Seismicity Models of Moderate Earthquakes in Kanto, Japan Utilizing Multiple Predictive Parameters

Abstract Background The neonatal period can be associated with a multitude of medical and social problems. Little is known about the reasons that lead to neonatal readmissions in a pediatric hospital and their individual outcomes. Objective To record the diagnosis of neonatal admissions in a pediatric hospital after discharge from a maternity unit. Predictive parameters are to be identified and a possible trend over the years is to be examined. Methods The medical history of newborns admitted to a pediatric hospital in the Rhine-Main area from 01/01/2004 to 31/12/2013 was retrospectively analyzed based on provided medical files. Results The data of 2851 newborns was recorded. 72% of the patients were delivered by vaginal birth. During the period under examination, there was a certain fluctuation although no significant trend in the number of admissions per year (p=0.062). The most frequent primary diagnoses were jaundice (27%), newborn infection (12.4%), and feeding problems (12.3%). Exclusively breastfed newborns had fewer feeding problems than newborns with a mixed or purely formula diets (p < 0.001). Conclusions The results of this study showed that the hospital readmissions of newborns throughout the years did not increase. Unfortunately, owing to the retrospective character of the study, it is not possible to make a clear statement as to whether hospitalization can be prevented with more intensive preventative measures. A prospective study on this matter is being planned.

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An insight into predictive parameters of tablet capping by machine learning and multivariate tools

International Journal of Pharmaceutics ◽

10.1016/j.ijpharm.2021.120439 ◽

2021 ◽

pp. 120439

Author(s):

Shubhajit Paul ◽

Yukteshwar Baranwal ◽

Yin-Chao Tseng

Keyword(s):

Machine Learning ◽

Predictive Parameters ◽

Insight Into

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Differential Association of Uncoupling Protein 2 Polymorphisms with Pattern Identification among Korean Stroke Patients: A Diagnostic System in Traditional Korean Medicine

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2012/532078 ◽

2012 ◽

Vol 2012 ◽

pp. 1-9 ◽

Cited By ~ 2

Author(s):

Ji Hye Lim ◽

Mi Mi Ko ◽

Hoyoung Lee ◽

Ho Yeon Go ◽

Tae-Woong Moon ◽

...

Keyword(s):

Uncoupling Protein ◽

Mitochondrial Protein ◽

Diagnostic System ◽

Cell Types ◽

Pattern Identification ◽

Uncoupling Protein 2 ◽

Stroke Patients ◽

Standard Pattern ◽

Yin Deficiency ◽

Predictive Parameters

Uncoupling protein 2 (UCP2), a mitochondrial protein present in many organs and cell types, is known to dissipate the proton gradient formed by the electron transport chain. Its function is correlated with predictive parameters, such as obesity, diabetes, and metabolic syndromes. We analyzed the distribution of UCP2 polymorphisms in stroke patients diagnosed with one of the following four stroke subtypes based on the TKM standard pattern identification (PI): Qi-deficiency (QD), Dampness and Phlegm (D&P), Yin-deficiency (YD), and Fire and Heat (F&D). We studied a total of 1,786 stroke patients (397/QD, 645/D&P, 223/YD, and 522/F&D, 586/normal). Genotyping for the G-1957A, G-866A and A55V UCP2 polymorphisms was performed using the TaqMan. G-866A and A55V were significantly associated with the D&P and H&F subtypes. The frequency of subjects with the A allele of G-866A was significantly lower than the frequency of subjects with the GG type. The A55V polymorphism was also shown similar effect with G-866A in the dominant model. In contrast, no SNPs were shown to be associated with the QD or YD subtypes in this study. These results showed that the G-866A and A55V UCP2 polymorphisms may be genetic factors for specific PI types among Korean stroke patients.

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