Amifostine protects normal cells from DNA damage induction by ionizing radiation or chemotherapeutics, whereas cancer cells typically remain uninfluenced. While confirming this phenomenon, we have ...revealed by comet assay and currently the most sensitive method of DNA double strand break (DSB) quantification (based on γH2AX/53BP1 high-resolution immunofluorescence microscopy) that amifostine treatment supports DSB repair in γ-irradiated normal NHDF fibroblasts but alters it in MCF7 carcinoma cells. These effects follow from the significantly lower activity of alkaline phosphatase measured in MCF7 cells and their supernatants as compared with NHDF fibroblasts. Liquid chromatography-mass spectrometry confirmed that the amifostine conversion to WR-1065 was significantly more intensive in normal NHDF cells than in tumor MCF cells. In conclusion, due to common differences between normal and cancer cells in their abilities to convert amifostine to its active metabolite WR-1065, amifostine may not only protect in multiple ways normal cells from radiation-induced DNA damage but also make cancer cells suffer from DSB repair alteration.
We present a novel approach to estimate the time-varying ascertainment rate in almost real-time, based on the surveillance of positively tested infectious and hospital admission data. We also address ...the age dependence of the estimate. The ascertainment rate estimation is based on the Bayes theorem. It can be easily calculated and used (i) as part of a mechanistic model of the disease spread or (ii) to estimate the unreported infections or changes in their proportion in almost real-time as one of the early-warning signals in case of undetected outbreak emergence. The paper also contains a case study of the COVID-19 epidemic in the Czech Republic. The case study demonstrates the usage of the ascertainment rate estimate in retrospective analysis, epidemic monitoring, explanations of differences between waves, usage in the national Anti-epidemic system, and monitoring of the effectiveness of non-pharmaceutical interventions on Czech nationwide surveillance datasets. The Czech data reveal that the probability of hospitalization due to SARS-CoV-2 infection for the senior population was 12 times higher than for the non-senior population in the monitored period from the beginning of March 2020 to the end of May 2021. In a mechanistic model of COVID-19 spread in the Czech Republic, the ascertainment rate enables us to explain the links between all basic compartments, including new cases, hospitalizations, and deaths.
It is not known whether the results of decompressive surgery to treat the mild and moderate forms of spondylotic cervical myelopathy (CSM) are any better than those of a conservative approach. A ...10-year prospective randomised study was performed. The objective of the study was to compare conservative and operative treatments of mild and moderate, non-progressive, or slowly progressive, forms of CSM. Sixty-four patients were randomised into two groups of 32. Group A was treated conservatively while group B was treated surgically. The clinical outcome was evaluated by modified JOA score, timed 10-m walk, score of daily activities recorded by video and evaluated by two observers blinded to the type of therapy, and by subjective assessment by the patients themselves. Seventeen patents died of natural, unrelated causes, during the follow-up. A total of 25 patients in the conservatively and 22 in the surgically treated group were used for the final evaluation. There was no statistically significant difference between both groups in mJOA score, in subjective evaluation by the patients themselves and in evaluation of video-recordings of daily living activities by two observers blinded to treatment mode. There was neither any difference found in the percentage of patients losing the ability to walk nor in the time taken to cover the 10-m track from a standing start. Comparison of conservative and surgical treatment in mild and moderate forms of CSM in a 10-year follow-up has not shown, on average, a significant difference in results. In both groups, patients get better and worse. According to the power analysis it is necessary admit that these results possess the low ability to answer definitely the question which treatment is better for the patients with a mild and moderate non-progressive CSM because of the low number of patients for the final evaluation and for clinically negligible differences between two compared arms. These findings can serve as a worthy odds-on hypothesis which needs the confirmation.
Chronic periodontitis (CP) and diabetes mellitus (DM) involve several aspects of immune functions, including neutrophil activity and cytokine biology. Considering the critical function of chemokine ...interleukin-8 (IL-8) in the inflammatory process, the aims of this study were to determine: (i) IL-8 plasma levels; (ii)
(-251A/T, rs4073) and its receptor 2 (
, +1208C/T, rs1126579) polymorphisms, and (iii) the presence of the selected periodontal bacteria in types 1 and 2 DM patients (T1DM and T2DM) and systemically healthy controls (HC) with known periodontal status. This case⁻control study comprises of 153 unrelated individuals: 36/44 patients suffering from T1DM+CP/T2DM+CP and 32/41 from HC+CP/non-periodontitis HC. Both the clinical and biochemical parameters were monitored. The genotypes were determined using qPCR, IL-8 plasma levels were measured using an ELISA kit. Subgingival bacterial colonization was analyzed with a DNA microarray detection kit. The IL-8 plasma levels differed significantly between non-periodontitis HC and T1DM+CP/T2DM+CP patients (
< 0.01). Even in HC+CP, IL-8 concentrations were significantly lower than in T1DM+CP/T2DM+CP patients (
≤ 0.05). No significant associations between the IL-8 plasma levels and the studied
and
polymorphisms or the occurrence of selected periodontal bacteria (
> 0.05) were found. CP does not influence the circulating IL-8 levels. Patients with T1DM+CP/T2DM+CP had higher circulating IL-8 levels than HC+CP/non-periodontitis HC.
The recent human monkeypox virus (HMPXV) outbreak in non-endemic countries that started in May 2022 has raised concerns among public health authorities worldwide. Healthcare workers (HCWs) play a ...decisive role during epidemics in transmitting accurate information to the public and motivating them to pursue protective behaviours, including immunisation.
A cross-sectional survey-based study was conducted in the Czech Republic in September 2022 to evaluate HMPXV-related knowledge and vaccination perceptions among HCWs. The study utilised a digital self-administered questionnaire (SAQ) to collect data from the target population. The proposed SAQ inquired about participants' sociodemographic and anamnestic characteristics, perceived knowledge of HMPXV, factual knowledge, and vaccination perceptions according to the health belief model (HBM).
A total of 341 participants were included in this study; most of them were females (88.9%), allied HCWs (89.4%), heterosexuals (87.1%), married (61.9%), and vaccinated against COVID-19 (91.2%). Only 8.8% of the participants agreed to receive vaccination against HMPXV; 44.9% rejected it, while 46.3% were hesitant. While digital news portals (47.5%) and social media (25.8%) were among the most utilised sources of information about HMPXV, the scientific journals (5.6%), ECDC (5%), and the U.S. CDC (1.5%) were the least common sources. The participants demonstrated suboptimal levels of factual knowledge, especially regarding HMPXV vaccines (1.5 ± 1.2 (0-4)) and treatments (0.9 ± 0.9 (0-4)). Additionally, several misconceptions were detectable among the participants, regarding topics such as the availability of effective vaccines and antivirals against HMPXV, the risk of vertical transmission, and homosexual stigmatisation. The HBM indicated that the cues to action and perceived susceptibility were the most important constructs to predict HMPXV vaccine acceptance.
the findings of this study call upon public health practitioners and health policymakers in the Czech Republic to act accordingly in order to determine the drivers of vaccine hesitancy among Czech HCWs. Dedicated educational campaigns should aim to counter the HCWs' misconceptions around HMPXV, and future studies should aim to explore the prevalence and drivers of HMPXV vaccine hesitancy among the general population.
The main objective of this study was to investigate the impact of prenatal and early postnatal stress on hippocampal volume in young adulthood. In sharp contrast to numerous results in animal models, ...our data from a neuroimaging follow-up (n = 131) of a community-based birth cohort from the Czech Republic (European Longitudinal Study of Pregnancy and Childhood) showed that in typically developing young adults, hippocampal volume was not associated with birth weight, stressful life events during the prenatal or early postnatal period, or dysregulated mood and wellbeing in the mother during the early postnatal period. Interestingly, mother's anxiety/co-dependence during the first weeks after birth did show long-lasting effects on the hippocampal volume in young adult offspring irrespective of sex. Further analyses revealed that these effects were subfield-specific; present in CA1, CA2/3, CA4, GC-DG, subiculum, molecular layer, and HATA, hippocampal subfields identified by translational research as most stress- and glucocorticoid-sensitive, but not in the remaining subfields. Our findings provide evidence that the type of early stress is critical when studying its effects on the human brain.
Vaccine hesitancy, spurred by misinterpretation of Adverse Events (AEs), threatens public health. Despite sporadic reports of oral AEs post-COVID-19 vaccination, systematic analysis is scarce. This ...study evaluates these AEs using the Australian Database of Adverse Event Notifications (DAEN). A secondary analysis of DAEN data was conducted, with the analysis period commencing from the start of the COVID-19 vaccination rollout in February 2021 and the inception of the influenza vaccine database in 1971, both through until December 2022. The focus of the analysis was on oral AEs related to COVID-19 and influenza vaccines. Reports were extracted according to a predefined schema and then stratified by vaccine type, sex, and age. Oral paresthesia was the most common oral AE after COVID-19 vaccination (75.28 per 10,000 reports), followed by dysgeusia (73.96), swollen tongue (51.55), lip swelling (49.43), taste disorder (27.32), ageusia (25.85), dry mouth (24.75), mouth ulceration (18.97), oral hypoaesthesia (15.60), and oral herpes (12.74). While COVID-19 and influenza vaccines shared most oral AEs, taste-related AEs, dry mouth, and oral herpes were significantly more common after COVID-19 vaccination. mRNA vaccines yielded more oral AEs than other types. Females had higher oral AE incidence. Most oral AEs did not differ significantly between COVID-19 and influenza vaccination. However, specific oral AEs, particularly taste-related, dry mouth, and oral herpes, were more prevalent after COVID-19 vaccination compared with seasonal influenza, especially in females and mRNA vaccine recipients.
No universal solution, based on an approved pedagogical approach, exists to parametrically describe, effectively manage, and clearly visualize a higher education institution's curriculum, including ...tools for unveiling relationships inside curricular datasets.
We aim to solve the issue of medical curriculum mapping to improve understanding of the complex structure and content of medical education programs. Our effort is based on the long-term development and implementation of an original web-based platform, which supports an outcomes-based approach to medical and healthcare education and is suitable for repeated updates and adoption to curriculum innovations.
We adopted data exploration and visualization approaches in the context of medical curriculum innovations in higher education institutions domain. We have developed a robust platform, covering detailed formal metadata specifications down to the level of learning units, interconnections, and learning outcomes, in accordance with Bloom's taxonomy and direct links to a particular biomedical nomenclature. Furthermore, we used selected modeling techniques and data mining methods to generate academic analytics reports from medical curriculum mapping datasets.
We present a solution that allows users to effectively optimize a curriculum structure that is described with appropriate metadata, such as course attributes, learning units and outcomes, a standardized vocabulary nomenclature, and a tree structure of essential terms. We present a case study implementation that includes effective support for curriculum reengineering efforts of academics through a comprehensive overview of the General Medicine study program. Moreover, we introduce deep content analysis of a dataset that was captured with the use of the curriculum mapping platform; this may assist in detecting any potentially problematic areas, and hence it may help to construct a comprehensive overview for the subsequent global in-depth medical curriculum inspection.
We have proposed, developed, and implemented an original framework for medical and healthcare curriculum innovations and harmonization, including: planning model, mapping model, and selected academic analytics extracted with the use of data mining.
Whole genome expression profiling of large cohorts of different types of cancer led to the identification of distinct molecular subcategories (subtypes) that may partially explain the observed ...inter-tumoral heterogeneity. This is also the case of colorectal cancer (CRC) where several such categorizations have been proposed. Despite recent developments, the problem of subtype definition and recognition remains open, one of the causes being the intrinsic heterogeneity of each tumor, which is difficult to estimate from gene expression profiles. However, one of the observations of these studies indicates that there may be links between the dominant tumor morphology characteristics and the molecular subtypes. Benefiting from a large collection of CRC samples, comprising both gene expression and histopathology images, we investigated the possibility of building image-based classifiers able to predict the molecular subtypes. We employed deep convolutional neural networks for extracting local descriptors which were then used for constructing a dictionary-based representation of each tumor sample. A set of support vector machine classifiers were trained to solve different binary decision problems, their combined outputs being used to predict one of the five molecular subtypes.
A hierarchical decomposition of the multi-class problem was obtained with an overall accuracy of 0.84 (95%CI=0.79-0.88). The predictions from the image-based classifier showed significant prognostic value similar to their molecular counterparts.
popovici@iba.muni.cz.
Source code used for the image analysis is freely available from https://github.com/higex/qpath .
Supplementary data are available at Bioinformatics online.
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