Review of microplastics and chemical risk posed by plastic packaging on the marine environment to inform the Global Plastics Treaty.

Plastic overproduction and the resulting increase in consumption has made plastic pollution ubiquitous in all ecosystems. Recognizing this, the United Nations (UN) has started negotiations to establish a global treaty to end plastic pollution, especially in the marine environment. The basis of the treaty has been formulated in terms of turning off the tap, signaling the will to prevent plastic pollution at its source.

Artificial intelligence in diabetic retinopathy: Bibliometric analysis.

Background: The use of artificial intelligence in diabetic retinopathy has become a popular research focus in the past decade. However, no scientometric report has provided a systematic overview of this scientific area.

Aims: We utilized a bibliometric approach to identify and analyse the academic literature on artificial intelligence in diabetic retinopathy and explore emerging research trends, key authors, co-authorship networks, institutions, countries, and journals.

Deep Learning for the Diagnosis of Esophageal Cancer in Endoscopic Images: A Systematic Review and Meta-Analysis.

Esophageal cancer, one of the most common cancers with a poor prognosis, is the sixth leading cause of cancer-related mortality worldwide. Early and accurate diagnosis of esophageal cancer, thus, plays a vital role in choosing the appropriate treatment plan for patients and increasing their survival rate. However, an accurate diagnosis of esophageal cancer requires substantial expertise and experience.

Proton Pump Inhibitors Use and the Risk of Pancreatic Cancer: Evidence from Eleven Epidemiological Studies, Comprising 1.5 Million Individuals.

Previous epidemiological studies have shown that proton pump inhibitor (PPI) may modify the risk of pancreatic cancer. We conducted an updated systematic review and meta-analysis of observational studies assessing the effect of PPI on pancreatic cancer. PubMed, Embase, Scopus, and Web of Science were searched for studies published between 1 January 2000, and 1 May 2022.

Increased risk of atrial fibrillation in patients with psoriasis: A meta-analysis of observational studies.

Background: Several epidemiological studies have shown that psoriasis increases the risk of developing atrial fibrillation but evidence of this is still scarce.

Aims: Our objective was to systematically review, synthesise and critique the epidemiological studies that provided information about the relationship between psoriasis and atrial fibrillation risk.

Methods: We searched through PubMed, EMBASE and the bibliographies for articles published between 1 January 2000, and 1 November 2017, that reported on the association between psoriasis and atrial fibrillation.

Artificial Intelligence in Gastric Cancer: Identifying Gastric Cancer Using Endoscopic Images with Convolutional Neural Network.

Gastric cancer (GC) is one of the most newly diagnosed cancers and the fifth leading cause of death globally. Identification of early gastric cancer (EGC) can ensure quick treatment and reduce significant mortality. Therefore, we aimed to conduct a systematic review with a meta-analysis of current literature to evaluate the performance of the CNN model in detecting EGC.

Palearctic passerine migrant declines in African wintering grounds in the Anthropocene (1970-1990 and near future): A conservation assessment using publicly available GIS predictors and machine learning.

The Anthropocene causes many massive and novel impacts, e.g., on migratory birds and their habitats.

Clinical Characteristics and Neonatal Outcomes of Pregnant Patients With COVID-19: A Systematic Review.

Coronavirus disease 2019 (COVID-19) characterized by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created serious concerns about its potential adverse effects. There are limited data on clinical, radiological, and neonatal outcomes of pregnant women with COVID-19 pneumonia. This study aimed to assess clinical manifestations and neonatal outcomes of pregnant women with COVID-19.

Acoustic preadaptation to transmit vocal individuality of savanna nightjars in noisy urban environments.

As urbanization has expanded dramatically, the impacts of urban noise on wildlife have drawn increasing attention. However, previous studies have focused primarily on diurnal songbirds and much less on nocturnal nonpasserines such as nightjars. The savanna nightjar has recently successfully colonized urban areas in Taiwan.

Determinants of establishment success: Comparing alien and native freshwater fishes in Taiwan.

Many parts of Asia, including Taiwan, have suffered severely from freshwater fish invasions. However, few studies using an assemblage approach have been conducted in the region so far that would help to prioritize suitable preventive actions. In this study, we focused on the invasion process from the import stage to the establishment stage, and defined establishment success as the success during this predefined process.

Artificial Intelligence in Ophthalmology: A Meta-Analysis of Deep Learning Models for Retinal Vessels Segmentation.

Background And Objective: Accurate retinal vessel segmentation is often considered to be a reliable biomarker of diagnosis and screening of various diseases, including cardiovascular diseases, diabetic, and ophthalmologic diseases. Recently, deep learning (DL) algorithms have demonstrated high performance in segmenting retinal images that may enable fast and lifesaving diagnoses. To our knowledge, there is no systematic review of the current work in this research area.

Statin Use and the Risk of Hepatocellular Carcinoma: A Meta-Analysis of Observational Studies.

: Statins are the first-line medication to treating hypercholesterolemia. Several studies have investigated the impact of statins on the risk of hepatocellular carcinoma (HCC). However, the extent to which statins may prevent HCC remains uncertain.

Association Between Atrial Fibrillation and Dementia: A Meta-Analysis.

A potential evidence from previous epidemiological studies remains conflicting findings regarding the association between atrial fibrillation (AF) and dementia risk. We, therefore, carried out a meta-analysis of relevant studies to investigate the magnitude of the association between AF and dementia risk. We performed a systematic literature search of PubMed, EMBASE, and Google Scholar for potential studies between January 1, 1990, and December 31, 2018, with no restriction on the publication language.

Association between Use of Statin and Risk of Dementia: A Meta-Analysis of Observational Studies.

Background And Aims: The impact of statin on dementia risk reduction has been a subject of debate over the last decade, but the evidence remains inconclusive. Therefore, we performed a meta-analysis of relevant observational studies to quantify the magnitude of the association between statin therapy and the risk of dementia.

Methods: We systematically searched for relevant studies published from January 2000 to March 2018 using EMBASE, Google, Google Scholar, PubMed, Scopus, and Web of Science.

Prediction of sepsis patients using machine learning approach: A meta-analysis.

Study Objective: Sepsis is a common and major health crisis in hospitals globally. An innovative and feasible tool for predicting sepsis remains elusive. However, early and accurate prediction of sepsis could help physicians with proper treatments and minimize the diagnostic uncertainty.

Risk of Hemorrhagic Stroke in Patients Exposed to Nonsteroidal Anti-Inflammatory Drugs: A Meta-Analysis of Observational Studies.

Background And Aim: Nonsteroidal anti-inflammatory drugs (NSAIDs) are one of the most common pain relief medications, but the risk of hemorrhagic stroke in patients taking these medications is unclear. In this study, our aim was to systematically review, synthesize, and critique the epidemiological studies that evaluate the association between NSAIDs and hemorrhagic stroke risk. We therefore assessed the current state of knowledge, filling the gaps in our existing concern, and make a recommendation for future research.

Encephalitis induced by a newly discovered ruminant rhadinovirus in a free-living Formosan sambar deer (Rusa unicolor swinhoei).

We documented a case of a free-living Formosan sambar deer (Rusa unicolor swinhoei) infected with a newly discovered ruminant Rhadinovirus (RuRv). Non-purulent encephalitis was the primary histological lesion of the sambar deer. We conducted nested PCR to screen for herpesvirus using generic primers targeting the DNA polymerase gene.

Exploring the Association between Statin Use and the Risk of Parkinson's Disease: A Meta-Analysis of Observational Studies.

Background: Parkinson's disease (PD) is a progressive disorder of the central nervous system. The prevalence of PD varies considerably by age group; it has a higher prevalence in patients aged 60 years and more. Several studies have shown that statin, a cholesterol-lowering medication, reduces the risk of developing PD, but evidence for this is so far inconclusive.

Gender-based personalized pharmacotherapy: a systematic review.

Purpose: In general, male and female are prescribed the same amount of dosage even if most of the cases female required less dosage than male. Physicians are often facing problem on appropriate drug dosing, efficient treatment, and drug safety for a female in general. To identify and synthesize evidence about the effectiveness of gender-based therapy; provide the information to patients, providers, and health system intervention to ensure safety treatment; and minimize adverse effects.

Contrasting determinants for the introduction and establishment success of exotic birds in Taiwan using decision trees models.

Background: Biological invasions have become a major threat to biodiversity, and identifying determinants underlying success at different stages of the invasion process is essential for both prevention management and testing ecological theories. To investigate variables associated with different stages of the invasion process in a local region such as Taiwan, potential problems using traditional parametric analyses include too many variables of different data types (nominal, ordinal, and interval) and a relatively small data set with too many missing values.

Methods: We therefore used five decision tree models instead and compared their performance.

Biodiversity and health: Lessons and recommendations from an interdisciplinary conference to advise Southeast Asian research, society and policy.

Southeast Asia is an economic, biodiverse, cultural and disease hotspot. Due to rapid socio-economic and environmental changes, the role of biodiversity and ecosystems for human health ought to be examined and communicated to decision-makers and the public. We therefore summarized the lessons and recommendations from an interdisciplinary conference convened in Cambodia in 2014 to advise Southeast Asian societies on current research efforts, future research needs, and to provide suggestions for improved education, training and science-policy interactions.