Levels Of Disease Severity Research Articles

Behavior of new entries and developed tomato hybrids carrying Ty-2 genes

Tomato yellow leaf curl disease (TYLCD) is a serious problem hampering tomato production worldwide. In the Mediterranean Basin, disease incidence and severity are higher in the dry season increasing whitefly (Bemisia tabaci) populations. Effectiveness of resistance to Tomato yellow leaf curl virus (TYLCV) depends on both tomato host resistance and TYLCV complex species. So far, six different Ty tomato resistance genes have been identified. Two main TYLCV complex species, Tomato yellow leaf curl virus-Israel (TYLCV-Is) and Tomato yellow leaf curl Sardinia virus (TYLCSV), have been identified in Tunisia. The present work aimed to evaluate entries heterozygous for Ty-2 gene to help predict hybrid performance. Two tomato entries homozygous for the Ty-2 TYLCV resistance gene, one tomato hybrid homozygous for Ty-2 and two heterozygous hybrids were included, besides two susceptible tomato entries. Resistance response to TYLCD was recorded based on disease incidence and severity levels. Data analysis was performed according to presence/absence of Ty-2 gene and taking into account homozygosity and heterozygosity of Ty-2. Generalized linear model analysis was applied to check significance of individual factors' effects (i.e. effect of tomato entries or tomato groups of entries based on presence or absence of homozygous/heterozygous Ty-2 gene, block unit within the field trial and the year of the trial) on the dependent variables (disease incidence and severity). Further multicomparison tests gave evidence on significant effect of Ty-2 homozygous gene tomato entries on TYLCD incidence and severity levels. The results were discussed with special focus on the relevance use of heterozygous hybrid tomato varieties.

Effect of Chemokine Gene Variants on Covid-19 Disease Severity

ABSTRACT Patients immune phenotype/genotype data may be useful to understand the molecular mechanisms involved in SARS-CoV-2 infection and can contribute to the identify the different levels of disease severity. The roles of chemokines have been reported in the coronavirus-related diseases SARS and MERS and they may likewise play a critical role in the development of the symptoms of COVID-19 disease. We analyzed the association of the MCP-1-A2518 G, SDF-1-3’A, CCR5-delta32, CCR5-A55029 G, CXCR4-C138T and CCR2-V64I gene polymorphisms with COVID-19 severity to further unveil the immunological pathways leading to disease severity and death. Polymerase chain reaction(PCR)/Sanger sequencing analysis was performed for detection of the variations in 60 asymptomatic and 119 severe COVID-19 patients. In our study, we found that the frequencies of MCP-1 of GA genotype and G allele carriers were significantly higher in severe COVID-19 patients than the asymptomatic COVID-19 patients (p < .0001 and p: .005, respectively). However, no significant association was found for any of the other polymorphisms with the severity of COVID-19. Our findings suggest that there is a positive association between MCP-1-A2518 G gene variants with the severity of COVID-19. However, larger studies in different population which will focus on gene expression levels will help us to understand the capability of the mechanism role.

Immunomodulatory Molecular Mechanisms of Luffa cylindrica for Downy Mildews Resistance Induced by Growth-Promoting Endophytic Fungi.

Downy mildew (DM), caused by P. cubensis, is harmful to cucurbits including luffa, with increased shortcomings associated with its control through cultural practices, chemical fungicides, and resistant cultivars; there is a prompt need for an effective, eco-friendly, economical, and safe biocontrol approach. Current research is therefore dealt with the biocontrol of luffa DM1 through the endophytic fungi (EF) consortium. Results revealed that T. harzianum (ThM9) and T. virens (TvA1) showed pathogen-dependent inducible metabolic production of squalene and gliotoxins by higher gene expression induction of SQS1/ERG9 (squalene synthase) and GliP (non-ribosomal peptide synthetase). Gene expression of lytic enzymes of EF was also induced with subsequently higher enzyme activities upon confrontation with P. cubensis. EF-inoculated luffa seeds showed efficient germination with enhanced growth potential and vigor of seedlings. EF-inoculated plants showed an increased level of growth-promoting hormone GA with higher gene expression of GA2OX8. EF-pre-inoculated seedlings were resistant to DM and showed an increased GSH content and antioxidant enzyme activities (SOD, CAT, POD). The level of MDA, H2O2, REL, and disease severity was reduced by EF. ACC, JA, ABA, and SA were overproduced along with higher gene expression of LOX, ERF, NCED2, and PAL. Expression of defense-marker genes (PPO, CAT2, SOD, APX, PER5, LOX, NBS-LRR, PSY, CAS, Ubi, MLP43) was also modulated in EF-inoculated infected plants. Current research supported the use of EF inoculation to effectively escalate the systemic immunity against DM corresponding to the significant promotion of induced systemic resistance (ISR) and systemic acquired resistance (SAR) responses through initiating the defense mechanism by SA, ABA, ET, and JA biosynthesis and signaling pathways in luffa.

The effect of COVID 19 vaccination on kidney recipients

BackgroundNearly one year from the onset of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, safe and effective vaccines began distribution around the world. This study aimed to assess the rate of COVID-19 disease among vaccinated kidney transplant patients and the types of symptoms found within them. DesignThis cross-sectional study was performed at the transplant ward and Organ Procurement Unit of Sina Hospital, Tehran, Iran. As a sample size, 159 cadavers' kidney recipients received two doses of the Sinopharm SARS-CoV-2 vaccine. The required data were collected using a checklist via conducting a face-to-face interview. ResultsThe mean age of the vaccinated participants was 49.44 ± 13.87 years old. There were 73 (45.91%) vaccinated cases of SARS-CoV-2 infection during the study period, 18 cases (12.6%) occurred among fully vaccinated individuals, and 53 cases (33.3%) were among individuals who had received only one dose of vaccine.45% of the fully vaccinated patients (received 2 doses vaccine) contracted SARS-CoV-2 from their families; 35% were infected through participation in social events (35%).There was a significant difference in disease severity levels between the fully vaccinated group and the one-dose vaccinated (p < 0.023). The severe disease occurred in 2 patients after vaccination, who were subsequently admitted to the hospital.There was a significant difference between the number of kidney transplant days and infection with SARS-CoV-2 before (P = 0.15) and after vaccination (p < 0.015). ConclusionEven after vaccination, kidney recipients are still at the risk of contracting SARS-CoV-2. In addition to these results, the efficacy of vaccination in preventing death caused by SARS-CoV-2 was confirmed.

Context-aware deconvolution of cell–cell communication with Tensor-cell2cell

Cell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, and tissue microenvironment. Single-cell technologies measure the molecules mediating cell–cell communication, and emerging computational tools can exploit these data to decipher intercellular communication. However, current methods either disregard cellular context or rely on simple pairwise comparisons between samples, thus limiting the ability to decipher complex cell–cell communication across multiple time points, levels of disease severity, or spatial contexts. Here we present Tensor-cell2cell, an unsupervised method using tensor decomposition, which deciphers context-driven intercellular communication by simultaneously accounting for multiple stages, states, or locations of the cells. To do so, Tensor-cell2cell uncovers context-driven patterns of communication associated with different phenotypic states and determined by unique combinations of cell types and ligand-receptor pairs. As such, Tensor-cell2cell robustly improves upon and extends the analytical capabilities of existing tools. We show Tensor-cell2cell can identify multiple modules associated with distinct communication processes (e.g., participating cell–cell and ligand-receptor pairs) linked to severities of Coronavirus Disease 2019 and to Autism Spectrum Disorder. Thus, we introduce an effective and easy-to-use strategy for understanding complex communication patterns across diverse conditions.

Development of a chromatographic lateral flow immunoassay for detection of African swine fever virus antigen in blood

African swine fever (ASF) is a highly lethal disease of domestic and wild swine caused by African swine fever virus (ASFV). The disease currently circulates in Africa, Europe, Asia and on the island of Hispaniola. The ongoing epizootics in Europe and Asia have produced millions of animal deaths and severe economic losses. No effective vaccine is available for ASF, making rapid and accurate detection of ASFV essential for disease mitigation strategies. Currently available diagnostics for ASFV possess significant limitations related to assay performance, deployability, and/or turn-around time; therefore there is an unmet need for pen-side diagnostic tests with sufficient sensitivity and specificity. A chromatographic lateral flow immunoassay (LFIA) was developed for the detection of ASFV antigen in EDTA-treated whole blood using monoclonal antibodies targeting the viral p30 protein. The assay requires only water to perform and provides results in 25 min, making it well-suited for field use. The LFIA was capable of detecting genotype I and genotype II strains of ASFV in EDTA blood from experimentally infected pigs at varying time-points after infection, though it was unable to detect a genotype X ASFV strain. Diagnostic sensitivity correlated with clinical disease severity, body temperature, and viral DNA levels, and was over 90% in animals showing moderate to severe ASF-related symptoms after challenge with virulent genotype II virus. The LFIA also showed a robust diagnostic specificity of over 98%, which is essential to field testing for a high consequence to foregin animal disease. The LFIA targeting the viral p30 protein can reliably detect ASFV in whole blood from animals showing moderate to severe clinical signs of infection with virulent genotype I and II isolates, making it a promising candidate for use as a field-deployable antigen detection assay. Additional evaluation using field samples and different virus strains is required to further assess the utility of this rapid diagnostic test.

Genetic diversity of the pea root pathogen Aphanomyces euteiches in Europe

AbstractThe oomycete pathogen Aphanomyces euteiches causes root rot in various legume species. In this study we focused on A. euteiches causing root rot in pea (Pisum sativum), thereby being responsible for severe yield losses in pea production. We aimed to understand the genetic diversity of A. euteiches in Europe, covering a north‐to‐south gradient spanning from Sweden, Norway and Finland to the UK, France and Italy. A collection of 85 European A. euteiches strains was obtained, all isolated from infected pea roots from commercial vining pea cultivation fields. The strains were genotyped using 22 simple‐sequence repeat markers. Multilocus genotypes were compiled and the genetic diversity between individual strains and population structure between countries was analysed. The population comprising strains from Italy was genetically different and did not share ancestry with any other population. Also, strains originating from Finland and the eastern parts of Sweden were found to be significantly different from the other populations, while strains from the rest of Europe were more closely related. A subset of 10 A. euteiches strains from four countries was further phenotyped on two susceptible pea genotypes, as well as on one genotype with partial resistance towards A. euteiches. All strains were pathogenic on all pea genotypes, but with varying levels of disease severity. No correlation between the genetic relatedness of strains and virulence levels was found. In summary, our study identified three genetically distinct groups of A. euteiches in Europe along a north‐to‐south gradient, indicating local pathogen differentiation.

Congenital Heart Disease: Growth Evaluation and Sport Activity in a Paediatric Population.

(1) Objective: To evaluate: (i) the associations of age and disease severity with anthropometric indices and weight status, (ii) the difference in the frequency of sports activity among different levels of disease severity in paediatric patients with congenital heart disease (CHD). (2) Methods: Clinical data of Caucasian children (aged 2–18 years) diagnosed with CHD (2005–2018) were retrospectively collected from the electronic register of outpatient visits. Of the 475 children with CHD, 368 children and their 1690 complete anthropometric measurements were eligible for inclusion in our analysis. (3) Results: Significant increase with age was observed for weight z-score [beta (95%CI): 0.03 (0.02, 0.05) for one-unit of age] and BMI z-score [0.06 (0.03, 0.08)] but not for height z-score. The probability of being underweight and overweight/obese increased and decreased with disease severity, respectively. The obesity probability of patients with mild CHD (0.06 [95%CI: 0.03, 0.08]) was not statistically distinguishable from that of patients with moderate CHD (0.03 [95%CI: 0.02, 0.05]), whereas it was lower in patients with severe CHD (0.004 [95%CI: 0.0, 0.009]). No obese patients with a univentricular heart defect were observed. Days spent in sport activities were equal to 1.9 [95%CI: 1.6, 2.2] days/week, 1.9 [1.5, 2.2], 1.4 [1.1, 1.7] and 0.7 [0.1, 1.3] in patients with mild, moderate, severe and univentricular CHD, respectively. (4) Conclusions: The risk of being overweight and obese should not be underestimated in paediatric patients diagnosed with CHD, especially in children with mild or moderate heart defects. It could be prevented or reduced by promoting a healthy lifestyle.

Does the rubella immunoglobulin G affect the severity of COVID- 19?

Objective & aimThe coronavirus disease, so far (COVID-19) has brought about millions of infections and fatalities throughout the world. Our aim was to determine the correlation between rubella IGG titers with the severity COVID-19. Materials & methodsThis study was conducted among COVID-19 confirmed patients over 18 years of age. The disease severity levels were categorized by WHO interim guidance. The rubella-specific IgG antibody-titer spectrum was measured (within first 48 h of hospitalization) by enzyme-linked immunosorbent assay (ELISA).ResultIn a study of 46 inpatients with varying COVID-19 disease severity (mild, moderate, severe, and critical), we observed a negative correlation between rubella IgG antibody titers and COVID‐19 severity (P-Value = 0.017), There was an interaction between COVID-19 vaccination history and rubella IGG on severity COVID-19 (P-Value = 0.0015). There was an interaction between age group under 44 years (including national measles- rubella (MR) vaccination in Iran) and rubella IGG titers on severity COVID-19 too (p-value = 0.014).ConclusionIn conclusion, MR vaccination seems to have a positive effect in reducing the severity of the disease, emphasizing that, the important and separate effect of the IGG rubella (due to natural or extrinsic immunity) titers is determining.

Determination of Risk Factors and Some Biomarkers Parameters during Infected Iraqis with Covid-19

Covid-19 is a global challenge that drives health care to its limits. Biological parameters associated with increased risk of severe or fatal disease courses were identified, including conditions connected with a poor state of health, organ damage, and coagulation dysfunction. In a recent study, risk factors like age, sex, blood group (ABO), smoking, and several biomarkers like white blood cells, lymphocytes, C-reactive protein (CRP), ferritin, D-dimer, and potassium level were considered. One hundred nasopharyngeal swabs and blood samples were collected from Iraqi patients and classified according to the severity of the disease into five groups: Asymptomatic, Mild, Moderate, Severe, and Deceased, according to the recommendations of the World Health Organization (WHO). The current study was based on the risk factors and their effect on disease severity (age, sex, blood type, and smoking). As a result, there was a substantial positive linear link (R2=0.91) between getting older and increasing disease severity. Study results were showed a little statistically significant difference in the number of males and females infected with SARS-CoV-2. Interestingly, males were shown to be more susceptible to infection than females. Also, because type (O) blood is more extensively distributed in the Middle East population than the other blood types, those with type (O) blood are more susceptible to infection. Because smokers and non-smokers were distributed at random across different disease severity levels, there was no statistically significant link between smoking status and COVID-19 severity. All parameters (plasma protein and liver enzymes) showed statistically significant differences, especially between the deceased groups except K level, which did not differ significantly in all groups. This study aimed to investigate some biological markers during infection to see if there was a link between these measurements and risk factors, as well as the severity and progression of the disease.

Excess costs of mental disorders by level of severity

IntroductionMental disorders are highly prevalent in Germany, and associated with decreased quality of life for those affected as well as high economic burden for the society. The purpose of this study was to determine the excess costs of mental disorders and to examine how these differ with respect to disease severity.MethodsWe analyzed mean 6-month costs using the baseline data from the RECOVER trial in Hamburg, Germany, which evaluates an innovative stepped-care model for mental disorders. Four severity levels were classified based on the current level of mental illness, loss of functioning, and psychiatric diagnosis. In this work, direct costs (outpatient, inpatient, and social/informal care) and indirect costs (sick leave, unemployment, and early retirement) were estimated using interview-based data on health care utilization and productivity losses. Excess costs were determined by matching a comparison group of the German general population without mental disorders. Group differences in sociodemographic covariates and somatic comorbidities were balanced using entropy balancing. Excess costs by severity levels were estimated using generalized linear models (GLM) with gamma distribution and log-link function.ResultsOverall, the RECOVER group included n = 816 and the comparison group included n = 3226 individuals. Mean total 6-month excess costs amounted to 19,075€, with higher indirect excess costs (13,331€) than direct excess costs (5744€) in total excess costs. The excess costs increased with increasing disease severity, ranging from 6,123€ with mild disease severity (level 1) to 31,883€ with severe mental illness (level 4). Indirect excess costs ranged from 5612€ in level 1 to 21,399€ in level 4, and were statistically significant for all disease severity levels. In contrast, direct excess costs were only statistically significant for the levels 2 to 4, and ranged from 511€ in level 1 to 10,485€ in level 4. The main cost drivers were hospital stays (level 2–4), sick leave and unemployment (all levels), and early retirement (level 3–4).DiscussionMental disorders are associated with high costs that increase with the level of disease severity, which was also shown for individual ICD-10 diagnosis groups. Due to their influence on costs, indirect costs and disease severity levels should be considered in future cost-of-illness studies of mental disorders.Clinical trial registrationclinicaltrials.gov, trial registration number NCT03459664.

Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.

Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.

Quantitative Computed Tomography Parameters in Coronavirus Disease 2019 Patients and Prediction of Respiratory Outcomes Using a Decision Tree.

BackgroundChest computed tomography (CT) scans play an important role in the diagnosis of coronavirus disease 2019 (COVID-19). This study aimed to describe the quantitative CT parameters in COVID-19 patients according to disease severity and build decision trees for predicting respiratory outcomes using the quantitative CT parameters.MethodsPatients hospitalized for COVID-19 were classified based on the level of disease severity: (1) no pneumonia or hypoxia, (2) pneumonia without hypoxia, (3) hypoxia without respiratory failure, and (4) respiratory failure. High attenuation area (HAA) was defined as the quantified percentage of imaged lung volume with attenuation values between −600 and −250 Hounsfield units (HU). Decision tree models were built with clinical variables and initial laboratory values (model 1) and including quantitative CT parameters in addition to them (model 2).ResultsA total of 387 patients were analyzed. The mean age was 57.8 years, and 50.3% were women. HAA increased as the severity of respiratory outcome increased. HAA showed a moderate correlation with lactate dehydrogenases (LDH) and C-reactive protein (CRP). In the decision tree of model 1, the CRP, fibrinogen, LDH, and gene Ct value were chosen as classifiers whereas LDH, HAA, fibrinogen, vaccination status, and neutrophil (%) were chosen in model 2. For predicting respiratory failure, the decision tree built with quantitative CT parameters showed a greater accuracy than the model without CT parameters.ConclusionsThe decision tree could provide higher accuracy for predicting respiratory failure when quantitative CT parameters were considered in addition to clinical characteristics, PCR Ct value, and blood biomarkers.

Correlation between Intestinal Microflora in Irritable Bowel Syndrome and Severity.

Background Irritable bowel syndrome (IBS) is a common chronic functional gastrointestinal disease accompanied by changes in intestinal microecology. This study investigated the relationship between gut microbiota and disease severity in patients with irritable bowel syndrome (IBS). Methods An observational study was performed on 60 IBS patients (study group) and 20 healthy controls admitted to our hospital from January 2013 to December 2014. Fecal samples were taken after admission to measure intestinal flora including Bifidobacterium, Lactobacillus, Enterobacter, and Enterococcus, and patient blood was collected to determine serum D-lactate and diamine oxidase (DAO) levels. The gut microbiota and serum markers of the two groups were analyzed. The correlation of gut microbiota index levels and serum markers with disease severity, as well as the correlation between gut microbiota index levels and serum markers, were analyzed. Results The levels of intestinal Lactobacillus and Bifidobacterium were lower, while the levels of Enterococcus and Enterobacter and serum D-lactate were higher in the study group than those in the control group. The levels of intestinal Lactobacillus and Bifidobacterium were lower, while the levels of Enterococcus and Enterobacter, serum D-lactate, and DAO were higher in patients with moderate IBS than those in patients with mild IBS. The levels of intestinal Lactobacillus and Bifidobacterium were lower in patients with severe IBS than those with moderate IBS, while the levels of Enterococcus and Enterobacter, serum D-lactate, and DAO were higher in patients with severe IBS. There was a significant negative correlation between the levels of Lactobacillus and Bifidobacterium and disease severity and a significant positive correlation between the levels of Enterococcus and Enterobacter, D-lactate, and DAO and disease severity. There was a significant negative correlation between the levels of Lactobacillus and Bifidobacterium and serum D-lactate and DAO, while there was a significant positive correlation between the levels of Enterococcus and Enterobacter and serum D-lactate and DAO (P < 0.05). Conclusion Intestinal flora, D-lactate, and DAO were abnormal in IBS patients, and intestinal flora was closely correlated with disease severity, D-lactate, and DAO levels.

Cognitive disorders and sleep disturbances in long COVID

HintergrundIn den letzten 2 Jahren der COVID-19(„coronavirus disease 2019“)-Pandemie ist das Wissen um Langzeitfolgen der Erkrankung, das sog. „Long-COVID“, rapide gewachsen. Es bleiben jedoch noch viele Fragen offen, v. a. was die Ursachen überdauernder Beschwerden und ihre Prognose betrifft. Kognitive Störungen und Schlafstörungen gehören zu den häufig beklagten Beschwerden. Beide gehen mit starkem Leidensdruck und deutlicher Alltagsbeeinträchtigung einher.Ziel der ArbeitWie ist die Datenlage zum Auftreten kognitiver Störungen und Schlafstörungen bei Long-COVID? Welches sind Einflussfaktoren und was ist bekannt zum Verlauf und zu möglichen zugrunde liegenden Mechanismen? Welche Therapieoptionen gibt es?Material und MethodeIn einem narrativen Review werden die wichtigsten Befunde zu kognitiven Störungen und Schlafstörungen bei Long-COVID dargestellt. Es wird ein Überblick gegeben über die Kohortenstudien mit Daten zu Prävalenz und Einflussfaktoren beider Symptomkomplexe. Es werden derzeitige Kenntnisse und Hypothesen zu pathophysiologischen Mechanismen dargestellt und ein Ausblick auf Behandlungsansätze gegeben.ErgebnisseEtwa ein Fünftel der Betroffenen berichtet mehr als 3 Monate nach einer SARS-CoV-2(„severe acute respiratory syndrome coronavirus 2“)-Infektion über kognitive Einschränkungen, etwa ein Drittel über Schlafstörungen, wobei es neben insomnischen auch zu hypersomnische Beschwerden kommt. Kognitive Störungen und Schlafstörungen treten bei Betroffenen aller Schweregrade auf. Es gibt Hinweise auf eine Besserung kognitiver Defizite im Verlauf, allerdings sind weitere Längsschnittstudien notwendig.DiskussionNeben der Prognose sind die zugrunde liegenden Krankheitsmechanismen noch unzureichend verstanden. Zudem besteht großer Forschungsbedarf zur Wirksamkeit und zu spezifischen Wirkfaktoren therapeutischer Interventionen.

Identification of Anemia and Its Severity Level in a Peripheral Blood Smear Using 3-Tier Deep Neural Network

The automatic detection of blood cell elements for identifying morphological deformities is still a challenging research domain. It has a pivotal role in cognition and detecting the severity level of disease. Using a simple microscope, manual disease detection, and morphological disorders in blood cells is mostly time-consuming and erroneous. Due to the overlapped structure of RBCs, pathologists face challenges in differentiating between normal and abnormal cell shape and size precisely. Currently, convolutional neural network-based algorithms are effective tools for addressing this issue. Existing techniques fail to provide effective anemia detection, and severity level prediction due to RBCs’ dense and overlapped structure, non-availability of standard datasets related to blood diseases, and severity level detection techniques. This work proposed a three tier deep convolutional fused network (3-TierDCFNet) to extract optimum morphological features and identify anemic images to predict the severity of anemia. The proposed model comprises two modules: Module-I classifies the input image into two classes, i.e., Healthy and Anemic, while Module-II detects the anemia severity level and categorizes it into Mild or Chronic. After each tier’s training, a validation function is employed to reduce the inappropriate feature selection. To authenticate the proposed model for healthy, anemic RBC classification and anemia severity level detection, a state-of-the-art anemic and healthy RBC dataset was developed in collaboration with Shaukat Khanum Hospital and Research Center (SKMCH&amp;RC), Pakistan. To evaluate the proposed model, the training, validation, and test accuracies were computed along with recall, F1-Score, and specificity. The global results reveal that the proposed model achieved 91.37%, 88.85%, and 86.06% training, validation, and test accuracies with 98.95%, 98.12%, and 98.12% recall F1-Score and specificity, respectively.

Clustering of EORTC QLQ-C30 health-related quality of life scales across several cancer types: Validation study

IntroductionThe European Organisation for Research and Treatment of Cancer Quality of Life Core Questionnaire (EORTC QLQ-C30) measures 15 health-related quality of life (HRQoL) scales relevant to the disease and treatment of patients with cancer. A study by Martinelli (2011) demonstrated that these scales could be grouped into three main clusters: physical, psychological and gastrointestinal. This study aims to validate Martinelli's findings in an independent dataset and evaluate whether these clusters are consistent across cancer types and patient characteristics. MethodsPre-defined criteria for successful validation were three main clusters should emerge with a minimum R-squared value of 0.51 using pooled baseline-data. A cluster analysis was performed on the 15 QLQ-C30 HRQoL-scales in the overall dataset, as well as by cancer type and selected patient characteristics to examine the robustness of the results. ResultsThe dataset consisted of 20,066 patients pooled across 17 cancer types. Overall, three main clusters were identified (R2 = 0.61); physical-cluster included role-functioning, physical-functioning, social-functioning, fatigue, pain, and global-health status; psychological-cluster included emotional-functioning, cognitive-functioning, and insomnia; gastro-intestinal-cluster included nausea/vomiting and appetite loss. The results were consistent across different levels of disease severity, socio-demographic and clinical characteristics with minor variations by cancer type. Global-health status was found to be strongly linked to the scales included in the physical-functioning-related cluster. ConclusionThis study successfully validated prior findings by Martinelli (2011): the QLQ-C30 scales are interrelated and can be grouped into three main clusters. Knowing how these multidimensional HRQoL scales are related to each other can help clinicians and patients with cancer in managing symptom burden, guide policymakers in defining social-support plans and inform selection of HRQoL scales in future clinical trials.

Soluble ACE2 and angiotensin II levels are modulated in hypertensive COVID-19 patients treated with different antihypertension drugs

Purpose This study examines the effect of antihypertensive drugs on ACE2 and Angiotensin II levels in hypertensive COVID-19 patients. Introduction Hypertension is a common comorbidity among severe COVID-19 patients. ACE2 expression can be modulated by antihypertensive drugs such as ACEis and ARBs, which may affect COVID-19's prognosis. BB and CCB reduce mortality, according to some evidence. Their effect on circulating levels of ACE2 and angiotensin II, as well as the severity of COVID-19, is less well studied. Materials and methods The clinical data were collected from 200 patients in four different antihypertensive medication classes (ACEi, ARB, BB, and CCB). Angiotensin II and ACE2 levels were determined using standard ELISA kits. ACE2, angiotensin II, and other clinical indices were evaluated by linear regression models. Results Patients on ACEi (n = 57), ARB (n = 68), BB (n = 15), or CCB (n = 30) in this study had mild (n = 76), moderate (n = 76), or severe (n = 52) COVID-19. ACE2 levels were higher in COVID-19 patients with severe disease (p = 0.04) than mild (p = 0.07) and moderate (p = 0.007). The length of hospital stay is correlated with ACE2 levels (r = 0.3, p = 0.003). Angiotensin II levels decreased with severity (p = 0.04). Higher ACE2 levels are associated with higher CRP and D-dimer levels. Elevated Angiotensin II was associated with low levels of CRP, D-dimer, and troponin. ACE2 levels increase with disease severity in patients taking an ARB (p = 0.01), patients taking ACEi, the degree of disease severity was associated with a decrease in angiotensin II. BB patients had the lowest disease severity. Conclusion We found different levels of soluble ACE2, and angiotensin II are observed among COVID-19 patients taking different antihypertensive medications and exhibiting varying levels of disease severity. COVID-19 severity increases with elevated ACE2 levels and lower angiotensin II levels indicating that BB treatment reduces severity regardless of levels of ACE2 and angiotensin II.

Increased Resilience of Peas Toward Root Rot Pathogens Can Be Predicted by the Nematode Metabolic Footprint

Legumes are important drivers of soil fertility, however, their frequent use in rotations fosters long-lived soil-borne pathogens that can seriously compromise legume root health and nitrogen fixation. To overcome this, the current study aims at improving the general soil suppressiveness toward pests and diseases by agroecosystem management that can be predicted by nematode-based bioindicators. Two long-term organically managed agroecosystems comparing plow and shallow non-inversion tillage were analyzed for free-living nematode communities. Soils out of these agroecosystems were evaluated further in a greenhouse assay for their ability to suppress pea root rot caused by Didymella pinodella, Fusarium avenaceum, and F. redolens. There was a general trend for higher levels of pea root rot disease severity following inoculations with single pathogens, however, this effect was heterogeneous among experiments and tillage systems. This was mainly due to an already very high resident population of D. pinodella in soil and the presence of seed-borne F. oxysporum determined by their high incidence in pea roots irrespective of the soil and inoculated pathogens. Additional inoculation with D. pinodella, for example, resulted in only 8.5% biomass reduction compared to the non-inoculated control, in both tillage systems. Similar biomass losses were recorded in non-inversion tilled soils inoculated with F. redolens. When analyzed across inoculation treatments, the pea root rot disease severity was only slightly reduced in non-inversion tilled soils when compared to the plough systems (11% in Exp 1 and, 9% in Exp 2), however in both experiments non-inversion tillage resulted in greater pea biomass (33 and 19% in Exp1 and 2, respectively). Furthermore, the metabolic, enrichment, and bacterivore carbon footprints of nematodes were 88, 81, and 97% higher, respectively, in the non-inversion tilled soils compared to the plough. The metabolic carbon footprint of nematodes correlated negatively with pea root rot disease severity (rho = −0.71, p = 0.047). Hence, non-inversion tillage was effective in controlling pea root rot. The use of nematode metabolic footprints for predicting soil health should be extended for various agroecosystems aiming for its general use in evaluating effects of agroecosystem management through researchers and potentially farm management advisors.

COVID-19 and Autoimmune Liver Diseases.

SARS-CoV-2 infection can trigger autoimmune responses, either by a systemic hyperstimulation of the immune system or molecular mimicry (or both). We here summarize the current knowledges about autoimmune liver diseases (AILDs) and COVID-19, focusing on (a) the risk of SARS-CoV-2 infection in patients affected by AILDs and/or under pharmacological treatment with immunosuppressants; (b) the capability of vaccination against SARS-CoV-2 to trigger autoimmune responses in the liver; and (c) the efficacy of vaccines against SARS-CoV-2 in patients with AILDs. Although unconclusive results have been obtained regarding the risk of being infected by SARS-CoV-2, generally indicating that all patients with chronic liver diseases have the same risk, irrespective of the etiology, the use of immunosuppressants in patients with AILDs seems to be correlated to COVID-19 severity. Few cases of autoimmune hepatitis (AIH) after SARS-CoV-2 vaccination have been reported, all characterized by a complete remission upon steroid treatment, but further evidence is needed to demonstrate the causality assessment. Humoral responses have been observed in patients with AILDs upon vaccination. In conclusion, the link between SARS-CoV-2 infection and AILDs is far to be completely elucidated. In these patients, the use of immunosuppressants has been correlated to an increase of disease severity and lower levels of antibodies upon vaccination.