No abstract

Over the past few years, there has been increased interest in data mining and machine learning methods to improve hospital performance, in particular hospitals want to improve their intensive care unit statistics by reducing the number of patients dying inside the intensive care unit. Research has focused on prediction of measurable outcomes, including risk of complications, mortality and length of hospital stay. The length of stay is an important metric both for healthcare providers and patients, influenced by numerous factors. In particular, the length of stay in critical care is of great significance, both to patient experience and the cost of care, and is influenced by factors specific to the highly complex environment of the intensive care unit. The length of stay is often used as a surrogate for other outcomes, where those outcomes cannot be measured; for example as a surrogate for hospital or intensive care unit mortality. The length of stay is also a parameter, which has been used to identify the severity of illnesses and healthcare resource utilisation. This paper examines a range of length of stay and mortality prediction applications in acute medicine and the critical care unit. It also focuses on the methods of analysing length of stay and mortality prediction. Moreover, the paper provides a classification and evaluation for the analytical methods of the length of stay and mortality prediction associated with a grouping of relevant research papers published in the years 1984 to 2016 related to the domain of survival analysis. In addition, the paper highlights some of the gaps and challenges of the domain.

Telomeres cap the ends of eukaryotic chromosomes and distinguish them from broken DNA ends to suppress DNA damage response, cell cycle arrest and genomic instability. Telomeres are elongated by telomerase to compensate for incomplete replication and nuclease degradation and to extend the proliferation potential of germ and stem cells and most cancers. However, telomeres in somatic cells gradually shorten with age, ultimately leading to cellular senescence. Hoyeraal-Hreidarsson syndrome (HHS) is characterized by accelerated telomere shortening and diverse symptoms including bone marrow failure, immunodeficiency, and neurodevelopmental defects. HHS is caused by germline mutations in telomerase subunits, factors essential for its biogenesis and recruitment to telomeres, and in the helicase RTEL1. While diverse phenotypes were associated with RTEL1 deficiency, the telomeric role of RTEL1 affected in HHS is yet unknown. Inducible ectopic expression of wild-type RTEL1 in patient fibroblasts rescued the cells, enabled telomerase-dependent telomere elongation and suppressed the abnormal cellular phenotypes, while silencing its expression resulted in gradual telomere shortening. Our observations reveal an essential role of the RTEL1 C-terminus in facilitating telomerase action at the telomeric 3′ overhang. Thus, the common etiology for HHS is the compromised telomerase action, resulting in telomere shortening and reduced lifespan of telomerase positive cells.

Current mortality prediction models and scoring systems for intensive care unit patients are generally usable only after at least 24 or 48 h of admission, as some parameters are unclear at admission. However, some of the most relevant measurements are available shortly following admission. It is hypothesized that outcome prediction may be made using information available in the earliest phase of intensive care unit admission. This study aims to investigate how early hospital mortality can be predicted for intensive care unit patients. We conducted a thorough time-series analysis on the performance of different data mining methods during the first 48 h of intensive care unit admission. The results showed that the discrimination power of the machine-learning classification methods after 6 h of admission outperformed the main scoring systems used in intensive care medicine (Acute Physiology and Chronic Health Evaluation, Simplified Acute Physiology Score and Sequential Organ Failure Assessment) after 48 h of admission.

Telomere maintenance protects the cell against genome instability and senescence. Accelerated telomere attrition is a characteristic of premature aging syndromes including Dyskeratosis congenita (DC). Mutations in hRTEL1 are associated with a severe form of DC called Hoyeraal-Hreidarsson syndrome (HHS). HHS patients carry short telomeres and HHS cells display telomere damage. Here we investigated how hRTEL1 contributes to telomere maintenance in human primary as well as tumor cells. Transient depletion of hRTEL1 resulted in rapid telomere shortening only in the context of telomerase-positive cells with very long telomeres and high levels of telomerase. The effect of hRTEL1 on telomere length is telomerase dependent without impacting telomerase biogenesis or targeting of the enzyme to telomeres. Instead, RTEL1 depletion led to a decrease in both G-overhang content and POT1 association with telomeres with limited telomere uncapping. Strikingly, overexpression of POT1 restored telomere length but not the overhang, demonstrating that G-overhang loss is the primary defect caused by RTEL1 depletion. We propose that hRTEL1 contributes to the maintenance of long telomeres by preserving long G-overhangs, thereby facilitating POT1 binding and elongation by telomerase.

No abstract

Macrolides (e.g., erythromycin, fidaxomicin, clarithromycin, and azithromycin) are a class of bacteriostatic antibiotics commonly employed in medicine against various gram-positive and atypical bacterial species mostly related to respiratory tract infections, besides they possess anti-inflammatory and immunomodulatory effects. Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome of coronavirus 2 (SARS-CoV-2). It was first detected in Wuhan, Hubei, China, in December 2019 and resulted in a continuing pandemic. Macrolides have been extensively researched as broad adjunctive therapy for COVID-19 due to its immunostimulant abilities. Among such class of drugs, azithromycin is described as azalide and is well-known for its ability to decrease the production of pro-inflammatory cytokines, including matrix metalloproteinases, tumor necrosis factor-alpha, interleukin (IL)-6, and IL-8. In fact, a report recently published highlighted the effectiveness of combining azithromycin and hydroxychloroquine for COVID-19 treatment. Indeed, it has been underlined that azithromycin quickly prevents SARS-CoV-2 infection by raising the levels of both interferons and interferon-stimulated proteins at the same time which reduces the virus replication and release. In this sense, the current review aims to evaluate the applications of macrolides for the treatment of COVID-19.

Inherited bone marrow failure syndromes (IBMFS) represent a group of disorders typified by impaired production of one or several blood cell types. The telomere biology disorders dyskeratosis congenita (DC) and its severe variant Høyeraal-Hreidarsson (HH) syndrome are rare IBMFS characterized by bone marrow failure, developmental defects, and various premature aging complications associated with critically short telomeres. Here we identified biallelic variants in the gene encoding the 5'-to-3' DNA exonuclease Apollo/SNM1B in three unrelated patients presenting with a DC/HH phenotype consisting of early onset hypocellular bone marrow failure, B and NK lymphopenia, developmental anomalies, microcephaly and/or intrauterine growth retardation. All three patients carry a homozygous or compound heterozygous (in combination with a null-allele) missense variant affecting the same residue L142 (L142F or L142S) located in the catalytic domain of Apollo. Apollo-deficient cells from patients exhibited spontaneous chromosome instability and impaired DNA repair that was complemented by CRISPR/Cas9-mediated gene correction. Furthermore, patients' cells showed signs of telomere fragility that were however not associated with global reduction of telomere length. Unlike patients' cells, human Apollo KO HT1080-cell lines showed strong telomere dysfunction accompanied by excessive telomere shortening, suggesting that the L142S and L142F Apollo variants are hypomorphic. Collectively, these findings define human Apollo as a genome caretaker and identify biallelic Apollo variants as a genetic cause of a hitherto unrecognized severe IBMFS combining clinical hallmarks of DC/HH with normal telomere length.