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Precision management is a critical component of healthcare, where access to accurate and timely data is essential for effective decision-making. In the healthcare industry, precision management involves the use of multiple data sources to understand patient needs and improve health outcomes. Multi-source data interpretation, specifically at the field scale, is becoming increasingly popular as a means to obtain a comprehensive view of patient care. Field scale precision management in healthcare involves the integration of data from various sources, including electronic health records, patient-generated data, and social determinants of health. Through the use of advanced analytics and machine learning algorithms, this data can be processed and interpreted to identify patterns, trends, and insights that can help healthcare providers make more informed decisions. The application of multi-source data interpretation in healthcare is particularly important because it allows for a more holistic view of patient health, taking into account factors beyond traditional medical metrics. For example, social determinants of health, such as access to healthy food and safe housing, can have a significant impact on patient health outcomes, and these factors can be identified through the analysis of non-medical data sources. Overall, the use of multi-source data interpretation for field scale precision management in healthcare has the potential to significantly improve patient outcomes by providing healthcare providers with a more complete understanding of patient needs and circumstances. With advances in technology and analytics, healthcare providers can better harness the power of data to optimize patient care and improve health outcomes at scale. [ABSTRACT FROM AUTHOR]

Elevated lipoprotein (a) [Lp(a)] and coronary artery disease (CAD) risk has been renewed interested in recent years. However, the association between Lp(a) and acute myocardial infarction (AMI) risk in patients with normal low-density lipoprotein cholesterol (LDL-C) levels has yet to been established. A hospital-based observational study including 558 AMI patients and 1959 controls was conducted. Lp(a) level was significantly higher in AMI patients with normal LDL-C levels than that in non-CAD group (median: 134.5 mg/l vs 108 mg/l, P<0.001). According to Lp(a) quartiles (Q1, <51 mg/l; Q2, 51–108 mg/l; Q3, 108–215 mg/l; Q4, ≥215 mg/l), the incidence of AMI increased with the elevated Lp(a) quartiles (P<0.001 and P for trend<0.001). Logistic regression analysis suggested that patients with Q3 and Q4 of Lp(a) values had 1.666 (95%CI = 1.230–2.257, P<0.001) and 1.769 (95%CI = 1.305–2.398, P< 0.001) folds of AMI risk compared with patients with Q1, after adjusting for traditional confounders. Subgroup analyses stratified by gender and age showed that the association only existed in male and late-onset subgroups. In addition, we analyzed the association of Lp(a) with AMI risk in different cut-off values (cut-off 1 = 170 mg/l, cut-off 2 = 300 mg/l). A total of 873 (34.68%) and 432 (17.16%) participants were measured to have higher Lp(a) levels according to cut-off 1 and cut-off 2, respectively. Participants with high Lp(a) levels had 1.418- (cut-off1, 95%CI = 1.150–1.748, P<0.001) and 1.521- (cut-off 2, 95%CI = 1.179–1.963, P< 0.001) folds of AMI risk compared with patients with low Lp(a) levels. The present large-scale study revealed that elevated Lp(a) levels were associated with increased AMI risk in Chinese population with normal LDL-C levels. [ABSTRACT FROM AUTHOR]

The WPI-NaCas-GLY antimicrobial film takes full advantage of the controlled release of active or antimicrobial agents as well as demonstrates a great potential for functioning as an alternative biodegradable polymer in practical applications. The moisture sorption kinetics of the film as an important carrier of active agents was investigated at various relative humidities (RH). The results indicated that the moisture sorption characterization and procedure of this film can be described well by the empirical Peleg model with higher confidence and concordance. The model could predict the film's moisture content at any time (Mt), the time to reach any given level of R (tR), the equilibrium moisture at any RH condition (Me), and isotherm trend based upon experimental data and modeled constants k1, k2, a, b, c, and d without giving consideration to their physical meaning. The water vapor transmission rate of the WPI-NaCas-GLY antimicrobial film increased exponentially with increasing RH due to its hydrophilicity, which was primarily caused by the presence of glycerol in a higher content. The results also suggested that aw predominately affects the film's Me values compared with the temperature factor by fixed nonlinear multiple regression analyses. [ABSTRACT FROM AUTHOR]

Background Studies had investigated the relationships between endothelial lipase (EL) 584C/T polymorphism and high density lipoprotein cholesterol (HDL-C) level and coronary heart disease (CHD), but the results were controversial. To investigate a more authentic associations between EL 584C/T polymorphism and HDL-C level, and the risk of CHD, we performed this meta-analysis. Methods We searched electric databases for all articles on the associations between EL 584 C/T polymorphism and HDL-C level, and CHD risk. Odds ratios (ORs) with 95% confidence interval (CI) were used to evaluate the strength of the association between the EL 584 C/T polymorphism and the CHD susceptibility. The pooled standardized mean difference (SMD) with 95% CI was used for the meta-analysis of EL 584C/T polymorphism and HDL-C level. Begg's funnel plots and Egger's test were used to examine the publication bias. Results For CHD association, the pooled OR was 0.829 (95% CI: 0.701-0.980, P = 0.028) for the dominant model and 0.882 (95% CI: 0.779-0.999, P = 0.049) for the allelic model. By metaregression analysis, we found that only total sample size could influence the initial heterogeneity. When the subgroup analysis was carried out, we found that the protective effect only existed in the subgroups of relatively small sample size. Sensitivity analyses indicated that Tang's study influenced the overall results significantly. We calculated the pooled ORs again after excluding Tang's study and found the association between EL 584C/T polymorphism and the risk of CHD was not significant for any genetic model. For HDL-C level association, the carriers of 584 T allele had a higher HDL-C level than the noncarriers. The pooled SMD was 0.399 (95% CI: 0.094-0.704, P = 0.010). When the studies were stratified by ethnicity and total sample size, the positive effects existed in the Caucasians and in subgroups of larger sample size. No significant publication bias was found in the present meta-analysis. Conclusions The results of the present meta-analysis suggest that the carriers of EL 584 T allele have a higher HDL-C level in Caucasian populations. Whereas, it might not be a protective factor for CHD. [ABSTRACT FROM AUTHOR]

A nanogel combined with a molecularly imprinted polymer (MIP-nanogel) receptor was prepared using the specificity determinant as a template in aqueous media. The artificial receptor can serve as the selective recognition element for angiotensins I and II and a novel way to control hypertension was investigated. [ABSTRACT FROM AUTHOR]

OBJECTIVE--We have previously shown that serum insulin levels decrease threefold and blood glucose levels remain normal in mice fed a leucine-deficient diet, suggesting increased insulin sensitivity. The goal of the current study is to investigate this possibility and elucidate the underlying cellular mechanisms. RESEARCH DESIGN AND METHODS--Changes in metabolic parameters and expression of genes and proteins involved in regulation of insulin sensitivity were analyzed in mice, human HepG2 cells, and mouse primary hepatocytes under leucine deprivation. RESULTS--We show that leucine deprivation improves hepatic insulin sensitivity by sequentially activating general control nonderepressible (GCN)2 and decreasing mammalian target of rapamycin/S6K1 signaling. In addition, we show that activation of AMP-activated protein kinase also contributes to leucine deprivation-increased hepatic insulin sensitivity. Finally, we show that leucine deprivation improves insulin sensitivity under insulin-resistant conditions. CONCLUSIONS--This study describes mechanisms underlying increased hepatic insulin sensitivity under leucine deprivation. Furthermore, we demonstrate a novel function for GCN2 in the regulation of insulin sensitivity. These observations provide a rationale for short-term dietary restriction of leucine for the treatment of insulin resistance and associated metabolic diseases. [ABSTRACT FROM AUTHOR]

Activating transcription factor 4 (ATF4) has been shown to play key roles in many physiological processes. There are no reports, however, demonstrating a direct link between ATF4 and lipid metabolism. We noticed that Atf4-deficient mice are lean, suggesting a possible role for ATF4 in regulating lipid metabolism. The goal of our current study is to investigate the involvement of ATF4 in lipid metabolism and elucidate the underlying mechanisms. Studies using Atf4-deficient mice revealed increased energy expenditure, as measured by oxygen consumption. These mice also showed increases in lipolysis, expression of uncoupling protein 2 (UCP2) and β-oxidation genes and decreases in expression of lipogenic genes in white adipose tissue (WAT), suggesting increased utilization and decreased synthesis of fatty acids, respectively. Expression of UCP1, 2 and 3 was also increased in brown adipose tissue (BAT), suggesting increased thermogenesis. The effect of ATF4 deletion on expression of UCPs in BAT suggests that increased thermogenesis may underlie increased energy expenditure. Thus, our study identifies a possible new function for ATF4 in regulating lipid metabolism and thermogenesis. [ABSTRACT FROM AUTHOR]

OBJECTIVE--White adipose tissue (WAT) and brown adipose tissue (BAT) play distinct roles in adaptation to changes in nutrient availability, with WAT serving as an energy store and BAT regulating thermogenesis. We previously showed that mice maintained on a leucine-deficient diet unexpectedly experienced a dramatic reduction in abdominal fat mass. The cellular mechanisms responsible for this loss, however, are unclear. The goal of current study is to investigate possible mechanisms. RESEARCH DESIGN AND METHODS--Male C57BL/6J mice were fed either control, leucine-deficient, or pair-fed diets for 7 days. Changes in metabolic parameters and expression of genes and proteins related to lipid metabolism were analyzed in WAT and BAT. RESULTS--We found that leucine deprivation for 7 days increases oxygen consumption, suggesting increased energy expenditure. We also observed increases in lipolysis and expression of β-oxidation genes and decreases in expression of lipogenic genes and activity of fatty acid synthase in WAT, consistent with increased use and decreased synthesis of fatty acids, respectively. Furthermore, we observed that leucine deprivation increases expression of uncoupling protein (UCP)-1 in BAT, suggesting increased thermogenesis. CONCLUSIONS--We show for the first time that elimination of dietary leucine produces significant metabolic changes in WAT and BAT. The effect of leucine deprivation on UCP1 expression is a novel and unexpected observation and suggests that the observed increase in energy expenditure may reflect an increase in thermogenesis in BAT. Further investigation will be required to determine the relative contribution of UCP1 upregulation and thermogenesis in BAT to leucine deprivation-stimulated fat loss. [ABSTRACT FROM AUTHOR]

In this paper the recognition of Small Cell Carcinoma (SCC) is studied. For each type we select 128 samples for training, and randomly measure 200 cells in each sample. We introduce multi‐scale morphology based on centroid coordinates to extract the boundaries of nuclei and obtain feature images of nuclei. The features of lung cancer cells are described by morphological and colorimetrical parameters, which is valuable to recognize SCC. Then the architecture of self‐organizing feature mapping (SOFM) neural network is studied for recognition of SCC. The weights of the network are adjusted by self‐organizing competition, and finally inputted patterns are classified. This algorithm has the advantage of parallelism and fast‐convergence, and may simplify the analysis of SCC. Clinical experiment results show that the correctness ratio of this system may reach 95.3% while recognizing lung cancer cell types. Our work is significant to the pathological researches of lung cancer, assistant clinic diagnosis, and assessment of therapeutic effects. Meanwhile a software system named as SCC.LUNG is established for automatic analysis. [ABSTRACT FROM AUTHOR]