Automated pediatric brain tumor imaging assessment tool from CBTN: Enhancing suprasellar region inclusion and managing limited data with deep learning.

Background: Fully automatic skull-stripping and tumor segmentation are crucial for monitoring pediatric brain tumors (PBT). Current methods, however, often lack generalizability, particularly for rare tumors in the sellar/suprasellar regions and when applied to real-world clinical data in limited data scenarios. To address these challenges, we propose AI-driven techniques for skull-stripping and tumor segmentation.

Empowering Data Sharing in Neuroscience: A Deep Learning De-identification Method for Pediatric Brain MRIs.

Background And Purpose: Privacy concerns, such as identifiable facial features within brain scans, have hindered the availability of pediatric neuroimaging datasets for research. Consequently, pediatric neuroscience research lags adult counterparts, particularly in rare disease and under-represented populations. The removal of face regions (image defacing) can mitigate this, however existing defacing tools often fail with pediatric cases and diverse image types, leaving a critical gap in data accessibility.

Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors.

Background And Purpose: Tumor segmentation is essential in surgical and treatment planning and response assessment and monitoring in pediatric brain tumors, the leading cause of cancer-related death among children. However, manual segmentation is time-consuming and has high interoperator variability, underscoring the need for more efficient methods. After training, we compared 2 deep-learning-based 3D segmentation models, DeepMedic and nnU-Net, with pediatric-specific multi-institutional brain tumor data based on multiparametric MR images.

A multi-institutional pediatric dataset of clinical radiology MRIs by the Children's Brain Tumor Network.

Pediatric brain and spinal cancers remain the leading cause of cancer-related death in children. Advancements in clinical decision-support in pediatric neuro-oncology utilizing the wealth of radiology imaging data collected through standard care, however, has significantly lagged other domains. Such data is ripe for use with predictive analytics such as artificial intelligence (AI) methods, which require large datasets.

Streamlining pipeline efficiency: a novel model-agnostic technique for accelerating conditional generative and virtual screening pipelines.

The discovery of potential therapeutic agents for life-threatening diseases has become a significant problem. There is a requirement for fast and accurate methods to identify drug-like molecules that can be used as potential candidates for novel targets. Existing techniques like high-throughput screening and virtual screening are time-consuming and inefficient.

Development of an antibody fused with an antimicrobial peptide targeting Pseudomonas aeruginosa: A new approach to prevent and treat bacterial infections.

The increase in emerging drug resistant Gram-negative bacterial infections is a global concern. In addition, there is growing recognition that compromising the microbiota through the use of broad-spectrum antibiotics can impact long term patient outcomes. Therefore, there is the need to develop new bactericidal strategies to combat Gram-negative infections that would address these specific issues.

The Brain Tumor Segmentation (BraTS) Challenge 2023: .

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations.

Automated tumor segmentation and brain tissue extraction from multiparametric MRI of pediatric brain tumors: A multi-institutional study.

Background: Brain tumors are the most common solid tumors and the leading cause of cancer-related death among all childhood cancers. Tumor segmentation is essential in surgical and treatment planning, and response assessment and monitoring. However, manual segmentation is time-consuming and has high interoperator variability.

Automated Tumor Segmentation and Brain Tissue Extraction from Multiparametric MRI of Pediatric Brain Tumors: A Multi-Institutional Study.

Background: Brain tumors are the most common solid tumors and the leading cause of cancer-related death among all childhood cancers. Tumor segmentation is essential in surgical and treatment planning, and response assessment and monitoring. However, manual segmentation is time-consuming and has high interoperator variability.

Automated Quantification of Abnormal QRS Peaks From High-Resolution ECGs Predicts Late Ventricular Arrhythmias in Hypertrophic Cardiomyopathy: A 5-Year Prospective Multicenter Study.

Background Patients with hypertrophic cardiomyopathy (HCM) are at risk of ventricular arrhythmia (VA) attributed to abnormal electrical activation arising from myocardial fibrosis and myocyte disarray. We sought to quantify intra-QRS peaks (QRSp) in high-resolution ECGs as a measure of abnormal activation to predict late VA in patients with HCM. Methods and Results Prospectively enrolled patients with HCM (n=143, age 53±14 years) with prophylactic implantable cardioverter-defibrillators had 3-minute, high-resolution (1024 Hz), digital 12-lead ECGs recorded during intrinsic rhythm.

Microvolt QRS Alternans in Hypertrophic Cardiomyopathy: A Novel Risk Marker of Late Ventricular Arrhythmias.

Background Unlike T-wave alternans (TWA), the relation between QRS alternans (QRSA) and ventricular arrhythmia (VA) risk has not been evaluated in hypertrophic cardiomyopathy (HCM). We assessed microvolt QRSA/TWA in relation to HCM risk factors and late VA outcomes in HCM. Methods and Results Prospectively enrolled patients with HCM (n=130) with prophylactic implantable cardioverter-defibrillators underwent digital 12-lead ECG recordings during ventricular pacing (100-120 beats/min).

VIS832, a novel CD138-targeting monoclonal antibody, potently induces killing of human multiple myeloma and further synergizes with IMiDs or bortezomib in vitro and in vivo.

Therapeutically targeting CD138, a define multiple myeloma (MM) antigen, is not yet approved for patients. We here developed and determined the preclinical efficacy of VIS832, a novel therapeutic monoclonal antibody (MoAb) with differentiated CD138 target binding to BB4 that is anti-CD138 MoAb scaffold for indatuximab ravtansine (BT062). VIS832 demonstrated enhanced CD138-binding avidity and significantly improved potency to kill MM cell lines and autologous patient MM cells regardless of resistance to current standard-of-care therapies, via robust antibody-dependent cellular cytotoxicity and phagocytosis mediated by NK and macrophage effector cells, respectively.

Characterization of an Antibody Recognizing the Conserved Inner Core of Lipopolysaccharides.

Bacterial infections are a growing public health threat with carbapenem-resistant being classified as a Priority 1 critical threat by the World Health Organization. Antibody-based therapeutics can serve as an alternative and in some cases supplement antibiotics for the treatment of bacterial infections. The glycans covering the bacterial cell surface have been proposed as intriguing targets for binding by antibodies; however, antibodies that can engage with high affinity and specificity with glycans are much less common compared to antibodies that engage with protein antigens.

An Interventional Study on Comprehensive Emergency Care and Trauma Registry for Road Traffic Injuries in India: A Protocol.

Road traffic injuries (RTIs) stands as one of the leading causes of mortality and morbidity across the globe. Effective injury surveillance systems and pre-hospital and in-hospital interventions set up in developing countries have shown promising results in controlling the problem. This study aimed to standardise and evaluate an evidence-based intervention for safety, efficacy and quality of post-crash pre-hospital and in-hospital trauma care services to improve the outcome in RTI victims.

Quantifying the nativeness of antibody sequences using long short-term memory networks.

Antibodies often undergo substantial engineering en route to the generation of a therapeutic candidate with good developability properties. Characterization of antibody libraries has shown that retaining native-like sequence improves the overall quality of the library. Motivated by recent advances in deep learning, we developed a bi-directional long short-term memory (LSTM) network model to make use of the large amount of available antibody sequence information, and use this model to quantify the nativeness of antibody sequences.

Structural prediction of antibody-APRIL complexes by computational docking constrained by antigen saturation mutagenesis library data.

IgA nephropathy (IgAN) is the most prevalent cause of primary glomerular disease worldwide, and the cytokine A PRoliferation-Inducing Ligand (APRIL) is emerging as a key player in IgAN pathogenesis and disease progression. For a panel of anti-human APRIL antibodies with known antagonistic activity, we sought to define their structural mode of engagement to understand molecular mechanisms of action and aid rational antibody engineering. Reliable computational prediction of antibody-antigen complexes remains challenging, and experimental methods such as X-ray co-crystallography and cryoEM have considerable technical, resource, and throughput barriers.

Multicenter Study of Ischemic Ventricular Tachycardia Ablation With Decrement-Evoked Potential (DEEP) Mapping With Extra Stimulus.

Objectives: The authors conducted a multicenter study of decrement-evoked potential (DEEP)-based functional ventricular tachycardia (VT) substrate modification to evaluate if such a mechanistic and physiological strategy is feasible and efficient in clinical practice and provides reduction in the VT burden.

Background: Only a fraction of the myocardium targeted in current VT substrate modification procedures is involved in the initiation and perpetuation of VT. The physiological basis of the DEEP strategy for identification of areas of initiation and maintenance of VT was recently established.

Antibody-Bactericidal Macrocyclic Peptide Conjugates To Target Gram-Negative Bacteria.

To combat antimicrobial infections, new active molecules are needed. Antimicrobial peptides, ever abundant in nature, are a fertile starting point to develop new antimicrobial agents but suffer from low stability, low specificity, and off-target toxicity. These drawbacks have limited their development.

Extending human IgG half-life using structure-guided design.

Engineering of antibodies for improved pharmacokinetics through enhanced binding to the neonatal Fc receptor (FcRn) has been demonstrated in transgenic mice, non-human primates and humans. Traditionally, such approaches have largely relied on random mutagenesis and display formats, which fail to address related critical attributes of the antibody, such as effector functions or biophysical stability. We have developed a structure- and network-based framework to interrogate the engagement of IgG with multiple Fc receptors (FcRn, C1q, TRIM21, FcγRI, FcγRIIa/b, FcγRIIIa) simultaneously.

Automated Quantification of Low-Amplitude Abnormal QRS Peaks From High-Resolution ECG Recordings Predicts Arrhythmic Events in Patients With Cardiomyopathy.

Background: Cardiomyopathy patients are at risk of sudden death, typically from scar-related abnormalities of electrical activation that promote ventricular tachyarrhythmias. Abnormal intra-QRS peaks may provide a measure of altered activation. We hypothesized that quantification of such QRS peaks (QRSp) in high-resolution ECGs would predict arrhythmic events in implantable cardioverter-defibrillator (ICD)-eligible cardiomyopathy patients.

Evaluation of a novel high-resolution mapping system for catheter ablation of ventricular arrhythmias.

Background: The mapping of ventricular arrhythmias in humans using a minibasket 64-electrode catheter paired with a novel automatic mapping system (Rhythmia) has not been evaluated.

Objective: The purpose of this study was to evaluate the safety and efficacy of mapping ventricular arrhythmias and clinical outcomes after ablation using this system.

Methods: Electroanatomic maps for ventricular arrhythmias were obtained during 20 consecutive procedures in 19 patients (12 with ventricular tachycardia [VT] and 2 with ventricular ectopy [VE]).

A Structural and Mathematical Modeling Analysis of the Likelihood of Antibody-Dependent Enhancement in Influenza.

Broadly neutralizing monoclonal antibodies (bNAbs) for viral infections, such as HIV, respiratory syncytial virus (RSV), and influenza, are increasingly entering clinical development. For influenza, most neutralizing antibodies target influenza virus hemagglutinin. These bNAbs represent an emerging, promising modality for treatment and prophylaxis of influenza due to their multiple mechanisms of antiviral action and generally safe profile.

Safety and Upper Respiratory Pharmacokinetics of the Hemagglutinin Stalk-Binding Antibody VIS410 Support Treatment and Prophylaxis Based on Population Modeling of Seasonal Influenza A Outbreaks.

Background: Seasonal influenza is a major public health concern in vulnerable populations. Here we investigated the safety, tolerability, and pharmacokinetics of a broadly neutralizing monoclonal antibody (VIS410) against Influenza A in a Phase 1 clinical trial. Based on these results and preclinical data, we implemented a mathematical modeling approach to investigate whether VIS410 could be used prophylactically to lessen the burden of a seasonal influenza epidemic and to protect at-risk groups from associated complications.

Rapid Device-Detected Nonsustained Ventricular Tachycardia in the Risk Stratification of Hypertrophic Cardiomyopathy.

Background: Nonsustained ventricular tachycardia (NSVT) detected by ambulatory Holter (Holter NSVT) is a major risk factor for sudden cardiac death in hypertrophic cardiomyopathy (HCM). We hypothesized that the prognostic utility of Holter NSVT in HCM would improve with prolonged monitoring and a higher heart rate cut-off for detection.

Methods: We enrolled 60 patients (44 ± 14 years) with HCM, who had a prophylactic implantable cardioverter defibrillator (ICD).