Citations

Abstract Study Objectives The majority of patients with insomnia exhibit abnormal sleep in objective testing (e.g. decreased sleep duration, decreased slow wave sleep [SWS]). Previous studies have suggested that some of these objective measures of poor sleep, such as decreased sleep duration, are associated with a higher risk of hypertension in insomnia. We examined the relationship between SWS and morning and evening blood pressure (BP) levels in patients with clinically diagnosed insomnia. Methods A total of 229 normal sleepers and 1378 insomnia patients were included in this study. Insomnia was defined based on standard diagnostic criteria with symptoms lasting ≥6 months. All participants underwent in-laboratory polysomnography. Patients were classified into quartiles of percent SWS. Evening and morning hypertension were defined using BP measurements taken in the evening before and in the morning after polysomnography, respectively. Multivariable logistic regression models were used to assess the relationship between insomnia, SWS, and hypertension. Results Insomniacs with <3.5% SWS (OR 3.27, 95% confidence intervals [CI]: 1.31 to 7.66) and those with 3.5%–10.2% SWS (OR 2.38, 95% CI: 1.28 to 5.91) had significantly greater odds of morning hypertension compared to normal sleepers. No associations were seen in insomnia with 10.2%–15.8% SWS and with >15.8% SWS. Significant effect modifications by sex (p = .043) were found, as decreased SWS was associated with morning hypertension only in men. Odds of evening hypertension were not significantly associated with SWS. Conclusions Decreased SWS is associated with morning hypertension in a dose-dependent manner in insomnia, especially in men.

Congenital cytomegalovirus (cCMV) is the most common infectious cause of disability in children, including sensorineural hearing loss. There is interest in developing a pre-conception vaccine that could confer protective immunity on a woman of child-bearing age, hence resulting in a reduced cCMV disease burden. Other populations, including solid organ transplant (SOT) and hematopoietic stem cell transplant (HSCT) patients, could also benefit from CMV vaccination. To review and discuss vaccines that are in clinical development, a workshop, sponsored by the National Institutes of Health (NIH) and the National Institute of Allergy and Infectious Diseases (NIAID), was empaneled. At this workshop, correlates of protective immunity against CMV, epidemiologic features of CMV transmission, and vaccine platforms in development were reviewed. Representatives from academia, pharma, and the NIH engaged in discussion on the current state-of-the-art in CMV vaccinology. A summary of the presentations from this is provided in this report.

Anatomic teaching has long informed surgical knowledge, experience, and skills. One tool for teaching that emerged during the Renaissance was the fugitive anatomic sheet, which used flap layers to reveal different levels of anatomy. In 1538, Vogtherr introduced the first fugitive sheets, which included illustrations of male and female figures with a torso paper flap that, when lifted, revealed the internal organs in a cartoonish style. The popularity of these anatomic fugitive sheets spurred an increase in small print-and-sale workshops. In 1543, Vesalius included fugitive anatomic sheets in his books Fabrica and Epitome , containing large paper flapped models that could be created by cutting out and gluing images of human internal anatomy onto a base layer. Students could tack these manikins up to a nearby wall during dissection. Significant collaboration between Vesalius and his publisher occurred to coordinate the integration of large foldable sheets featuring the cutout models into his works. Vesalius's groundbreaking discoveries, his use of the most advanced printing techniques, and his innovative teaching style are fundamental aspects of the legacy of medical education. This article shows these remarkable fugitive anatomic sheets from the original publications of Fabrica and Epitome together for the first time. It explores the innovative concepts and applications of Vesalius's unique printings.

Neuropathic pain is a debilitating chronic condition that lacks effective treatment. The role of cytokine- and chemokine-mediated neuroinflammation in its pathogenesis has been well documented. Follistatin (FST) is a secreted protein known to antagonize the biological activity of cytokines in the transforming growth factor–β (TGF-β) superfamily. The involvement of FST in neuropathic pain and the underlying mechanism remain largely unknown. Here, we report that FST was up-regulated in A-fiber sensory neurons after spinal nerve ligation (SNL) in mice. Inhibition or deletion of FST alleviated neuropathic pain and reduced the nociceptive neuron hyperexcitability induced by SNL. Conversely, intrathecal or intraplantar injection of recombinant FST, or overexpression of FST in the dorsal root ganglion (DRG) neurons, induced pain hypersensitivity. Furthermore, exogenous FST increased neuronal excitability in nociceptive neurons. The biolayer interferometry (BLI) assay and coimmunoprecipitation (co-IP) demonstrated direct binding of FST to the insulin-like growth factor–1 receptor (IGF1R), and IGF1R inhibition reduced FST-induced activation of extracellular signal–regulated kinase (ERK) and protein kinase B (AKT), as well as neuronal hyperexcitability. Further co-IP analysis revealed that the N-terminal domain of FST exhibits the highest affinity for IGF1R, and blocking this interaction with a peptide derived from FST attenuated Nav1.7-mediated neuronal hyperexcitability and neuropathic pain after SNL. In addition, FST enhanced neuronal excitability in human DRG neurons through IGF1R. Collectively, our findings suggest that FST, released from A-fiber neurons, enhances Nav1.7-mediated hyperexcitability of nociceptive neurons by binding to IGF1R, making it a potential target for neuropathic pain treatment.

ABSTRACTObjectiveTo study the association between dietary patterns and subgingival microbiota.MethodsParticipants (n = 651) who were enrolled in the Oral Infections, Glucose Intolerance, and Insulin Resistance Study (ORIGINS) with subgingival plaque sampling (n = 890 plaques) and a dietary assessment were included. 16S rRNA gene amplicon sequences of subgingival plaque from sites with either probing depth <4 or ≥4 mm were processed separately and used to obtain α‐diversity metrics (Faith, Shannon, Simpson, Observed) and taxa ratios (Red Complex to Corynebacterium [RCLR], Treponema to Corynebacterium [TCLR], and Treponema to Neisseria [TNLR]). Food frequency questionnaires (FFQs) were processed to calculate Alternate Healthy Eating Index (AHEI) and A Priori Diet Quality Score (APDQS) scores. Mixed regression models examined the mean levels of microbial metrics across quartiles of diet quality. Means ± standard errors are reported along with p‐values.ResultsIn multivariable models assessing the association between diet scores and α‐diversity metrics, higher AHEI values were significantly associated with lower Faith (p‐value = 0.01) and Observed (p‐value = 0.04) diversity values; similar findings were observed for APDQS (p‐value = 0.01, p‐value = 0.04). In multivariable models assessing the association between diet scores (AHEI and APDQS) and taxa ratios (RCLR, TCLR and TNLR), as the AHEI quartile increased, all taxa ratios decreased significantly as follows: −1.06 ± 0.093 in Q1 to −1.34 ± 0.099 in Q4 (RCLR), −0.43 ± 0.077 in Q1 to −0.64 ± 0.083 in Q4 (TCLR) and −0.09 ± 0.083 in Q1 to −0.38 ± 0.089 in Q4 (TNLR), respectively. In contrast, as the APDQS quartiles increased, only TNLR decreased significantly from −0.08 ± 0.085 in Q1 to −0.34 ± 0.091 in Q4.ConclusionDiets rich in fruits, vegetables, whole grains and other nutritionally rich plant foods are associated with lower oral microbial diversity and favourable ratios of pathogenic to commensal microbiota.

ABSTRACTPancreatoblastoma is a rare malignant neoplasm. Cytologic diagnosis is challenging due to the tumor's heterogeneity and requirement of the presence of squamoid nests. Commonly affects children, but the tumor rarely is seen in adult patients. We are reporting three cases from two patients. First patient was a 38‐year‐old male with a mass in the pancreatic body and numerous hepatic lesions. Fine‐needle aspiration (FNA) of the pancreas showed a biphasic malignancy, predominantly composed of a primitive component with intermingled squamoid nests. Subsequent Liver FNA from the same patient showed a similar biphasic malignancy. NUT carcinoma was the top differential and was ruled out by molecular testing. Second patient was a 24‐year‐old female with a history of pancreatoblastoma related to Gardner's syndrome initially diagnosed in 2015 at age 17, status post distal pancreatectomy and chemotherapy. Celiac lymph node FNA in 2021 showed few cohesive clusters of atypical epithelioid cells, which were highlighted by beta‐catenin. Lastly, the literature was reviewed; differential diagnosis and ancillary testing were discussed.

AbstractThe Psychiatric Pediatric Issues Task Force of the International League Against Epilepsy (ILAE) aimed to develop recommendations for the diagnosis and treatment of anxiety and depression in children and adolescents with epilepsy. The Task Force conducted a systematic review and identified two studies that assessed the accuracy of four screening measures for depression and anxiety symptoms compared with a psychiatric interview. Nine studies met the eligibility criteria for treatment of anxiety and depressive disorders or symptoms. The risk of bias and certainty of evidence were assessed. The evidence generated by this review followed by consensus where evidence was missing generated 47 recommendations. Those with a high level of agreement (≥80%) are summarized. Diagnosis: (1) Universal screening for anxiety and depression is recommended. Closer surveillance is recommended for children after 12 years, at higher risk (e.g., suicide‐related behavior), with subthreshold symptoms, and experiencing seizure worsening or therapeutic modifications. (2) Multiple sources of ascertainment and a formal screening are recommended. Clinical interviews are recommended whenever possible. The healthcare provider must always explain that symptom recognition is essential to optimize treatment outcomes and reduce morbidity. (3) Questioning about the relationship between symptoms of anxiety or depression with seizure worsening/control and behavioral adverse effects of antiseizure medications is recommended. Treatment: (1) An individualized treatment plan is recommended. (2) For mild depression, active monitoring must be considered. (3) Referral to a mental health care provider must be considered for moderate to severe depression and anxiety. (4) Clinical care pathways must be developed. (5) Psychosocial interventions must be tailored and age‐appropriate. (6) Healthcare providers must monitor children with epilepsy who are prescribed antidepressants, considering symptoms and functioning that may not improve simultaneously. (7) Caregiver education is essential to ensure treatment adherence. (8) A shared‐care model involving all healthcare providers is recommended for children and adolescents with epilepsy and mental health disorders. We identified clinical decisions in the management of depression and anxiety that lack solid evidence and provide consensus‐based guidance to address the care of children and adolescents with epilepsy.

Abstract Current studies regarding the secondary use of electronic health records (EHR) predominantly rely on domain expertise and existing medical knowledge. Though significant efforts have been devoted to investigating the application of machine learning algorithms in the EHR, efficient and powerful representation of patients is needed to unleash the potential of discovering new medical patterns underlying the EHR. Here, we present an unsupervised method for embedding high-dimensional EHR data at the patient level, aimed at characterizing patient heterogeneity in complex diseases and identifying new disease patterns associated with clinical outcome disparities. Inspired by the architecture of modern language models—specifically transformers with attention mechanisms, we use patient diagnosis and procedure codes as vocabularies and treat each patient as a sentence to perform the patient embedding. We applied this approach to 34,851 unique medical codes across 1,046,649 longitudinal patient events, including 102,739 patients from the electronic Medical Records and GEnomics (eMERGE) Network. The resulting patient vectors demonstrated excellent performance in predicting future disease events (median AUROC = 0.87 within one year) and bulk phenotyping (median AUROC = 0.84). We then illustrated the utility of these patient vectors in revealing heterogeneous comorbidity patterns, exemplified by disease subtypes in colorectal cancer and systemic lupus erythematosus, and capturing distinct longitudinal disease trajectories. External validation using EHR data from the University of Washington confirmed robust model performance, with median AUROCs of 0.83 and 0.84 for bulk phenotyping tasks and disease onset prediction, respectively. Importantly, the model reproduced the clustering results of disease subtypes identified in the eMERGE cohort and uncovered variations in overall mortality among these subtypes. Together, these results underscore the potential of representation learning in EHRs to enhance patient characterization and associated clinical outcomes, thereby advancing disease forecasting and facilitating personalized medicine.