Hochschulbibliothekszentrum des Landes Nordrhein-Westfalen (hbz)
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Severe adverse reactions to benzathine penicillin G in rheumatic heart disease: A systematic review and meta-analysis
No full textBACKGROUND: Fear of severe adverse reaction (SAR) and reluctance of health care providers to administer intramuscular injections are major contributing factors to poor adherence of benzathine penicillin G (BPG) in the management of rheumatic heart disease (RHD). However, data on the risk of SARs following BPG injections for RHD are relatively limited and inconclusive. Our systematic review and meta-analysis aimed to evaluate the incidence of SARs associated with BPG injections used for secondary prophylaxis of RHD. METHODS: A systematic literature search of PubMed, Scopus and Web of Science databases was conducted to identify relevant studies reporting adverse reactions following BPG injections in patients with acute rheumatic fever (ARF) and/or RHD. A random effect meta-analysis was performed to estimate the pooled incidence of SARs. RESULT: Nine studies (eight cohort and one randomized controlled trial), comprising 11,587 participants and > 154,760 BPG injections, were included in the analysis. The pooled incidence of SARs was 9.7 per 10,000 cases (95% CI: 0.1–29.2) and 1.1 per 10,000 BPG injections (95% CI: 0.4–2.2). Six fatal reactions were reported (0.05% of patients and 24% of SARs), all occurring in patients with severe RHD. CONCLUSION: SARs following BPG injections in patients with ARF or RHD are rare. Our findings highlight the importance of balancing the low rate of SARs against the benefits of BPG in secondary prophylaxis for RHD, particularly in high-risk populations. High-quality longitudinal research and comprehensive adverse reaction reporting are essential to address safety concerns among healthcare providers and patients that impact BPG delivery
A mechanism of global gene expression regulation is disrupted by multiple disease states and drug treatments
No full textConventional expression studies quantify messenger RNA (mRNA) transcript levels gene-by-gene. We recently showed that protein expression is modulated at a global scale by amino acid availability, suggesting that mRNA expression levels might be equivalently affected. Through re-analysis of public transcriptomic datasets, it was confirmed that nucleobase supply interacts with the specific demands of mRNA A + U:C + G sequence composition to shape a global profile of expression, which can be quantified as a gradient of average expression change by average composition change. In mammals, each separate organ and cell-type displays a distinct baseline profile of global expression. These profiles can shift dynamically across the circadian day and the menstrual cycle. They are also significantly distorted by viral infection, multiple complex genetic disorders (including Alzheimer’s disease, schizophrenia, and autoimmune disorders), and after treatment with 115 of the 597 chemical entities analysed. These included known toxins and nucleobase analogues, but also many commonly prescribed medications such as antibiotics and proton pump inhibitors, thus revealing a new mechanism of drug action and side-effect. As well as key roles in disease susceptibility, mRNAs with extreme compositions are significantly over-represented in gene ontologies such as transcription and cell division, making these processes particularly sensitive to swings in global expression. This may permit efficient, en bloc transcriptional reprogramming of cell state through simple adjustment of nucleobase proportion and supply. It is also proposed that this mechanism helped mitigate the loss of essential amino acid synthesis in higher organisms. In summary, global expression regulation is invisible to conventional transcriptomic analysis, but its measurement allows a useful distinction between active, promoter-mediated gene expression changes and passive, cell state-dependent transcriptional competence. Linking cell metabolism directly to gene expression offers an entirely new perspective on evolution, disease aetiopathology (including gene x environment - GxE - interactions), and the nature of the pharmacological response
Development of a nomogram for overall survival prediction in primary upper lobe lung cancer patients: A SEER population-based analysis
No full textBACKGROUND: The upper lobe is the most common site of primary lung cancer, however, very few reports focus on its prognosis. This study aims to identify prognostic factors of lung cancer in the upper lobe, as well as to establish an effective nomogram for individualized overall survival (OS) prediction. METHODS: Patients diagnosed with lung cancer were collected from the Surveillance, Epidemiology, and End Results Program (SEER) database for the period of 2010–2017,as recorder in the 2021 SEER database release. The demographic characteristics and OS differed in the primary sites of the upper, middle and lower lobes were drawn. The primary upper lobe lung cancer patients were further stratified by the risk indicators including Mets at DX-bone, stage, histology, grade and sex; and their OS differences in stratification were compared by the Kaplan-Meier method and the Log-Rank test. The univariate and the multivariate Cox regression were employed to determine the independent prognostic factors for the primary upper lobe lung cancer and to build a nomogram model for its OS prediction. RESULTS: Depending on the different primary sites of lung cancer occurrence, all the collected patients were divided into three groups of the upper lobe (30295 individuals), the middle lobe (2801 individuals) and the lower lobe (16757 individuals), where the upper lobe group gained our attention with the largest population and an overwhelmingly low OS compared to the middle lobe group (P <0.0001). With the results of the univariate and multivariate Cox regression model analyses, age, sex, grade, histology type, stage, regional lymph nodes removed, bone metastasis and liver metastasis were selected as the prognostic factors and a prediction nomogram model was built. The calibration curves showed no significant bias from the reference line and the concordance index between the survival nomogram prediction and the actual outcome for 2-year and 3-year OS was 0.761 (95% CI, 0.757–0.765). The time-dependent receiver operating characteristic curves showed that the areas under curve for 2-year and 3-year OS were 0.840 and 0.836, respectively. CONCLUSION: A novel nomogram was established which achieved good performance in predicting the probability of OS in the primary upper lobe lung cancer, indicating its potential value in individualized prediction of the clinical outcome in these patients
Hyers Ulam stability and bifurcation control of leptospirosis disease dynamics and preventations: Modeling with singular and non-singular kernels
No full textDue to its various uses, the dynamical system is a significant research area in the field of mathematical biology. The model is first developed by applying the usual derivative with combined recovery measures of humans as well as animals for leptospirosis transmission and then converted into a generalized form of the fractal fractional sense with power law kernel, exponential law kernel, and Mittag-Leffler kernel. We verify all the fundamental characteristics of the newly developed model for the validation analysis of the system such as equilibrium points, local stability, positivity of solutions, reproductive number, and existence of a unique solution. Also, bifurcation analysis has been used for newly developed systems to observe the impact of each sub-compartment with the effect of different parameters. The results on Hyers Ulam stability are established by utilizing different kernels to observe its stable state. We used a numerical scheme based on the Lagrange polynomials for all three cases of fractal fractional derivatives having different kernels. The efficiency of the fractional operators with comparative analysis of different kernels is shown in simulation form to verify the validity and real behavior of leptospirosis transmission for humans as well as animals. he graphical explanation of our model’s solution depicts the effectiveness of our techniques applied and this study helps for future predictions and developing better control strategies
Separated or joint models of repeated multivariate data to estimate individuals’ disease trajectories with application to scleroderma
No full textEstimating a patient’s disease trajectory as defined by clinical measures is an essential task in medicine. Given multiple biomarkers, there is a practical choice of whether to estimate the joint distribution of all biomarkers in a single model or to model the univariate marginal distribution of each marker separately ignoring the covariance structure among measures. To fully utilize all trajectory-relevant information in multiple longitudinal markers, a joint model is required, but its complexity and computational burden may only be warranted when joint estimates of trajectories are substantially more efficient than separate estimates. This paper derives general expressions for the inefficiency of univariate or “separated" estimates of population-average trajectories and individual’s random effects as compared to the fully efficient multivariate or “combined" estimates. Then, in two settings: (1) a general bivariate case; and (2) our motivating clinical case study with 5 measures, we find that separated estimates of fixed effects are nearly fully efficient. However, joint estimates of random effects can be meaningfully more efficient for measures with substantial missing data when other strongly correlated measures are observed more frequently. This increased efficiency of the joint model derives more from joint shrinkage of random effects in multivariate space than from improved estimates of the subject-specific trajectories obtained when accounting for correlations in measurements. These findings have application to a diverse array of chronic diseases where biomarkers’ trajectories guide clinical decisions
Mechanistic role of pyroptosis in Kawasaki disease: An integrative bioinformatics analysis of immune dysregulation, machine learning-based biomarker discovery, WGCNA, and drug repurposing insights
No full textKawasaki disease (KD) is an acute vasculitis that primarily affects children under five and is a leading cause of acquired heart disease in this age group. Despite the standard treatment with intravenous immunoglobulin (IVIG), approximately 10–20% of patients exhibit IVIG resistance, leading to persistent inflammation and an increased risk of coronary artery aneurysms（CAA）. The underlying molecular mechanisms driving KD, particularly the role of pyroptosis, remain incompletely understood. In this study, we employed integrative bioinformatics approaches to investigate the mechanistic role of pyroptosis in KD. By analyzing transcriptomic datasets, we identified differentially expressed genes (DEGs) associated with pyroptosis and immune dysregulation. Weighted Gene Co-Expression Network Analysis (WGCNA) was utilized to uncover key co-expressed gene modules, followed by functional enrichment analyses to explore the biological significance of these genes. Through machine learning-based biomarker discovery, we identified MYD88 and S100A12 as critical pyroptosis-related genes in KD. Their diagnostic potential was validated using external datasets, and their involvement in immune cell infiltration was assessed through computational deconvolution techniques. Furthermore, drug repurposing analysis and molecular docking simulations suggested that Atogepant, Ubrogepant, and Zanubrutinib could serve as potential therapeutic candidates targeting S100A12 and MYD88. These findings provide novel insights into the molecular pathogenesis of KD and highlight potential biomarkers and therapeutic targets for improving KD diagnosis and treatment strategies
Surface processes and drivers of the snow water stable isotopic composition at Dome C, East Antarctica – a multi-dataset and modelling analysis
No full text<jats:p>Abstract. Water stable isotope records in polar ice cores have been largely used to reconstruct past local temperatures and other climatic information such as evaporative source region conditions of the precipitation reaching the ice core sites. However, recent studies have identified post-depositional processes taking place at the ice sheet's surface, modifying the original precipitation signal and challenging the traditional interpretation of ice core isotopic records. In this study, we use a combination of existing and new datasets of precipitation, snow surface, and subsurface isotopic compositions (δ18O and deuterium excess (d-excess)); meteorological parameters; ERA5 reanalyses; outputs from the isotope-enabled climate model ECHAM6-wiso; and a simple modelling approach to investigate the transfer function of water stable isotopes from precipitation to the snow surface and subsurface at Dome C in East Antarctica. We first show that water vapour fluxes at the surface of the ice sheet result in a net annual sublimation of snow, from 3.1 to 3.7 mm w.e. yr−1 (water equivalent) between 2018 and 2020, corresponding to 12 % to 15 % of the annual surface mass balance. We find that the precipitation isotopic signal cannot fully explain the mean, nor the variability in the isotopic composition observed in the snow, from annual to intra-monthly timescales. We observe that the mean effect of post-depositional processes over the study period enriches the snow surface in δ18O by 3.0 ‰ to 3.3 ‰ and lowers the snow surface d-excess by 3.4 ‰ to 3.5 ‰ compared to the incoming precipitation isotopic signal. We also show that the mean isotopic composition of the snow subsurface is not statistically different from that of the snow surface, indicating the preservation of the mean isotopic composition of the snow surface in the top centimetres of the snowpack. This study confirms previous findings about the complex interpretation of the water stable isotopic signal in the snow and provides the first quantitative estimation of the impact of post-depositional processes on the snow isotopic composition at Dome C, a crucial step for the accurate interpretation of isotopic records from ice cores.
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Successful pregnancy of an SMA type 3 sitter on Nusinersen therapy - a case report
No full text<jats:title>Abstract</jats:title><jats:sec>
<jats:title>Background</jats:title>
<jats:p>Due to improved treatment options, more SMA patients reach childbearing age. Currently, limited data on pregnant SMA patients is available, especially in relation to disease-modifying therapies (DMT). This case report helps to elucidate new approaches for future guidelines in the management of pregnancy and SMA.</jats:p>
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<jats:title>Case Report</jats:title>
<jats:p>A 33-year-old wheelchair-bound patient with SMA type 3 (sitter) became pregnant following 36 months of Nusinersen treatment. The last dose was administered in the third gestational week. After pregnancy was confirmed, therapy was stopped immediately. A healthy child was born in the 34th gestational week by caesarean section. After a short nursing period, Nusinersen was restarted 6 weeks after the expected gestational date. At this time, the patient reported deteriorated motor functions, which stabilized at a lower level compared to pre-pregnancy in the 2-year follow-up, despite restarting Nusinersen treatment.</jats:p>
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<jats:title>Discussion</jats:title>
<jats:p>So far, only few cases of successful pregnancies of SMA patients on DMT have been reported. In natural history, the majority of patients experienced an increased deterioration of motor function while fetal outcome was not impaired. Our case shows that although Nusinersen treatment was applied in the third gestational week prior to proof of pregnancy, outcome was positive for mother and child. Future studies will have to determine whether ongoing treatment with Nusinersen during pregnancy should be recommended.</jats:p>
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Isolated inflammatory involvement of the occipital artery in giant cell arteritis and polymyalgia rheumatica: findings from a retrospective analysis and the critical role of MRI in diagnosis
No full text<jats:title>Abstract</jats:title>
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<jats:title>Background</jats:title>
<jats:p>Diagnosis of Giant Cell Arteritis (GCA) and Polymyalgia rheumatica (PMR) may be challenging as many patients present with non-specific symptoms. Superficial cranial arteries are predilection sites of inflammatory affection. Ultrasound is typically the diagnostic tool of first choice supplementary to clinical and laboratory examination. Inflammation of temporal arteries can be detected sonographically with high reliability. However, due to the vessel’s course and location, occipital arteries evade sonographic detectability.</jats:p>
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<jats:title>Objective</jats:title>
<jats:p>The aim of our study was to evaluate the infestation pattern of superficial cranial arteries in GCA and PMR patients with special focus on the occipital arteries.</jats:p>
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<jats:title>Methods</jats:title>
<jats:p>90 treatment-naïve patients with clinically and/or histologically proven GCA and/or PMR (51 GCA, 20 PMR, 10 GCA-PMR) were included in the study. All patients underwent contrast-enhanced, fat-suppressed, high-resolution black blood 2D T1-weighted spin echo imaging at 3T MRI. Images were read by three different readers independently. Temporal and occipital arteries were assessed regarding vasculitic affection. Circumferential mural hyperenhancement and thickening of the vessel wall ≥ 600 μm was considered positive for vasculitis.</jats:p>
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<jats:title>Results</jats:title>
<jats:p>9/90 (10%) of all patients revealed inflammatory changes of the occipital artery only. Prevalence of isolated inflammatory affection of occipital artery was even higher in the GCA subgroup with 7/51 (14%) patients.</jats:p>
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<jats:title>Conclusion</jats:title>
<jats:p>14% of GCA patients and 10% of GCA-PMR patients present with signs of inflammation of the occipital artery only. Since the occipital artery is not accessible to routine ultrasound examination, MRI renders incremental value in the diagnosis of GCA and PMR patients.</jats:p>
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Aerosol trace element solubility and deposition fluxes over the Mediterranean Sea and Black Sea basins
No full text<jats:p>Abstract. Aerosol samples collected during summer 2013 on GEOTRACES cruise GA04 in the Mediterranean and Black seas were analysed for their soluble and total metal and major ion composition. The fractional solubilities (soluble divided by total concentrations) of the lithogenic elements (Al, Ti, Mn, Fe, Co and Th) varied strongly with atmospheric dust loading. Solubilities of these elements in samples that contained high concentrations of mineral dust were noticeably lower than at equivalent dust concentrations over the Atlantic Ocean. This behaviour probably reflects the distinct transport and pollutant regimes of the Mediterranean basin. Elements with more intense anthropogenic sources (P, V, Ni, Cu, Zn, Cd and Pb) had a variety of largely independent sources in the region and generally displayed higher fractional solubilities than the lithogenic elements. Calculated dry-deposition fluxes showed a west-to-east decline in the N/P ratio in deposition over the Mediterranean, a factor that contributes to the P-limited status of the eastern basin. Atmospheric deposition may make a significant contribution to the surface water budgets of Mn and Zn in the western Mediterranean.
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