Abstract The identification of a suitable distribution model is a prerequisite for the parametric estimation of reference intervals and other statistical laboratory tasks. Classification of normal ...vs. lognormal distributions from healthy populations is easy, but from mixed populations, containing unknown proportions of abnormal results, it is challenging. We demonstrate that Bowley’s skewness coefficient differentiates between normal and lognormal distributions. This classifier is robust and easy to calculate from the quartiles Q 1– Q 3 according to the formula ( Q 1 − 2 · Q 2 + Q 3)/( Q 3 − Q 1). We validate our algorithm with a more complex procedure, which optimizes the exponent λ of a power transformation. As a practical application, we show that Bowley’s skewness coefficient is suited selecting the adequate distribution model for the estimation of reference limits according to a recent International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) recommendation, especially if the data is right-skewed.
Wastewater-based epidemiology (WBE) has great potential to monitor community public health, especially during pandemics. However, it faces substantial hurdles in pathogen surveillance through WBE, ...encompassing data representativeness, spatiotemporal variability, population estimates, pathogen decay, and environmental factors. This paper aims to enhance the reliability of WBE data, especially for early outbreak detection and improved sampling strategies within sewer networks. The tool implemented in this paper combines a monitoring model and an optimization model to facilitate the optimal selection of sampling points within sewer networks. The monitoring model utilizes parameters such as feces density and average water consumption to define the detectability of the virus that needs to be monitored. This allows for standardization and simplicity in the process of moving from the analysis of wastewater samples to the identification of infection in the source area. The entropy-based model can select optimal sampling points in a sewer network to obtain the most specific information at a minimum cost. The practicality of our tool is validated using data from Hildesheim, Germany, employing SARS-CoV-2 as a pilot pathogen. It is important to note that the tool's versatility empowers its extension to monitor other pathogens in the future.
Tinnitus, vertigo and dizziness are symptoms commonly reported among Long and Post COVID patients, however the severity of these symptoms has not been assessed in large trials. Therefore, in this ...study a large cohort of Long COVID patients was surveyed about the presence and severity of tinnitus and vertigo or dizziness symptoms. The online survey was completed by a German cohort of 1,082 adult Long COVID patients after a mean period of 43.2 weeks ± 23.4 weeks after infection. Eighty percent were not fully vaccinated (at least two vaccinations) at the time of their first COVID symptoms and 9.8% were hospitalized in the course of their acute SARS-CoV-2 infection. At the time of the survey, 60% of patients reported the presence of vertigo or dizziness with a mean severity of 4.6 ± 2.7 on a scale of 1 (least severe) to 10 (most severe) and 30% complained of tinnitus with a mean severity of 4.8 ± 3.0. Approximately one fifth of the participants with tinnitus and vertigo or dizziness, rated their symptoms to be severe. The data shown in this study confirms that tinnitus and vertigo or dizziness are common symptoms in Long COVID patients and demonstrates, that a compelling number of patients rate their symptoms as severe. The self-reported severity highlights the need for Long COVID clinics to address these symptoms effectively. We suggest a multidisciplinary diagnostic and therapeutic approach to prevent further morbidity and socioeconomic burden for Long COVID patients suffering from severe vertigo, dizziness or tinnitus.
Abstract
Background
Viral and autoimmune encephalitis may present with similar symptoms, but require different treatments. Thus, there is a need for biomarkers to improve diagnosis and understanding ...of pathogenesis. We hypothesized that virus-host cell interactions lead to different changes in central nervous system (CNS) metabolism than autoimmune processes and searched for metabolite biomarkers in cerebrospinal fluid (CSF) to distinguish between the two conditions.
Methods
We applied a targeted metabolomic/lipidomic analysis to CSF samples from patients with viral CNS infections (n = 34; due to herpes simplex virus n = 9, varicella zoster virus n = 15, enteroviruses n = 10), autoimmune neuroinflammation (n = 25; autoimmune anti-NMDA-receptor encephalitis n = 8, multiple sclerosis n = 17), and non-inflamed controls (n = 31; Gilles de la Tourette syndrome n = 20, Bell’s palsy with normal CSF cell count n = 11). 85 metabolites passed quality screening and were evaluated as biomarkers. Standard diagnostic CSF parameters were assessed for comparison.
Results
Of the standard CSF parameters, the best biomarkers were: CSF cell count for viral infections vs. controls (area under the ROC curve, AUC = 0.93), Q-albumin for viral infections vs. autoimmune neuroinflammation (AUC = 0.86), and IgG index for autoimmune neuroinflammation vs. controls (AUC = 0.90). Concentrations of 2 metabolites differed significantly (p < 0.05) between autoimmune neuroinflammation and controls, with proline being the best biomarker (AUC = 0.77). In contrast, concentrations of 67 metabolites were significantly higher in viral infections than controls, with SM.C16.0 being the best biomarker (AUC = 0.94). Concentrations of 68 metabolites were significantly higher in viral infections than in autoimmune neuroinflammation, and the 10 most accurate metabolite biomarkers (AUC = 0.89–0.93) were substantially better than Q-albumin (AUC = 0.86). These biomarkers comprised six phosphatidylcholines (AUC = 0.89–0.92), two sphingomyelins (AUC = 0.89, 0.91), and acylcarnitines isobutyrylcarnitine (C4, AUC = 0.92) and isovalerylcarnitine (C5, AUC = 0.93). Elevated C4 and C5 concentrations suggested dysfunctional mitochondrial β-oxidation and correlated only moderately with CSF cell count (Spearman
ρ
= 0.41 and 0.44), indicating that their increase is not primarily driven by inflammation.
Conclusions
Changes in CNS metabolism differ substantially between viral CNS infections and autoimmune neuroinflammation and reveal CSF metabolites as pathophysiologically relevant diagnostic biomarkers for the differentiation between the two conditions. In viral CNS infections, the observed higher concentrations of free phospholipids are consistent with disruption of host cell membranes, whereas the elevated short-chain acylcarnitines likely reflect compromised mitochondrial homeostasis and energy generation.
Rare diseases (RD) result in a wide variety of clinical presentations, and this creates a significant diagnostic challenge for health care professionals. We hypothesized that there exist a set of ...consistent and shared phenomena among all individuals affected by (different) RD during the time before diagnosis is established.
We aimed to identify commonalities between different RD and developed a machine learning diagnostic support tool for RD.
20 interviews with affected individuals with different RD, focusing on the time period before their diagnosis, were performed and qualitatively analyzed. Out of these pre-diagnostic experiences, we distilled key phenomena and created a questionnaire which was then distributed among individuals with the established diagnosis of i.) RD, ii.) other common non-rare diseases (NRO) iii.) common chronic diseases (CD), iv.), or psychosomatic/somatoform disorders (PSY). Finally, four combined single machine learning methods and a fusion algorithm were used to distinguish the different answer patterns of the questionnaires.
The questionnaire contained 53 questions. A total sum of 1763 questionnaires (758 RD, 149 CD, 48 PSY, 200 NRO, 34 healthy individuals and 574 not evaluable questionnaires) were collected. Based on 3 independent data sets the 10-fold stratified cross-validation method for the answer-pattern recognition resulted in sensitivity values of 88.9% to detect the answer pattern of a RD, 86.6% for NRO, 87.7% for CD and 84.2% for PSY.
Despite the great diversity in presentation and pathogenesis of each RD, patients with RD share surprisingly similar pre-diagnosis experiences. Our questionnaire and data-mining based approach successfully detected unique patterns in groups of individuals affected by a broad range of different rare diseases. Therefore, these results indicate distinct patterns that may be used for diagnostic support in RD.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Immunocompromised people (ICP) and elderly individuals (older than 80 years) are at increased risk for severe coronavirus infections. To protect against serious infection with SARS-CoV-2, ICP are ...taking precautions that may include a reduction of social contacts and participation in activities which they normally enjoy. Furthermore, for these people, there is an uncertainty regarding the effectiveness of the vaccination. The COVID-19 Contact (CoCo) Immune study strives to characterize the immune response to COVID-19 vaccination in immunocompromised, elderly people, and patients with hematological or oncological diseases. The study uses blood-based screenings to monitor the humoral and cellular immune response in these groups after vaccination. Questionnaires and qualitative interviews are used to describe the level of social participation.
The CoCo Immune Study is a mixed methods prospective, longitudinal, observational study at two large university hospitals in Northern Germany. Starting in March 2021, it monitors anti-SARS-CoV-2 immune responses and collects information on social participation in more than 600 participants, at least 18 years old. Inclusion criteria and subcohorts: Participants with (1) regularly intake of immunosuppressive medication (ICP-cohort) or (2) age ≥ 80 years (80 + -cohort). Additionally, patients with current or former (3) myeloid, (4) lymphatic disease or (5) solid tumor under checkpoint inhibition (3-5: HO-cohort).
(1) refusal to give informed consent, (2) contraindication to blood testing, (3) inability to declare consent. Participants complete a questionnaire at four different time points: prior to full vaccination, and 1, 6 and 12 months after completed vaccination. In addition, participants draw blood samples themselves or through a local health care provider and send them with their questionnaires per post at the respective time points after vaccination. Patients of the HO cohort dispense additional blood samples at week 3 to 12 and at month 6 to 9 after 2nd vaccination to gain additional knowledge in B and T cell responses. Selected participants are invited to qualitative interviews about social participation.
This observational study is designed to gain insight into the immune response of people with weakened immune systems and to find out how social participation is affected after COVID-19 vaccination.
This study was registered with German Clinical Trial Registry (registration number: DRKS00023972) on 30th December 2020.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Leakages can occur in a district heating network, resulting in high economical damage. The propagating pressure wave resulting from large, spontaneous leakages reaches sensors at different locations ...in the network. This leads to pressure drops registered at each sensor at a different point in time. The time differences help to localize the leakage. Different algorithms are presented and applied in this paper to estimate the pressure drop time points based on non-uniform, time-discrete sensor signals. Five of the nine algorithms are self-developed with, e.g., parts of linear regression, whereas the other four algorithms have already been described in the literature, such as change-point detection. In this paper, several recorded events were investigated, and the algorithms were applied to real measurement data. After detection, leakage localization was performed to determine the affected exclusion area. A performance criterion was used as a measure to compare the algorithms. For practical application, the best-performing algorithm was identified. Furthermore, the events were classified according to how well they could be evaluated.
Epstein-Barr virus (EBV) is a widely spread pathogen associated with lymphoproliferative diseases, B/ T/ NK cell lymphomas, nasopharyngeal carcinoma (NPC) and gastric carcinoma (GC). EBV lytic ...reactivations contribute to the genomic instability, inflammation and tumorigenesis of NPC, promoting cancer progression. Patients with NPC refractory to standard therapies show dismal survival. EBV gp350 is an envelope protein detectable in NPC specimens intracellularly and on the cell membrane of malignant cells, and is a potential viral antigen for T cell-directed immunotherapies. The potency of T cells engineered with a chimeric antigen receptor (CAR) targeting gp350 against EBV
lymphoproliferative disease was previously shown.
Here, we advanced towards preclinical and non-clinical developments of this virus-specific CAR-T cell immunotherapy against NPC. Different gp350CAR designs were inserted into a lentiviral vector (LV) backbone.
A construct expressing the scFv 7A1-anti-gp350 incorporating the CD8 transmembrane and CD28.CD3ζ signaling domain (ZT002) was selected. High titer ZT002 (~1x10
TU/ml) was manufactured in HEK 293T/17 suspension cells in serum free media as large-scale production under good manufacturing practices (GMP). A LV multiplicity of infection (MOI) of 1 resulted in high frequencies of functional gp350CAR
T cells (>70%) at a low (<2) vector copy numbers in the genome. ZT002 was therefore used to establish gp350CAR-T batch run production methods. GMP upscaling and validation of T cell transduction and expansion in several runs resulted in average 3x10
gp350CAR-T cells per batch. >80% CD3
gp350CAR-T cells bound to purified gp350 protein.
cytotoxicity and cytokine secretion assays (IFN-γ and TNF-α) confirmed the specificity of gp350CAR-T cells against gp350
NPC, GC and lymphoma cell targets. Immunocompromised B-NDG mice (NOD.CB17-
/Bcgen) were challenged s.c. with a EBV
NPC C666.1 cell line expressing gp350 and then treated with escalating doses of gp350CAR-T cells or with non-transduced T cells. gp350CAR-T cells promoted antitumor responses, bio-distributed in several tissues, infiltrated in tumors and rejected gp350
tumor cells.
These results support the use of gp350CAR-T cells generated with ZT002 as an Innovative New Drug to treat patients with solid and liquid EBV-associated malignancies.
Human cytomegalovirus (HCMV) causes serious complications to immune compromised hosts. Dendritic cells (iDCgB) expressing granulocyte-macrophage colony-stimulating factor, interferon-alpha and ...HCMV-gB were developed to promote de novo antiviral adaptive responses. Mice reconstituted with a human immune system (HIS) were immunized with iDCgB and challenged with HCMV, resulting into 93% protection. Immunization stimulated the expansion of functional effector memory CD8+ and CD4+ T cells recognizing gB. Machine learning analyses confirmed bone marrow T/CD4+, liver B/IgA+ and spleen B/IgG+ cells as predictive biomarkers of immunization (≈87% accuracy). CD8+ and CD4+ T cell responses against gB were validated. Splenic gB-binding IgM-/IgG+ B cells were sorted and analyzed at a single cell level. iDCgB immunizations elicited human-like IgG responses with a broad usage of various IgG heavy chain V gene segments harboring variable levels of somatic hypermutation. From this search, two gB-binding human monoclonal IgGs were generated that neutralized HCMV infection in vitro. Passive immunization with these antibodies provided proof-of-concept evidence of protection against HCMV infection. This HIS/HCMV in vivo model system supported the validation of novel active and passive immune therapies for future clinical translation.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
There is strong but mostly circumstantial evidence that genetic factors modulate the severity of influenza infection in humans. Using genetically diverse but fully inbred strains of mice it has been ...shown that host sequence variants have a strong influence on the severity of influenza A disease progression. In particular, C57BL/6J, the most widely used mouse strain in biomedical research, is comparatively resistant. In contrast, DBA/2J is highly susceptible.
To map regions of the genome responsible for differences in influenza susceptibility, we infected a family of 53 BXD-type lines derived from a cross between C57BL/6J and DBA/2J strains with influenza A virus (PR8, H1N1). We monitored body weight, survival, and mean time to death for 13 days after infection. Qivr5 (quantitative trait for influenza virus resistance on chromosome 5) was the largest and most significant QTL for weight loss. The effect of Qivr5 was detectable on day 2 post infection, but was most pronounced on days 5 and 6. Survival rate mapped to Qivr5, but additionally revealed a second significant locus on chromosome 19 (Qivr19). Analysis of mean time to death affirmed both Qivr5 and Qivr19. In addition, we observed several regions of the genome with suggestive linkage. There are potentially complex combinatorial interactions of the parental alleles among loci. Analysis of multiple gene expression data sets and sequence variants in these strains highlights about 30 strong candidate genes across all loci that may control influenza A susceptibility and resistance.
We have mapped influenza susceptibility loci to chromosomes 2, 5, 16, 17, and 19. Body weight and survival loci have a time-dependent profile that presumably reflects the temporal dynamic of the response to infection. We highlight candidate genes in the respective intervals and review their possible biological function during infection.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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