Burden of bacteraemia is rising due to increased average life expectancy in developed countries. This study aimed to compare the epidemiology and outcomes of bacteraemia in two similarly ageing populations with different ethnicities in Singapore and Denmark. Historical cohorts from the second largest acute-care hospital in Singapore and in the hospitals of two Danish regions included patients aged 15 and above who were admitted from 1 January 2006 to 31 December 2016 with at least 1 day of hospital stay and a pathogenic organism identified. Among 13 144 and 39 073 bacteraemia patients from Singapore and Denmark, similar 30-day mortality rates (16.5%; 20.3%), length of hospital stay (median 14 (IQR: 9–28) days; 11 (6–21)), and admission rate to ICU (15.5%; 15.6%) were observed, respectively. Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus ranked among the top four in both countries. However, Singaporeans had a higher proportion of patients with diabetes (46.8%) and renal disease (29.5%) than the Danes (28.0% and 13.7%, respectively), whilst the Danes had a higher proportion of patients with chronic pulmonary disease (18.0%) and malignancy (35.3%) than Singaporeans (9.7% and 16.2%, respectively). Our study showed that top four causative organisms and clinical outcomes were similar between the two cohorts despite pre-existing comorbidities differed.

At present, analysis of diet and bladder cancer (BC) is mostly based on the intake of individual foods. The examination of food combinations provides a scope to deal with the complexity and unpredictability of the diet and aims to overcome the limitations of the study of nutrients and foods in isolation. This article aims to demonstrate the usability of supervised data mining methods to extract the food groups related to BC. In order to derive key food groups associated with BC risk, we applied the data mining technique C5.0 with 10-fold cross-validation in the BLadder cancer Epidemiology and Nutritional Determinants study, including data from eighteen case–control and one nested case–cohort study, compromising 8320 BC cases out of 31 551 participants. Dietary data, on the eleven main food groups of the Eurocode 2 Core classification codebook, and relevant non-diet data (i.e. sex, age and smoking status) were available. Primarily, five key food groups were extracted; in order of importance, beverages (non-milk); grains and grain products; vegetables and vegetable products; fats, oils and their products; meats and meat products were associated with BC risk. Since these food groups are corresponded with previously proposed BC-related dietary factors, data mining seems to be a promising technique in the field of nutritional epidemiology and deserves further examination.

This research communication describes a genome-wide association study for Italian buffalo mammary gland morphology. Three single nucleotide polymorphisms (AX-85117983, AX-8509475 and AX-85117518) were identified to be significantly associated with buffalo anterior teat length, posterior teat length and distance between anterior and posterior teat, respectively. Two significant signals for buffalo mammary gland morphology were observed in two genomic regions on the chromosome 10, and chromosome 20. One of the regions located on the chromosome 10 has the most likely candidate genes ACTC1 and GJD2, both of which have putative roles in the regulation of mammary gland development. This study provides new insights into the genetic variants of buffalo mammary gland morphology and may be beneficial for understanding of the genetic regulation of mammary growth.

This Research Communication describes the polymorphisms in the coding region of DGAT1 gene in Riverine buffalo, Swamp buffalo and crossbred buffalo, and associations between polymorphisms and milk production performance in Riverine buffalo. Two polymorphisms of DGAT1were identified, located in exon 13 and exon 17, respectively. The distribution of the genotypes of the two SNP loci in different buffalo population varied, especially the polymorphism located in exon 13 which was not found in the Swamp buffalo. Moreover, SNP located in exon 17 was a nonsynonymous switch resulting in the animo acid sequence changed from an arginine (Arg) to a histidine (His) at position 484. Both SNPs were in Hardy–Weinberg equilibrium, and the polymorphism of g.8330T>C in the exon 13 was significantly associated with peak milk yield, total milk yield and protein percentage. The C variant was associated with an increase in milk yield and peak yield but less in protein percentage compared with the T variant. The polymorphisms of g.9046T>C in exon 17 were significantly associated with fat percentage, in that the buffaloes with TT genotype had a significantly higher fat percentage than those with CC genotype. These findings reveal the difference in the genetic evolution of the DGAT1 between Riverine buffalo and Swamp buffalo, and provide evidence that the DGAT1 gene has potential effects for Riverine buffalo milk production traits, which can be used as a candidate gene for marker-assisted selection in buffalo breeding.

The Multilink model that Dijkstra, Wahl, Buytenhuijs, van Halem, Al-jibouri, de Korte, and Rekké (2018) present is an excellent example that connects empirical patterns obtained from behavioral studies with mechanisms that can be implemented in computational models. We have previously argued that implementation of computational models is important because it forces the researchers to be explicit about assumptions and to specify parameters and variables that may be absent in verbal models. The Multilink model, along with BIA/BIA+ and many other models, provides concrete hypotheses regarding the role of variables such as word frequency, word length, orthographic similarity, and phonological neighborhood for researchers to test and verify against empirical data (see examples in the special issue on computational modeling published in this journal; Li, 2013).

This Research Communication describes the association between genetic variation within the prolactin (PRL) gene and the milk production traits of Italian Mediterranean river buffalo (Bufala mediterranea Italiana). High resolution melting (HRM) techniques were developed for genotyping 465 buffaloes. The association of genetic polymorphism with milk production traits was performed and subsequently the effects of parity and calving season were evaluated. Single nucleotide polymorphisms (SNPs) were identified at exons 2 and 5 and at introns 1 and 2. All the SNPs were in Hardy–Weinberg equilibrium, and statistical analysis showed that the polymorphism of intron1 was significantly (P < 0·05) associated with milk yield, milk protein content and peak milk yield. The average contribution of the intron1 genotype (r2intron1) to total phenotypic variance in milk production traits was 0·09, and the TT genotype showed lower values than CC and CT genotypes. A nonsynonymous SNP was identified in exon 2, which resulted in an amino acid change from arginine to cysteine. Moreover, the polymorphism of exon 2 was associated significantly with milk fat content (P < 0·05), and the buffaloes with TT genotype showed higher total fat content than the buffaloes with CT genotype. These findings provide evidence that polymorphisms of the buffalo PRL gene are associated with milk production traits and PRL can be used as a candidate gene for marker-assisted selection in Italian Mediterranean river buffalo breeding.

A recent movement in cognitive neuroscience is the study of brain networks through functional and effective connectivity. The brain networks approach has already found its influences in the study of the neurobiology of language, but has yet to impact research in the neurocognition of bilingualism and second language. In this article, we briefly review some preliminary evidence in this emerging field and suggest that the understanding of the dynamic changes in brain networks enables us to capture second language learning success, thereby providing new insights into the neural bases of individual differences, neuroplasticity, and bilingualism.

Consumption of fruits and vegetables has been investigated for their role in the prevention of many chronic conditions. Among the fruits, mango provides numerous bioactive compounds such as carotenoids, vitamin C and phenolic compounds, which have been shown to have antioxidant and anti-inflammatory properties. The present study examined the effects of dietary supplementation of freeze-dried mango pulp, in comparison with the hypolipidaemic drug, fenofibrate, and the hypoglycaemic drug, rosiglitazone, in reducing adiposity and alterations in glucose metabolism and lipid profile in mice fed a high-fat (HF) diet. Male C57BL/6J mice were randomly divided into six treatment groups (eight to nine/group): control (10 % energy from fat); HF (60 % energy from fat); HF+1 or 10 % freeze-dried mango (w/w); HF+fenofibrate (500 mg/kg diet); HF+rosiglitazone (50 mg/kg diet). After 8 weeks of treatment, mice receiving the HF diet had a higher percentage body fat (P = 0·0205) and epididymal fat mass (P = 0·0037) compared with the other treatment groups. Both doses of freeze-dried mango, similar to fenofibrate and rosiglitazone, prevented the increase in epididymal fat mass and the percentage of body fat. Freeze-dried mango supplementation at the 1 % dose improved glucose tolerance as shown by approximately 35 % lower blood glucose area under the curve compared with the HF group. Moreover, freeze-dried mango lowered insulin resistance, as indicated by the homeostasis model assessment of insulin resistance, to a similar extent as rosiglitazone and modulated NEFA. The present findings demonstrate that incorporation of freeze-dried mango in the diet of mice improved glucose tolerance and lipid profile and reduced adiposity associated with a HF diet.