Dysregulated STAT3 signaling and T cell immunometabolic dysfunction define a targetable, high mortality subphenotype of critically ill children.

Sepsis is the leading cause of death of hospitalized children worldwide. Despite the established link between immune dysregulation and mortality in pediatric sepsis, it remains unclear which host immune factors contribute causally to adverse sepsis outcomes. Identifying modifiable pathobiology is an essential first step to successful translation of biologic insights into precision therapeutics. We designed a prospective, longitudinal cohort study of 88 critically ill pediatric patients with multiple organ dysfunction syndrome (MODS), including patients with and without sepsis, to define subphenotypes associated with targetable mechanisms of immune dysregulation. We first assessed plasma proteomic profiles and identified shared features of immune dysregulation in MODS patients with and without sepsis. We then employed consensus clustering to define three subphenotypes based on protein expression at disease onset and identified a strong association between subphenotype and clinical outcome. We next identified differences in immune cell frequency and activation state by MODS subphenotype and determined the association between hyperinflammatory pathway activation and cellular immunophenotype. Using single cell transcriptomics, we demonstrated STAT3 hyperactivation in lymphocytes from the sickest MODS subgroup and then identified an association between STAT3 hyperactivation and T cell immunometabolic dysregulation. Finally, we compared proteomics findings between patients with MODS and patients with inborn errors of immunity that amplify cytokine signaling pathways to further assess the impact of STAT3 hyperactivation in the most severe patients with MODS. Overall, these results identify a potentially pathologic and targetable role for STAT3 hyperactivation in a subset of pediatric patients with MODS who have high severity of illness and poor prognosis.

Optimizing the use of Ki-67 proliferative index as a prognostic biomarker in meningiomas using digital analysis.

OBJECTIVE: Ki-67 immunohistochemistry is widely used as a prognostic marker in meningiomas, but visual estimations tend to be imprecise. Whether the average Ki-67 over an entire slide, a particular block, or areas of high staining (hotspots) is prognostic for recurrence-free survival (RFS) and overall survival (OS) is unknown. This study aimed to generate evidence-based recommendations for the optimal use of Ki-67 immunohistochemistry in the workup of meningiomas. METHODS: All tissue blocks from a retrospective cohort of 221 patients with primary meningioma (141 WHO grade 1, 64 WHO grade 2, 16 WHO grade 3) were immunostained for Ki-67 and scanned using automated digital analysis software. QuPath was used to quantify the average Ki-67 proliferation index per slide as well as the Ki-67 hotspot in a 2.2-mm2 area within each slide. The best block was defined subjectively by a neuropathologist as the most representative tissue block from each case. The pathology report Ki-67 was determined by visual estimation. Age, sex, WHO grade, extent of resection, tumor location, and quantitative Ki-67 labeling were tested to determine risk factors for RFS and OS. RESULTS: Multivariable analyses demonstrated that WHO grade 2 (HR 2.42, p = 0.018), subtotal resection (HR 8.16, p < 0.0001), near-total resection (HR 2.24, p = 0.041), QuPath Ki-67 averaged across all blocks (HR per % increase = 1.72, p = 0.030), and pathology report Ki-67 (HR per % increase = 1.05, p = 0.0026) were associated with shorter RFS. The average Ki-67 in the best block, maximum across all slides, and maximum hotspot in the best block were not associated with RFS. Only male sex was independently associated with shorter OS (HR 8.52, p = 0.0003). The pathology report Ki-67 was, on average, 6.5 times higher than the QuPath average. CONCLUSIONS: These data on Ki-67 in meningiomas indicate the following: 1) visual estimation substantially overestimates Ki-67, 2) digital quantification of average Ki-67 across all tissue blocks provides more prognostic information than small hotspot regions or an entire single block, and 3) Ki-67 is not informative for OS. The results suggest that best practices for incorporating Ki-67 into meningioma prognostication include digital quantification of average Ki-67 over multiple blocks.

Impaired immune responses in the airways are associated with poor outcome in critically ill COVID-19 patients.

Introduction: Mounting evidence indicates that an individual's humoral adaptive immune response plays a critical role in the setting of SARS-CoV-2 infection, and that the efficiency of the response correlates with disease severity. The relationship between the adaptive immune dynamics in the lower airways with those in the systemic circulation, and how these relate to an individual's clinical response to SARS-CoV-2 infection, are less understood and are the focus of this study. Material and methods: We investigated the adaptive immune response to SARS-CoV-2 in paired samples from the lower airways and blood from 27 critically ill patients during the first wave of the pandemic (median time from symptom onset to intubation 11 days). Measurements included clinical outcomes (mortality), bronchoalveolar lavage fluid (BALF) and blood specimen antibody levels, and BALF viral load. Results: While there was heterogeneity in the levels of the SARS-CoV-2-specific antibodies, we unexpectedly found that some BALF specimens displayed higher levels than the paired concurrent plasma samples, despite the known dilutional effects common in BALF samples. We found that survivors had higher levels of anti-spike, anti-spike-N-terminal domain and anti-spike-receptor-binding domain IgG antibodies in their BALF (p<0.05), while there was no such association with antibody levels in the systemic circulation. Discussion: Our data highlight the critical role of local adaptive immunity in the airways as a key defence mechanism against primary SARS-CoV-2 infection.

Visible light-mediated difluoromethylation/cyclization in batch and flow: scalable synthesis of CHF2-containing benzimidazo- and indolo[2,1-a]isoquinolin-6(5H)-ones.

We report here a practical and cost-effective method for the synthesis of CHF2-containing benzimidazo- and indolo[2,1,a]-isoquinolin-6(5H)-ones through a visible light-mediated difluoromethylation/cyclization cascade. The method, which affords functionalized multifused N-heterocyclic scaffolds in moderate to high yields under mild reaction conditions, is also easily scalable using low-cost 3D printed photoflow reactors.

Toward parametric Bayesian adaptive procedures for multi-frequency categorical loudness scaling.

A series of Bayesian adaptive procedures to estimate loudness growth across a wide frequency range from individual listeners was developed, and these procedures were compared. Simulation experiments were conducted based on multinomial psychometric functions for categorical loudness scaling across ten test frequencies estimated from 61 listeners with normal hearing and 87 listeners with sensorineural hearing loss. Adaptive procedures that optimized the stimulus selection based on the interim estimates of two types of category-boundary models were tested. The first type of model was a phenomenological model of category boundaries adopted from previous research studies, while the other type was a data-driven model derived from a previously collected set of categorical loudness scaling data. An adaptive procedure without Bayesian active learning was also implemented. Results showed that all adaptive procedures provided convergent estimates of the loudness category boundaries and equal-loudness contours between 250 and 8000 Hz. Performing post hoc model fitting, using the data-driven model, on the collected data led to satisfactory accuracies, such that all adaptive procedures tested in the current study, independent of modeling approach and stimulus-selection rules, were able to provide estimates of the equal-loudness-level contours between 20 and 100 phons with root-mean-square errors typically under 6 dB after 100 trials.

Combining machine learning with high-content imaging to infer ciprofloxacin susceptibility in isolates of Salmonella Typhimurium.

Antimicrobial resistance (AMR) is a growing public health crisis that requires innovative solutions. Current susceptibility testing approaches limit our ability to rapidly distinguish between antimicrobial-susceptible and -resistant organisms. Salmonella Typhimurium (S. Typhimurium) is an enteric pathogen responsible for severe gastrointestinal illness and invasive disease. Despite widespread resistance, ciprofloxacin remains a common treatment for Salmonella infections, particularly in lower-resource settings, where the drug is given empirically. Here, we exploit high-content imaging to generate deep phenotyping of S. Typhimurium isolates longitudinally exposed to increasing concentrations of ciprofloxacin. We apply machine learning algorithms to the imaging data and demonstrate that individual isolates display distinct growth and morphological characteristics that cluster by time point and susceptibility to ciprofloxacin, which occur independently of ciprofloxacin exposure. Using a further set of S. Typhimurium clinical isolates, we find that machine learning classifiers can accurately predict ciprofloxacin susceptibility without exposure to it or any prior knowledge of resistance phenotype. These results demonstrate the principle of using high-content imaging with machine learning algorithms to predict drug susceptibility of clinical bacterial isolates. This technique may be an important tool in understanding the morphological impact of antimicrobials on the bacterial cell to identify drugs with new modes of action.

Calcified meningiomas demonstrate equivocal grade, proliferation, and immediate surgical outcomes.

BACKGROUND: Meningioma calcification is thought to predict lessened growth potential and aggression. However, historical studies have mostly focused on correlating calcification of small (diameter < 2.5 cm) meningiomas, rather than analyzing traits of calcified meningiomas across all sizes. OBJECTIVE: To investigate the pathologic and clinical implications of meningioma calcification. METHODS: We utilized a historical database of 342 consecutive, newly diagnosed intracranial meningiomas with preoperative CT and MRI scans treated at a single institution from 2005 to 2019. We correlated the presence of calcification with patient demographics, grade, MIB-1 index, location, volume, Simpson grade, and recurrence with both univariate and multivariate generalized linear models. RESULTS: On univariate analysis, no single variable correlated with tumor calcification. Notably, neither tumor WHO grade (p = 0.91) nor MIB-1index (p = 0.62) predicted calcification. After accounting for demographic characteristics and tumor volume and location, there was no significant association between WHO grade (p = 0.52) and MIB-1index (p = 0.54) and calcification. Calcification had no influence on rate resection grade (p = 0.59) or recurrence (p = 0.80). CONCLUSION: In this series, calcified meningiomas exhibited equal WHO grading distribution, proliferation indexes, and immediate surgical outcomes than their noncalcified counterparts. These findings question the historical role of using meningioma calcification as an independent guide to their management.

Gestational weight gain and adverse birth outcomes in South African women with HIV on antiretroviral therapy and without HIV: a prospective cohort study.

INTRODUCTION: Outside of pregnancy, evidence shows that persons with HIV initiating or switching to dolutegravir (DTG)-based antiretroviral therapy (ART) experience greater weight gain compared to those on other ART classes. However, there are few data on the impact of DTG-based ART on gestational weight gain (GWG) in sub-Saharan Africa where HIV is most common. According to the National Academy of Medicine (NAM), GWG below and above NAM guidelines is associated with adverse birth outcomes. Therefore, the objective of this study was to describe GWG by HIV status and ART regimen, and examine the associations with adverse birth outcomes. METHODS: We enrolled pregnant women with HIV (WHIV) and without HIV (≥18 years) in a peri-urban primary healthcare facility in Cape Town, South Africa between 2019 and 2022. GWG was study-measured at 24-28 (baseline) and 33-38 weeks gestation and converted to GWG rate (kg/week) in accordance with NAM guidelines. GWG z-scores were generated using the INTEGROWTH-21 and US standards to account for differing lengths of gestation. Birth outcome data were obtained from medical records. Associations of GWG z-score with adverse birth outcomes were assessed using multivariable linear or log-binomial regression. RESULTS: Among 292 participants (48% WHIV), median age was 29 years (IQR, 25-33), median pre-pregnancy body mass index (BMI) was 31 kg/m2 (IQR, 26-36) and 20% were primiparous at baseline. The median weekly rate of GWG was 0.30 kg/week (IQR, 0.12-0.50), 35% had GWG below NAM standards (59% WHIV) and 48% had GWG above NAM standards (36% WHIV). WHIV gained weight more slowly (0.25 vs. 0.37 kg/week, p<0.01) than women without HIV. Weekly rate of GWG did not differ by ART regimen (DTG-based ART 0.25 vs. efavirenz-based ART 0.27 kg/week, p = 0.80). In multivariable analyses, GWG z-score was positively associated with continuous birth weight (mean difference = 68.53 95% CI 8.96, 128.10) and categorical high birth weight of >4000 g (RR = 2.18 95% CI 1.18, 4.01). CONCLUSIONS: Despite slower GWG among WHIV, nearly half of all women gained weight faster than recommended by the NAM. GWG was positively associated with infant birth weight. Interventions to support healthy GWG in sub-Saharan Africa are urgently needed.

Multi-Scale Digital Pathology Patch-Level Prostate Cancer Grading Using Deep Learning: Use Case Evaluation of DiagSet Dataset.

Prostate cancer remains a prevalent health concern, emphasizing the critical need for early diagnosis and precise treatment strategies to mitigate mortality rates. The accurate prediction of cancer grade is paramount for timely interventions. This paper introduces an approach to prostate cancer grading, framing it as a classification problem. Leveraging ResNet models on multi-scale patch-level digital pathology and the Diagset dataset, the proposed method demonstrates notable success, achieving an accuracy of 0.999 in identifying clinically significant prostate cancer. The study contributes to the evolving landscape of cancer diagnostics, offering a promising avenue for improved grading accuracy and, consequently, more effective treatment planning. By integrating innovative deep learning techniques with comprehensive datasets, our approach represents a step forward in the pursuit of personalized and targeted cancer care.

Ensemble Deep Learning-Based Image Classification for Breast Cancer Subtype and Invasiveness Diagnosis from Whole Slide Image Histopathology.

Cancer diagnosis and classification are pivotal for effective patient management and treatment planning. In this study, a comprehensive approach is presented utilizing ensemble deep learning techniques to analyze breast cancer histopathology images. Our datasets were based on two widely employed datasets from different centers for two different tasks: BACH and BreakHis. Within the BACH dataset, a proposed ensemble strategy was employed, incorporating VGG16 and ResNet50 architectures to achieve precise classification of breast cancer histopathology images. Introducing a novel image patching technique to preprocess a high-resolution image facilitated a focused analysis of localized regions of interest. The annotated BACH dataset encompassed 400 WSIs across four distinct classes: Normal, Benign, In Situ Carcinoma, and Invasive Carcinoma. In addition, the proposed ensemble was used on the BreakHis dataset, utilizing VGG16, ResNet34, and ResNet50 models to classify microscopic images into eight distinct categories (four benign and four malignant). For both datasets, a five-fold cross-validation approach was employed for rigorous training and testing. Preliminary experimental results indicated a patch classification accuracy of 95.31% (for the BACH dataset) and WSI image classification accuracy of 98.43% (BreakHis). This research significantly contributes to ongoing endeavors in harnessing artificial intelligence to advance breast cancer diagnosis, potentially fostering improved patient outcomes and alleviating healthcare burdens.

Associations between fasting glucose rate-of-change and the missense variant, rs373863828, in an adult Samoan cohort.

BACKGROUND: The A allele of rs373863828 in CREB3 regulatory factor is associated with high Body Mass Index, but lower odds of type 2 diabetes. These associations have been replicated elsewhere, but to date all studies have been cross-sectional. Our aims were (1) to describe the development of type 2 diabetes and change in fasting glucose between 2010 and 2018 among a longitudinal cohort of adult Samoans without type 2 diabetes or who were not using diabetes medications at baseline, and (2) to examine associations between fasting glucose rate-of-change (mmol/L per year) and the A allele of rs373863828. METHODS: We describe and test differences in fasting glucose, the development of type 2 diabetes, body mass index, age, smoking status, physical activity, urbanicity of residence, and household asset scores between 2010 and 2018 among a cohort of n = 401 adult Samoans, selected to have a ~2:2:1 ratio of GG:AG: AA rs373863828 genotypes. Multivariate linear regression was used to test whether fasting glucose rate-of-change was associated with rs373863828 genotype, and other baseline variables. RESULTS: By 2018, fasting glucose and BMI significantly increased among all genotype groups, and a substantial portion of the sample developed type 2 diabetes mellitus. The A allele was associated with a lower fasting glucose rate-of-change (ß = -0.05 mmol/L/year per allele, p = 0.058 among women; ß = -0.004 mmol/L/year per allele, p = 0.863 among men), after accounting for baseline variables. Mean fasting glucose and mean BMI increased over an eight-year period and a substantial number of individuals developed type 2 diabetes by 2018. However, fasting glucose rate-of-change, and type 2 diabetes development was lower among females with AG and AA genotypes. CONCLUSIONS: Further research is needed to understand the effect of the A allele on fasting glucose and type 2 diabetes development. Based on our observations that other risk factors increased over time, we advocate for the continued promotion for diabetes prevention and treatment programming, and the reduction of modifiable risk factors, in this setting.

Selective regulation of a defined subset of inflammatory and immunoregulatory genes by an NF-κB p50-IκBζ pathway.

The five NF-κB family members and three nuclear IκB proteins play important biological roles, but the mechanisms by which distinct members of these protein families contribute to selective gene transcription remain poorly understood, especially at a genome-wide scale. Using nascent transcript RNA-seq, we observed considerable overlap between p50-dependent and IκBζ-dependent genes in Toll-like receptor 4 (TLR4)-activated macrophages. Key immunoregulatory genes, including Il6, Il1b, Nos2, Lcn2, and Batf, are among the p50-IκBζ-codependent genes. IκBζ-bound genomic sites are occupied at earlier time points by NF-κB dimers. However, p50-IκBζ codependence does not coincide with preferential binding of either p50 or IκBζ, as RelA co-occupies hundreds of genomic sites with the two proteins. A common feature of p50-IκBζ-codependent genes is a nearby p50/RelA/IκBζ-cobound site exhibiting p50-dependent binding of both RelA and IκBζ. This and other results suggest that IκBζ acts in concert with RelA:p50 heterodimers. Notably, p50-IκBζ-codependent genes comprise a high percentage of genes exhibiting the greatest differential expression between TLR4-stimulated and tumor necrosis factor receptor (TNFR)-stimulated macrophages. Thus, our genome-centric analysis reveals a defined p50-IκBζ pathway that selectively activates a set of key immunoregulatory genes and serves as an important contributor to differential TNFR and TLR4 responses.

Smoking cessation among sexual minority women: Differences in cigarette quit ratios across age, race/ethnicity, and sexual orientation.

OBJECTIVE: Sexual minority (SM) women experience tobacco-related disparities and report a higher prevalence of cigarette use, as well as subgroup differences in use, but little is known about their quitting behavior. This study used data from a national sample of United States SM women to examine cigarette quit ratios overall and by age, race/ethnicity, and sexual orientation. METHODS: Using baseline survey data from the Generations Study (2016-2017, N = 812), we calculated quit ratios among SM women reporting lifetime smoking (100+ cigarettes) who reported currently smoking "not at all" relative to those reporting smoking "every day or some days." Quitting was compared across cohort, race/ethnicity, and sexual orientation, controlling for household income. RESULTS: SM women reporting lifetime smoking in the older cohort were significantly more likely to report quitting than those in the younger cohort. Bisexual women also reported a greater likelihood of quitting than gay/lesbian women. There was no association between race/ethnicity and the probability of quitting smoking. CONCLUSIONS: SM women remain a priority for tobacco prevention and cessation efforts. There is evidence that the probability of quitting cigarettes differs across sexual orientation and age cohorts, which has implications for tailoring of interventions and tobacco communications.

Trends in management of patients with new-onset refractory status epilepticus (NORSE) from 2016 to 2023: An interim analysis.

In response to the evolving treatment landscape for new-onset refractory status epilepticus (NORSE) and the publication of consensus recommendations in 2022, we conducted a comparative analysis of NORSE management over time. Seventy-seven patients were enrolled by 32 centers, from July 2016 to August 2023, in the NORSE/FIRES biorepository at Yale. Immunotherapy was administered to 88% of patients after a median of 3 days, with 52% receiving second-line immunotherapy after a median of 12 days (anakinra 29%, rituximab 25%, and tocilizumab 19%). There was an increase in the use of second-line immunotherapies (odds ratio [OR] = 1.4, 95% CI = 1.1-1.8) and ketogenic diet (OR = 1.8, 95% CI = 1.3-2.6) over time. Specifically, patients from 2022 to 2023 more frequently received second-line immunotherapy (69% vs 40%; OR = 3.3; 95% CI = 1.3-8.9)-particularly anakinra (50% vs 13%; OR = 6.5; 95% CI = 2.3-21.0), and the ketogenic diet (OR = 6.8; 95% CI = 2.5-20.1)-than those before 2022. Among the 27 patients who received anakinra and/or tocilizumab, earlier administration after status epilepticus onset correlated with a shorter duration of status epilepticus (ρ = .519, p = .005). Our findings indicate an evolution in NORSE management, emphasizing the increasing use of second-line immunotherapies and the ketogenic diet. Future research will clarify the impact of these treatments and their timing on patient outcomes.

Antibodies to Helminth Defense Molecule-1 are associated with inflammation, organomegaly, and decreased nutritional status in schistosomiasis japonica.

Immunomodulation enhances parasite fitness by reducing inflammation-induced morbidity in the mammalian host, as well as by attenuating parasite-targeting immune responses. Using a whole proteome differential screening method, we identified Schistosoma japonicum Helminth Defense Molecule (SjHDM-1) as a target of antibodies expressed by S. japonicum resistant, but not susceptible, individuals. In a longitudinal cohort study (N=644) conducted in a S. japonicum endemic region of the Philippines, antibody levels to SjHDM-1 did not predict resistance to reinfection but were associated with increased measures of inflammation. Individuals with high levels of anti-SjHDM-1 IgG had higher levels of C-reactive protein compared to individuals with low anti-SjHDM-1. High anti-SjHDM-1 IgG responses were also associated with reduced biomarkers of nutritional status (albumin), as well as decreased anthropometric measures of nutritional status (WAZ and HAZ) and increased measures of hepatomegaly. Our results suggest that anti-SjHDM-1 responses inhibit the immunomodulatory function of SjHDM-1, resulting in increased morbidity.

Profiles of trauma exposure type and their associations to pain-related outcomes among adults with chronic pain: A two-year longitudinal study.

Individuals with chronic pain report disproportionally higher rates of trauma; yet, it is unclear whether different types of trauma (e.g., sexual, accidental trauma) are associated with worse pain outcomes. The present study sought to: 1) identify subgroups of people with chronic pain based on trauma type; and 2) determine whether subgroups differ in terms of pain characteristics over a two-year period. Individuals with chronic pain (N = 1,451) participated in an online study and completed self-report questionnaires at baseline, 3-, 12- and 24-month follow-up. Trauma was assessed via the Life Events Checklist for DSM-5. Pain intensity and interference were measured via the Brief Pain Inventory and pain distribution was evaluated using the Widespread Pain Index. Latent class analyses produced a three-class solution consisting of individuals with high and diverse trauma (16.3%), high sexual trauma (18.4%), and low/accidental trauma (57.1%) with the rest of the sample endorsing no trauma history (8.2%). After controlling for key demographic variables and baseline outcome levels, individuals in the high and diverse trauma group endorsed higher levels of pain severity and interference at the 3 and 12-month follow-ups compared to the group with no trauma (p<.01). Additionally, relative to the no trauma group, individuals in the high sexual trauma group reported higher levels of pain interference and more widespread pain at the 3-month follow-up (p<.05). Findings underscore the importance of screening for trauma and suggest that the type and variety of trauma experienced may be relevant to pain-related outcomes. PERSPECTIVE: This article highlights how an individual's unique trauma history may be related to their current pain experience. Knowledge of the type and frequency of past trauma may have relevant clinical implications for the treatment of chronic pain.