Characteristics of predictor sets found using differential prioritization

<p>Abstract</p> <p>Background</p> <p>Feature selection plays an undeniably important role in classification problems involving high dimensional datasets such as microarray datasets. For filter-based feature selection, two well-known criteria used in forming predictor sets are relevance and redundancy. However, there is a third criterion which is at least as important as the other two in affecting the efficacy of the resulting predictor sets. This criterion is the degree of differential prioritization (DDP), which varies the emphases on relevance and redundancy depending on the value of the DDP. Previous empirical works on publicly available microarray datasets have confirmed the effectiveness of the DDP in molecular classification. We now propose to establish the fundamental strengths and merits of the DDP-based feature selection technique. This is to be done through a simulation study which involves vigorous analyses of the characteristics of predictor sets found using different values of the DDP from toy datasets designed to mimic real-life microarray datasets.</p> <p>Results</p> <p>A simulation study employing analytical measures such as the distance between classes before and after transformation using principal component analysis is implemented on toy datasets. From these analyses, the necessity of adjusting the differential prioritization based on the dataset of interest is established. This conclusion is supported by comparisons against both simplistic rank-based selection and state-of-the-art equal-priorities scoring methods, which demonstrates the superiority of the DDP-based feature selection technique. Reapplying similar analyses to real-life multiclass microarray datasets provides further confirmation of our findings and of the significance of the DDP for practical applications.</p> <p>Conclusion</p> <p>The findings have been achieved based on analytical evaluations, not empirical evaluation involving classifiers, thus providing further basis for the usefulness of the DDP and validating the need for unequal priorities on relevance and redundancy during feature selection for microarray datasets, especially highly multiclass datasets.</p

Application of Deep Learning Models for Automated Identification of Parkinson’s Disease: A Review (2011–2021)

Parkinson’s disease (PD) is the second most common neurodegenerative disorder affecting over 6 million people globally. Although there are symptomatic treatments that can increase the survivability of the disease, there are no curative treatments. The prevalence of PD and disability-adjusted life years continue to increase steadily, leading to a growing burden on patients, their families, society and the economy. Dopaminergic medications can significantly slow down the progression of PD when applied during the early stages. However, these treatments often become less effective with the disease progression. Early diagnosis of PD is crucial for immediate interventions so that the patients can remain self-sufficient for the longest period of time possible. Unfortunately, diagnoses are often late, due to factors such as a global shortage of neurologists skilled in early PD diagnosis. Computer-aided diagnostic (CAD) tools, based on artificial intelligence methods, that can perform automated diagnosis of PD, are gaining attention from healthcare services. In this review, we have identified 63 studies published between January 2011 and July 2021, that proposed deep learning models for an automated diagnosis of PD, using various types of modalities like brain analysis (SPECT, PET, MRI and EEG), and motion symptoms (gait, handwriting, speech and EMG). From these studies, we identify the best performing deep learning model reported for each modality and highlight the current limitations that are hindering the adoption of such CAD tools in healthcare. Finally, we propose new directions to further the studies on deep learning in the automated detection of PD, in the hopes of improving the utility, applicability and impact of such tools to improve early detection of PD globally.</jats:p

Epidemiological risk factors for adult dengue in Singapore: an 8-year nested test negative case control study

10.1186/s12879-016-1662-4BMC Infectious Diseases16132

Larval Development of Aedes aegypti and Aedes albopictus in Peri-Urban Brackish Water and Its Implications for Transmission of Arboviral Diseases

Aedes aegypti (Linnaeus) and Aedes albopictus Skuse mosquitoes transmit serious human arboviral diseases including yellow fever, dengue and chikungunya in many tropical and sub-tropical countries. Females of the two species have adapted to undergo preimaginal development in natural or artificial collections of freshwater near human habitations and feed on human blood. While there is an effective vaccine against yellow fever, the control of dengue and chikungunya is mainly dependent on reducing freshwater preimaginal development habitats of the two vectors. We show here that Ae. aegypti and Ae. albopictus lay eggs and their larvae survive to emerge as adults in brackish water (water with <0.5 ppt or parts per thousand, 0.5–30 ppt and >30 ppt salt are termed fresh, brackish and saline respectively). Brackish water with salinity of 2 to 15 ppt in discarded plastic and glass containers, abandoned fishing boats and unused wells in coastal peri-urban environment were found to contain Ae. aegypti and Ae. albopictus larvae. Relatively high incidence of dengue in Jaffna city, Sri Lanka was observed in the vicinity of brackish water habitats containing Ae. aegypti larvae. These observations raise the possibility that brackish water-adapted Ae. aegypti and Ae. albopictus may play a hitherto unrecognized role in transmitting dengue, chikungunya and yellow fever in coastal urban areas. National and international health authorities therefore need to take the findings into consideration and extend their vector control efforts, which are presently focused on urban freshwater habitats, to include brackish water larval development habitats

Identification of a Cryptic Prokaryotic Promoter within the cDNA Encoding the 5′ End of Dengue Virus RNA Genome

Infectious cDNA clones of RNA viruses are important research tools, but flavivirus cDNA clones have proven difficult to assemble and propagate in bacteria. This has been attributed to genetic instability and/or host cell toxicity, however the mechanism leading to these difficulties has not been fully elucidated. Here we identify and characterize an efficient cryptic bacterial promoter in the cDNA encoding the dengue virus (DENV) 5′ UTR. Following cryptic transcription in E. coli, protein expression initiated at a conserved in-frame AUG that is downstream from the authentic DENV initiation codon, yielding a DENV polyprotein fragment that was truncated at the N-terminus. A more complete understanding of constitutive viral protein expression in E. coli might help explain the cloning and propagation difficulties generally observed with flavivirus cDNA

Familial aggregation of lung cancer in a high incidence area in China

To investigate whether lung cancer clusters in families in a high incidence county of China, an analysis was conducted using data on domestic fuel history and tobacco use for family members of 740 deceased lung cancer probands and 740 controls (probands' spouses). Lung cancer prevalence was compared among first-degree relatives of probands and of controls, taking into account various factors using logistic regression and generalised estimating equations. First-degree relatives of probands, compared with those of controls, showed an excess risk of lung cancer (odds ratio (OR)=2.05, 95% confidence interval (CI): 1.68–2.53). Overall, female relatives of probands had a greater risk than did their male counterparts, and the risk was 2.90-fold for parents of probands as compared with parents of spouses. Female relatives of probands had 2.67-fold greater risk than female controls. Lung cancer risk was particularly marked among mothers (OR=3.78, 95% CI: 2.03–7.12). Having two or more affected relatives was associated with a 2.69–5.40-fold risk increase. The risk elevation was also found for other cancers overall. Results confirm previous findings of a genetic predisposition to lung cancer, and also imply that lung cancer may share a genetic background with other cancers

Reduced microvascular density in omental biopsies of children with chronic kidney disease

Endothelial dysfunction is an early manifestation of cardiovascular disease (CVD) and consistently observed in patients with chronic kidney disease (CKD). We hypothesized that CKD is associated with systemic damage to the microcirculation, preceding macrovascular pathology. To assess the degree of "uremic microangiopathy", we have measured microvascular density in biopsies of the omentum of children with CKD.Omental tissue was collected from 32 healthy children (0-18 years) undergoing elective abdominal surgery and from 23 age-matched cases with stage 5 CKD at the time of catheter insertion for initiation of peritoneal dialysis. Biopsies were analyzed by independent observers using either a manual or an automated imaging system for the assessment of microvascular density. Quantitative immunohistochemistry was performed for markers of autophagy and apoptosis, and for the abundance of the angiogenesis-regulating proteins VEGF-A, VEGF-R2, Angpt1 and Angpt2.Microvascular density was significantly reduced in uremic children compared to healthy controls, both by manual imaging with a digital microscope (median surface area 0.61% vs. 0.95%, p<0.0021 and by automated quantification (total microvascular surface area 0.89% vs. 1.17% p = 0.01). Density measured by manual imaging was significantly associated with age, height, weight and body surface area in CKD patients and healthy controls. In multivariate analysis, age and serum creatinine level were the only independent, significant predictors of microvascular density (r2 = 0.73). There was no immunohistochemical evidence for apoptosis or autophagy. Quantitative staining showed similar expression levels of the angiogenesis regulators VEGF-A, VEGF-receptor 2 and Angpt1 (p = 0.11), but Angpt2 was significantly lower in CKD children (p = 0.01).Microvascular density is profoundly reduced in omental biopsies of children with stage 5 CKD and associated with diminished Angpt2 signaling. Microvascular rarefaction could be an early systemic manifestation of CKD-induced cardiovascular disease

High Density Microarray Analysis Reveals New Insights into Genetic Footprints of Listeria monocytogenes Strains Involved in Listeriosis Outbreaks

Listeria monocytogenes, a foodborne bacterial pathogen, causes invasive and febrile gastroenteritis forms of listeriosis in humans. Both invasive and febrile gastroenteritis listeriosis is caused mostly by serotypes 1/2a, 1/2b and 4b strains. The outbreak strains of serotype 1/2a and 4b could be further classified into several epidemic clones but the genetic bases for the diverse pathophysiology have been unsuccessful. DNA microarray provides an important tool to scan the entire genome for genetic signatures that may distinguish the L. monocytogenes strains belonging to different outbreaks. We have designed a pan-genomic microarray chip (Listeria GeneChip) containing sequences from 24 L. monocytogenes strains. The chip was designed to identify the presence/absence of genomic sequences, analyze transcription profiles and identify SNPs. Analysis of the genomic profiles of 38 outbreak strains representing 1/2a, 1/2b and 4b serotypes, revealed that the strains formed distinct genetic clusters adhering to their serotypes and epidemic clone types. Although serologically 1/2a and 1/b strains share common antigenic markers microarray analysis revealed that 1/2a strains are further apart from the closely related 1/2b and 4b strains. Within any given serotype and epidemic clone type the febrile gastroenteritis and invasive strains can be further distinguished based on several genetic markers including large numbers of phage genome, and intergenic sequences. Our results showed that the microarray-based data can be an important tool in characterization of L. monocytogenes strains involved in both invasive and gastroenteritis outbreaks. The results for the first time showed that the serotypes and epidemic clones are based on extensive pan-genomic variability and the 1/2b and 4bstrains are more closely related to each other than the 1/2a strains. The data also supported the hypothesis that the strains causing these two diverse outbreaks are genotypically different and this finding might be important in understanding the pathophysiology of this organism

A silviculture-oriented spatio-temporal model for germination in Pinus pinea L. in the Spanish Northern Plateau based on a direct seeding experiment

Natural regeneration in Pinus pinea stands commonly fails throughout the Spanish Northern Plateau under current intensive regeneration treatments. As a result, extensive direct seeding is commonly conducted to guarantee regeneration occurrence. In a period of rationalization of the resources devoted to forest management, this kind of techniques may become unaffordable. Given that the climatic and stand factors driving germination remain unknown, tools are required to understand the process and temper the use of direct seeding. In this study, the spatio-temporal pattern of germination of P. pinea was modelled with those purposes. The resulting findings will allow us to (1) determine the main ecological variables involved in germination in the species and (2) infer adequate silvicultural alternatives. The modelling approach focuses on covariates which are readily available to forest managers. A two-step nonlinear mixed model was fitted to predict germination occurrence and abundance in P. pinea under varying climatic, environmental and stand conditions, based on a germination data set covering a 5-year period. The results obtained reveal that the process is primarily driven by climate variables. Favourable conditions for germination commonly occur in fall although the optimum window is often narrow and may not occur at all in some years. At spatial level, it would appear that germination is facilitated by high stand densities, suggesting that current felling intensity should be reduced. In accordance with other studies on P. pinea dispersal, it seems that denser stands during the regeneration period will reduce the present dependence on direct seeding