieved. The filter's broad frequency range, compact size, low insertion loss, high out-of-band linearity, and zero static power consumption are essential for protecting RF transceivers from interference, thus facilitating their use in mobile applications like IoT and 6 G networks.

Identifying data-driven subtypes of major depressive disorder with electronic health records.

BACKGROUND: Efforts to reduce the heterogeneity of major depressive disorder (MDD) by identifying subtypes have not yet facilitated treatment personalization or investigation of biology, so novel approaches merit consideration. METHODS: We utilized electronic health records drawn from 2 academic medical centers and affiliated health systems in Massachusetts to identify data-driven subtypes of MDD, characterizing sociodemographic features, comorbid diagnoses, and treatment patterns. We applied Latent Dirichlet Allocation (LDA) to summarize diagnostic codes followed by agglomerative clustering to define patient subgroups. RESULTS: Among 136,371 patients (95,034 women [70 %]; 41,337 men [30 %]; mean [SD] age, 47.0 [14.0] years), the 15 putative MDD subtypes were characterized by comorbidities and distinct patterns in medication use. There was substantial variation in rates of selective serotonin reuptake inhibitor (SSRI) use (from a low of 62 % to a high of 78 %) and selective norepinephrine reuptake inhibitor (SNRI) use (from 4 % to 21 %). LIMITATIONS: Electronic health records lack reliable symptom-level data, so we cannot examine the extent to which subtypes might differ in clinical presentation or symptom dimensions. CONCLUSION: These data-driven subtypes, drawing on representative clinical cohorts, merit further investigation for their utility in identifying more homogeneous patient populations for basic as well as clinical investigation.

Clinical decision support for bipolar depression using large language models.

Management of depressive episodes in bipolar disorder remains challenging for clinicians despite the availability of treatment guidelines. In other contexts, large language models have yielded promising results for supporting clinical decisionmaking. We developed 50 sets of clinical vignettes reflecting bipolar depression and presented them to experts in bipolar disorder, who were asked to identify 5 optimal next-step pharmacotherapies and 5 poor or contraindicated choices. The same vignettes were then presented to a large language model (GPT4-turbo; gpt-4-1106-preview), with or without augmentation by prompting with recent bipolar treatment guidelines, and asked to identify the optimal next-step pharmacotherapy. Overlap between model output and gold standard was estimated. The augmented model prioritized the expert-designated optimal choice for 508/1000 vignettes (50.8%, 95% CI 47.7-53.9%; Cohen's kappa = 0.31, 95% CI 0.28-0.35). For 120 vignettes (12.0%), at least one model choice was among the poor or contraindicated treatments. Results were not meaningfully different when gender or race of the vignette was permuted to examine risk for bias. By comparison, an un-augmented model identified the optimal treatment for 234 (23.0%, 95% CI 20.8-26.0%; McNemar's p < 0.001 versus augmented model) of the vignettes. A sample of community clinicians scoring the same vignettes identified the optimal choice for 23.1% (95% CI 15.7-30.5%) of vignettes, on average; McNemar's p < 0.001 versus augmented model. Large language models prompted with evidence-based guidelines represent a promising, scalable strategy for clinical decision support. In addition to prospective studies of efficacy, strategies to avoid clinician overreliance on such models, and address the possibility of bias, will be needed.

Characteristics of contemporary atrial fibrillation clinical trials and their association with industry sponsorship.

BACKGROUND: Industry sponsorship is an important source of funding for atrial fibrillation (AF) clinical trials, the implications of which have not been analyzed. OBJECTIVE: The purpose of this study was to determine the characteristics of contemporary AF clinical trials and to evaluate their association with funding source. METHODS: We systematically assessed all completed AF trials registered in the ClinicalTrials.gov database between conception to October 31, 2023, and extracted publicly available information including funding source, trial size, demographic distribution, intervention, location, and publication status. Trial characteristics were compared using the Wilcoxon rank-sum test and Fisher exact test for continuous and categorical variables, respectively. RESULTS: Of the 253 clinical trials assessed, 171 (68%) reported industry funding. Industry funding was associated with a greater median number of patients enrolled (172 vs 80; P <.001), publication rate (56.7% vs 42.7%; P = .04), probability of being product-focused (48.0% vs 24.4%; P <.001), and multicontinental recruitment location (25.2% vs 2.4%; P <.001) when compared to nonindustry-funded trials. However, industry funding was not associated with a significant difference in median impact factor (7.7 vs 7.7; P = .723). The overall proportion of industry-funded trials did not change over time (P = 1). CONCLUSION: Industry-funded clinical trials in AF often are larger, more frequently published, multicontinental, and product-focused. Industry funding was found to be associated with significant differences in study enrollment and publication metrics.

Disparities in seizure outcomes revealed by large language models.

OBJECTIVE: Large-language models (LLMs) can potentially revolutionize health care delivery and research, but risk propagating existing biases or introducing new ones. In epilepsy, social determinants of health are associated with disparities in care access, but their impact on seizure outcomes among those with access remains unclear. Here we (1) evaluated our validated, epilepsy-specific LLM for intrinsic bias, and (2) used LLM-extracted seizure outcomes to determine if different demographic groups have different seizure outcomes. MATERIALS AND METHODS: We tested our LLM for differences and equivalences in prediction accuracy and confidence across demographic groups defined by race, ethnicity, sex, income, and health insurance, using manually annotated notes. Next, we used LLM-classified seizure freedom at each office visit to test for demographic outcome disparities, using univariable and multivariable analyses. RESULTS: We analyzed 84 675 clinic visits from 25 612 unique patients seen at our epilepsy center. We found little evidence of bias in the prediction accuracy or confidence of outcome classifications across demographic groups. Multivariable analysis indicated worse seizure outcomes for female patients (OR 1.33, P ≤ .001), those with public insurance (OR 1.53, P ≤ .001), and those from lower-income zip codes (OR ≥1.22, P ≤ .007). Black patients had worse outcomes than White patients in univariable but not multivariable analysis (OR 1.03, P = .66). CONCLUSION: We found little evidence that our LLM was intrinsically biased against any demographic group. Seizure freedom extracted by LLM revealed disparities in seizure outcomes across several demographic groups. These findings quantify the critical need to reduce disparities in the care of people with epilepsy.

Disparities in Genetic Testing for Neurologic Disorders.

BACKGROUND AND OBJECTIVES: Genetic testing is now the standard of care for many neurologic conditions. Health care disparities are unfortunately widespread in the US health care system, but disparities in the utilization of genetic testing for neurologic conditions have not been studied. We tested the hypothesis that access to and results of genetic testing vary according to race, ethnicity, sex, socioeconomic status, and insurance status for adults with neurologic conditions. METHODS: We analyzed retrospective data from patients who underwent genetic evaluation and testing through our institution's neurogenetics program. We tested for differences between demographic groups in 3 steps of a genetic evaluation pathway: (1) attending a neurogenetic evaluation, (2) completing genetic testing, and (3) receiving a diagnostic result. We compared patients on this genetic evaluation pathway with the population of all neurology outpatients at our institution, using univariate and multivariable logistic regression analyses. RESULTS: Between 2015 and 2022, a total of 128,440 patients were seen in our outpatient neurology clinics and 2,540 patients underwent genetic evaluation. Black patients were less than half as likely as White patients to be evaluated (odds ratio [OR] 0.49, p < 0.001), and this disparity was similar after controlling for other demographic factors in multivariable analysis. Patients from the least wealthy quartile of zip codes were also less likely to be evaluated (OR 0.67, p < 0.001). Among patients who underwent evaluation, there were no disparities in the likelihood of completing genetic testing, nor in the likelihood of a diagnostic result after adjusting for age. Analyses restricted to specific indications for genetic testing supported these findings. DISCUSSION: We observed unequal utilization of our clinical neurogenetics program for patients from marginalized and minoritized demographic groups, especially Black patients. Among patients who do undergo evaluation, all groups benefit similarly from genetic testing when it is indicated. Understanding and removing barriers to accessing genetic testing will be essential to health care equity and optimal care for all patients with neurologic disorders.

Cognitive Symptoms of Post-COVID-19 Condition and Daily Functioning.

Importance: The frequent occurrence of cognitive symptoms in post-COVID-19 condition has been described, but the nature of these symptoms and their demographic and functional factors are not well characterized in generalizable populations. Objective: To investigate the prevalence of self-reported cognitive symptoms in post-COVID-19 condition, in comparison with individuals with prior acute SARS-CoV-2 infection who did not develop post-COVID-19 condition, and their association with other individual features, including depressive symptoms and functional status. Design, Setting, and Participants: Two waves of a 50-state nonprobability population-based internet survey conducted between December 22, 2022, and May 5, 2023. Participants included survey respondents aged 18 years and older. Exposure: Post-COVID-19 condition, defined as self-report of symptoms attributed to COVID-19 beyond 2 months after the initial month of illness. Main Outcomes and Measures: Seven items from the Neuro-QoL cognition battery assessing the frequency of cognitive symptoms in the past week and patient Health Questionnaire-9. Results: The 14 767 individuals reporting test-confirmed COVID-19 illness at least 2 months before the survey had a mean (SD) age of 44.6 (16.3) years; 568 (3.8%) were Asian, 1484 (10.0%) were Black, 1408 (9.5%) were Hispanic, and 10 811 (73.2%) were White. A total of 10 037 respondents (68.0%) were women and 4730 (32.0%) were men. Of the 1683 individuals reporting post-COVID-19 condition, 955 (56.7%) reported at least 1 cognitive symptom experienced daily, compared with 3552 of 13 084 (27.1%) of those who did not report post-COVID-19 condition. More daily cognitive symptoms were associated with a greater likelihood of reporting at least moderate interference with functioning (unadjusted odds ratio [OR], 1.31 [95% CI, 1.25-1.36]; adjusted [AOR], 1.30 [95% CI, 1.25-1.36]), lesser likelihood of full-time employment (unadjusted OR, 0.95 [95% CI, 0.91-0.99]; AOR, 0.92 [95% CI, 0.88-0.96]) and greater severity of depressive symptoms (unadjusted coefficient, 1.40 [95% CI, 1.29-1.51]; adjusted coefficient 1.27 [95% CI, 1.17-1.38). After including depressive symptoms in regression models, associations were also found between cognitive symptoms and at least moderate interference with everyday functioning (AOR, 1.27 [95% CI, 1.21-1.33]) and between cognitive symptoms and lower odds of full-time employment (AOR, 0.92 [95% CI, 0.88-0.97]). Conclusions and Relevance: The findings of this survey study of US adults suggest that cognitive symptoms are common among individuals with post-COVID-19 condition and associated with greater self-reported functional impairment, lesser likelihood of full-time employment, and greater depressive symptom severity. Screening for and addressing cognitive symptoms is an important component of the public health response to post-COVID-19 condition.

Performance of a Maternal Risk Stratification System for Predicting Low Apgar Scores.

OBJECTIVE: Maternal risk stratification systems are increasingly employed in predicting and preventing obstetric complications. These systems focus primarily on maternal morbidity, and few tools exist to stratify neonatal risk. We sought to determine if a maternal risk stratification score was associated with neonatal morbidity. STUDY DESIGN: Retrospective cohort study of patients with liveborn infants born at ≥24 weeks at four hospitals in one health system between January 1, 2020, and December 31, 2020. The Expanded Obstetric Comorbidity Score (EOCS) is used as the maternal risk score. The primary neonatal outcome was 5-minute Apgar <7. Logistic regression models determined associations between EOCS and neonatal morbidity. Secondary analyses were performed, including stratifying outcomes by gestational age and limiting analysis to "low-risk" term singletons. Model discrimination assessed using the area under the receiver operating characteristic curves (AUC) and calibration via calibration plots. RESULTS: A total of 14,497 maternal-neonatal pairs were included; 236 (1.6%) had 5-minute Apgar <7; EOCS was higher in 5-minute Apgar <7 group (median 41 vs. 11, p < 0.001). AUC for EOCS in predicting Apgar <7 was 0.72 (95% Confidence Interval (CI) 0.68, 0.75), demonstrating relatively good discrimination. Calibration plot revealed that those in the highest EOCS decile had higher risk of neonatal morbidity (7.6 vs. 1.7%, p < 0.001). When stratified by gestational age, discrimination weakened with advancing gestational age: AUC 0.70 for <28 weeks, 0.63 for 28 to 31 weeks, 0.64 for 32 to 36 weeks, and 0.61 for ≥37 weeks. When limited to term low-risk singletons, EOCS had lower discrimination for predicting neonatal morbidity and was not well calibrated. CONCLUSION: A maternal morbidity risk stratification system does not perform well in most patients giving birth, at low risk for neonatal complications. The findings suggest that the association between EOCS and 5-minute Apgar <7 likely reflects a relationship with prematurity. This study cautions against intentional or unintentional extrapolation of maternal morbidity risk for neonatal risk, especially for term deliveries. KEY POINTS: · EOCS had moderate discrimination for Apgar <7.. · Predictive performance declined when limited to low-risk term singletons.. · Relationship between EOCS and Apgar <7 was likely driven by prematurity..

Acute neutrophilic vasculitis (leukocytoclasia) in 36 COVID-19 autopsy brains.

BACKGROUND: Hypercytokinemia, the renin-angiotensin system, hypoxia, immune dysregulation, and vasculopathy with evidence of immune-related damage are implicated in brain morbidity in COVID-19 along with a wide variety of genomic and environmental influences. There is relatively little evidence of direct SARS-CoV-2 brain infection in COVID-19 patients. METHODS: Brain histopathology of 36 consecutive autopsies of patients who were RT-PCR positive for SARS-CoV-2 was studied along with findings from contemporary and pre-pandemic historical control groups. Immunostaining for serum and blood cell proteins and for complement components was employed. Microcirculatory wall complement deposition in the COVID-19 cohort was compared to historical control cases. Comparisons also included other relevant clinicopathological and microcirculatory findings in the COVID-19 cohort and control groups. RESULTS: The COVID-19 cohort and both the contemporary and historical control groups had the same rate of hypertension, diabetes mellitus, and obesity. The COVID-19 cohort had varying amounts of acute neutrophilic vasculitis with leukocytoclasia in the microcirculation of the brain in all cases. Prominent vascular neutrophilic transmural migration was found in several cases and 25 cases had acute perivasculitis. Paravascular microhemorrhages and petechial hemorrhages (small brain parenchymal hemorrhages) had a slight tendency to be more numerous in cohort cases that displayed less acute neutrophilic vasculitis. Tissue burden of acute neutrophilic vasculitis with leukocytoclasia was the same in control cases as a group, while it was significantly higher in COVID-19 cases. Both the tissue burden of acute neutrophilic vasculitis and the activation of complement components, including membrane attack complex, were significantly higher in microcirculatory channels in COVID-19 cohort brains than in historical controls. CONCLUSIONS: Acute neutrophilic vasculitis with leukocytoclasia, acute perivasculitis, and associated paravascular blood extravasation into brain parenchyma constitute the first phase of an immune-related, acute small-vessel inflammatory condition often termed type 3 hypersensitivity vasculitis or leukocytoclastic vasculitis. There is a higher tissue burden of acute neutrophilic vasculitis and an increased level of activated complement components in microcirculatory walls in COVID-19 cases than in pre-pandemic control cases. These findings are consistent with a more extensive small-vessel immune-related vasculitis in COVID-19 cases than in control cases. The pathway(s) and mechanism for these findings are speculative.

SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity.

Pregnancy is a risk factor for increased severity of SARS-CoV-2 and other respiratory infections. The mechanisms underlying this risk have not been well-established, partly due to a limited understanding of how pregnancy shapes immune responses. To gain insight into the role of pregnancy in modulating immune responses at steady state and upon perturbation, we collected peripheral blood mononuclear cells (PBMC), plasma, and stool from 226 women, including 152 pregnant individuals (n = 96 with SARS-CoV-2 infection and n = 56 healthy controls) and 74 non-pregnant women (n = 55 with SARS-CoV-2 and n = 19 healthy controls). We found that SARS-CoV-2 infection was associated with altered T cell responses in pregnant compared to non-pregnant women. Differences included a lower percentage of memory T cells, a distinct clonal expansion of CD4-expressing CD8 + T cells, and the enhanced expression of T cell exhaustion markers, such as programmed cell death-1 (PD-1) and T cell immunoglobulin and mucin domain-3 (Tim-3), in pregnant women. We identified additional evidence of immune dysfunction in severely and critically ill pregnant women, including a lack of expected elevation in regulatory T cell (Treg) levels, diminished interferon responses, and profound suppression of monocyte function. Consistent with earlier data, we found maternal obesity was also associated with altered immune responses to SARS-CoV-2 infection, including enhanced production of inflammatory cytokines by T cells. Certain gut bacterial species were altered in pregnancy and upon SARS-CoV-2 infection in pregnant individuals compared to non-pregnant women. Shifts in cytokine and chemokine levels were also identified in the sera of pregnant individuals, most notably a robust increase of interleukin-27 (IL-27), a cytokine known to drive T cell exhaustion, in the pregnant uninfected control group compared to all non-pregnant groups. IL-27 levels were also significantly higher in uninfected pregnant controls compared to pregnant SARS-CoV-2-infected individuals. Using two different preclinical mouse models of inflammation-induced fetal demise and respiratory influenza viral infection, we found that enhanced IL-27 protects developing fetuses from maternal inflammation but renders adult female mice vulnerable to viral infection. These combined findings from human and murine studies reveal nuanced pregnancy-associated immune responses, suggesting mechanisms underlying the increased susceptibility of pregnant individuals to viral respiratory infections.

Enhancing cognitive control with transcranial magnetic stimulation in subject-specific frontoparietal networks.

BACKGROUND: Cognitive control processes, including those involving frontoparietal networks, are highly variable between individuals, posing challenges to basic and clinical sciences. While distinct frontoparietal networks have been associated with specific cognitive control functions such as switching, inhibition, and working memory updating functions, there have been few basic tests of the role of these networks at the individual level. METHODS: To examine the role of cognitive control at the individual level, we conducted a within-subject excitatory transcranial magnetic stimulation (TMS) study in 19 healthy individuals that targeted intrinsic ("resting") frontoparietal networks. Person-specific intrinsic networks were identified with resting state functional magnetic resonance imaging scans to determine TMS targets. The participants performed three cognitive control tasks: an adapted Navon figure-ground task (requiring set switching), n-back (working memory), and Stroop color-word (inhibition). OBJECTIVE: Hypothesis: We predicted that stimulating a network associated with externally oriented control [the "FPCN-B" (fronto-parietal control network)] would improve performance on the set switching and working memory task relative to a network associated with attention (the Dorsal Attention Network, DAN) and cranial vertex in a full within-subjects crossover design. RESULTS: We found that set switching performance was enhanced by FPCN-B stimulation along with some evidence of enhancement in the higher-demand n-back conditions. CONCLUSION: Higher task demands or proactive control might be a distinguishing role of the FPCN-B, and personalized intrinsic network targeting is feasible in TMS designs.

Building an ethnically and racially diverse neurology workforce.

As diversity among patient populations continues to grow, racial and ethnic diversity in the neurology workforce is increasingly essential to the delivery of culturally competent care and for enabling inclusive, generalizable clinical research. Unfortunately, diversity in the workforce is an area in which the field of neurology has historically lagged and faces formidable challenges, including an inadequate number of trainees entering the field, bias experienced by trainees and faculty from minoritized racial and ethnic backgrounds, and 'diversity tax', the disproportionate burden of service work placed on minoritized people in many professions. Although neurology departments, professional organizations and relevant industry partners have come to realize the importance of diversity to the field and have taken steps to promote careers in neurology for people from minoritized backgrounds, additional steps are needed. Such steps include the continued creation of diversity leadership roles in neurology departments and organizations, the creation of robust pipeline programmes, aggressive recruitment and retention efforts, the elevation of health equity research and engagement with minoritized communities. Overall, what is needed is a shift in culture in which diversity is adopted as a core value in the field.