A Systematic Review of Mechanisms, Incidence, and Management of Trastuzumab Deruxtecan Induced ILD/Pneumonitis in Solid Tumors.

Trastuzumab deruxtecan (T-DXd) has been approved to treat various tumors. While most adverse events (AEs) associated with T-DXd are manageable, interstitial lung disease (ILD)/pneumonitis is a notable AE of special concern. This review describes the incidence, severity, and management of T-DXd-induced ILD/pneumonitis across different tumors.

Bidirectional Mendelian randomization and mediation analysis of million-scale data reveal causal relationships between thyroid-related phenotypes, smoking, and lung cancer.

Emerging evidence highlights the role of thyroid hormones in cancer, though findings are controversial. Research on thyroid-related traits in lung carcinogenesis is limited. Using UK Biobank data, we conducted bidirectional Mendelian randomization (MR) to assess causal links between lung cancer risk and thyroid dysfunction (hypothyroidism/hyperthyroidism) or function traits (free thyroxine [FT4], normal-range TSH).

Identification of a novel forkhead transcription factor MtFKH1 for cellulase and xylanase gene expression in Myceliophthora thermophila (ATCC 42464).

Myceliophthora thermophila is a thermophilic fungus, known to produce industrially important enzymes in biorefineries. The mechanism underlying cellulase and xylanase expression in filamentous fungi is a complex regulatory network controlled by numerous transcription factors (TFs). These TFs in M.

A nomogram for predicting prognosis for young cervical neuroendocrine carcinoma: A SEER-based study and external validation.

Background: Neuroendocrine carcinoma of the cervix (NECC) is a rare and highly aggressive subtype of cervical carcinomas with poor prognosis. NECC tends to occur in young age which could severely impair mental and physical health of young patients. Therefore, this study aims to develop an individualized prognostic nomogram for young NECC patients.

NLRP3 inflammasome in health and disease (Review).

Activation of inflammasomes is the activation of inflammation‑related caspase mediated by the assembly signal of multi‑protein complex and the maturity of inflammatory factors, such as IL‑1β and IL‑18. Among them, the Nod‑like receptor family pyrin domain containing 3 (NLRP3) inflammasome is the most thoroughly studied type of inflammatory corpuscle at present, which is involved in the occurrence and development of numerous human diseases. Therefore, targeting the NLRP3 inflammasome has become the focus of drug development for related diseases.

Developing novel Lin28 inhibitors by computer aided drug design.

Lin28 is a key regulator of cancer stem cell gene network that promotes therapy-resistant tumor progression in various tumors. However, no Lin28 inhibitor has been approved to treat cancer patients, urging exploration of novel compounds as candidates to be tested for clinical trials. In this contribution, we applied computer-aided drug design (CADD) in combination with quantitative biochemical and biological assays.

First Report of Causing Leaf Blight on in China.

Peacock plant (Calathea orbifolia (Linden) H.A.Kenn.

Evaluation of UHT milk spoilage caused by proteases from psychrophilic bacteria based on peptidomics.

The quality issues of ultra-high-temperature (UHT) milk, such as protein hydrolysis and aging gels throughout shelf life, are caused by proteases from psychrophilic bacteria. However, existing enzyme activity detection techniques have low sensitivity and cannot accomplish the detection of product deterioration caused by low enzyme activity. In this study, an attempt was made to analyze the relationship between enzymatically cleaved peptides and product quality using peptidomics techniques.

Real-world comparison of palbociclib, abemaciclib, and dalpiciclib as first-line treatments for Chinese HR+/HER2-metastatic breast cancer patients: a multicenter study (YOUNGBC-28).

Background: In recent years, the combination of CDK4/6 inhibitors (CDK4/6i) and endocrine therapy (ET) has emerged as the standard first-line treatment for hormone receptor positive (HR+) and human epidermal growth factor receptor 2 negative (HER2-) metastatic breast cancer (MBC) patients. However, the comparison between the efficacy of CDK4/6i has been poorly explored before. Moreover, it remains unclear about the optimal choice of CDK4/6i in the first-line treatment for HR+/HER2- MBC patients in Asian, especially Chinese populations.

Targeting resident astrocytes attenuates neuropathic pain after spinal cord injury.

Astrocytes derive from different lineages and play a critical role in neuropathic pain after spinal cord injury (SCI). Whether selectively eliminating these main origins of astrocytes in lumbar enlargement could attenuate SCI-induced neuropathic pain remains unclear. Through transgenic mice injected with an adeno-associated virus vector and diphtheria toxin, astrocytes in lumbar enlargement were lineage traced, targeted, and selectively eliminated.

Inetetamab for injection in combination with vinorelbine weekly or every three weeks in HER2-positive metastatic breast cancer: A multicenter, randomized, phase II clinical trial.

Objective: We aimed to investigate the pharmacokinetics, safety, efficacy, and immunogenicity of different dosing regimens (weekly and every three weeks) of inetetamab in combination with vinorelbine in human epidermal growth factor receptor 2 (HER2)+ patients with metastatic breast cancer who had received one or more chemotherapy regimens.

Methods: HER2+ patients with metastatic breast cancer who had received one or more chemotherapy regimens were included. Eligible patients received inetetamab administered weekly or every three weeks in combination with vinorelbine injection chemotherapy.

Development and Validation of a Risk Prediction Model for Pseudarthrosis Following Transforaminal Lumbar Interbody Fusion: A Retrospective Analysis.

Background: Pseudarthrosis is a common complication of transforaminal lumbar interbody fusion (TLIF) that can affect the long-term prognosis and increase revision surgery risk. Therefore, it is crucial to investigate the risk factors associated with pseudarthrosis and develop a predictive model.

Methods: Patients who underwent TLIF at a single hospital between January 2019 and June 2021 were included.

Invited Review for 20th Anniversary Special Issue of PLRev "AI for Mechanomedicine".

Mechanomedicine is an interdisciplinary field that combines different areas including biomechanics, mechanobiology, and clinical applications like mechanodiagnosis and mechanotherapy. The emergence of artificial intelligence (AI) has revolutionized mechanomedicine, providing advanced tools to analyze the complex interactions between mechanics and biology. This review explores how AI impacts mechanomedicine across four key aspects, i.

Evaluating the association between immunological proteins and common intestinal diseases using a bidirectional two-sample Mendelian randomization study.

Dysregulation of intestinal homeostasis, characterized by imbalanced immunological proteins, contributes to the pathogenesis of common intestinal diseases, e.g., irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), and colorectal cancer (CRC).

Beyond clinical trials: CDK4/6 inhibitor efficacy predictors and nomogram model from real-world evidence in metastatic breast cancer.

Background: CDK4/6 inhibitors (CDK4/6i) have shown promising results in the treatment of hormone receptor-positive (HR+) metastatic breast cancer (MBC) when combined with endocrine therapy (ET). It is crucial to evaluate the actual effectiveness and safety of CDK4/6i in clinical practice, as well as to analyze the factors that can predict their outcomes.

Methods: Patients with HR+ MBC who received CDK4/6i-based therapy between May 2016 and May 2023 at Hunan Cancer Hospital were evaluated for progression-free survival (PFS).

Personalized forward collision warning model with learning from human preferences.

The Forward Collision Warning (FCW) system has been widely equipped on vehicles to reduce rear-end crashes, which are considered the most common type of crash. However, existing FCW systems have the problem of low response rates, which restrict their safety improvement effects. This study aims to address this issue by building personalized FCW models based on human risk preferences.

Learning explainable task-relevant state representation for model-free deep reinforcement learning.

State representations considerably accelerate learning speed and improve data efficiency for deep reinforcement learning (DRL), especially for visual tasks. Task-relevant state representations could focus on features relevant to the task, filter out irrelevant elements, and thus further improve performance. However, task-relevant representations are typically obtained through model-based DRL methods, which involves the challenging task of learning a transition function.