The genetic landscape of germline DDX41 variants predisposing to myeloid neoplasms.

Germline DDX41 variants are the most common mutations predisposing to acute myeloid leukemia (AML)/myelodysplastic syndrome (MDS) in adults, but the causal variant (CV) landscape and clinical spectrum of hematologic malignancies (HMs) remain unexplored. Here, we analyzed the genomic profiles of 176 patients with HM carrying 82 distinct presumably germline DDX41 variants among a group of 9821 unrelated patients. Using our proposed DDX41-specific variant classification, we identified features distinguishing 116 patients with HM with CV from 60 patients with HM with variant of uncertain significance (VUS): an older age (median 69 years), male predominance (74% in CV vs 60% in VUS, P = .03), frequent concurrent somatic DDX41 variants (79% in CV vs 5% in VUS, P < .0001), a lower somatic mutation burden (1.4 ± 0.1 in CV vs 2.9 ± 0.04 in VUS, P = .012), near exclusion of canonical recurrent genetic abnormalities including mutations in NPM1, CEBPA, and FLT3 in AML, and favorable overall survival (OS) in patients with AML/MDS. This superior OS was determined independent of blast count, abnormal karyotypes, and concurrent variants, including TP53 in patients with AML/MDS, regardless of patient's sex, age, or specific germline CV, suggesting that germline DDX41 variants define a distinct clinical entity. Furthermore, unrelated patients with myeloproliferative neoplasm and B-cell lymphoma were linked by DDX41 CV, thus expanding the known disease spectrum. This study outlines the CV landscape, expands the phenotypic spectrum in unrelated DDX41-mutated patients, and underscores the urgent need for gene-specific diagnostic and clinical management guidelines.

Considering the cellular landscape in marrow stimulation techniques for cartilage repair.

BACKGROUND: Marrow stimulation is a common reparative approach to treat injuries to cartilage and other soft tissues (e.g., rotator cuff). It involves the recruitment of bone marrow elements and mesenchymal stem cells (MSCs) into the defect, theoretically initiating a regenerative process. However, the resulting repair tissue is often weak and susceptible to deterioration with time. The populations of cells at the marrow stimulation site (beyond MSCs), and their contribution to inflammation, vascularity, and fibrosis, may play a role in quality of the repair tissue. SUMMARY: In this review, we accomplish three goals: 1) systematically review clinical trials on the augmentation of marrow stimulation and evaluate their assumptions on the biological elements recruited; 2) detail the cellular populations in bone marrow and their impact on healing; and 3) highlight emerging technologies and approaches that could better guide these specific cell populations towards enhanced cartilage or soft tissue formation. KEY MESSAGES: We found that most clinical trials do not account for cell heterogeneity, nor do they specify the regenerative element recruited, and those that do typically utilize descriptions such as "clots", "elements", and "blood". Furthermore, our review of bone marrow cell populations demonstrates a dramatically heterogenous cell population, including hematopoietic cells, immune cells, fibroblasts, macrophages, and only a small population of MSCs. Finally, the field has developed numerous innovative techniques to enhance the chondrogenic potential (and reduce the anti-regenerative impacts) of these various cell types. We hope this review will guide approaches that account for cellular heterogeneity and improve marrow stimulation techniques to treat chondral defects.

Multiple embryo manipulations in PGT-A cycles may result in inferior clinical outcomes.

RESEARCH QUESTION: Do embryos that undergo a thaw, biopsy and re-vitrification (TBR) for pre-implantation genetic testing for aneuploidy (PGT-A) have different ploidy and transfer outcomes compared with fresh biopsied embryos? DESIGN: Retrospective cohort study of all embryos that underwent the following procedures: fresh biopsy for PGT-A (fresh biopsy); embryos that were warmed, biopsied for PGT-A and re-vitrified (single biopsy TBR); embryos with a no signal result after initial biopsy that were subsequently warmed, biopsied and re-vitrified (double biopsy TBR). The patients who underwent transfers of those embryos at a single academic institution between March 2013 and December 2021 were also studied. RESULTS: About 30% of embryos planned for TBR underwent attrition. Euploidy rates were similar after biopsy: fresh biopsy (42.7%); single biopsy TBR (47.5%) (adjusted RR: 0.99, 0.88 to 1.12); and double biopsy TBR 50.3% (adjusted RR: 0.99, 0.80 to 1.21). Ongoing pregnancy over 8 weeks was not statistically significant (double biopsy TBR: 6/19 [31.6%] versus fresh biopsy: 650/1062 [61.2%]) (adjusted RR 0.52, 95% CI 0.26 to 1.03). The miscarriage rate increased (double biopsy TBR: 4/19 [21.1%] versus fresh biopsy: 66/1062 [6.2%])(RR 3.39, 95% CI 1.38 to 8.31). Live birth rate was also lower per transfer for the double biopsy TBR group (double biopsy TBR [18.75%] versus fresh biopsy [53.75%]) (RR 0.35, 95% CI 0.12 to 0.98), though not after adjustment (adjusted RR 0.37, 95% CI 0.13 to 1.09). These differences were not seen when single biopsy TBR embryos were transferred. CONCLUSIONS: Embryos that undergo TBR have an equivalent euploidy rate to fresh biopsied embryos. Despite that, double biopsy TBR embryos may have impaired transfer outcomes.

Stricker Learning Span criterion validity: a remote self-administered multi-device compatible digital word list memory measure shows similar ability to differentiate amyloid and tau PET-defined biomarker groups as in-person Auditory Verbal Learning Test.

OBJECTIVE: The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey's Auditory Verbal Learning Test (AVLT). METHOD: Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer's disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A-T-, n = 195). Analyses were repeated among CU participants only. RESULTS: The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p's > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A- vs A+) to large (A-T- vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups. CONCLUSIONS: Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

Comprehensive geriatric assessment predicts listing for kidney transplant in patients with end-stage renal disease: a retrospective cohort study.

BACKGROUND: Comprehensive geriatric assessment (CGA) involves a formal broad approach to assess frailty and creating a plan for management. However, the impact of CGA and its components on listing for kidney transplant in older adults has not been investigated. METHODS: We performed a single-center retrospective study of patients with end-stage renal disease who underwent CGA during kidney transplant candidacy evaluation between 2017 and 2021. All patients ≥ 65 years old and those under 65 with any team member concern for frailty were referred for CGA, which included measurements of healthcare utilization, comorbidities, social support, short physical performance battery, Montreal Cognitive Assessment (MoCA), and Physical Frailty Phenotype (FPP), and estimate of surgical risk by the geriatrician. RESULTS: Two hundred and thirty patients underwent baseline CGA evaluation; 58.7% (135) had high CGA ("Excellent" or "Good" rating for transplant candidacy) and 41.3% (95) had low CGA ratings ("Borderline," "Fair," or "Poor"). High CGA rating (OR 8.46; p < 0.05), greater number of CGA visits (OR 4.93; p = 0.05), younger age (OR 0.88; p < 0.05), higher MoCA scores (OR 1.17; p < 0.05), and high physical activity (OR 4.41; p < 0.05) were all associated with listing on transplant waitlist. CONCLUSIONS: The CGA is a useful, comprehensive tool to help select older adults for kidney transplantation. Further study is needed to better understand the predictive value of CGA in predicting post-operative outcomes.

Impact of aspirin use on rates of metastasis in patients with esophageal cancer: insights from the National Inpatient Sample.

Despite advancing treatment methods, esophageal cancer (EC) maintains a high mortality rate and poor prognosis. Through various mechanisms, aspirin has been suggested to have a chemopreventive effect on EC. However, the long-term impact, particularly regarding the rate of metastasis, needs to be further elucidated. NIS 2016-2020 was used to identify adult patients (age > 18 years) with EC using ICD-10 codes. Patients with missing demographics and mortality were excluded. Patients were stratified into two groups based on aspirin use. Data were collected on patient demographics, Elixhauser Comorbidity Index (ECI), and comorbidities (hypertension, chronic pulmonary disease, coronary artery disease (CAD), chronic kidney disease (CKD), congestive heart failure (CHF), coagulopathy, alcohol use, smoking, and obesity). The outcomes studied were rates of total metastasis, gastrointestinal (GI) metastasis, non-GI metastasis, and lymphoid metastasis. Multivariate logistic regression analysis was performed to evaluate the impact of aspirin use on various metastases after adjusting for patient demographics, comorbidities, and ECI. Out of 190,655 patients, 20,650 (10.8%) patients were aspirin users. Majority of the patients in the aspirin group were aged > 65 years (74.7%), males (82.1%), White race (84%), and had medicare insurance (71%). There was a higher incidence of diabetes, hypertension, chronic pulmonary disease, CAD, CKD, CHF, and smoking in aspirin users than non-aspirin users. Patients with aspirin users had a lower incidence of metastasis (28.9% vs. 38.7%, P < 0.001), GI metastasis (14.2% vs. 20.6%, P < 0.001), non-GI metastasis (15.1% vs. 22%, P < 0.001), and lymphoid metastasis (8.9% vs. 11.3%, P < 0.001) than non-aspirin users. After adjusting for confounding factors, patients with aspirin use had lower odds of having metastasis (aOR-0.73, 95% CI-0.70-0.77, P < 0.001). Our study noted that aspirin use is associated with a reduction in the rate of metastasis in patients with EC. These studies support the use of aspirin in patients with EC and suggest the need for further studies to understand the mechanism by which aspirin use reduces metastasis in patients with EC.

Trends in heart failure costs for commercially insured patients in the United States (2006-2021).

BACKGROUND: Although prior research has estimated the overarching cost burden of heart failure (HF), a thorough analysis examining medical expense differences and trends, specifically among commercially insured patients with heart failure, is still lacking. Thus, the study aims to examine historical trends and differences in medical costs for commercially insured heart failure patients in the United States from 2006 to 2021. METHODS: A population-based, cross-sectional analysis of medical and pharmacy claims data (IQVIA PharMetrics® Plus for Academic) from 2006 to 2021 was conducted. The cohort included adult patients (age > = 18) who were enrolled in commercial insurance plans and had healthcare encounters with a primary diagnosis of HF. The primary outcome measures were the average total annual payment per patient and per cost categories encompassing hospitalization, surgery, emergency department (ED) visits, outpatient care, post-discharge care, and medications. The sub-group measures included systolic, diastolic, and systolic combined with diastolic, age, gender, comorbidity, regions, states, insurance payment, and self-payment. RESULTS: The study included 422,289 commercially insured heart failure (HF) patients in the U.S. evaluated from 2006 to 2021. The average total annual cost per patient decreased overall from $9,636.99 to $8,201.89, with an average annual percentage change (AAPC) of -1.11% (95% CI: -2% to -0.26%). Hospitalization and medication costs decreased with an AAPC of -1.99% (95% CI: -3.25% to -0.8%) and - 3.1% (95% CI: -6.86-0.69%). On the other hand, post-discharge, outpatient, ED visit, and surgery costs increased by an AAPC of 0.84% (95% CI: 0.12-1.49%), 4.31% (95% CI: 1.03-7.63%), 7.21% (95% CI: 6.44-8.12%), and 9.36% (95% CI: 8.61-10.19%). CONCLUSIONS: The study's findings reveal a rising trend in average total annual payments per patient from 2006 to 2015, followed by a subsequent decrease from 2016 to 2021. This decrease was attributed to the decline in average patient costs within the Medicare Cost insurance category after 2016, coinciding with the implementation of the Medicare Access and CHIP Reauthorization Act (MACRA) of 2015. Additionally, expenses related to surgical procedures, emergency department (ED) visits, and outpatient care have shown substantial growth over time. Moreover, significant differences across various variables have been identified.

Reliability of a Modified Watson-Jones Classification for Tibial Tubercle Fractures in Children.

OBJECTIVES: The first case report describing a pediatric fracture of the tibial tubercle was published in 1852 in the Medical Times and Gazette, a Journal of Medical Science, literature, criticism, and news. A century later, in 1955, Sir Watson-Jones introduced the first classification system for this fracture. Despite the existence of several classification systems for pediatric tibial tubercle fractures in the medical literature, a crucial aspect of their validation-reliability and reproducibility-has not yet been systematically evaluated. METHODS: In this study, a modified Watson-Jones (mWJ) classification system of tibial tubercle fractures in children was assessed for intraobserver and interobserver variability. Using the mWJ classification, 3 board-certified pediatric orthopaedic surgeons and 3 orthopaedic surgery residents, classified thirty tibial tubercle fractures based on anteroposterior and lateral radiographs on 2 separate occasions in a 2-week duration. Further comparison was made to evaluate the impact of advanced imaging, specifically computed tomography or magnetic resonance imaging, on diagnostic reliability and reproducibility. RESULTS: The study found substantial intraobserver reliability of the mWJ classification based on radiographs alone, with a Cohen weighted kappa (κ w ) coefficient of 0.733. When advanced imaging was utilized, the reliability of the classification improved to κ w = 0.783. Similarly, interobserver reliability demonstrated substantial consistency among observers when using radiographs alone (κ w = 0.69) and improved agreement with advanced imaging (κ w = 0.75). Notably, there was no significant difference in reliability scores between senior-level attendings and residents when analyzed as separate groups. CONCLUSION: Fracture classification systems are clinically relevant tools that help organize and transfer knowledge efficiently, provide treatment guidance, propose prognostic expectations, and improve communication in academic literature. The present study demonstrated substantial reproducibility of an mWJ fracture classification system both between and within individual surgeon raters. LEVEL OF EVIDENCE: Level III-diagnostic.

Preoperative Symptoms of Depression are Associated With Worse Capability 6-weeks and 6-months After Total Hip Arthroplasty for Osteoarthritis.

BACKGROUND: Symptoms of depression have been associated with greater incapability following total hip arthroplasty (THA). A brief, 2-question, measure of symptoms of depression - the Patient Health Questionnaire-2 (PHQ-2) - may be sufficient to measure associations with the magnitude of incapability during recovery from THA. This study investigated whether preoperative symptoms of depression (measured with the PHQ-2) correlated with levels of incapability 6 weeks and 6 months after THA, accounting for demographic and clinical factors. METHODS: We performed a prospective cohort study across 5 centers and recruited 101 patients undergoing THA, of whom 90 (89%) completed follow-up. Patients completed demographics, a preoperative 2-item (PHQ-2) measure of symptoms of depression, and the Hip Dysfunction and Osteoarthritis Outcome Score for Joint Replacement (HOOS JR) at 6-weeks and 6-months postoperatively. Negative binomial regression models determined factors associated with HOOS JR at 6 weeks and 6 months, accounting for potential confounders. RESULTS: Accounting for potential confounding factors, we found that higher preoperative PHQ-2 scores (reflecting greater symptoms of depression) were associated with lower HOOS JR scores (reflecting a greater level of hip disability) at both 6 weeks (regression coefficient = -0.67, P < .001) and 6 months (regression coefficient = -1.9, P < .001) after THA. CONCLUSIONS: Symptoms of depression on a 2-question preoperative questionnaire are common, and greater symptoms of depression are associated with reduced capability within the first year following THA. These findings support the prioritization of routine mental health assessments before THA. Measuring mindset using relatively brief instruments will be important considering the current shift toward implementing self-reported measures of health status in clinical practice and incorporating them within alternative payment models.

Hydroxyapatite deposition disease, an overlooked differential diagnosis in the emergency department: a case series and review of literature.

Hydroxyapatite crystal deposition disease (HADD) poses diagnostic challenges in the emergency department (ED) as it may clinically present similarly to infection and other musculoskeletal conditions. Misdiagnosis often leads to unnecessary treatments and resource over-utilization. This review article provides an overview of HADD in seven patients who presented to the ED secondary to an acute presentation of this disease process. HADD is a prevalent pathology, which commonly involves the shoulder, followed by the hip, elbow, wrist, and knee. Predisposing risk factors, such as diabetes and certain genetic factors, have also been identified. Clinical history and imaging, particularly radiographs, play a vital role in diagnosing HADD, with characteristic calcification patterns observed in different stages of the disease. Conservative nonsurgical therapy is the mainstay of treatment, providing effective symptom relief in over 90% of cases. By recognizing HADD as a crucial differential diagnosis for patients with acute or chronic pain, healthcare resource utilization can be optimized, leading to improved patient care in the ED.

A New Community-to-Hospital Specialist Otology Pathway Using Telemedicine: A Pilot Study of 50 Patients.

INTRODUCTION: Pathway innovation using smartphone otoscopy and tablet-based audiometry technologies to deliver ear and hearing services via trained audiologists may improve efficiency of the service. An ENT-integrated-community-ear service (ENTICES-combining community audiology management, remote ENT review and novel technologies) was piloted. We aimed to assess the efficiency and safety of ENTICES. METHOD: ENTICES was a community-based and audiologist-led pathway. Patients with otological symptoms were self-referred to this service. Smartphone otoscopy and tablet-based audiograms were performed. Two otologists reviewed all decisions made in the community by audiologists based on video-otoscopy, hearing tests and chart reviews. Data on the first 50 consecutive new patients attending either consultant-led hospital otology clinics (HOC), audiologist-led hospital advanced audiology diagnostics (AAD) or ENTICES clinics were collected between 1 August 2021 and 31 December 2021. Data were collected through chart reviews and questionnaires to compare the three pathways with respect to efficiency, patient satisfaction, technology utility and safety. RESULTS: No audiology-led ENTICES decisions were amended by hospital otologists following remote review. Remote review of video-otoscopy with history was sufficient for a diagnosis in 80% of cases. Adding hearing tests and standardised history increased the diagnostic yield to 98%. Patient satisfaction scores showed 100% service recommendation. The cost per patient, per visit, was £83.36, £99.07 and £69.72 for AAD, HOC or ENTICES, respectively. CONCLUSION: ENTICES provides a safe ear and hearing service that patients rated highly. Thirty-two per cent of hospital otology patients were eligible for this service. For those patients, ENTICES is 20% more cost-effective and can reduce the number of clinic visits by up to 60% compared with HOC.

Predicting dental anxiety in young adults: classical statistical modelling approach versus machine learning approach.

OBJECTIVES: To predict and identify the key demographic and clinical exposure factors associated with dental anxiety among young adults, and to compare if the traditional statistical modelling approach provides similar results to the machine learning (ML) approach in predicting factors for dental anxiety. METHODS: A cross-sectional study of Western Illinois University students. Three survey instruments (sociodemographic questionnaire, modified dental anxiety scale (MDAS), and dental concerns assessment tool (DCA)) were distributed via email to the students using survey monkey. The dependent variable was the mean MDAS scores, while the independent variables were the sociodemographic and dental concern assessment variables. Multivariable analysis was done by comparing the classical statistical model and the machine learning model. The classical statistical modelling technique was conducted using the multiple linear regression analysis and the final model was selected based on Akaike information Criteria (AIC) using the backward stepwise technique while the machine learining modelling was performed by comparing two ML models: LASSO regression and extreme gradient boosting machine (XGBOOST) under 5-fold cross-validation using the resampling technique. All statistical analyses were performed using R version 4.1.3. RESULTS: The mean MDAS was 13.73 ± 5.51. After careful consideration of all possible fitted models and their interaction terms the classical statistical approach yielded a parsimonious model with 13 predictor variables with Akaike Information Criteria (AIC) of 2376.4. For the ML approach, the Lasso regression model was the best-performing model with a mean RMSE of 0.617, R2 of 0.615, and MAE of 0.483. Comparing the variable selection of ML versus the classical statistical model, both model types identified 12 similar variables (out of 13) as the most important predictors of dental anxiety in this study population. CONCLUSION: There is a high burden of dental anxiety within this study population. This study contributes to reducing the knowledge gap about the impact of clinical exposure variables on dental anxiety and the role of machine learningin the prediction of dental anxiety. The predictor variables identified can be used to inform public health interventions that are geared towards eliminating the individual clinical exposure triggers of dental anxiety are recommended.

Inconsistent Partitioning and Unproductive Feature Associations Yield Idealized Radiomic Models.

Background Radiomics is the extraction of predefined mathematic features from medical images for the prediction of variables of clinical interest. While some studies report superlative accuracy of radiomic machine learning (ML) models, the published methodology is often incomplete, and the results are rarely validated in external testing data sets. Purpose To characterize the type, prevalence, and statistical impact of methodologic errors present in radiomic ML studies. Materials and Methods Radiomic ML publications were reviewed for the presence of performance-inflating methodologic flaws. Common flaws were subsequently reproduced with randomly generated features interpolated from publicly available radiomic data sets to demonstrate the precarious nature of reported findings. Results In an assessment of radiomic ML publications, the authors uncovered two general categories of data analysis errors: inconsistent partitioning and unproductive feature associations. In simulations, the authors demonstrated that inconsistent partitioning augments radiomic ML accuracy by 1.4 times from unbiased performance and that correcting for flawed methodologic results in areas under the receiver operating characteristic curve approaching a value of 0.5 (random chance). With use of randomly generated features, the authors illustrated that unproductive associations between radiomic features and gene sets can imply false causality for biologic phenomenon. Conclusion Radiomic machine learning studies may contain methodologic flaws that undermine their validity. This study provides a review template to avoid such flaws. © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Jacobs in this issue.

Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT.

Background Adrenal masses are common, but radiology reporting and recommendations for management can be variable. Purpose To create a machine learning algorithm to segment adrenal glands on contrast-enhanced CT images and classify glands as normal or mass-containing and to assess algorithm performance. Materials and Methods This retrospective study included two groups of contrast-enhanced abdominal CT examinations (development data set and secondary test set). Adrenal glands in the development data set were manually segmented by radiologists. Images in both the development data set and the secondary test set were manually classified as normal or mass-containing. Deep learning segmentation and classification models were trained on the development data set and evaluated on both data sets. Segmentation performance was evaluated with use of the Dice similarity coefficient (DSC), and classification performance with use of sensitivity and specificity. Results The development data set contained 274 CT examinations (251 patients; median age, 61 years; 133 women), and the secondary test set contained 991 CT examinations (991 patients; median age, 62 years; 578 women). The median model DSC on the development test set was 0.80 (IQR, 0.78-0.89) for normal glands and 0.84 (IQR, 0.79-0.90) for adrenal masses. On the development reader set, the median interreader DSC was 0.89 (IQR, 0.78-0.93) for normal glands and 0.89 (IQR, 0.85-0.97) for adrenal masses. Interreader DSC for radiologist manual segmentation did not differ from automated machine segmentation (P = .35). On the development test set, the model had a classification sensitivity of 83% (95% CI: 55, 95) and specificity of 89% (95% CI: 75, 96). On the secondary test set, the model had a classification sensitivity of 69% (95% CI: 58, 79) and specificity of 91% (95% CI: 90, 92). Conclusion A two-stage machine learning pipeline was able to segment the adrenal glands and differentiate normal adrenal glands from those containing masses. © RSNA, 2022 Online supplemental material is available for this article.

Effect of modernized collaborative care for depression on depressive symptoms and cardiovascular disease risk biomarkers: eIMPACT randomized controlled trial.

Although depression is a risk and prognostic factor for cardiovascular disease (CVD), clinical trials treating depression in patients with CVD have not demonstrated cardiovascular benefits. We proposed a novel explanation for the null results for CVD-related outcomes: the late timing of depression treatment in the natural history of CVD. Our objective was to determine whether successful depression treatment before, versus after, clinical CVD onset reduces CVD risk in depression. We conducted a single-center, parallel-group, assessor-blinded randomized controlled trial. Primary care patients with depression and elevated CVD risk from a safety net healthcare system (N = 216, Mage = 59 years, 78% female, 50% Black, 46% with income <$10,000/year) were randomized to 12 months of the eIMPACT intervention (modernized collaborative care involving internet cognitive-behavioral therapy [CBT], telephonic CBT, and/or select antidepressants) or usual primary care for depression (primary care providers supported by embedded behavioral health clinicians and psychiatrists). Outcomes were depressive symptoms and CVD risk biomarkers at 12 months. Intervention participants, versus usual care participants, exhibited moderate-to-large (Hedges' g = -0.65, p < 0.01) improvements in depressive symptoms. Clinical response data yielded similar results - 43% of intervention participants, versus 17% of usual care participants, had a ≥ 50% reduction in depressive symptoms (OR = 3.73, 95% CI: 1.93-7.21, p < 0.01). However, no treatment group differences were observed for the CVD risk biomarkers - i.e., brachial flow-mediated dilation, high-frequency heart rate variability, interleukin-6, high-sensitivity C-reactive protein, ß-thromboglobulin, and platelet factor 4 (Hedges' gs = -0.23 to 0.02, ps ≥ 0.09). Our modernized collaborative care intervention - which harnessed technology to maximize access and minimize resources - produced clinically meaningful improvements in depressive symptoms. However, successful depression treatment did not lower CVD risk biomarkers. Our findings indicate that depression treatment alone may not be sufficient to reduce the excess CVD risk of people with depression and that alternative approaches are needed. In addition, our effective intervention highlights the utility of eHealth interventions and centralized, remote treatment delivery in safety net clinical settings and could inform contemporary integrated care approaches. Trial Registration:ClinicalTrials.gov Identifier: NCT02458690.

JAK2 R683S Mutation Resulting in Dual Diagnoses of Chronic Eosinophilic Leukemia and Myelodysplastic/Myeloproliferative Overlap Syndrome.

A 66-year-old male presented with hypereosinophilia, thrombocytosis, extensive thrombosis refractory to direct oral anticoagulant therapy, and evidence of end-organ damage, including rash, splenic infarcts, and pulmonary infiltrates. Bone marrow biopsy revealed myeloid malignancy consistent with both chronic eosinophilic leukemia and myelodysplastic/myeloproliferative neoplasms (MDS/MPN) with SF3B1 mutation and thrombocytosis. Next-generation sequencing of the patient's eosinophils and neutrophil compartments revealed pathologic variants in EZH2 and SF3B1 in addition to a noncanonical JAK2 R683S mutation that has not been previously described in myeloproliferative disorders or other chronic myeloid neoplasms. These mutations were not present in the patient's lymphoid cell fraction, suggesting that the hematopoietic malignancy arose in a myeloid-committed progenitor cell. Based on this case and previous work from our group, we propose that noncanonical JAK2 mutations may permit signal transduction that biases toward eosinophilic differentiation in chronic myeloid neoplasms. Although the patient's blood counts initially responded to ruxolitinib and hydroxyurea, the response was not durable. Early referral for allogenic bone marrow transplant appears necessary to prevent long-term complications and disease progression in myeloid neoplasms with clonal hypereosinophilia driven by noncanonical JAK2 mutations.

Clinical utility of targeted next-generation sequencing panel in routine diagnosis of hereditary hemolytic anemia: A national reference laboratory experience.

INTRODUCTION: Hereditary hemolytic anemias (HHA) comprise a heterogeneous group of disorders resulting from defective red blood cell (RBC) cytoskeleton, RBC enzyme deficiencies, and hemoglobin (Hb) synthesis disorders such as thalassemia or sideroblastic anemia. MATERIALS AND METHODS: Our hemolytic anemia diagnostic next-generation sequencing (NGS) panel includes 28 genes encoding RBC cytoskeletal proteins, membrane transporter, RBC enzymes, and certain bilirubin metabolism genes. The panel covers the complete coding region of these genes, splice junctions, and, wherever appropriate, deep intronic or regulatory regions are also included. Four hundred fifty-six patients with unexplained hemolytic anemia were evaluated using our NGS panel between 2015 and 2019. RESULTS: We identified pathogenic/likely pathogenic variants in 111/456 (24%) patients that were responsible for the disease phenotype (e.g., moderate to severe hemolytic anemia and hyperbilirubinemia). Approximately 40% of the mutations were novel. As expected, 45/456 (10%) patients were homozygous for the promoter polymorphism in the UGT1A1 gene, A(TA)7 TAA (UGT1A1*28). 8/45 homozygous UGT1A1*28 cases were associated with additional pathogenic mutations causing hemolytic anemia, likely exacerbating hyperbilirubinemia. The most common mutated genes were membrane cytoskeleton genes SPTA1, and SPTB, followed by PKLR. Complex interactions between SPTA1 low expression alleles, alpha-LELY and alpha-LEPRA alleles, and intragenic SPTA1 variants were associated with hereditary pyropoikilocytosis and autosomal recessive hereditary spherocytosis in 23/111 patients. CONCLUSIONS: Our results demonstrate that hemolytic anemia is underscored by complex molecular interactions of previously known and novel mutations in RBC cytoskeleton/enzyme genes, and therefore, NGS should be considered in all patients with clinically unexplained hemolytic anemia and in neonates with hyperbilirubinemia. Moreover, low expression alleles alpha-LELY and alpha-LEPRA should be included in all targeted HHA panels.

The cutaneous effects of blue light from electronic devices: a systematic review with health hazard identification.

The biologic effects of visible light, particularly blue light, on the skin at doses and irradiances representative of sunlight have been established. Recent research studies investigated the effects of blue light (BL) from electronic screen devices; however, it is unclear if the evidence can be generalized to real life. The aim of this systematic review was to evaluate available evidence regarding clinical effects of BL emitted from electronic devices on human skin using the framework established by the Office of Health Assessment and Translation (OHAT). A systematic literature search was conducted by two librarians in Ovid MEDLINE, Embase.com, and Web of Science for relevant articles published from 1946 to March 2022. In vitro and in vivo studies that investigated the effects of BL from electronic devices on skin were included. From the 87 articles gathered from database searches and 1 article identified from citation search, only 9 met the inclusion criteria (6 in vitro and 3 in vivo studies). Human and animal literature with the highest level of evidence ratings were considered with mechanistic data to form one of five human hazard identifications for each outcome category using the OHAT protocol: (1) known, (2) presumed, (3) suspected, (4) not classifiable, or (5) not identified to be a hazard to humans. Literature-based evidence integration did not identify exposure to BL from electronic devices as a hazard to skin pigmentation, redness, yellowness, or melasma exacerbation. Exposure to BL from electronic devices was not classified as a skin photoaging hazard. Low confidence in representative exposure characterization drove high OHAT risk-of-bias ratings for the majority of included studies. While these conclusions hold true for the limited existing data, a larger number of future studies with high-confidence evidence are needed to verify and strengthen hazard identification conclusions.

Highly Active and Dispersed Pd Nanoparticles Stabilized by Lacunary Phosphomolybdate: Synthesis, Characterization, and Liquid Phase Hydrogenation of Levulinic Acid to γ-Valerolactone.

In the current scenario, one of the crucial reaction conversions is the synthesis of renewable biofuels and value-added chemicals from the hydrogenation of biomass. Therefore, in the present work, we are proposing aqueous phase conversion of levulinic acid to γ-valerolactone via hydrogenation using formic acid as a sustainable green hydrogen source over a sustainable heterogeneous catalyst. The catalyst based on Pd nanoparticles stabilized by lacunary phosphomolybdate (PMo11Pd) was designed for the same and characterized by EDX, FT-IR, 31P NMR, powder XRD, XPS, TEM, HRTEM, and HAADF-STEM analyses. A detailed optimization study was done to achieve maximum conversion (95% conversion), using a very small amount of Pd (1.879 × 10-3 mmol) with notable TON (2585) at 200 °C in 6 h. The regenerated catalyst was found to be workable (reusable) up to three cycles without any change in activity. Also, a plausible reaction mechanism was proposed. The catalyst exhibits superior activity against reported catalysts.

The RNA polymerase "switch region" is a target for inhibitors.

The alpha-pyrone antibiotic myxopyronin (Myx) inhibits bacterial RNA polymerase (RNAP). Here, through a combination of genetic, biochemical, and structural approaches, we show that Myx interacts with the RNAP "switch region"--the hinge that mediates opening and closing of the RNAP active center cleft--to prevent interaction of RNAP with promoter DNA. We define the contacts between Myx and RNAP and the effects of Myx on RNAP conformation and propose that Myx functions by interfering with opening of the RNAP active-center cleft during transcription initiation. We further show that the structurally related alpha-pyrone antibiotic corallopyronin (Cor) and the structurally unrelated macrocyclic-lactone antibiotic ripostatin (Rip) function analogously to Myx. The RNAP switch region is distant from targets of previously characterized RNAP inhibitors, and, correspondingly, Myx, Cor, and Rip do not exhibit crossresistance with previously characterized RNAP inhibitors. The RNAP switch region is an attractive target for identification of new broad-spectrum antibacterial therapeutic agents.