The Quick Sequential Organ Failure Assessment (qSOFA) Score is a Poor Mortality Predictor in Patients with Complicated Intra-abdominal Infections

BACKGROUND: Despite the evolution in surgical treatment and antimicrobial therapy in the last years the complicated intra-abdominal infections (cIAIs) are still associated with high morbidity and mortality. Different scoring systems are already available for early prognostic evaluation and yet none has been widely accepted. AIM: Our aim was to evaluate the prognostic accuracy of quick sequential organ failure assessment (qSOFA), one of the most recent scores, in patients with cIAIs. MATERIALS AND METHODS: We studied retrospectively 110 patients with cIAIs admitted to the Department of Surgical Diseases (DSD) at University Hospital “Prof. Dr. Stoyan Kirkovich” Stara Zagora from January 2017 to July 2019. Area under receiver operating characteristics (AUROC) curves of systemic inflammatory response syndrome (SIRS), qSOFA, and Mannheim Peritonitis Index (MPI) were analyzed and a comparison of ROC curves was performed to explore their prognostic performance. RESULTS: Twenty-five (22.7%) patients died during hospitalization. qSOFA score showed poor prognostic accuracy (AUROC = 0.698, 95% CI = 0.566–0.829), worse than MPI score (AUROC = 0.698 vs. 0.844), but better than SIRS (AUROC = 0.698 vs. 0.583). The qSOFA score ≥2 points was observed with lack of sensitivity (32.0%) as outcome predictor. ROC curve analysis showed prognostic inferiority of qSOFA compared to MPI (difference between areas = 0.146, p = 0.0232). CONCLUSION: In patients with cIAIs, quick-SOFA score was observed with poor prognostic performance

The Role of the Molecular Subtypes in the Prognosis of Breast Cancer Patients

BACKGROUND: Understanding the biology of the tumor, by dividing it into molecular subtypes, has made it possible to individualize the therapeutic approach in high-risk patients. AIM: We aimed to determine the importance of established molecular subtypes in the prognosis and the importance of disease-free and overall survival (OS) in patients with non-metastatic breast cancer. MATERIALS AND METHODS: We analyzed 94 patients with non-metastatic breast cancer for the period 2010–2018. The median follow-up time was 60 months. The mean age in the study group was 60.03 years (SD ± 10.52). According to the characteristics of the studied indicators, we divided the group into Luminal A (n-59 [62.7%]), Luminal B/HER2 (−) (n-2 [2.1%]), Luminal B/HER2 (+) (n-8 [8.5%]), HER2 overexpressing (n-3 [3.2%]), and triple-negative subtype (n-22 [23.5%]). In all patients in the study group, we analyzed the 5-year overall survival (OS) and disease-free survival (DFS) and referred it to molecular subtypes, lymphatic status, HER-2 status, the presence or absence of endocrine therapy for the follow-up period, tumor differentiation, and type of surgery. RESULTS: We observed the 5-year OS in 92% of patients identified as Luminal A; at 50% of Luminal B/HER2 (−) neg.; in 62.5% with Luminal B/HER2 (+), in 67% with HER2-overexpressing carcinoma; and in 66.7% of patients with triple-negative subtype. The total cancer-associated mortality rate in the analyzed period reached 15.9% (n = 15). Patients with mastectomy (p = 0.019, p = 0.027), positive axilla with more than 4 lymph node (LN) (p = 0.000; p = 0.000), and Luminal B/HER-2 (+) tumors (p = 0.004; p = 0.003) were the independent prognostic factors for worse DFS and OS in our study group. Histological differentiation and HER-2 expression were in unsatisfactory correlation (p = 0.077; p = 0.044 and p = 0.081; p = 0.055, respectively). CONCLUSION: Molecular subtypes are essential in the prognosis of breast cancer and maybe a criterion for an individualized therapeutic approach

Neutrophil CD64 – A potential biomarker in patients with complicated intra-abdominal infections? – A literature review

Complicated intra-abdominal infections (cIaIs) respresent a serious cause of morbidity and mortality. Early diagnosis and well-timed treatment can improve patients’ outcome, whereas the delay in management often result in rapid progression to circulatory collapse, multiple organ failure, and death. Neutrophil CD64 antigen expression has been studied for several years as infectious and sepsis biomarker and has several characteristics that make it good for clinical employment. It has been suggested to be predictive of positive bacterial cultures and a useful test for management of sepsis and other significant bacterial infections. Our review concluded that the neutrophil CD64 expression could be a promising and meaningful biomarker in patients with cIaIs. It shows good potential for evaluating the severity of the disease and could give information about the outcome. However, more large studies should be performed before using it in clinical practice

Chloroplast genome assembly approaches from NGS data

The advent of Next Generation Sequencing platforms led to increase of research in whole genome assembly algorithms and software. Illumina Genome Analyzer produces a large amount of sequencing data, with a shorted read length, higher coverage and different errors in comparison to Sanger Sequencing. In response to this, several new assemblers were developed specifically for de novo assembly of next generation sequencing. This study compares software assembly packages named Edena, SPAdes, ABySS and analyzes results delivered by de novo assembly experiments. We show that assembly job of small genome can be completed in a short time on a 32 bit Linux OS with 4 GB RAM, indicating than de novo assembly can be executed and millions of very reads assembled on a desktop computer

The Multiverse of Plant Small RNAs: How Can We Explore It?

Plant small RNAs (sRNAs) are a heterogeneous group of noncoding RNAs with a length of 20–24 nucleotides that are widely studied due to their importance as major regulators in various biological processes. sRNAs are divided into two main classes—microRNAs (miRNAs) and small interfering RNAs (siRNAs)—which differ in their biogenesis and functional pathways. Their identification and enrichment with new structural variants would not be possible without the use of various high-throughput sequencing (NGS) techniques, allowing for the detection of the total population of sRNAs in plants. Classifying sRNAs and predicting their functional role based on such high-performance datasets is a nontrivial bioinformatics task, as plants can generate millions of sRNAs from a variety of biosynthetic pathways. Over the years, many computing tools have been developed to meet this challenge. Here, we review more than 35 tools developed specifically for plant sRNAs over the past few years and explore some of their basic algorithms for performing tasks related to predicting, identifying, categorizing, and quantifying individual sRNAs in plant samples, as well as visualizing the results of these analyzes. We believe that this review will be practical for biologists who want to analyze their plant sRNA datasets but are overwhelmed by the number of tools available, thus answering the basic question of how to choose the right one for a particular study

Can we predict death using scoring systems in patients with local peritonitis ? A retrospective study

Introduction: Prognostic scores in patients with local peritonitis (LP) have not yet been studied exhaustively. Aim: We, therefore, aimed in this study to evaluate the ability of several scoring systems to predict death in LP. Materials and methods: A retrospective analysis including 68 patients with LP was conducted at Prof. Dr. Stoyan Kirkovich University Hospital in Stara Zagora from January 2017 to August 2021. Clinical and laboratory data needed for calculating the scoring systems were collected at admission or postoperatively. We compared the prognostic performance of WSES SSS, MPI, SIRS, and qSOFA using area under the receiver operation characteristics (AUROC) curves and bivariate correlation analysis. Results: The observed mortality rate was 8.8%. Among all scores, MPI showed the best prognostic performance (AUROC=0.805, 95% CI 0.660–0.950). A threshold MPI >25 points permitted prediction of adverse outcome with a sensitivity of 66.7% and a specificity of 80.6%. The only significant correlation was found between outcome and MPI (p=0.012, r=0.302). Conclusions: The MPI has the ability to prognosticate mortality in patients with LP unlike WSES SSS, qSOFA and SIRS

Plant-Derived Recombinant Vaccines against Zoonotic Viruses

Emerging and re-emerging zoonotic diseases cause serious illness with billions of cases, and millions of deaths. The most effective way to restrict the spread of zoonotic viruses among humans and animals and prevent disease is vaccination. Recombinant proteins produced in plants offer an alternative approach for the development of safe, effective, inexpensive candidate vaccines. Current strategies are focused on the production of highly immunogenic structural proteins, which mimic the organizations of the native virion but lack the viral genetic material. These include chimeric viral peptides, subunit virus proteins, and virus-like particles (VLPs). The latter, with their ability to self-assemble and thus resemble the form of virus particles, are gaining traction among plant-based candidate vaccines against many infectious diseases. In this review, we summarized the main zoonotic diseases and followed the progress in using plant expression systems for the production of recombinant proteins and VLPs used in the development of plant-based vaccines against zoonotic viruses