Solving Patient Allocation Problem during an Epidemic Dengue Fever Outbreak by Mathematical Modelling

Dengue fever is a mosquito-borne disease that has rapidly spread throughout the last few decades. Most preventive mechanisms to deal with the disease focus on the eradication of the vector mosquito and vaccination campaigns. However, appropriate mechanisms of response are indispensable to face the consequent events when an outbreak takes place. This study applied single and multiple objective linear programming models to optimize the allocation of patients and additional resources during an epidemic dengue fever outbreak, minimizing the summation of the distance travelled by all patients. An empirical study was set in Ciudad del Este, Paraguay. Data provided by a privately run health insurance cooperative was used to verify the applicability of the models in this study. The results can be used by analysts and decision makers to solve patient allocation problems for providing essential medical care during an epidemic dengue fever outbreak.

Lipids and Lipoproteins in Health and Disease

This Special Issue, “Lipids and Lipoproteins in Health and Disease: Focus on Targeting Atherosclerosis”, contains research articles and reviews devoted to the study of lipids in different processes, with a focus on the pathological changes that happen during atherosclerosis [...]

OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction

Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The ‘omics’ techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease.

Deregulation of ncRNA in Neurodegenerative Disease: Focus on circRNA, lncRNA and miRNA in Amyotrophic Lateral Sclerosis

Parallel and massive sequencing of total RNA samples derived from different samples are possible thanks to the use of NGS (Next Generation Sequencing) technologies. This allowed characterizing the transcriptomic profile of both cell and tissue populations, increasing the knowledge of the molecular pathological processes of complex diseases, such as neurodegenerative diseases (NDs). Among the NDs, Amyotrophic Lateral Sclerosis (ALS) is caused by the progressive loss of motor neurons (MNs), and, to date, the diagnosis is often made by exclusion because there is no specific symptomatologic picture. For this reason, it is important to search for biomarkers that are clinically useful for carrying out a fast and accurate diagnosis of ALS. Thanks to various studies, it has been possible to propose several molecular mechanisms associated with the disease, some of which include the action of non-coding RNA, including circRNAs, miRNAs, and lncRNAs which will be discussed in the present review. The evidence analyzed in this review highlights the importance of conducting studies to better characterize the different ncRNAs in the disease to use them as possible diagnostic, prognostic, and/or predictive biomarkers of ALS and other NDs.

A Poor Research Landscape Hinders the Progression of Knowledge and Treatment of Reproductive Diseases

Reproductive diseases have gone under the radar for many years, resulting in insufficient diagnostics and treatments. Infertility rates are rising, preeclampsia claims over 70 000 maternal and 500 000 neonatal lives globally per year, and endometriosis affects 10% of all reproductive-aged women but is often undiagnosed for many years. Policy changes have been enacted to mitigate the gender inequality in research investigators and subjects of medical research. However, the disparities in reproductive research advancement still exist. Here, we analyzed the reproductive science research landscape to quantify the gravity of the current situation. We find that non-reproductive organs are researched 5-20 times more annually than reproductive organs, leading to an exponentially increasing relative knowledge gap in reproductive sciences. Additionally, reproductive organs (breast and prostate) are mainly researched when there is a disease focus, leading to a lack of basic understanding of the reproductive organs. This gap in knowledge affects reproductive syndromes and other bodily systems and research areas, such as cancer biology and regenerative medicine. Current researchers, funding organizations and educators must take action to combat this longstanding disregard of reproductive science.

Vaccine hesitancy in online spaces: A scoping review of the research literature, 2000-2020

We review 100 articles published from 2000 to early 2020 that research aspects of vaccine hesitancy in online communication spaces and identify several gaps in the literature prior to the COVID-19 pandemic. These gaps relate to five areas: disciplinary focus; specific vaccine, condition, or disease focus; stakeholders and implications; research methodology; and geographical coverage. Our findings show that we entered the global pandemic vaccination effort without a thorough understanding of how levels of confidence and hesitancy might differ across conditions and vaccines, geographical areas, and platforms, or how they might change over time. In addition, little was known about the role of platforms, platforms’ politics, and specific sociotechnical affordances in the spread of vaccine hesitancy and the associated issue of misinformation online.