The impact of artificial intelligence on sustainable development performance of public healthcare supply chain-an empirical study based on listed Chinese pharmaceutical companies.

With the continuous deepening of the digital transformation of the public healthcare supply chain, as the next step of digitalization, intelligent transformation has received much attention, especially how artificial intelligence can improve the sustainable development performance of the supply chain needs to be studied. In order to fill this gap, this paper establishes a research model of artificial intelligence, green supply chain management practice, industry competition and sustainable development performance of public healthcare supply chain. Taking Chinese listed pharmaceutical enterprises as research objects, this paper conducts empirical analysis on 301 valid questionnaires through questionnaire survey and structural equation model.

Neurite orientation dispersion and density imaging in myelin oligodendrocyte glycoprotein antibody-associated disease and neuromyelitis optica spectrum disorders.

Background: Aquaporin-4 antibody positive (AQP4+) neuromyelitis optica spectrum disorders (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) are two distinct antibody-mediated neuroinflammatory diseases. Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI) are advanced diffusion-weighted MRI models providing quantitative metrics sensitive to cerebral microstructural changes. This study aims to differentiate brain tissue damage in NMOSD and MOGAD from controls and investigate its association with clinical disability, using NODDI and DTI-derived measures, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity.

A quantitative multi-parameter mapping protocol standardized for clinical research in multiple sclerosis.

Quantitative magnetic resonance imaging (qMRI) involves mapping microstructure in standardized units sensitive to histological properties and supplements conventional MRI, which relies on contrast weighted images where intensities have no biophysical meaning. While measuring tissue properties such as myelin, iron or water content is desired in a disease context, qMRI changes may typically reflect mixed influences from aging or pre-clinical degeneration. We used a fast multi-parameter mapping (MPM) protocol for clinical routine at 3T to reconstruct whole-brain quantitative maps of magnetization transfer saturation (MT), proton density (PD), longitudinal (R1), and transverse relaxation rate (R2*) with 1.

Coordination strategy and contract design of platform supply chain for large-scale sports events with low carbon preference.

The organization of sports events, while generating economic benefits, inevitably imposes significant environmental pressures. Conducting green and low-carbon sports events have become a global consensus. In addressing the carbon emissions and benefit coordination issues on the production end of infrastructure construction for large-scale sports events, we considers the significant role of digital platforms in the industry's low-carbon transformation and upgrade, and innovatively incorporates platforms as decision-making entities and investigates the equilibrium strategies for low-carbon cooperation under three different power structures: one led by the sports events materials supplier, one by the materials distributor, and one by the integrated service platform.

Smartphone-assisted ratiometric fluorescent sensor for visual detection of chlortetracycline.

The development of a highly selective and sensitive method for detecting chlortetracycline (CTC) is crucial for safeguarding public health and food safety. Herein, a novel ratiometric fluorescence sensor called SiC@ZIF-8@MIP was constructed to specifically recognize and sensitively detect CTC. The sensor has the advantages of fast response speed (7 min), wide linear range (0.

Efficacy and safety of azilsartan medoxomil in the treatment of hypertension: a systematic review and meta-analysis.

Background: Angiotensin II receptor blockers (ARBs) are utilized for the management of hypertension and diabetes. Previous meta-analyses suggested that azilsartan medoxomil (AZL-M) improved blood pressure (BP) reduction, but there were no safety findings or suggestions for patients with hypertension or diabetes.

Methods: We performed an efficacy and safety meta-analysis of randomized controlled trials (RCTs) evaluating AZL-M therapy for reducing BP in patients with hypertension.

Efficacy and safety of nonsteroidal mineralocorticoid receptor antagonists for renal and cardiovascular outcomes in patients with chronic kidney disease: a meta-analysis of randomized clinical trials.

To systematically review the efficacy and safety of nonsteroidal mineralocorticoid receptor antagonists (MRAs) in chronic kidney disease (CKD). We systematically searched six databases to identify randomized controlled trials (RCTs) about nonsteroidal MRAs for CKD, from inception to 22 August 2023. Two reviewers independently screened the retrieved articles, extracted data, and assessed the risk of bias of included RCTs using the Cochrane risk of bias tool.

Application of Patient-Based Real-Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening.

Background: Patient-based real-time quality control (PBRTQC) has gained attention because of its potential to continuously monitor the analytical quality in situations wherein internal quality control (IQC) is less effective. Therefore, we tried to investigate the application of PBRTQC method based on an artificial intelligence monitoring (AI-MA) platform in quality risk monitoring of Down syndrome (DS) serum screening.

Methods: The DS serum screening item determination data and relative IQC data from January 4 to September 7 in 2021 were collected.

Intelligent selection of healthcare supply chain mode - an applied research based on artificial intelligence.

Introduction: Due to the inefficiency and high cost of the current healthcare supply chain mode, in order to adapt to the great changes in the global economy and public health, it is urgent to choose an effective mode for sustainable development of healthcare supply chain. The aim of this paper is to use artificial intelligence systems to make intelligent decisions for healthcare supply chain mode selection.

Methods: Firstly, according to the economic benefits, social benefits and environmental benefits of healthcare supply chain, this paper identifies different healthcare supply chain modes in combination with artificial intelligence technology.

Combining proton exchange rate ( ) MRI with quantitative susceptibility mapping to further stratify the gadolinium-negative multiple sclerosis lesions.

Background: Conventional gadolinium (Gd)-enhanced MRI is currently used for stratifying the lesion activity of multiple sclerosis (MS) despite limited correlation with disability and disease activity. The stratification of MS lesion activity needs further improvement to better support clinics.

Purpose: To investigate if the novel proton exchange rate ( ) MRI combined with quantitative susceptibility mapping (QSM) may help to further stratify non-enhanced (Gd-negative) MS lesions.

Therapeutic strategies for brachial plexus injury.

Brachial plexus avulsion (BPA), a severe acute peripheral nerve injury in adults, results in total loss of the motor function in the upper limb. Although immediate re-implantation surgery is widely performed to repair this lesion, the motor function cannot be fully restored. The main cause is that the growth velocity of axon is extremely slow in order to re-innervate the target muscles before atrophy develops.

MRI features and evolution of autoimmune glial fibrillary acidic protein astrocytopathy: A retrospective cross-sectional and longitudinal study.

Background: Autoimmune glial fibrillary acidic protein astrocytopathy (AGA) is a relatively novel disease. The early diagnosis of this inflammatory central nervous system (CNS) disorder remains challenging.

Objectives: We aimed to explore the imaging manifestations and evolution of AGA to facilitate its successful diagnosis and monitoring.

Community-Based Rehabilitation Promotes the Functional Recovery of Patients After Intracerebral Hemorrhage.

Background: Intracerebral hemorrhage (ICH), a severe disorder with the high death rate, high recurrence rate and high disability rate, affected the quality of human life. Community-based rehabilitation (CBR) helps disabled people at both community and family levels. However, the effect of CBR on the recovery of people after ICH remains unclear.

Deep learning for predicting COVID-19 malignant progression.

As COVID-19 is highly infectious, many patients can simultaneously flood into hospitals for diagnosis and treatment, which has greatly challenged public medical systems. Treatment priority is often determined by the symptom severity based on first assessment. However, clinical observation suggests that some patients with mild symptoms may quickly deteriorate.

Splicing factor SRSF6 mediates pleural fibrosis.

Pleural fibrosis is defined as an excessive deposition of extracellular matrix that results in destruction of the normal pleural tissue architecture and compromised function. Tuberculous pleurisy, asbestos injury, and rheumatoid pleurisy are main causes of pleural fibrosis. Pleural mesothelial cells (PMCs) play a key role in pleural fibrosis.

In Vivo Proton Exchange Rate (k ) MRI for the Characterization of Multiple Sclerosis Lesions in Patients.

Background: Currently available radiological methods do not completely capture the diversity of multiple sclerosis (MS) lesion subtypes. This lack of information hampers the understanding of disease progression and potential treatment stratification. For example, inflammation persists in some lesions after gadolinium (Gd) enhancement resolves.

Temporal lung changes in high-resolution chest computed tomography for coronavirus disease 2019.

Objective: To evaluate temporal lung changes in coronavirus disease 2019 (COVID-19) in high-resolution computed tomography (HRCT) and to determine the appropriate computed tomographic (CT) follow-up time.

Methods: Eighty-six patients with two or more HRCT scans who were diagnosed with COVID-19 were included. The CT score and major CT findings were evaluated.