Exploring factors affecting patient satisfaction in online healthcare: A machine learning approach grounded in empathy theory.

Objective: Empathy between doctors and patients is crucial in enhancing patient satisfaction with medical consultations. This study, grounded in empathy theory, employs natural language processing and machine learning algorithms to explore the factors influencing patient satisfaction in online healthcare services, particularly the impact of doctor-patient empathy.

Methods: Utilizing the three dimensions of the Jefferson Scale of Physician Empathy, seven variables were extracted from patient-doctor dialogs as independent variables, with patient satisfaction as the dependent variable.

Aggregation-Induced Emission CN-Based Nanoparticles to Alleviate Hypoxic Liver Fibrosis via Triggering HSC Ferroptosis and Enhancing Photodynamic Therapy.

Hypoxia can lead to liver fibrosis and severely limits the efficacy of photodynamic therapy (PDT). Herein, carbon nitride (CN)-based hybrid nanoparticles (NPs) VPSGCNs@TSI for light-driven water splitting were utilized to solve this problem. CNs were doped with selenide glucose (Se-glu) to enhance their red/NIR region absorption.

Health information needs and feedback of users in the online TCM community.

To improve the information service quality of the online Traditional Chinese Medicine (TCM) community, this study investigated users' information needs, feedback and the relationship between them. Using qualitative content analysis, the basic characteristics of users' needs were obtained. Logistic regression was used to explore the impact of different need characteristics of feedback.

Carbon Nitride-Based siRNA Vectors with Self-Produced O Effects for Targeting Combination Therapy of Liver Fibrosis via HIF-1α-Mediated TGF-β1/Smad Pathway.

Hypoxia is an important feature, which can upregulate the hypoxia-inducible factor-1α (HIF-1α) expression and promote the activation of hepatic stellate cells (HSCs), leading to liver fibrosis. Currently, effective treatment for liver fibrosis is extremely lacking. Herein, a safe and effective method is established to downregulate the expression of HIF-1α in HSCs via targeted delivery of VA-PEG-modified CNs-based nanosheets-encapsulated (VA-PEG-CN@GQDs) HIF-1α small interfering RNA (HIF-1α-siRNA).

Online dialogue with medical professionals: An empirical study of an online "Ask the Doctor" platform.

Background: Accessing medical resources has been a challenging issue in China, particularly for people who do not live in big cities. Online "Ask the doctor" (AtD) services are gaining popularity rapidly. On AtDs, patients or their caregivers can ask questions to medical professionals and receive medical advice without going through the hassles of visiting local hospitals or doctors' offices.

Identifying the predictors of severe psychological distress by auto-machine learning methods.

Social stress in daily life and the COVID-19 pandemic have greatly impacted the mental health of the population. Early detection of a predisposition to severe psychological distress is essential for timely interventions. This paper analyzed 4036 samples participating in the 2019-2020 National Health Information Trends Survey (HINTS) and identified 57 candidate predictors of severe psychological distress based on univariate chi-square and -test analyses.

Development of novel hydrazidoarylaminopyrimidine-based BTK/FLT3 dual inhibitors with potent in vivo anti-hematological malignancies effects.

Computer-aided drug design and structure-based drug design techniques were used to find 18 novel hydrazidoarylaminopyrimidine-based BTK/FLT3 dual inhibitors. At 1 μM and 0.05 μM, the majority of the target compounds inhibited BTK and FLT3 by more than 80%, respectively.

A new flavonoid glycoside from (Stokes) F.A. Barkley.

(Stokes) F.A. Barkley, also called 'Qishu', is a shrub belonging to the Anacardiaceae family and producing lacquer.