Artificial intelligence in emergency neuroradiology: Current applications and perspectives.

Emergency neuroradiology provides rapid diagnostic decision-making and guidance for management for a wide range of acute conditions involving the brain, head and neck, and spine. This narrative review aims at providing an up-to-date discussion about the state of the art of applications of artificial intelligence in emergency neuroradiology, which have substantially expanded in depth and scope in the past few years. A detailed analysis of machine learning and deep learning algorithms in several tasks related to acute ischemic stroke involving various imaging modalities, including a description of existing commercial products, is provided.

Harnessing open science practices to teach ecology and evolutionary biology using interactive tutorials.

Open science skills are increasingly important for a career in ecology and evolutionary biology (EEB) as efforts to make data and analyses publicly available continue to become more commonplace. While learning core concepts in EEB, students are also expected to gain skills in conducting open science to prepare for future careers. Core open science skills like programming, data sharing, and practices that promote reproducibility can be taught to undergraduate students alongside core concepts in EEB.

Exploring the Use of Natural Language Processing for Objective Assessment of Disorganized Speech in Schizophrenia.

Objective: Measurement-based care tools in psychiatry are useful for symptom monitoring and detecting response to treatment, but methods for quick and objective measurement are lacking especially for acute psychosis. The aim of this study was to explore potential language markers, detected by natural language processing (NLP) methods, as a means to objectively measure the severity of psychotic symptoms of schizophrenia in an acute clinical setting.

Methods: Twenty-two speech samples were collected from seven participants who were hospitalized for schizophrenia, and their symptoms were evaluated over time with SAPS/SANS and TLC scales.

Quantitative proteomics and biological activity of extracellular vesicles engineered to express SARS-CoV-2 spike protein.

SARS-CoV-2 viral infection led to the devastating COVID-19 pandemic, where illness stemmed from interactions between virions and recipient host cells resulting in multi-layered pathological consequences. The role of the infection portal is now understood to be the cellular angiotensin converting enzyme-2 (ACE2) receptor, which binds to viral spike (S) protein initiating virion internalisation process. Since SARS-CoV-2 virions bear some resemblance to endogenously produced small extracellular vesicles (sEVs) we reasoned that EVs engineered to express S protein (viral mimics) may interfere with viral infection.

Next-generation sequencing-based analysis to assess the pattern of relapse in patients with Philadelphia-positive acute lymphoblastic leukemia.

In this study, we performed serial monitoring using targeted DNA sequencing to identify genetic alterations in adults with Philadelphia-positive acute lymphoblastic leukemia (Ph-ALL). Deep sequencing was performed by targeting the coding regions of 45 genes with recurrent driver mutations and 1129 single nucleotide polymorphism sites. Of the 43 patients that we examined, at least one case of genetic alterations was detected in 38 (88%) of the 43 patients at diagnosis (somatic mutations in 10 patients [23%] and copy number aberrations [CNA] in 36 patients [84%]).

The 17-gene stemness score associates with relapse risk and long-term outcomes following allogeneic haematopoietic cell transplantation in acute myeloid leukaemia.

A 17-gene stemness (LSC17) score determines risk in acute myeloid leukaemia patients treated with standard chemotherapy regimens. The present study further analysed the impact of the LSC17 score at diagnosis on outcomes following allogeneic haematopoietic cell transplantation (HCT). Out of 452 patients with available LSC17 score, 123 patients received allogeneic HCT.

Single cell proteogenomic sequencing identifies a relapse-fated AML subclone carrying -ITD with CN-LOH at chr13q.

Internal tandem duplication of the Feline McDonough Sarcoma (FMS)-like tyrosine kinase 3 (-ITD) is one of the most clinically relevant mutations in acute myeloid leukemia (AML), with a high -ITD allelic ratio (AR) (≥0.5) being strongly associated with poor prognosis. -ITDs are heterogeneous, varying in size and location, with some patients having multiple -ITDs.

Identifying Modifiable Predictors of Long-Term Survival in Liver Transplant Recipients With Diabetes Mellitus Using Machine Learning.

Diabetes mellitus (DM) significantly impacts long-term survival after liver transplantation (LT). We identified survival factors for LT recipients who had DM to inform preventive care using machine-learning analysis. We analyzed risk factors for mortality in patients from across the United States using the Scientific Registry of Transplant Recipients (SRTR).

Allosteric Modulation of Binding Specificity by Alternative Packing of Protein Cores.

Hydrophobic cores are often viewed as tightly packed and rigid, but they do show some plasticity and could thus be attractive targets for protein design. Here we explored the role of different functional pressures on the core packing and ligand recognition of the SH3 domain from human Fyn tyrosine kinase. We randomized the hydrophobic core and used phage display to select variants that bound to each of three distinct ligands.