DeepComBat: A statistically motivated, hyperparameter-robust, deep learning approach to harmonization of neuroimaging data.

Neuroimaging data acquired using multiple scanners or protocols are increasingly available. However, such data exhibit technical artifacts across batches which introduce confounding and decrease reproducibility. This is especially true when multi-batch data are analyzed using complex downstream models which are more likely to pick up on and implicitly incorporate batch-related information.

Single-cell multi-omic and spatial profiling of human kidneys implicates the fibrotic microenvironment in kidney disease progression.

Kidneys are intricate three-dimensional structures in the body, yet the spatial and molecular principles of kidney health and disease remain inadequately understood. We generated high-quality datasets for 81 samples, including single-cell, single-nuclear, spot-level (Visium) and single-cell resolution (CosMx) spatial-RNA expression and single-nuclear open chromatin, capturing cells from healthy, diabetic and hypertensive diseased human kidneys. Combining these data, we identify cell types and map them to their locations within the tissue.

Spatial Single-cell Analysis Decodes Cortical Layer and Area Specification.

The human cerebral cortex, pivotal for advanced cognitive functions, is composed of six distinct layers and dozens of functionally specialized areas. The layers and areas are distinguished both molecularly, by diverse neuronal and glial cell subtypes, and structurally, through intricate spatial organization. While single-cell transcriptomics studies have advanced molecular characterization of human cortical development, a critical gap exists due to the loss of spatial context during cell dissociation.

Optimizing EEG monitoring in critically ill children at risk for electroencephalographic seizures.

Objective: Strategies are needed to optimally deploy continuous EEG monitoring (CEEG) for electroencephalographic seizure (ES) identification and management due to resource limitations. We aimed to construct an efficient multi-stage prediction model guiding CEEG utilization to identify ES in critically ill children using clinical and EEG covariates.

Methods: The largest prospective single-center cohort of 1399 consecutive children undergoing CEEG was analyzed.

A subpopulation of lipogenic brown adipocytes drives thermogenic memory.

Sustained responses to transient environmental stimuli are important for survival. The mechanisms underlying long-term adaptations to temporary shifts in abiotic factors remain incompletely understood. Here, we find that transient cold exposure leads to sustained transcriptional and metabolic adaptations in brown adipose tissue, which improve thermogenic responses to secondary cold encounter.

Deciphering tumor ecosystems at super resolution from spatial transcriptomics with TESLA.

Cell populations in the tumor microenvironment (TME), including their abundance, composition, and spatial location, are critical determinants of patient response to therapy. Recent advances in spatial transcriptomics (ST) have enabled the comprehensive characterization of gene expression in the TME. However, popular ST platforms, such as Visium, only measure expression in low-resolution spots and have large tissue areas that are not covered by any spots, which limits their usefulness in studying the detailed structure of TME.

DeepComBat: A Statistically Motivated, Hyperparameter-Robust, Deep Learning Approach to Harmonization of Neuroimaging Data.

Neuroimaging data from multiple batches (i.e. acquisition sites, scanner manufacturer, datasets, etc.

SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning.

Spatially resolved transcriptomics (SRT) has advanced our understanding of the spatial patterns of gene expression, but the lack of single-cell resolution in spatial barcoding-based SRT hinders the inference of specific locations of individual cells. To determine the spatial distribution of cell types in SRT, we present SpaDecon, a semi-supervised learning approach that incorporates gene expression, spatial location, and histology information for cell-type deconvolution. SpaDecon was evaluated through analyses of four real SRT datasets using knowledge of the expected distributions of cell types.

Challenging Cases in Neuroimmunology.

Neuroimmunology is rapidly evolving field extending from well-known, but incompletely understood conditions like multiple sclerosis, to novel antibody-mediated disorders, of which dozens have been described in the past 10 years. The ongoing expansion in knowledge needed to effectively diagnose and treat these patients presents myriad challenges for clinicians. Here, we discuss six informative cases from our institution.

Subject satisfaction and psychological well-being with escalating abobotulinumtoxinA injection dose for the treatment of moderate to severe glabellar lines.

Background: Previous studies indicate that the efficacy and durability of a single AbobotulinumtoxinA (ABO) treatment for moderate to severe glabellar lines may be enhanced with increasing dose, while safety outcomes remain consistent with those of the licensed dose (50 U).

Aims: Evaluation of subject-reported indicators of treatment efficacy, satisfaction, and psychological well-being with ABO dose escalation.

Methods: A Phase 2, 36-week, multicenter, randomized, dose-ranging, double-blind, placebo-controlled study was conducted in adults with moderate to severe glabellar lines.

SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network.

Recent advances in spatially resolved transcriptomics (SRT) technologies have enabled comprehensive characterization of gene expression patterns in the context of tissue microenvironment. To elucidate spatial gene expression variation, we present SpaGCN, a graph convolutional network approach that integrates gene expression, spatial location and histology in SRT data analysis. Through graph convolution, SpaGCN aggregates gene expression of each spot from its neighboring spots, which enables the identification of spatial domains with coherent expression and histology.

AbobotulinumtoxinA for the Treatment of Moderate-to-Severe Glabellar Lines: A Randomized, Dose-Escalating, Double-Blind Study.

Objective: To evaluate the efficacy and safety of AbobotulinumtoxinA (ABO) dose escalation in the correction of moderate-to-severe glabellar lines.

Design: Phase 2, 36-week, multicenter, randomized, dose-ranging, double-blind, placebo-controlled study.

Methods: Adults with moderate-to-severe glabellar lines received a single ABO treatment, dosed at 50, 75, 100, or 125 U, or placebo.

Statistical and machine learning methods for spatially resolved transcriptomics with histology.

Recent developments in spatially resolved transcriptomics (SRT) technologies have enabled scientists to get an integrated understanding of cells in their morphological context. Applications of these technologies in diverse tissues and diseases have transformed our views of transcriptional complexity. Most published studies utilized tools developed for single-cell RNA sequencing (scRNA-seq) for data analysis.

Update on Nonfacial Fat Transplantation.

Background: Fat transplantation is becoming increasingly popular for off-face rejuvenation.

Objective: To provide an update in the literature of current knowledge and emerging concepts in the use of fat transplantation for nonfacial applications.

Materials And Methods: This update includes the potential benefits and risks of using fat transfer techniques on the body.

A Large, Open-Label, Phase 3 Safety Study of DaxibotulinumtoxinA for Injection in Glabellar Lines: A Focus on Safety From the SAKURA 3 Study.

Background: SAKURA 3 was a Phase 3, open-label, repeat-dose safety study of DaxibotulinumtoxinA for Injection (DAXI); a component of the largest Phase 3 clinical development program of an aesthetic neuromodulator in glabellar lines.

Objective: To evaluate the use of DAXI (40U) up to 3 treatments for moderate or severe glabellar lines.

Methods: Eligible subjects rolled over from the placebo-controlled trials (n = 477) or were de novo (n = 2,214) and received 1 to 3 treatments over a maximum of 84 weeks.

Male Body Contouring.

Background: Men are increasingly seeking out cosmetic procedures, especially minimally and noninvasive body-contouring procedures.

Objective: With the relative lack of scientific evidence related specifically to the use of body-contouring procedures in men, there is a need for more education and scientific discussion in this growing group.

Materials And Methods: Understanding the male anatomy and aesthetics, and how body-contouring techniques and new modalities can be used in men, can lead to better outcomes.

Combination Therapy for Rejuvenation of the Outer Thigh and Buttock: A Review and Our Experience.

Background: Combination therapies are becoming more popular as a multifaceted approach to treating common aesthetic conditions.

Objective: Often, the use of multiple techniques and modalities can lead to improved outcomes; however, there is a lack of current evidence on the use of combination therapies in the literature.

Methods And Materials: With the recent expansion of minimally and noninvasive options for treatment of the outer thigh and buttock, it is important to understand how these techniques can be used together while avoiding increased risk.

Non-invasive, external ultrasonic lipolysis.

Numerous nonsurgical techniques and devices have sought to reproduce the effectiveness of liposuction. Unfortunately, the vast majority of these has fallen short of adequate results or has been plagued with complications. UltraShape (UltraShape; Yoqneam, Israel) is a device that is able to accomplish the reduction of the subcutaneous fat with a procedure that is both comfortable and leads to good patient satisfaction.