Artificial intelligence in medical imaging empowers precision neoadjuvant immunochemotherapy in esophageal squamous cell carcinoma.

Neoadjuvant immunochemotherapy (nICT) has demonstrated significant potential in improving pathological response rates and survival outcomes for patients with locally advanced esophageal squamous cell carcinoma (ESCC). However, substantial interindividual variability in therapeutic outcomes highlights the urgent need for more precise predictive tools to guide clinical decision-making. Traditional biomarkers remain limited in both predictive performance and clinical feasibility.

A Rare Case: Composite Paraganglioma-Ganglioneuroma in a Neurofibromatosis 1 Patient and Literature Review.

Background: Pheochromocytomas and paragangliomas (PPGLs) are rare catecholamine-secreting neuroendocrine tumors originating from the embryonic neural crest. Approximately 30% of PPGLs are hereditary and are frequently associated with genetic syndromes, including neurofibromatosis type 1 (NF1). Composite PPGLs, which include components of both PPGLs and related tumors such as ganglioneuromas, are extremely rare in NF1 patients.

A Qualitative Examination of the Content Validity of the EQ-5D-5L and EQ-5D-Y-3L in Adult and Paediatric Patients With Duchenne Muscular Dystrophy.

Objective: This study examined the content validity of EQ-5D for Chinese patients with DMD. Specifically, it investigated: (1) the content validity of EQ-5D-5L in adult DMD patients and (2) the content validity of EQ-5D-Y-3L (Y-3L) in DMD patients aged 8-15 years.

Method: This qualitative study used semi-structured interviews and conducted one-on-one and online, with two groups of individuals with DMD to examine the content validity of the EQ-5D-5L and Y-3L.

Pre-diagnostic plasma proteomics profile uncovers new biomarkers and mechanistic insights for incident kidney cancer.

Background: The pathophysiological changes driving incident kidney cancer remain unclear. This study aimed to identify protein biomarkers and underlying mechanisms using pre-diagnostic plasma proteomics.

Materials And Methods: Among 48,851 UK Biobank participants, 165 were diagnosed with kidney cancer, and 2,911 plasma proteins were analyzed.

Predicting binding affinities of liquid crystal monomers: An activity cliffs-driven multidimensional feature fusion model.

Liquid crystal monomers (LCMs) have emerged as novel endocrine disrupting chemicals that affect the growth, development, and metabolism of organisms by binding to nuclear hormone receptors (NHRs). However, the studies on the impact of LCMs' molecular features on their binding affinities remain limited. In this study, considering the challenge of activity cliffs in linear quantitative structure-activity relationship modeling, a multidimensional feature fusion model was developed to predict the binding affinities of 1173 LCMs to 15 NHRs.