Redefining the Tea Green Leafhopper: Matsuda (Hemiptera: Cicadellidae) as a Vital Asset in Premium Tea Production.

This review explores the evolving role of the tea green leafhopper, , in the tea industry, transitioning from a recognized pest to a significant enhancer of tea quality. Recent research highlights how its feeding behavior stimulates the production of desirable secondary metabolites, thereby improving the flavor profiles and market value of premium teas, particularly varieties like Taiwan's "Oriental Beauty". As consumer demand for unique and artisanal teas rises, the economic benefits associated with are becoming increasingly evident, prompting farmers to adopt sustainable agricultural practices that often involve reduced pesticide use.

Real-time web-based assessment of total population risk of future emergency department utilization: statewide prospective active case finding study.

Background: An easily accessible real-time Web-based utility to assess patient risks of future emergency department (ED) visits can help the health care provider guide the allocation of resources to better manage higher-risk patient populations and thereby reduce unnecessary use of EDs.

Objective: Our main objective was to develop a Health Information Exchange-based, next 6-month ED risk surveillance system in the state of Maine.

Methods: Data on electronic medical record (EMR) encounters integrated by HealthInfoNet (HIN), Maine's Health Information Exchange, were used to develop the Web-based surveillance system for a population ED future 6-month risk prediction.

A data-driven algorithm integrating clinical and laboratory features for the diagnosis and prognosis of necrotizing enterocolitis.

Background: Necrotizing enterocolitis (NEC) is a major source of neonatal morbidity and mortality. Since there is no specific diagnostic test or risk of progression model available for NEC, the diagnosis and outcome prediction of NEC is made on clinical grounds. The objective in this study was to develop and validate new NEC scoring systems for automated staging and prognostic forecasting.

Investigation of maternal environmental exposures in association with self-reported preterm birth.

Identification of maternal environmental factors influencing preterm birth risks is important to understand the reasons for the increase in prematurity since 1990. Here, we utilized a health survey, the US National Health and Nutrition Examination Survey (NHANES) to search for personal environmental factors associated with preterm birth. 201 urine and blood markers of environmental factors, such as allergens, pollutants, and nutrients were assayed in mothers (range of N: 49-724) who answered questions about any children born preterm (delivery <37 weeks).

Integrating multiple 'omics' analyses identifies serological protein biomarkers for preeclampsia.

Background: Preeclampsia (PE) is a pregnancy-related vascular disorder which is the leading cause of maternal morbidity and mortality. We sought to identify novel serological protein markers to diagnose PE with a multi-'omics' based discovery approach.

Methods: Seven previous placental expression studies were combined for a multiplex analysis, and in parallel, two-dimensional gel electrophoresis was performed to compare serum proteomes in PE and control subjects.

Peptidomic Identification of Serum Peptides Diagnosing Preeclampsia.

We sought to identify serological markers capable of diagnosing preeclampsia (PE). We performed serum peptide analysis (liquid chromatography mass spectrometry) of 62 unique samples from 31 PE patients and 31 healthy pregnant controls, with two-thirds used as a training set and the other third as a testing set. Differential serum peptide profiling identified 52 significant serum peptides, and a 19-peptide panel collectively discriminating PE in training sets (n = 21 PE, n = 21 control; specificity = 85.

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

Background: Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation.

Correlation analyses of clinical and molecular findings identify candidate biological pathways in systemic juvenile idiopathic arthritis.

Background: Clinicians have long appreciated the distinct phenotype of systemic juvenile idiopathic arthritis (SJIA) compared to polyarticular juvenile idiopathic arthritis (POLY). We hypothesized that gene expression profiles of peripheral blood mononuclear cells (PBMC) from children with each disease would reveal distinct biological pathways when analyzed for significant associations with elevations in two markers of JIA activity, erythrocyte sedimentation rate (ESR) and number of affected joints (joint count, JC).

Methods: PBMC RNA from SJIA and POLY patients was profiled by kinetic PCR to analyze expression of 181 genes, selected for relevance to immune response pathways.