Atherogenesis and dyslipidemia increase the risk of cardiovascular disease, which is the leading cause of death in developed countries. While blood lipid levels have been studied as disease predictors, their accuracy in predicting cardiovascular risk is limited due to its high interindividual and interpopulation variability. The lipid ratios: atherogenic index of plasma (AIP=log TG/HDL-C) and the Castelli risk index 2 (CI2=LDL-C/HDL-C) have been proposed as better predictors of cardiovascular risk, but the genetic variability associated to these ratios has not been investigated. This study aimed to identify genetic associations with these indexes. The study population (n=426) included males (40%) and females (60%) aged 18-52 years (mean 39 years), the Infinium GSA array was used for genotyping. Regression models were developed using R and PLINK. AIP was associated with variation on APOC3, KCND3, CYBA, CCDC141/TTN, and ARRB1 (p-value < 2.1E-6) the three former previously associated to blood lipids, while CI2 was associated with variants on DIPK2B, LIPC, and 10q21.3 rs11251177 (p-value 1.1E-7) the latter previously linked to coronary atherosclerosis and hypertension. KCND3 rs6703437 was associated with both indexes. This study is the first to characterize the potential link between genetic variation and atherogenic indexes, AIP and CI2, highlighting the relation between genetic variation and dyslipidemia predictors. These results also contribute to consolidating the genetics of blood lipid and lipid indexes.

Offsite construction is increasingly being presented as a way to increase housing delivery and reduce the housing crisis. Housing Associations play a pivotal role in the delivery of affordable homes and therefore offsite construction could be beneficial in alleviating the crisis. For offsite construction uptake to increase, the conceptual and pragmatic advantages and challenges surrounding offsite housing in relation to evolving social domestic needs to be explored and understood. The purpose of this paper is to discuss the viability of offsite construction as not only a full-service solution to social housing provision, but an integral strategic partner for meeting the range of specialised fabrication needs for these new properties. A literature review is carried out to explore the conceptual and pragmatic advantages and challenges encountered by HAs adopting offsite construction methods. The paper also investigates which the housing tenures are most suited to offsite construction technology. The paper highlighted that whilst individual case studies and example homes offer one mode of justification for Housing Associations to move forward, it is the cumulative effect of cost savings, sustainability, specialised skill sets, labour reduction, structural innovation, and rate of construction that should be weighed and incorporated into this consideration-making process.

The COVID-19 pandemic has created unique challenges for people with comorbidities, including hereditary diseases and cancer cancers. Several studies have reported a link between the presence of disease-causing genetic variants and the outcome of the COVID-19 infection. In this study, we used clinical exome sequencing in a cohort of 840 COVID-19 patients to identify pathogenic and likely pathogenic genetic variants present in these individuals. While we did not identify any statistically significant differences in the overall burden of pathogenic variants between different patient groups, we discovered three known pathogenic alleles associated with hereditary cancer syndromes, including a frameshift mutation in MSH6 and two missense mutations in TP53. The patients carrying these mutations presented with different severity of the disease and outcome. Thus, a 58-year old male subject with an MSH6 mutation developed a severe form of COVID-19 that resulted in death, even though the patient had few pre-existing conditions and no evidence of malignant tumors. On the other hand, two female subjects carrying pathogenic TP53 variants successfully recovered from the disease despite suffering from various forms of cancer. Our results highlight the importance of personalized approaches to the diagnosis, management and treatment of COVID-19 in patients with specific genetic mutations. Further studies are needed to elucidate the complex relationship between these mutations and COVID-19.

The influence of diet and nutritional status of milk donors on the nutritional composition of donor human milk (DHM) is unknown. The present study aimed to determine the nutritional profile of DHM and the associations of donors’ dietary intake and nutritional status with micronutrient and lipid composition in DHM. For this purpose, 113 donors completed a food frequency questionnaire, provided a 5-day weighed dietary record, and collected milk for 5 consecutive days. Nutrient determinations in donors’ erythrocytes, plasma, urine, and milk were performed. Multiple linear regressions were conducted for the evaluation of the associations. We highlight the following results: DHM docosahexaenoic acid (DHA) was positively associated with donors’ plasma DHA content and donors’ DHA intake (R2 0.45, p < 0.001). For every 1 g/day of DHA intake, the percentage of DHA in DHM increased by 0.38% (% of total fat) and the percentage of total omega-3 in DHM increased by 0.78% (R2 0.29, p < 0.001). DHM saturated fatty acids were positively associated with erythrocyte dimethyl acetals, plasma stearic acid, trans fatty acids intake, and breastfeeding duration, and negatively associated with erythrocyte margaroleic acid (R2 0.34, p < 0.01). DHM cholecalciferol was associated with plasma cholecalciferol levels and dairy intake (R2 0.57, p < 0.01). Other weaker associations were found for free thiamine, free riboflavin, pyridoxal, dehydroascorbic acid, and lipid profile in DHM. In conclusion, the diet and nutritional status of donors influences the fatty acid profile and micronutrient content of DHM.

Medical data flows in streams as the data related to clinical tests and administered drugs by the doctors flows continuously. The doctors must be immediately alerted if negative associations are found among the drugs they prescribe. Data streams are to be processed in single scans as it is not possible to re-scan the data for any iterative processing. To detect negative drug connections, regular and frequent drug patterns must be processed. Negative correlations between disease-curing medications might create adverse responses that kill patients. This paper proposes an algorithm that finds the negative associations among regular and frequent patterns mined from medical data streams. The negative associations mined are the most effective and reduce the negative associations, which are more critical by 50%.

This paper discusses a significant public-private partnership (PPP) formed by the government and Taiwanese Farmer Associations. Particularly, it will investigate a pattern of the PPP that has successfully promoted rural development and agricultural modernization in Taiwan since 1950s. Taiwanese Farmer Associations (hereafter TFAs), similar to agricultural cooperatives in South Korea and Japan, have played a policy agent in fostering rural development in this island state since 1950s. TFA’s performance inherently came from Japanese Cooperatives before World War II. The Performances of those farmer organizations are combinations of economic, social, and educational synergies. The rural development experiences in Taiwan demonstrate that success of rural modernization is carried out by a special public-private partnership (PPP). First, this paper discusses formation and development of farmer cooperative organizations in East Asian societies and compare the similarities and differences of practice of those organizations and their relations to the governments among Taiwan, South Korea, and Japan. Secondly, this paper examines collaborative mold and process in which both the government and Taiwan Farmer Associations have been extensively involved. A specific cooperative apparatus between the government and TFA functioning and operating as a perfect PPP has been formed under administrative guidance of the state. Thirdly, this paper looks at input and various supports in financial and policy perspective by the public sector. Fourthly, the paper discusses legal framework, administrative apparatus, and governance pattern for TFA. Fifthly, the paper discuses that a specific PPP successfully involving in rural modernization in Taiwan is significantly derived from the state’ guidance that properly regulates a collaboration between the government and TFA. So-call East Asian model of PPP in agricultural modernization and rural community development may become a valuable experience for most of developing countries.

Crinoids (Echinodermata) exhibit unique characteristics that facilitate a wide range of symbiotic relationships with diverse organisms. Nonetheless, the comprehension of their interactions with microscopic copepod crustaceans is still in a nascent and fragmented state. Our analysis identifies 166 instances involving 35 copepod species representing in 6 families in association with 33 species of the Comatulida. The majority of these associations have been singularly reported, with their distribution covering five out of the 12 World Ocean ecoregions. A notable concentration of diversity is observed in the Central and Western Indo-Pacific regions, while documentation of Atlantic copepod-crinoid associations is markedly limited. Copepods are predominantly found in ectosymbiotic relationships, with a lesser incidence of endosymbiotic interactions. Among these, the genus Collocheres and Pseudanthessius emerge as particularly prominent, and the Comasteridae family is distinguished by its diverse copepod associations. While certain copepod families exhibit a specialization towards crinoids, others demonstrate specificity at the species level. The current scope of knowledge encompasses merely 5% of the potential crinoid host diversity, underscoring the critical need for more extensive research in this area.

In diabetic foot infections (DFI), the clinically virulence of skin commensals are generally pre-sumed to be of low virulence. In this single-center study, we divided the wound isolates into two groups: skin commensals (coagulase-negative staphylococci, micrococci, corynebacteria, cutibacteria); and, pyogenicpathogenic pathogens, and followed the patients for ≥ 6 months. In this retrospective study among 1,018 DFI episodes (392 [39%] with osteomyelitis), we identified skin commensals as the sole culture isolates (without accompanying pyogenicpathogenic patho-gens) in 54 cases (5%). After treatment (antibiotic therapy [median of 20 days], hyperbaric oxy-gen in 98 cases [10%]), 251 episodes (25%) were clinical failures. Group comparisons between those growing only skin commensals and controls found no difference in clinical failure (17% vs 24 %, p=0.23) or microbiological recurrence (11% vs 17 %, p=0.23). The skin commensals were mostly treated with non-beta-lactam oral antibiotics. In multivariate logistic regression analysis, isolation of only skin commensals was not associated with failure (odds ratio 0.4, 95% confi-dence interval 0.1-3.8). Clinicians might wish to consider these isolates as potential pathogens when selecting a targeted antibiotic regimen, which may equally base on oral non-beta-lactam antibiotic agents susceptible to the corresponding skin pathogens.

Most of the research in data mining concentrated on finding the positive associations that exist in frequent patterns. Frequent patterns have no bearing on the time duration and, therefore, lose interestingness. The Regularity of an itemset is related to the time at which the transaction occurred and the time distance between the transactions. Frequent Regular item sets can be generated considering the Frequency and the Regularity of the occurrence of the Item Sets. The frequent and regular Item sets will be so huge that they cannot be handled in real time. The count of Frequent and regular item sets gets reduced drastically when the properties “closed” and “Maximality” are applied. Finding negative associations among such patterns are important in the field of medicine. Many drugs administered to cure some diseases have counter reactions leading to many other diseases. Negative associations among the mined patterns are important as they reveal significant contradictions frequently among medical drugs administered by medical practitioners to cure some diseases. This paper proposes a method that mines medical databases to find regular, frequent patterns applied with closed and maximal properties and find negative associations among those patterns. The proposed algorithm is accurate to 98% and performs 9% more efficiently than the other algorithms presented in the literature.