Amivantamab Plus Lazertinib in Patients With EGFR-mutant Non-small Cell Lung Cancer (NSCLC) After Progression on Osimertinib and Platinum-based Chemotherapy: Results From CHRYSALIS-2 Cohort A.

Introduction: Treatment options for patients with epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) with disease progression on/after osimertinib and platinum-based chemotherapy are limited.

Methods: CHRYSALIS-2 Cohort A evaluated amivantamab+lazertinib in patients with EGFR exon 19 deletion- or L858R-mutated NSCLC with disease progression on/after osimertinib and platinum-based chemotherapy. Primary endpoint was investigator-assessed objective response rate (ORR).

Innovative machine learning approaches for indoor air temperature forecasting in smart infrastructure.

Efficient energy management and maintaining an optimal indoor climate in buildings are critical tasks in today's world. This paper presents an innovative approach to surrogate modeling for predicting indoor air temperature (IAT) in buildings, leveraging advanced machine learning techniques. At the core of this study is the application of Long Short-Term Memory (LSTM) networks for time-series modeling, which significantly enhances the capture of temporal dependencies in temperature predictions.

Ultrasound Imaging of the Superficial and Deep Fasciae Thickness of Upper Limbs in Lymphedema Patients Versus Healthy Subjects.

Background/objectives: Lymphedema, a common source of disability among oncology patients, necessitates continuous targeted rehabilitation. Recent studies have revealed the role of connective tissue in this pathology; however, despite existing research on ultrasound (US) use in lymphedema, no studies have specifically addressed the use of ultrasound to assess fasciae in patients with lymphedema. This study aims to provide a more objective characterization of typical US alterations in these patients by quantifying the thickness of superficial and deep fasciae and comparing them with those of healthy volunteers.

Innate immune response in COVID-19: single-cell multi-omics profile of NK lymphocytes in a clinical case series.

Background: COVID-19 pandemic caused by the Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) represents the biggest global health emergency in recent decades. The host immune response to SARS-CoV-2 seems to play a key role in disease pathogenesis and clinical manifestations, with Natural Killer (NK) lymphocytes being among the targets of virus-induced regulation.

Methods: This study performed a single-cell multi-omics analysis of transcripts and proteins of NK lymphocytes in COVID-19 patients, for the characterization of the innate immunological response to infection.