Reexamining the Role of Electroconvulsive Therapy in Anorexia Nervosa in Adolescents.

Electroconvulsive therapy (ECT) is rarely, if ever, considered for the treatment of severe anorexia nervosa (AN) or other eating disorders comorbid with an affective illness. Mood disorders are common in these patients, and psychotropic medications, although frequently used, have limited evidence of benefit in AN or copresenting depressive symptoms. Even when the illness is life threatening, ECT as a treatment may be overlooked. We present a case of an adolescent girl with severe AN and comorbid major depressive disorder with suicidality. This patient failed multiple medication trials but went on to experience complete remission from both the symptoms of her AN and major depressive disorder after undergoing a course of bilateral ECT. Electroconvulsive therapy may prove to be a fast and effective treatment strategy for mood disorders and suicidality in the setting of comorbid AN in adolescents.

Adoption of milk cooling technology among smallholder dairy farmers in Kenya.

Factors influencing adoption of milk cooling technology were studied with data for 90 smallholder dairy farmers who were randomly selected from seven dairy cooperative societies in Kiambu County, Kenya. Logistic regression identified the age of the household head, daily household milk consumption, freehold land ownership, fodder production area, number of female calves, cooperative membership and cooperative services as significant factors influencing farmers' willingness to invest in milk cooling technology. These findings offer an entry point for increased interventions by policy makers and various dairy sector stakeholders in promoting milk cooling technology with the aim of significantly reducing post-harvest losses and increasing the sector's competitiveness.

Dyadic Work in Conjunction With Electroconvulsive Therapy in a 12-Year-Old Female With Autism Spectrum Disorder and Catatonia.

Background: Attachment-based interventions have been extensively studied in neurotypical patient populations. In neurodivergent patient populations, however, emphasis on and current research into attachment-based interventions are centered on early childhood. Minimal research has been conducted in school-aged children with autism spectrum disorder (ASD), and even less research has focused on attachment-based interventions for children with significant comorbidities such as catatonia. Case Report: We present the case of a 12-year-old female that involved dyadic work in conjunction with biologic interventions for the treatment of ASD and catatonia. Psychosocial interventions were centered on an attachment-based framework and behavioral skills training that incorporated elements of parent management training. We observed and tracked the patient's uncooperativeness, underproductive speech, emotional withdrawal, and anxiety via the Brief Psychiatric Rating Scale for Children. Attachment- and behavioral-based interventions in conjunction with psychotropic medications and electroconvulsive therapy resulted in improvements. Conclusion: This case illustrates the potential advantages that attachment- and behavioral-based psychotherapeutic interventions can confer in complex cases involving neurodivergent patients. The case also highlights the lack of current research into and understanding of attachment theory in children and adolescents with ASD. Research is needed into the role of attachment-based interventions in patients with ASD and other psychiatric comorbidities, particularly in patient populations beyond preschool age. Initiating nonbiologic interventions in conjunction with biologic interventions may also enhance outcomes and warrants further investigation.

Exploring the biology of ctDNA release in colorectal cancer.

BACKGROUND: Circulating tumor DNA (ctDNA) has emerged as a promising tool for early cancer detection and minimal residual disease monitoring. However, the biology underlying ctDNA release and its variation across cancer types and histologies remains poorly understood. This study investigated the biology behind ctDNA shedding in colorectal cancer. METHODS: The study included a local cohort of 747 stage I-III colorectal cancer patients. All patients had ctDNA measurement prior to treatment and extensive clinical data. Primary tumor RNA sequencing and whole exome sequencing was performed in 95 and 652 patients respectively. Additionally, the study evaluated 89 non-small cell lung cancer patients from the TRACERx cohort, comprising primary tumor RNA sequencing and ctDNA measurement. RESULTS: We found tumor size and proliferative capacity to be key factors associated with ctDNA shedding in colorectal cancer. Furthermore, we found that the secretory and CMS3 colorectal cancer subtypes exhibited lower ctDNA shedding, while microsatellite instability (MSI) tumors had higher levels of ctDNA. Mutational analysis did not reveal any genes or pathways associated with ctDNA shedding in colorectal cancer. A comparison of transcriptomic profiles across multiple cancer types demonstrated that colorectal cancer and lung squamous cell carcinoma tumors shared a high-proliferative ctDNA shedding phenotype, while lung adenocarcinoma tumors displayed a distinct low-proliferative subgroup. Additionally, proliferation levels correlated with ctDNA detection sensitivity across multiple cancer types. CONCLUSION: These findings suggest that tumor size and proliferative capacity are drivers of ctDNA release in colorectal cancer and provide insights into the biology of ctDNA shedding on a pan-cancer level.

Exploring the molecular landscape of cancer of unknown primary: A comparative analysis with other metastatic cancers.

Cancer of unknown primary (CUP) tumors are biologically very heterogeneous, which complicates stratification of patients for treatment. Consequently, these patients face limited treatment options and a poor prognosis. With this study, we aim to expand on the current knowledge of CUP biology by analyzing two cohorts: a well-characterized cohort of 44 CUP patients, and 213 metastatic patients with known primary. These cohorts were treated at the same institution and characterized by identical molecular assessments. Through comparative analysis of genomic and transcriptomic data, we found that CUP tumors were characterized by high expression of immune-related genes and pathways compared to other metastatic tumors. Moreover, CUP tumors uniformly demonstrated high levels of tumor-infiltrating leukocytes and circulating T cells, indicating a strong immune response. Finally, the genetic landscape of CUP tumors resembled that of other metastatic cancers and demonstrated mutations in established cancer genes. In conclusion, CUP tumors possess a distinct immunophenotype that distinguishes them from other metastatic cancers. These results may suggest an immune response in CUP that facilitates metastatic tumor growth while limiting growth of the primary tumor.

Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment.

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole-genome sequencing (WGS). Here we now introduce MRD-EDGE, a machine-learning-guided WGS ctDNA single-nucleotide variant (SNV) and copy-number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by ~300× compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, vastly expanding its applicability within solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in TF in response to neoadjuvant immunotherapy in lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables plasma-only (non-tumor-informed) disease monitoring in advanced melanoma and lung cancer, yielding clinically informative TF monitoring for patients on immune-checkpoint inhibition.

Catatonia in Patients with Autism Spectrum Disorder.

Catatonia was first described by Karl Ludwig Kahlbaum in 1874, occurring in association with other psychiatric and medical disorders. However, in the nineteenth century the disorder was incorrectly classified as a subtype of schizophrenia. This misclassification persisted until the publication of DSM-5 in 2013 when important changes were incorporated. Although the etiology is unknown, disrupted gamma-aminobutyric acid has been proposed as the underlying pathophysiological mechanism. Key symptoms can be identified under 3 clinical domains: motor, speech, and behavioral. Benzodiazepines and electroconvulsive therapy are the only known effective treatments. Timely recognition and treatment have important outcome, and sometimes lifesaving, implications.

Catatonia in Patients with Autism Spectrum Disorder.

Catatonia was first described by Karl Ludwig Kahlbaum in 1874, occurring in association with other psychiatric and medical disorders. However, in the nineteenth century the disorder was incorrectly classified as a subtype of schizophrenia. This misclassification persisted until the publication of DSM-5 in 2013 when important changes were incorporated. Although the etiology is unknown, disrupted gamma-aminobutyric acid has been proposed as the underlying pathophysiological mechanism. Key symptoms can be identified under 3 clinical domains: motor, speech, and behavioral. Benzodiazepines and electroconvulsive therapy are the only known effective treatments. Timely recognition and treatment have important outcome, and sometimes lifesaving, implications.

Obtaining reliable likelihood ratio tests from simulated likelihood functions.

MIXED MODELS: Models allowing for continuous heterogeneity by assuming that value of one or more parameters follow a specified distribution have become increasingly popular. This is known as 'mixing' parameters, and it is standard practice by researchers--and the default option in many statistical programs--to base test statistics for mixed models on simulations using asymmetric draws (e.g. Halton draws). PROBLEM 1: INCONSISTENT LR TESTS DUE TO ASYMMETRIC DRAWS: This paper shows that when the estimated likelihood functions depend on standard deviations of mixed parameters this practice is very likely to cause misleading test results for the number of draws usually used today. The paper illustrates that increasing the number of draws is a very inefficient solution strategy requiring very large numbers of draws to ensure against misleading test statistics. The main conclusion of this paper is that the problem can be solved completely by using fully antithetic draws, and that using one dimensionally antithetic draws is not enough to solve the problem. PROBLEM 2: MAINTAINING THE CORRECT DIMENSIONS WHEN REDUCING THE MIXING DISTRIBUTION: A second point of the paper is that even when fully antithetic draws are used, models reducing the dimension of the mixing distribution must replicate the relevant dimensions of the quasi-random draws in the simulation of the restricted likelihood. Again this is not standard in research or statistical programs. The paper therefore recommends using fully antithetic draws replicating the relevant dimensions of the quasi-random draws in the simulation of the restricted likelihood and that this should become the default option in statistical programs. JEL classification: C15; C25.