Levels Of Disease Severity Research Articles

Stigmatization in psoriasis vulgaris: a qualitative study

Background: Psoriasis vulgaris is an autoimmune chronic inflammatory disease of the skin, which has become a global problem, with at least 100 million people affected. Although not life-threatening, psoriasis vulgaris affects the patient's life regarding physical appearance which can lead to shame, stigmatization, as well as mental health, thus affecting the quality of life. Objective: Qualitatively analyze about stigma and its psychological impact in psoriasis vulgaris patients. Research Method: A case study of a qualitative study to observe at the problem in depth and thoroughly. Subjects were recruited through outpatient clinic at the Department of Dermatology and Venereology, dr. Soetomo Hospital, Surabaya, Indonesia, with snowball sampling techniques, and conducted by telephone call. Results: The six informants, three men and three women, with range of 37 to 49 years old, married, with various levels of disease severity, revealing stigma of psoriasis vulgaris, and its psychological impact. Psoriasis vulgaris is a complex condition, having challenges to the informants' physical, psychological and social conditions. Conclusion: Living with a chronic skin disease such as psoriasis vulgaris can affect an individual's life in different ways in certain cultural settings and situations. Understanding the stigma and psychological impact of psoriasis vulgaris will be able to help patients openly share their discomfort so that they can develop more efficient treatment strategies for psoriasis vulgaris patients.

Neuropathic pain in primary knee osteoarthritis patients: correlation with physical function, quality of life, disease severity, and serum beta nerve growth factor levels

BackgroundNeuropathic mechanisms are thought to play a role in knee osteoarthritis (KOA) pain. Neuropathic pain questionnaires can promote diagnosis of a neuropathic component. Thus, we aimed to assess the frequency of neuropathic pain in primary KOA patients (using clinical questionnaires) and to investigate its correlation with socio-demographic factors, physical function, quality of life, disease severity, and serum beta nerve growth factor (β-NGF) levels.ResultsSeventy primary KOA patients were included. Neuropathic pain was detected in 52.9% of patients based on Douleur Neuropathique en 4 Questions (DN4) questionnaire and in 38.6% of patients based on Leeds assessment neuropathic pain symptoms and signs questionnaire (LANSS). Serum β-NGF levels were significantly higher in KOA patients than controls (P<0.0001), and in KOA patients with neuropathic pain compared with patients with non-neuropathic pain. DN4 score was positively correlated with Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain, stiffness, and physical function, and it was also negatively correlated with Osteoarthritis knee hip quality of life questionnaire (OAKHQOL) pain scores (rs=0.459, P<0.001; rs= 0.258, P= 0.031; rs= 0.307, P= 0.010; rs = −0.337, P= 0.004, respectively), while LANSS scale was positively correlated with symptom duration, WOMAC stiffness, Lequesne pain, and Lequesne index (rs= 0.260, P= 0.020; rs= 0.343, P= 0.004; rs= 0.344, P= 0.004; rs= 0.322, P= 0.007) and negatively correlated with OAKHQOL physical, OAKHQOL mental health, OAKHQOL social support, and total OAKHQOL scores (rs= −0.258, P= 0.031;rs= −0.254, P= 0.034; rs= −0.283, P= 0.018; rs= −0.261, P= 0.029 respectively).ConclusionsNeuropathic pain symptoms are frequent in primary KOA patients. KOA patients with neuropathic pain have worse quality of life, extreme disability, and higher serum β-NGF levels. Nerve growth factor inhibitors could have a potential role for not only relieving pain in KOA patients but also improving functional disability and quality of life in these patients.

Clinical and Immunological Assessment of Patients with Sars-Cov-2 Infections

▪Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induced coronavirus disease-2019 (COVID-19) has presented humanity with unprecedented challenges. Severe disease is associated with acute respiratory distress syndrome (ARDS), use of mechanical ventilation, ICU stay and prolonged hospitalization, The role of the immune system in the pathogenesis of COVID-19 disease is still unclear, which imposes limitations on identifying potential immunotherapy that can improve care for acute and chronic phases of COVID-19 in conjunction with current therapies. Research efforts are ongoing for more than 1 year to identify key immunological mechanisms involved in the disease process. While insightful, this knowledge is still incomplete and can be complemented with the assessment of immune response kinetics. Such assessment will help with the identification of early interventional modalities of immune cell regulation. With these considerations in mind, we aimed to assess several parameters of immune system regulation during the current medical care of patients with COVID-19.Methods: This is a pre-clinical prospective cohort study which involved laboratory-based assessments of blood samples obtained from COVID-19 patients and healthy volunteers. The study population was divided into three cohorts. Our first cohort included 18 years and older COVID-19 patients with respiratory complaints, oxygen (O2) saturations of less than or equal to 92 and pulmonary infiltrates on an imaging study or who were critically ill and required ventilatory support. Second cohort included 18 years and older COVID-19 patients who were hospitalized and did not require ventilatory support. Third cohort included participants with no prior diagnosis of COVID-19, or any recent viral respiratory symptoms including fever, cough or shortness of breath for the last 2 weeks. Patients with an established diagnosis of cancer or immunologic disorders were excluded. Blood specimens were collected over the period of hospitalization: specimen number 1 on day 1-3 of hospitalization, specimen number 2 on days 3-4 of hospitalization, specimen number 3 on days 5-7 of hospitalization, and specimen number 4 on 7-30 days after discharge. We performed capillary electrophoresis for serology and automated ELISA for cytokine measurement. We collected clinical data on patient demographic, clinical characteristics such as presence of any acute and chronic comorbidities and serum inflammatory markers C-Reactive Protein, D-Dimer and Ferritin.Results: We had 15 patients in cohort 1, 10 in cohort 2 and 15 in cohort 3. Patients in cohort 1 were older and had higher comorbidities. Males constituted a substantially high percentage of patients in cohort 1 and 2 (60% and 70% respectively). Patients had similar BMI in cohort 1 and 2. Total antibody levels were highest in cohort 1 but an upward trend over the course of hospitalization was noted in all cohorts. Most interesting pattern was noted in the context of antibodies against spike protein S1 receptor-binding domain (S1RBD) where patients in cohort 2 developed minimal S1RBD antibodies. Cohort 1 on average had higher levels of Interleukin 6(IL-6), Interleukin 8(IL-8), C-X-C motif chemokine ligand 10 (CXCL10) and other inflammatory cytokines except Interferon gamma (IFN-gamma) compared to Cohort 2. Remarkable difference in CXCL-10 levels was noted between the groups and healthy volunteers had the lowest levels. No significant difference in IFN-gamma was noted between cohorts and the levels quickly depleted over the course of the infection.Conclusion: Our analysis confirms that neutralizing antibodies do not correlate with lessened COVID-19 disease severity. Severe COVID-19 infection is secondary to ineffective innate immunity associated with immune overshoot. CXCL10 serves as a major component in triggering the cytokine storm that is a hallmark of SARS-CoV-2 infections. Our findings show an association between high levels of CXCL10 and more severe COVID-19 infection. There does not seem to be any significant correlation with disease severity and IFN-gamma levels. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

In vivo and in silico Virulence Analysis of Leptospira Species Isolated From Environments and Rodents in Leptospirosis Outbreak Areas in Malaysia.

The zoonotic disease leptospirosis is caused by pathogenic species of the genus Leptospira. With the advancement of studies in leptospirosis, several new species are being reported. It has always been a query, whether Leptospira species, serovars, and strains isolated from different geographical locations contribute to the difference in the disease presentations and severity. In an epidemiological surveillance study performed in Malaysia, we isolated seven novel intermediate and saprophytic species (Leptospira semungkisensis, Leptospira fletcheri, Leptospira langatensis, Leptospira selangorensis, Leptospira jelokensis, Leptospira perdikensis, Leptospira congkakensis) from environments and three pathogenic species from rodents (Leptospira borgpetersenii strain HP364, Leptospira weilii strain SC295, Leptospira interrogans strain HP358) trapped in human leptospirosis outbreak premises. To evaluate the pathogenic potential of these isolates, we performed an in vivo and in silico virulence analysis. Environmental isolates and strain HP364 did not induce any clinical manifestations in hamsters. Strain SC295 caused inactivity and weight loss with histopathological changes in kidneys, however, all hamsters survived until the end of the experiment. Strain HP358 showed a high virulent phenotype as all infected hamsters died or were moribund within 7 days postinfection. Lungs, liver, and kidneys showed pathological changes with hemorrhage as the main presentation. In silico analysis elucidated the genome size of strain HP358 to be larger than strains HP364 and SC295 and containing virulence genes reported in Leptospira species and a high number of specific putative virulence factors. In conclusion, L. interrogans strain HP358 was highly pathogenic with fatal outcome. The constituent of Leptospira genomes may determine the level of disease severity and that needs further investigations.

Near Real Time Monitoring of Potato Late Blight Disease Severity using Field Based Hyperspectral Observation

Field spectroscopic study was performed using a hand-held Field Spectroradiometer to examine spectral variability between healthy and late blight disease infected potato canopy. The purpose was to select a suitable spectral feature in the visible-near infrared region for late blight disease initiation and severity during winter season. The spectral regions at which significant differences in bio-optical response was observed between healthy and diseased canopy include, 680-730nm (47.84%), 750-900nm (76.14%) and 860-1040nm (68.60%). Correlation study was carried out among different spectral variables, sensitive to PLB disease, and field measured PLB disease severity. Out of all the spectral variables, Red-Edge Normalised Difference Vegetation Index (NDVI705) and Disease Water Stress Index (DWSI) showed significant negative correlation (0.87 and 0.84 at 95% confidence level) and capable to predict the different level of potato late blight disease severity. A remote sensing based novel disease severity method was developed from the above mentioned spectral variables using multi-linear regression model and validated with very high correlation (R2 = 0.883). The scoring method developed could be a good proximal indicator for real-time field monitoring of potato late blight disease.

Relationships between Demographic Factors and Chronic Conditions with Disease Severities.

Disease severities are the outcomes of an inpatient visit classification that assigns a diagnostic related group, including risk of mortality and severity of illness. Although widely used in healthcare, the analysis of factors affecting disease severities has not been adequately studied. In this study, we analyze the relationships between demographics and chronic conditions and specify their influence on disease severities. Descriptive statistics are used to investigate the relationships and the prevalence of chronic conditions. To evaluate the influence of demographic factors and chronic conditions on disease severities, several multinomial logistic regression models are performed and prediction models for disease severities are conducted based on National Inpatient Sample data for 2016 provided by the Healthcare Cost and Utilization Project database in the United States. The rate of patients with a chronic illness is 88.9% and the rate of patients with more than two chronic conditions is 67.6%; further, the rate is 62.7% for females, 73.9% for males, and 90% for the elderly. A high level of disease severity commonly appears in patients with more than two chronic conditions, especially in the elderly. For patients without chronic conditions, disease severities show a lower or safe level, even in the elderly.

Circulating Extracellular Vesicles Are Associated with Disease Severity and Interleukin-6 Levels in COPD: A Pilot Study.

Chronic obstructive pulmonary disease (COPD) is a complex condition in which systemic inflammation plays a role in extrapulmonary manifestations, including cardiovascular diseases: interleukin (IL)-6 has a role in both COPD and atherogenesis. The 2011 GOLD document classified patients according to FEV1, symptoms, and exacerbations history, creating four groups, from A (less symptoms/low risk) to D (more symptoms/high risk). Extracellular vesicles (EV) represent potential markers in COPD: nevertheless, no studies have explored their value in association to both disease severity and inflammation. We conducted a pilot study to analyze circulating endothelial-(E) and monocyte-derived (M) EV levels in 35 COPD patients, who were grouped according to the 2011 GOLD document; the relationship between EV and plasmatic markers of inflammation was analyzed. We found a statistically significant trend for increasing EEV, MEV, IL-6, from group A to D, and a significant correlation between EEV and IL-6. The associations between both EEV and MEV and disease severity, and between EEV and IL-6, suggest a significant interplay between pulmonary disease and inflammation, with non-respiratory cells (endothelial cells and monocytes) involvement, along with the progression of the disease. Thus, EV might help identify a high-risk population for extrapulmonary events, especially in the most severe patients.

Serum Soluble OX40 as a Diagnostic and Prognostic Biomarker for Drug-Induced Hypersensitivity Syndrome/Drug Reaction with Eosinophilia and Systemic Symptoms

Drug-induced hypersensitivity syndrome/drug reaction with eosinophilia and systemic symptoms (DIHS/DRESS) is a severe adverse drug reaction commonly associated with the reactivation of human herpesvirus 6 (HHV-6). There are currently no adequate biomarkers for the early diagnosis and detection of DIHS/DRESS. Notably, OX40 (CD134) has an important role in allergic inflammation and functions as a cellular receptor for HHV-6 entry. We previously reported that the membrane-bound form of OX40 in CD4+ T cells was upregulated in DIHS/DRESS. We sought to investigate the clinical significance of serum soluble OX40 (sOX40) in DIHS/DRESS. Serum sOX40 levels in patients with DIHS/DRESS (n= 39), maculopapular exanthema/erythema multiforme (n= 17), Stevens-Johnson syndrome/toxic epidermal necrolysis (n= 13), or autoimmune bullous diseases (n= 5), and levels in healthy volunteers (n= 5) were examined by enzyme-linked immunosorbent assay. Copy numbers of HHV-6, HHV-7, and cytomegalovirus in peripheral blood mononuclear cells were quantified using real-time PCR. Serum sOX40 levels in patients with DIHS/DRESS in the acute stage were elevated in parallel with high OX40 expression on CD4+ T cells. Serum sOX40 levels were significantly positively correlated with disease severity and serum levels of thymus and activation-regulated chemokine, IL-5, and IL-10. Human herpesvirus 6-positive patients had higher sOX40 levels than did HHV-6-negative patients, and serum sOX40 levels were correlated with HHV-6 DNA loads. Serum sOX40 levels can be a useful diagnostic marker for DIHS/DRESS that reflect disease severity. Elevated serum sOX40 levels also predict HHV-6 reactivation in patients with DIHS/DRESS.

The cost of clinical management of SARS-COV-2 (COVID-19) infection by level of disease severity in Ghana: a protocol-based cost of illness analysis

BackgroundAs the global strategies to fight the SARS-COV-2 infection (COVID-19) evolved, response strategies impacted the magnitude and distribution of health-related expenditures. Although the economic consequence of the COVID-19 pandemic has been dire, and its true scale is yet to be ascertained, one key component of the response is the management of infected persons which its cost has not been adequately examined, especially in Africa.MethodsTo fill gaps in context-specific cost of treating COVID-19 patients, we adopted a health system’s perspective and a bottom-up, point of care resource use data collection approach to estimate the cost of clinical management of COVID-19 infection in Ghana. The analysis was based on the national protocol for management of COVID-19 patients at the time, whether in public or private settings. No patients were enrolled into the study as it was entirely a protocol-based cost of illness analysis.ResultWe found that resource use and average cost of treatment per COVID-19 case varied significantly by disease severity level and treatment setting. The average cost of treating COVID-19 patient in Ghana was estimated to be US$11,925 (GH¢68,929) from the perspective of the health system; ranging from US$282 (GH¢1629) for patients with mild/asymptomatic disease condition managed at home to about US$23,382 (GH¢135,149) for critically ill patients requiring sophisticated and specialised care in hospitals. The cost of treatment increased by some 20 folds once a patient moved from home management to the treatment centre. Overheard costs accounted for 63–71% of institutionalised care compared to only 6% for home-based care. The main cost drivers in overhead category in the institutionalised care were personal protective equipment (PPEs) and transportation, whilst investigations (COVID-19 testing) and staff time for follow-up were the main cost drivers for home-based care.ConclusionCost savings could be made by early detection and effective treatment of COVID-19 cases, preferably at home, before any chance of deterioration to the next worst form of the disease state, thereby freeing up more resources for other aspects of the fight against the pandemic. Policy makers in Ghana should thus make it a top priority to intensify the early detection and case management of COVID-19 infections.

Phyllospheric Microbial Composition and Diversity of the Tobacco Leaves Infected by Didymella segeticola.

A Myriad of biotic and abiotic factors inevitably affects the growth and production of tobacco (Nicotiana tabacum L.), which is a model crop and sought-after worldwide for its foliage. Among the various impacts the level of disease severity poses on plants, the influence on the dynamics of phyllospheric microbial diversity is of utmost importance. In China, recurring reports of a phyto-pathogen, Didymella segeticola, a causal agent of tobacco leaf spot, accentuate the need for its in-depth investigation. Here, a high-throughput sequencing technique, IonS5TMXL was employed to analyze tobacco leaves infected by D. segeticola at different disease severity levels, ranging from T1G (least disease index) to T4G (highest disease index), in an attempt to explore the composition and diversity of phyllospheric microbiota. In all healthy and diseased tobacco leaves, the most dominant fungal phylum was Ascomycota with a high prevalence of genus Didymella, followed by Boeremia, Meyerozyma and Alternaria, whereas in the case of bacterial phyla, Proteobacteria was prominent with Pseudomonas being a predominant genus, followed by Pantoea. The relative abundance of fungi, i.e., Didymella and Boeremia (Ascomycota) and bacteria, i.e., Pseudomonas and Pantoea (Proteobacteria) were higher in diseased groups compared to healthy groups. Healthy tissues exhibited relatively rich and diverse fungal communities in contrast with diseased groups. The infection of D. segeticola had a complex and significant effect on fungal as well as bacterial alpha diversity. FUNGuild analysis indicated that the relative abundance of pathotrophs and saprotrophs in diseased tissues proportionally increased with disease severity. PICRUSt analysis of diseased tissues indicated that the relative abundance of bacterial cell motility and membrane transport-related gene sequences elevated with an increase in disease severity from T1G to T3G and then tended to decrease at T4G. Conclusively, the current study shows the typical characteristics of the tobacco leaf microbiome and provides insights into the distinct microbiome shifts on tobacco leaves infected by D. segeticola.

A novel self-learning framework for bladder cancer grading using histopathological images

In recent times, bladder cancer has increased significantly in terms of incidence and mortality. Currently, two subtypes are known based on tumour growth: non-muscle invasive (NMIBC) and muscle-invasive bladder cancer (MIBC). In this work, we focus on the MIBC subtype because it has the worst prognosis and can spread to adjacent organs. We present a self-learning framework to grade bladder cancer from histological images stained by immunohistochemical techniques. Specifically, we propose a novel Deep Convolutional Embedded Attention Clustering (DCEAC) which allows for the classification of histological patches into different levels of disease severity, according to established patterns in the literature. The proposed DCEAC model follows a fully unsupervised two-step learning methodology to discern between non-tumour, mild and infiltrative patterns from high-resolution 512 × 512 pixel samples. Our system outperforms previous clustering-based methods by including a convolutional attention module, which enables the refinement of the features of the latent space prior to the classification stage. The proposed network surpasses state-of-the-art approaches by 2–3% across different metrics, reaching a final average accuracy of 0.9034 in a multi-class scenario. Furthermore, the reported class activation maps evidence that our model is able to learn by itself the same patterns that clinicians consider relevant, without requiring previous annotation steps. This represents a breakthrough in MIBC grading that bridges the gap with respect to training the model on labelled data.

Comparison of Mini-Mental State Examination and Montreal Cognitive Assessment Ratings Across Levels of Parkinson's Disease Severity.

Cognitive impairment (CI) is common in Parkinson's disease (PD) and an important cause of disability. Screening facilitates early detection of CI and has implications for management. Preclinical disability is when patients have functional limitations but maintain independence through compensatory measures. The objective of this study was to investigate the relationship between scores on the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) with levels of PD severity and disability. PD patients (n = 2,234) in a large observational study were stratified by disease severity, based on Total Unified Parkinson's Disease Rating Scale (Total UPDRS) and Hoehn and Yahr (HY) stage. Using MMSE (n = 1,184) or MoCA (n = 1,050) and basic (ADL) and instrumental activities of daily living (IADL) scales for disability, linear regression analysis examined associations between cognitive status and disability. Cognition and disability were highly correlated, with the strongest correlation between IADL and MoCA. Only 16.0% of mean MMSE scores were below threshold for CI (28) and only in advanced PD (Total UPDRS 60+, HY≥3). MoCA scores fell below CI threshold (26) in 66.2% of the sample and earlier in disease (Total UPDRS 30+, HY≥2), corresponding with impairments in ADLs. In a large clinical dataset, a small fraction of MMSE scores fell below cutoff for CI, reinforcing that MMSE is an insensitive screening tool in PD. MoCA scores indicated CI earlier in disease and coincided with disability. This study shows that MoCA, but not MMSE is sensitive to the emergence of early cognitive impairment in PD and correlates with the concomitant onset of disability.

Predictive markers for the early prognosis of dengue severity: A systematic review and meta-analysis.

Predictive markers represent a solution for the proactive management of severe dengue. Despite the low mortality rate resulting from severe cases, dengue requires constant examination and round-the-clock nursing care due to the unpredictable progression of complications, posing a burden on clinical triage and material resources. Accordingly, identifying markers that allow for predicting disease prognosis from the initial diagnosis is needed. Given the improved pathogenesis understanding, myriad candidates have been proposed to be associated with severe dengue progression. Thus, we aim to review the relationship between the available biomarkers and severe dengue. We performed a systematic review and meta-analysis to compare the differences in host data collected within 72 hours of fever onset amongst the different disease severity levels. We searched nine bibliographic databases without restrictive criteria of language and publication date. We assessed risk of bias and graded robustness of evidence using NHLBI quality assessments and GRADE, respectively. This study protocol is registered in PROSPERO (CRD42018104495). Of 4000 records found, 40 studies for qualitative synthesis, 19 for meta-analysis. We identified 108 host and viral markers collected within 72 hours of fever onset from 6160 laboratory-confirmed dengue cases, including hematopoietic parameters, biochemical substances, clinical symptoms, immune mediators, viral particles, and host genes. Overall, inconsistent case classifications explained substantial heterogeneity, and meta-analyses lacked statistical power. Still, moderate-certainty evidence indicated significantly lower platelet counts (SMD -0.65, 95% CI -0.97 to -0.32) and higher AST levels (SMD 0.87, 95% CI 0.36 to 1.38) in severe cases when compared to non-severe dengue during this time window. The findings suggest that alterations of platelet count and AST level-in the first 72 hours of fever onset-are independent markers predicting the development of severe dengue.

Resistance varieties and pattern of disease progress of rust (Pucciana horiana p. henn) in Chrysanthemum

Rust is a major disease in chrysanthemum, which causes degradation of flower quality and results in up to 100% yield loss. Out of all the available strategies, breeding for host-plant resistance and knowledge of the pattern of disease progression in each variety is an effective strategy to control rust disease. The disease progress figured out the level of disease severity from time to time. It would be as guidance to control the disease, especially pesticide application. Six national superior and one introduced varieties were tested for their rust resistance. The varieties were studied to know the pattern of disease progression in each variety from vegetative to generative phase. The study was conducted from August 2014 to January 2015 in the plastic house of chrysanthemum plantation at Garung sub-District, Wonosobo regency, one of the centers chrysanthemum production in Central Java. The disease intensity was measured at 30, 60, and 90 days after planting. The results relayed that based on the rate of disease progress and the average of disease intensity, it could be identified that the superior national varieties of chrysanthemum, Kusumaswasti, Marimar, and Yulimar were more resistant to rust than the four other varieties tested. The rate of disease progress and the level of disease intensity of rust by the plant age determined the resistance of the chrysanthemum varieties to rust. Moreover, the result showed that each variety had a different rate and pattern of disease progression and could be used to control rust effectively.

Hemophagocytic Lymphohistiocytosis Trigged by COVID-19 Infection

The outbreak of the novel coronavirus-19 (COVID-19) rapidly grew into a worldwide pandemic. The link between the disease severity and higher levels of inflammatory markers was reported including cases of hemophagocytic lymphohistiocytosis (HLH), a potentially life-threatening disorder. We report herein a case of HLH trigged by COVID-19 infection and we review all reported cases of HLH secondary to COVID-19 among immunocompromised patients by searching PubMed publications till July 2021. A 69-year-old woman with a previous medical history of diabetes mellitus and rheumatoid arthritis treated with oral steroids presented for a 5-day history of fever, persistent cough, anorexia, and dyspnea. The diagnosis of COVID-19 was confirmed. She received empiric antibiotic therapy, oxygen supply, and corticosteroids. On day 17, laboratory investigations revealed bicytopenia with a platelets rate of 31,000/mm3 and an hemoglobin rate of 8.2 g/dL. Hyperferritinemia, hypertriglyceridemia, and hypofibrinogenemia were noted. Bone marrow aspiration and biopsy revealed images of hemophagocytosis. The HScore yielded 200 points, representing 80%–88% probability of HLH. We continued corticosteroids and treatment. The disease evolution was favorable. The diagnosis of HLH secondary to COVID-19 shoud be considered in front of cytopenia, hyperinflammatory state, and a worsening clinical condition. Prompt diagnosis and treatment improve the prognosis.

Comparison of the effects of three fungicides on clubroot disease of tumorous stem mustard and soil bacterial community

PurposeThe application of fungicides is one of the main strategies to prevent clubroot disease. Currently, numerous studies focus on changes in the soil microbial community at different levels of clubroot disease severity. However, the effects of fungicides on the soil microbial community and causative pathogen, Plasmodiophora brassicae, while preventing clubroot disease remain unclear.MethodsIn this study, we evaluated the control efficacy of three fungicides (fluazinam, metalaxyl-mancozeb, and carbendazim) on clubroot disease of tumorous stem mustard in greenhouse experiment. Uninoculated and Water treatments after inoculation were performed as controls. At three (3 W) and six weeks (6 W) post-inoculation of P. brassicae, soil properties, bacterial composition (sequencing of 16S rRNA genes), and effector gene expression of the pathogen were analyzed. The correlation of these factors with disease index (DI) was explored.ResultsFluazinam was the most effective in controlling clubroot disease of tumorous stem mustard with a controlled efficacy of 59.81%, and the abundance of P. brassicae in the soil decreased 21.29% after 3 weeks of treatment. Compared with other treatments, twelve out of twenty effector genes showed higher expression in fluazinam 3 W samples. Different fungicides had different effects on soil properties. EC (electrical conductivity), the main factor that positively associated with DI, was significantly lower in fluazinam treatment than the other two fungicide treatments. The application of fungicides, especially carbendazim, significantly reduced bacterial α-diversity and the composition of soil bacteria. Pseudomonas, Microbacterium, and Sphingobacterium (positively correlated with DI) were enriched in Water, metalaxyl-mancozeb, and carbendazim treatments, but were less abundant in fluazinam treatment. Among the three fungicide treatments, DI was significantly negatively correlated with Shannon and Chao 1 indices. Soil properties and the top bacterial genera that positively correlated with DI were influenced to a lesser degree in the fluazinam treatment.ConclusionAmong three fungicides, fluazinam was the most effective agent with the highest control effects against clubroot disease. The strong virulence of fluazinam against P. brassicae was one of the main reasons for the prevention of clubroot disease, and in addition the alteration of rhizosphere bacterial community by fluazinam to the detriment of P. brassicae infection. Based on our results, EC could be an indicator of the severity of clubroot disease.

IgG Antibodies Develop to Spike but Not to the Nucleocapsid Viral Protein in Many Asymptomatic and Light COVID-19 Cases.

Since SARS-CoV-2 appeared in late 2019, many studies on the immune response to COVID-19 have been conducted, but the asymptomatic or light symptom cases were somewhat understudied as respective individuals often did not seek medical help. Here, we analyze the production of the IgG antibodies to viral nucleocapsid (N) protein and receptor-binding domain (RBD) of the spike protein and assess the serum neutralization capabilities in a cohort of patients with different levels of disease severity. In half of light or asymptomatic cases the antibodies to the nucleocapsid protein, which serve as the main target in many modern test systems, were not detected. They were detected in all cases of moderate or severe symptoms, and severe lung lesions correlated with respective higher signals. Antibodies to RBD were present in the absolute majority of samples, with levels being sometimes higher in light symptom cases. We thus suggest that the anti-RBD/anti-N antibody ratio may serve as an indicator of the disease severity. Anti-RBD IgG remained detectable after a year or more since the infection, even with a slight tendency to raise over time, and the respective signal correlated with the serum capacity to inhibit the RBD interaction with the ACE-2 receptor.

Long COVID: long-term symptoms and morphological/radiological correlates

HintergrundNeurologische, pulmonale, kardiale und gastrointestinale Funktionsstörungen können in der postakuten Phase fortbestehen und ein Long-COVID-Syndrom bilden, das auch als postakute Folgeerscheinungen der SARS-CoV-2-Infektion (PASC) bezeichnet wird. Einige Patienten entwickeln trotz einer zu Beginn relativ milden Erkrankung anhaltende und schwächende Symptome und werden als „COVID-19 long haulers“ bezeichnet.FragestellungVorstellung von Symptomen, Anzeichen und Biomarkern bei Patienten, die zuvor an COVID-19 erkrankt waren und Erörterung der möglichen zugrunde liegenden Mechanismen und Folgen.MethodenBestehende Literatur und berichtete Fälle sowie Expertenmeinungen werden analysiert und diskutiert.ErgebnisseDas Long-COVID-Syndrom betrifft Überlebende von COVID-19 in allen Schweregraden der Erkrankung, selbst in leichten bis mittelschweren Fällen und bei jüngeren Erwachsenen, die keine Beatmungsunterstützung oder Krankenhaus- bzw. Intensivpflege benötigten. Problematisch ist, dass bei vielen Langzeitüberlebenden nie ein Labornachweis für COVID-19 erbracht wurde, was die Skepsis weckt, dass ihre anhaltenden Symptome eine physiologische Grundlage haben. Andererseits können einige Symptome, die bei einer postakuten COVID-19-Erkrankung auftreten, Folge einer kritischen Erkrankung oder eine Nebenwirkung von Behandlungen sein.SchlussfolgerungDa es sich bei COVID-19 um eine neue Krankheit handelt, lässt sich nicht feststellen, wie lange diese Auswirkungen anhalten werden. Eine langfristige Überwachung der postakuten COVID-19-Symptome und ein Screening auf häufige Komorbiditäten sind unerlässlich.

The Relationship between Platelet to Lymphocyte Ratio and Platelet Indices with Disease Severity Level of Systemic Lupus Erythematosus

Systemic Lupus Erythematosus (SLE) is an episodic, chronic autoimmune inflammatory disease characterized by remission and flare phases. Laboratory parameters required to assess the severity of disease activity in SLE include platelet count and platelet indices. Several studies regarding the Platelet to Lymphocyte Ratio (PLR) and platelet indices on the severity of SLE patients remain inconsistent. This study aimed to evaluate the relationship between PLR value and platelet index with the degree of disease severity in SLE patients. This study used a retrospective analytic observational design in SLE patients from January 2016 to December 2019 at Dr. Sardjito Central Hospital. Disease severity was assessed using the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) score. Platelet to Lymphocyte Ratio (PLR) values and platelet indices were measured with a hematology analyzer. The data were analyzed using correlation, bivariate, multiple regression tests, and the ROC curve to determine the PLR cut-off. There were 55 SLE patients with high activity (SLEDAI 11-19; n=30(54,54%)) and very high activity (SLEDAI 20; n=25(45.45%)). There was a significant correlation (p &lt;0.05) between the PLR value, platelet count, plateletcrit, and Mean Platelet Volume (MPV) with SLEDAI scores (p &lt;0.05), but only the MPV variable was significant as an independent variable (p=0.0357). In the ROC curve, a cut-off PLR value of 124 was obtained with a sensitivity of 68.0%, specificity of 66.7%, likelihood ratio=2.04 (AUC=0.659 with p-value=0.035) to detect very high disease activity. Based on the PLR value, platelet count and plateletcrit negatively correlated with SLEDAI score but were related to the very high degree of thrombocytopenia in disease activity. The MPV value reflected the high platelet turnover, which had a positive correlation with the SLEDAI score. Patients with a PLR value ≤124 were 2.04 times more likely to have a SLEDAI score of 20, indicating potential use as a predictor of disease activity. The PLR value and platelet indices were significantly related to the degree of SLE activity.

Multimodal Prediction of Alzheimer's Disease Severity Level Based on Resting-State EEG and Structural MRI

While several biomarkers have been developed for the detection of Alzheimer's disease (AD), not many are available for the prediction of disease severity, particularly for patients in the mild stages of AD. In this paper, we explore the multimodal prediction of Mini-Mental State Examination (MMSE) scores using resting-state electroencephalography (EEG) and structural magnetic resonance imaging (MRI) scans. Analyses were carried out on a dataset comprised of EEG and MRI data collected from 89 patients diagnosed with minimal-mild AD. Three feature selection algorithms were assessed alongside four machine learning algorithms. Results showed that while MRI features alone outperformed EEG features, when both modalities were combined, improved results were achieved. The top-selected EEG features conveyed information about amplitude modulation rate-of-change, whereas top-MRI features comprised information about cortical area and white matter volume. Overall, a root mean square error between predicted MMSE values and true MMSE scores of 1.682 was achieved with a multimodal system and a random forest regression model.