Do the combination models perform better than the fundamental models in forecasting the exchange rates?

This study examines the predictability of the simple average combination model and the inverse average error combination model in forecasting the out-of-sample EUR/USD, GBP/USD, and JPY/USD exchange rates from 1st July 2019 to 30th June 2020. Out of the three currency pairs examined, both of the combination models only show evidence in forecasting the JPY/USD exchange rate under the 1-month horizon, in which the absolute values of their z-statistics are smaller than the two-tailed 5% significance level critical value, 1.96. In terms of the forecast performance comparison of the simple average combination model, the inverse average error combination model, the PPP model, the uncovered interest rate parity model, the real interest differential model, and the Taylor rule fundamental model, none of them consistently outperforms the others. Nonetheless, I find that the inverse average error combination model overall produces lower average absolute errors than the simple average combination model. There is also evidence showing that the inverse average error combination model generates smaller forecast deviations as compared to the PPP model, the uncovered interest rate parity model, the real interest differential model, and the Taylor rule fundamental model, respectively for different currency pairs under different forecast horizons.

Gene Expression Patterns in Larval Schistosoma mansoni Associated with Infection of the Mammalian Host

The schistosome cercaria develops from undifferentiated germ balls within the daughter sporocyst located in the hepatopancreas of its snail intermediate host. This is where the proteins it uses to infect humans are synthesised. After a brief free life in fresh water, if the cercaria locates a host, it infects by direct penetration through the skin. It then transforms into the schistosomulum stage, adapted for life in human tissues. We have designed a large scale array comprising probes representing all known schistosome genes and used it in hybridisation experiments to establish which genes are turned on or off in the parasite during these stages in its life cycle. Genes encoding proteins involved in cell division were prominent in the germ ball along with those for proteases and potential immunomodulators, deployed during skin penetration. The non-feeding cercaria was the least active at synthesising proteins. Conversion to the schistosomulum was accompanied by transcription of genes involved in body remodeling, including production of a new outer surface, and gut activation long before ingestion of red blood cells begins. Our data help us to understand better the proteins deployed to achieve infection, and subsequent adaptations necessary for establishment of the parasite in the human host

Identification of IGF1, SLC4A4, WWOX, and SFMBT1 as Hypertension Susceptibility Genes in Han Chinese with a Genome-Wide Gene-Based Association Study

Hypertension is a complex disorder with high prevalence rates all over the world. We conducted the first genome-wide gene-based association scan for hypertension in a Han Chinese population. By analyzing genome-wide single-nucleotide-polymorphism data of 400 matched pairs of young-onset hypertensive patients and normotensive controls genotyped with the Illumina HumanHap550-Duo BeadChip, 100 susceptibility genes for hypertension were identified and also validated with permutation tests. Seventeen of the 100 genes exhibited differential allelic and expression distributions between patient and control groups. These genes provided a good molecular signature for classifying hypertensive patients and normotensive controls. Among the 17 genes, IGF1, SLC4A4, WWOX, and SFMBT1 were not only identified by our gene-based association scan and gene expression analysis but were also replicated by a gene-based association analysis of the Hong Kong Hypertension Study. Moreover, cis-acting expression quantitative trait loci associated with the differentially expressed genes were found and linked to hypertension. IGF1, which encodes insulin-like growth factor 1, is associated with cardiovascular disorders, metabolic syndrome, decreased body weight/size, and changes of insulin levels in mice. SLC4A4, which encodes the electrogenic sodium bicarbonate cotransporter 1, is associated with decreased body weight/size and abnormal ion homeostasis in mice. WWOX, which encodes the WW domain-containing protein, is related to hypoglycemia and hyperphosphatemia. SFMBT1, which encodes the scm-like with four MBT domains protein 1, is a novel hypertension gene. GRB14, TMEM56 and KIAA1797 exhibited highly significant differential allelic and expressed distributions between hypertensive patients and normotensive controls. GRB14 was also found relevant to blood pressure in a previous genetic association study in East Asian populations. TMEM56 and KIAA1797 may be specific to Taiwanese populations, because they were not validated by the two replication studies. Identification of these genes enriches the collection of hypertension susceptibility genes, thereby shedding light on the etiology of hypertension in Han Chinese populations

Do the combination models perform better than the fundamental models in forecasting the exchange rates?

This study examines the predictability of the simple average combination model and the inverse average error combination model in forecasting the out-of-sample EUR/USD, GBP/USD, and JPY/USD exchange rates from 1st July 2019 to 30th June 2020. Out of the three currency pairs examined, both of the combination models only show evidence in forecasting the JPY/USD exchange rate under the 1-month horizon, in which the absolute values of their z-statistics are smaller than the two-tailed 5% significance level critical value, 1.96. In terms of the forecast performance comparison of the simple average combination model, the inverse average error combination model, the PPP model, the uncovered interest rate parity model, the real interest differential model, and the Taylor rule fundamental model, none of them consistently outperforms the others. Nonetheless, I find that the inverse average error combination model overall produces lower average absolute errors than the simple average combination model. There is also evidence showing that the inverse average error combination model generates smaller forecast deviations as compared to the PPP model, the uncovered interest rate parity model, the real interest differential model, and the Taylor rule fundamental model, respectively for different currency pairs under different forecast horizons.

Conserved regulatory switches for the transition from natal down to juvenile feather in birds

The transition from natal downs for heat conservation to juvenile feathers for simple flight is a remarkable environmental adaptation process in avian evolution. However, the underlying epigenetic mechanism for this primary feather transition is mostly unknown. Here we conducted time-ordered gene co-expression network construction, epigenetic analysis, and functional perturbations in developing feather follicles to elucidate four downy-juvenile feather transition events. We report that extracellular matrix reorganization leads to peripheral pulp formation, which mediates epithelial-mesenchymal interactions for branching morphogenesis. α-SMA (ACTA2) compartmentalizes dermal papilla stem cells for feather renewal cycling. LEF1 works as a key hub of Wnt signaling to build rachis and converts radial downy to bilateral symmetry. Novel usage of scale keratins strengthens feather sheath with SOX14 as the epigenetic regulator. We show that this primary feather transition is largely conserved in chicken (precocial) and zebra finch (altricial) and discuss the possibility that this evolutionary adaptation process started in feathered dinosaurs