CASE REPORTTelcoplanin induced immediate anaphylactic shock and elevated serum procalcitonin: A case report

Introduction:Allergic diseases are an alarming and growing issue among children worldwide. Apart from food allergies, they include eczema, asthma, and allergic rhinitis, which can significantly impact a child’s daily life (1). Eczema leads to severe itching and skin inflammation, asthma causes breathing difficulties, and allergic rhinitis causes sneezing, a runny nose, and itchy eyes. Alarming statistics from the latest International Study of Asthma and Allergies in Childhood (ISAAC) conducted in 2013 reveal that the prevalence of these three conditions is high among children aged 6-7 years and 13-14 years. In the age group of 13-14 years, the concurrence of these conditions with current asthma symptoms ranged from 6.3% to 13.6%, while for those aged 6-7 years, the percentage of people with these conditions ranged from 5.1% to 11.9% (2).According to epidemiological studies, it has been found that childhood eczema, asthma, and allergic rhinitis often coexist (3,4). These conditions have varying degrees of prevalence in different regions of the world. For instance, in the age group of 13-14 years, the concurrence of three conditions with current asthma symptoms ranged from 6.3% to 13.6%. Similarly, among those aged 6-7 years, the percentage of people with these conditions ranged from 5.1% to 11.9%(1,2). The co-existence of these conditions makes it highly challenging for the child and the family, especially without the help of appropriately trained health professionals. This underscores the crucial and urgent need for better training in allergy care, a key factor in improving the quality of life for children with allergic diseases.

A document by Rajabu Athumani Bakari. Click on the document to view its contents.

This study conducts a systematic bibliometric analysis of the applications of artificial intelligence (AI) in river management systems from 2000 to 2024. By examining 477 publications retrieved from the Web of Science Core Collection and utilizing CiteSpace for visualization, we identify key research trends, collaborative networks, and emerging themes in this rapidly advancing field. The findings reveal a significant geographical concentration of research output, with China (101 papers), the United States (76 papers), and the United Kingdom (29 papers) ranking as the leading contributors. The analysis highlights an exponential increase in publications, particularly after 2020, with a primary focus on machine learning applications for water quality monitoring and real-time prediction systems. Notable institutions, including the University of Malaya, the Chinese Academy of Sciences, and Duy Tan University, have demonstrated high research productivity. Moreover, critical gaps are identified, such as insufficient stakeholder engagement and the need for more transparent AI model development. These insights offer valuable guidance to environmental managers and policymakers aiming to implement AI-driven solutions for sustainable river management.

Chiral framework materials, such as chiral metal-organic frameworks (MOFs) and chiral covalent organic frameworks (COFs), have been extensively reported and studied. However, research on chiral hydrogen-bonded organic frameworks (HOFs) is far behind. HOFs present a novel approach for creating chiral materials, thanks to their mild synthesis conditions, solution processability, and ease of repair and regeneration. This review provides a comprehensive overview of the design and synthesis strategies for chiral HOFs, highlighting recent advancements and exploring the applications of emerging chiral HOFs materials.

A document by Rajabu Athumani Bakari. Click on the document to view its contents.

The article resulted from reflection on an experience in a labyrinth when a butterfly seemed to appear out of nowhere, and immediately changed the experience of the labyrinth walk. The purpose of this article is to describe five domains that influence the effects and outcomes of engaging with labyrinths as wellbeing technology. The domains are: the Labyrinth, itself; the Individual human person, who is engaging with the labyrinth; the Social context in which the engagement is set; the Transcendent domain of spiritual reality; and the Environment in which the engagement takes place. Each of the domains is briefly described and supported by examples from labyrinth-related literature. The benefits arising from the proposed model include making explicit the sources of enablements and constraints giving rise to labyrinth effects, and validates the use of qualitative data and methods, alongside calls for quantitative evidence. I conclude that the model is consistent with a qualitative, theoretical approach to research that describes the complex dynamics of engaging with a labyrinth. Future research to identify the relevant qualities within each of the five domains is proposed. Such research might draw upon information already available in the labyrinth literature, or arise from extended socio-technical system analyses, in which each of the five domains are investigated.

A document by Yves Gashugi. Click on the document to view its contents.

Rivaroxaban, a direct factor Xa inhibitor, is an oral anticoagulant used in the prevention and treatment of thromboembolic disease. The clearance of rivaroxaban involves excretion unchanged via the kidneys where it is subject to active secretion into the renal tubules, involving P-glycoprotein (P-gp) and organic anion transporter 3 (OAT3). Pretomanid, a nitroimidazole antibiotic used for multidrug-resistant tuberculosis (MDR-TB), is an OAT3 inhibitor based on in vitro data. This case report describes a novel pharmacokinetic interaction between rivaroxaban and pretomanid in a 61-year-old male undergoing MDR-TB treatment. Following pretomanid initiation, rivaroxaban trough plasma concentration increased more than two-fold, prompting a halving of rivaroxaban dose, and subsequent restoration of trough concentration to pre-pretomanid value. This interaction appears to be mediated by pretomanid inhibition of OAT3, which reduces renal clearance of rivaroxaban. Other components of MDR-TB regimen and pre-existing medications are unlikely to be contributory based on their pharmacokinetic profiles. This case highlights the potential impact of drug interactions involving pretomanid and known OAT3 perpetrators on the pharmacokinetics of rivaroxaban and other OAT3 substrates, particularly those of low therapeutic index, such as methotrexate. Given the global rise in MDR-TB, further research into pretomanid as a perpetrator of drug interactions is warranted.

The achievement of optimal lifetime and efficiency in stationary battery energy storage systems (BESS) is crucial and may require custom-made operational strategies for each grid application. This work focuses on addressing one of the key operational challenges: power distribution among the sub-units of a BESS, which leads to uneven aging and affects the overall usable capacity of a multi-pack battery system. While adjusting power setpoints of these sub-units can improve efficiency and aging performance, it can inherently introduce challenges of state of charge (SOC) imbalance within the system. This imbalance, coupled with temperature inhomogeneities in the battery packs, significantly affect the aging rate and further exacerbate system imbalances. To mitigate imbalances, a model predictive control (MPC)-based optimizer for SOC balancing is developed and evaluated against conventional and literature-derived rule-based control (RBC) strategies. Mixed-integer linear programming (MILP) is incorporated into the MPC optimizer to account for non-linear inverter losses during operation. A 1D thermal simulation, developed in this study, is used to analyze the temperature imbalances caused by these control strategies. The simulation estimates the spatial temperature distribution within each pack at the end of the operation, considering internal dissipative losses in the battery modules under fixed boundary conditions for passive air cooling. The comparative case study conducted in this work focuses on key performance metrics such as availability index (AI), fulfilment factor (FF), inverter and battery efficiencies, and state of health (SOH). These metrics are computed by coupling the power split control strategies with 1D thermal and aging estimation models through an equivalent circuit model (ECM). It suggests that due to the delayed balance of the SOC and non-uniform power distribution in RBC strategies, the availability and energy throughput of the system is lower than the desired 100% achieved using MPC. In addition, higher battery pack temperatures of up to 314 K in one of the RBC strategies were estimated, while MPC control induced a maximum temperature of up to 300 K thereby also achieving more balanced temperatures across packs. With the help of the SOC and temperature profiles during their operation, these control strategies are compared for their aging. MPC control strategy exhibited the lowest drop in state of health due to maintaining lower temperatures and mean SOC levels.

Vegetation stability is vulnerable to climate change in Central Asia. However, how future climate variations and extremes influence the vegetation stability in Central Asia has not been well understood. In this study, we investigated future vegetation stability quantified by the variability of vegetation productivity and attribution to climatic variation and negative extremes in Central Asia under four Shared Socioeconomic Pathways scenarios (SSPs) during 2021-2100, using Coupled Model Intercomparison Project phase 6 simulations. We found that the interannual variability (IAV) of Net Primary Production (NPP) would be larger under higher anthropogenic emissions scenarios. The standard deviation of NPP IAV increases from 64.55 Tg C yr -1 under SSP1-2.6 to 78.01 Tg C y r -1 under SSP5-8.5. The north of Central Asia accounts for the largest contribution (48% -53%) to Central Asia’s NPP IAV under SSP1-2.6 to SSP5-8.5. Compared to temperature IAV, precipitation IAV exerts a larger contribution to NPP IAV in Central Asia, due to the higher sensitivity of NPP IAV to precipitation IAV. Dry conditions are the main climate extremes causing negative NPP extremes in Central Asia, especially in the north and southeast of Central Asia. Our findings identify the northern and southeastern regions with higher instability posed by future climate changes in Central Asia, and provide scientific guidance for regional water management to mitigate ecosystem instability.

This study investigates the effect of 1% sodium hydroxide-treated and untreated Ronier fibers (Borassus aethiopum) fibers on concrete’s mechanical and durability properties. Ronier fibers were incorporated into concrete at proportions of 0.5%, 1%, and 1.5% by volume. The fibers treated with 1% sodium hydroxide (NaOH) underwent chemical modification to enhance their bonding with the cement matrix and improve their durability in aggressive environments. The performance of the concrete was assessed through tests for compressive strength, tensile strength, flexural strength, durability properties such as water absorption, and resistance to sulfuric acid attacks. The results indicated that treatment with 1% sodium hydroxide significantly improved the performance of the fibers. Among the variations studied, concrete reinforced with 1% treated fibers demonstrated the best combination of mechanical and durability properties. The treated fibers increased the concrete’s tensile and flexural strength while maintaining adequate compressive strength. Durability assessments showed that 1% treated fibers effectively reduced water absorption and enhanced resistance to sulfuric acid, improving the concrete’s performance in aggressive environments. Although higher dosages of fibers (1.5%) provided better crack control, they slightly reduced workability and compressive strength.

Selective catalysis, particularly when differentiating substrates with similar reactivities in mixture, is a significant challenge. In this study, anomaly detection algorithms---tools traditionally used for identifying outliers in data cleaning---are applied to catalyst screening. We focus on developing catalytic methods to selectively oxidize cyclic alkanes over linear alkanes in mixtures such as naphtha. By inserting cyclohexane oxidation data one by one into a database of n-hexane oxidization, we used several anomaly detection algorithms to evaluate whether the inserted cyclohexane oxidation data could be considered anomalous. Conditions identified as anomalies imply that they are likely not suitable for n-hexane oxidization. However, these anomalies come from conditions for cyclohexane oxidation. As a result, they are promising conditions for selective oxidation of cyclohexane while leaving n-hexane unaltered. These anomalies were thus further investigated, leading to the discovery of a specific catalytic approach that selectively oxidizes cyclohexane. This application of anomaly detection offers a novel method to search for selective catalyst for chemical reactions involving mixed substrates.

Rationale: Liquid chromatography-isotope ratio mass spectrometry (LC-IRMS) is used to analyze stable carbon isotope ratios of polar non-volatile compounds. However, challenges with the persulfate-based oxidation interface have been reported, particularly for molecules with recalcitrant structures like those found in neonicotinoids. This study systematically investigates the oxidation efficiency of neonicotinoid-related structures in a commercial LC-IRMS. Methods: Neonicotinoid proxies of varying molecular complexity were evaluated for carbon recovery and stable carbon isotope ratio accuracy. LC-IRMS parameters such as oxidant concentration, reaction time, temperature, acid concentration, and the presence of AgNO 3 catalyst were varied. Carbon recoveries and δ 13C biases were determined by injecting an oxidation-independent inorganic carbon standard under identical conditions. Elemental analyzer isotope ratio mass spectrometry (EA-IRMS) was used to normalize δ 13C values. Results: Several neonicotinoid derivatives exhibited low carbon recovery and significant δ 13C bias. Increasing oxidant concentration, reactor temperature, and reaction time improved recoveries but did not fully mitigate isotopic biases. The addition of AgNO 3 improved carbon recoveries for most derivatives but introduced variability in δ 13C values, likely due to shifts in reaction mechanisms. A workflow to identify oxidation problems during method development was proposed. Conclusions: Optimization of LC-IRMS oxidation parameters is critical for urea, guanidine, and nitroguanidine derivatives and similar compounds. A systematic evaluation of oxidation efficiencies under different conditions is needed for optimal mineralization and thus more accurate δ 13C ratios.

Introduction: Oscillometry reference equations have been calculated using various devices and protocols in different countries. Therefore, applicability of these equations to different populations is challenging. Just one study has reported impulse oscillometry (IOS) reference values in Turkish children, and moreover just in preschool children. We aimed to determine IOS reference values for Turkish children aged three to nine years. Methods: We enrolled subjects without chronic respiratory disease aged 3-8 years who presented to Celal Bayar University Hospital Department of Pediatrics for non-respiratory reasons in this cross-sectional study. All subjects had IOS measurements with the Jaeger MS-IOS device. Mean values of the three measurements for resistance (R rs) and reactance (X rs) at 5, 10, 15 and 20 Hz, the area under the curve of X (AX) and the resonant frequency (f res) were recorded. Results: A total of 245 children (111 boys) aged 3.06 to 8.53 years were enrolled. Mean values of R and X at 5, 10, 15 and 20 Hz, AX and f res did not differ significantly between boys and girls. Multivariable linear regression analysis showed that in girls height was the sole determinant of R rs5, X rs10, X rs15, and AX while height and weight were significant determinants of R rs10, R rs15, and R rs20. In boys, height was the sole determinant of R rs5, R rs10, R rs15, R rs20, R rs5-20, X rs10, X rs15, X rs20, and AX. Conclusions: These results, which provide the IOS reference equations for normal Turkish children aged three to nine years, will be valuable in the evaluation of airway dynamics in health and disease states.

The accurate gland segmentation from digitized H&E (hematoxylin and eosin) histology images with a wide range of histologic grades of cancer is quite challenging. In recent years, several fully convolutional network methods have been proposed, with UNet being the most classic. The UNet model, with its symmetric structure, has shown excellent performance in gland segmentation tasks. However, the locality of convolution operations in UNet also limits its ability to capture global dependencies. To address this limitation, this paper proposes a novel deep glandular tissue image segmentation network based on Swin UNet, termed EMA-Swin UNet. This network replaces CNN modules with Swin Transformer modules to capture both local and global representations. Additionally, the EMA-Swin UNet incorporates an Efficient Multi-scale Attention (EMA) module to enhance multi-scale feature extraction for glandular tissues of various sizes by capturing global dynamic features and long-range smooth features from the encoder outputs. By integrating edge-detection pooling, we enhanced the refinement of prediction maps produced by the EMA-Swin UNet. Moreover, we standardized the staining across both the ClaS dataset and the six-grade tumor differentiation dataset from EBHI-Seg using Reinhard normalization. The final segmentation results are compared with those of classical gland segmentation algorithms on the ClaS and EBHI-Seg datasets, demonstrating the effectiveness of our proposed method. Particularly, on the GlaS dataset, the mDice reached 0.894.

Radiofrequency ablation (RFA) is a radical treatment modality for early stage hepatocellular carcinoma (HCC). In addition to direct elimination of tumor cells, RFA induces changes in infiltrating cells within the liver tumor immune microenvironment (TIME), thereby eliciting anti-tumor immune effects. Moreover, incomplete RFA (IRFA) leads to tumor recurrence and metastasis by inducing an immunosuppressive microenvironment. Immunotherapy is a systemic treatment that enhances anti-tumour immune responses to treat HCC. So, influencing the TIME makes it possible to combine RFA and immunotherapy, which may significantly enhance the anti-tumor immune function to attack residual tumor cells. This may become one of the important means to reduce the recurrence rate after RFA. This review discusses the impact of RFA on TIME of HCC, and the immune-related mechanisms leading to tumor cell survival and invasion after IRFA. Finally, we summarize the alterations in the TIME and treatment outcomes of combining RFA with immunotherapy in HCC, aiming to provide new insights and references for improving the effectiveness of RFA.

The overwhelming surge in depression detection research presents significant challenges for mental health professionals and researchers in keeping pace with new advancements. This issue is particularly critical as timely access to insights from recent studies is essential for effective diagnosis and intervention strategies. Manually summarizing the growing body of literature is labour-intensive and prone to inconsistencies, creating an urgent need for automated summarization tools. This study introduces DepressiLex, a specialized corpus comprising 40 research papers from 2023-2024 focused on depression detection. Using transformer-based models like including Pre-training with Extracted Gap-Sentences for Abstractive Summarization (PEGASUS), Bidirectional and Auto-Regressive Transformers (BART), the Text-to-Text Transfer Transformer (T5-Base), the Longformer-Encoder-Decoder (LED), and ProphetNet, to evaluate their effectiveness in generating abstractive summaries. We assessed their performance using metrics such as the Bilingual Evaluation Understudy (BLEU) and the Recall-Oriented Understudy for Gisting Evaluation (ROGUE), with the Longformer-Encoder-Decoder consistently outperforming the others. This engineering advancement fulfils a critical need in healthcare, providing mental health professionals with streamlined, artificial intelligence (AI)-enabled access to key insights, thereby significantly reducing the time and cognitive load involved in reviewing complex research. Additionally, word cloud visualizations highlight the dominant themes and terms across the summaries, underscoring the potential of transformer models to transform access to mental health knowledge.

Purpose: To estimate the time to resolution of COVID-19 symptoms and identify associated factors among COVID-19 patients. Methods: A prospective study was conducted with 2777 adults identified with SARS-CoV-2 infection between March and December 2020 at the Centro Hospitalar Universitário de São João. Data collected between November 2020 and April 2021 included sociodemographic, clinical, and infection-related variables. We used survival analysis to estimate the time until symptom resolution, and Cox regression identified associated factors using crude (HR) and adjusted hazard ratios (aHR). Results: Symptom resolution was not experienced by 36.5% of participants within the study period. Higher hazards of symptom resolution were observed among males [aHR:1.55, 95% Confidence Interval (CI):1.41–1.70], those with master/doctoral education (aHR:1.29, 95% CI:1.08–1.54), and better income perception. Lower hazards were seen in adults aged 40–49 (HR:0.79, 95% CI:0.68–0.93) and 50–59 (HR:0.76, 95% CI:0.65–0.90), individuals with comorbidities (aHR:0.83, 95% CI:0.74–0.92), and those hospitalised during the acute phase (aHR:0.71, 95% CI:0.61–0.82). Conclusions: Over one-third of COVID-19 patients had unresolved symptoms months post-infection. Middle age, female sex, lower education, poor income perception, comorbidities, and hospitalisation in the acute phase were the most significant predictors for non-resolving symptoms, underscoring the need for targeted interventions.

Question: Epidemiological studies suggest respiratory viral infections are major triggers of asthma exacerbations, and clinical studies have suggested the involvement of an increased interleukin-6 (IL-6) release. What is the pathophysiological role of IL-6 in asthma exacerbation, and which mechanisms lead to enhanced IL-6 release? Material & Methods: Exacerbations of ovalbumin-induced experimental allergic asthma were elicited in wildtype and IL-6 deficient mice by intra-nasal (i.n.) application of poly(I:C). Airway inflammation, cytokine expression and release, mucus production, and airway hyperresponsiveness were measured. IL-6 was neutralised by i.n. anti-IL-6 antibody application. Human bronchial epithelial cells were exposed to poly(I:C) or infected with human rhinovirus-16, with IL6 expression and DNA methylation quantified. Genome-wide DNA methylation was assessed in airway epithelial cells from adults with asthma (cohort I, n=54) and in nasal epithelial cells from children and adults in the All-Age-Asthma cohort (ALLIANCE, n=53 and n=108 respectively). Results: Poly (I:C)-induced experimental exacerbations in mice were preceded and paralleled by exaggerated IL-6 release in the airway epithelium, with IL-6 neutralisation completely preventing experimental exacerbations. Repetitive infection/stimulation with RV16 or poly(I:C) resulted in training of the IL-6 release in human respiratory epithelial cells. In patients, hypomethylation at the IL6 gene methylation was associated with high IL6 expression and future exacerbations. Answer: An exaggerated IL-6 release is required for exacerbation of experimental asthma, potentially the result of viral PAMP-induced immune training of airway epithelial cells. Additionally, patients with asthma carrying the epigenetic signature of a trained IL-6 response exacerbate more frequently. These findings open new avenues to identify and treat exacerbation-prone patients.

Mitral regurgitation (MR) can occasionally mimic aortic stenosis (AS) on echocardiographic Doppler imaging, leading to diagnostic challenges. We present the case of a 55-year-old male undergoing minimally invasive mitral valve surgery for severe MR caused by posterior mitral valve leaflet prolapse. Preoperative transthoracic echocardiography revealed severe MR with no significant aortic valve abnormalities. Intraoperative transesophageal echocardiography (TEE) initially showed a high transvalvular aortic gradient (3 m/s) in the transgastric long-axis view, suggestive of mild-to-moderate AS. However, detailed Doppler analysis revealed a double envelope signal, representing both eccentric MR and true aortic valve flow. Closer evaluation showed the MR signal occurred earlier in the cardiac cycle, aligning with its hemodynamic timing, while the true aortic flow followed isovolumetric contraction. Subsequent three-dimensional TEE confirmed normal aortic valve morphology and function. This case highlights the importance of correlating preoperative findings, Doppler signal timing, and imaging data to avoid misdiagnosis. Systematic echocardiographic evaluation, including signal timing analysis, can differentiate between MR and AS, ensuring accurate intraoperative decision-making and preventing unnecessary interventions.

Benzo[d]thiazol-2-ylmethanol undergoes progressive oligomerization when treated under solvothermal condition with FeCl 3·6H 2O to give heterocycle aggregate (1,2,3-tris(benzo-[ d]thiazol-2-yl)-2,9-dihydrobenzo-[ b]cyclopenta-[ e][1,4]-thiazine. Four single-crystal structures analyses have been performed on compounds isolated during the reactions and 15 consecutive steps have been deciphered from ESI-MS of both solid products and the intermediate reaction solutions. These progressive steps involve intermolecular C-C coupling (9 steps) and intramolecular ring expansion (6 steps). Each of the non-carbon atoms (N, O, and S) has its particular function due to their position on the heterocycle: (i) The N and O coordinated with Fe(III) to activate the reaction site, ( ii) C-O homolytic cleavage promoted C-C coupling reactions, and ( iii) C-S migration caused intramolecular ring expansion. Importantly, through theoretical calculations, decrease in Gibbs free energy of intramolecular reaction pathways support this mechanism and activation mode, which indicated that the Fe(III) is necessary for the reaction to progress. The investigation of photophysical properties revealed that the heterocyclic aggregates exhibited good luminescent behavior in the wavelength range of 535–610 nm, approaching the near infrared region. This finding underscores the significance of this reaction pathway and the identification of its mechanistic steps in facilitating the synthesis of functional oligomers and polymers from monomers, particularly through the catalytic promotion by inexpensive metal ions.

Detachment of aortic valve calcification lesions leading to arterial embolism is very rare in clinical practice, and is occasionally caused by surgical operation and external interference. Due to the different embolization sites, the clinical symptoms and imaging manifestations are also different, and insufficient knowledge of clinicians can easily lead to missed diagnosis and diagnostic errors. We report a very rare emergency case of a 36-year-old patient presenting with sudden syncope for 4 hours. Echocardiography revealed severe calcification of the aortic valve and active foci. Strong echoic lesions were also found in the distal segment of the brachiocephalic trunk, causing severe stenosis. We consider that the calcification loss of the aortic valve leads to insufficient blood supply to the brain and the occurrence of syncope. The patient received timely surgical treatment. Although the active detachment of aortic valve calcification lesions is very rare, we still need to consider this possibility.

Background and Purpose: Ivabradine is the only FDA-approved HCN channel blocker. This study aims to identify FDA-approved drugs for repurposing as HCN channel blockers, focusing on their effects on hHCN1 channel kinetics, blocking mechanisms, and binding site identification. Experimental Approach: FDA-approved drugs were screened using two criteria: bradycardia as a side effect and structural similarity to known HCN blockers. Selected compounds were docked on hHCN1 channels in closed conformation and open conformation homology model. Based on the established criteria and the additional neuroprotective effects, donepezil was selected for electrophysiological investigation. Molecular docking and site-directed mutagenesis were utilized to determine the residues interacting with donepezil. Key Results: Molecular docking studies on closed conformation of hHCN1 channels showed no binding poses for donepezil inside the pore, while all poses were located within the pore when docked onto the open conformation. Electrophysiological experiments revealed that donepezil effectively blocked hHCN1 channels in dose-dependent manner with a moderate potency, slowed activation kinetics, caused a hyperpolarizing shift in activation curve, and exhibited use-dependent, reversible blockade. Effective blocking required channel cycling between open and closed states. Molecular docking and site-directed mutagenesis identified L357, A383, Y386, and A387 as key residues for binding. Conclusion and Implications: Considering our results and the known neuroprotective effects of donepezil, our findings suggest that donepezil has the potential to be repurposed as a therapeutic hHCN1 channel blocker. This study also highlights the potential of drug repurposing in identifying novel HCN channel inhibitors, paving the way for future drug design targeting HCN channels.