A document by Steffen Mickenautsch. Click on the document to view its contents.

In Sjogren’s disease (SjD), the immune system targets the salivary and lacrimal glands, causing chronic inflammation, glandular dysfunction, and reduced tear and saliva production, leading to xerostomia and keratoconjunctivitis sicca1,2. The key immune mechanisms include B cell hyperactivity, marked by elevated circulating anti-SSA (Ro60 and Ro52), anti-SSB (La), and rheumatoid factors (RFs: IgM-RF, IgA-RF, and IgG-RF) antibodies, elevated expression of B cell activation and proliferation markers (e.g., CD86, CD38, HLA-DR, Ki67), increased secretion of IL6, BAFF, along with CD4+ T cell-driven inflammation and the formation of ectopic lymphoid structures, contributing to sustained autoimmunity

This study investigates into the combined effects of viscous dissipation and Joule heating on Magnetohydrodynamics (MHD) fluid flow, considering a viscous, incompressible fluid flowing over a porous, stretching horizontal sheet. The numerical analysis, employing the shooting technique, solves the dimensionless governing equations for momentum and heat transfer, yielding insights into the thermal behavior and fluid flow. Key parameters, including the Grashof number, permeability, Eckert number, heat source strength, and Prandtl number, are systematically examined, with results presented in detailed tables and discussions, providing a comprehensive understanding of their influences on MHD fluid flow.

Article type: Brief communication

This study investigates the role of forage cultivation in land restoration in Ethiopia, addressing the scarcity of organized evidence that has hindered its widespread adoption in sustainable land management practices. Despite global recognition of the benefits of forages in combating land degradation, research specific to Ethiopia remains fragmented. Through a systematic literature review and bibliometric analysis, this study synthesizes the multifunctionality of forages, highlighting that while thousands of studies address forages and restoration independently, only a few hundred explore their intersection. Findings reveal regional variations in forage-based land restoration research, with agroforestry and rotation systems prominent in the north, pasture improvement in the southwest, intercropping in central regions, and soil and water conservation in the south. Forage integration in rotation and intercropping systems delivered significant farm-level benefits, including enhanced food security, income, and soil health, while its inclusion in soil and water conservation, agroforestry, and pasture improvement contributed to landscape-level restoration outcomes. Forage species selection was found to be influenced by intervention types and goals, with grass-based varieties preferred for soil-water conservation and legumes for rotation systems to improve soil fertility and crop yields. Grass-legume mixtures demonstrated effectiveness in rehabilitating degraded pastures, stabilizing soils, and enhancing livestock productivity. Despite the potential of forages to reduce erosion, lower greenhouse gas emissions, and improve livelihoods, challenges persist in scaling successful models and accurately quantifying their impacts. The study concludes that forage cultivation, when tailored to regional contexts and integrated into diverse land management systems, offers a viable pathway for achieving land restoration and food security goals in Ethiopia, though scaling and impact quantification remain key challenges.

Brain metastases are common in patients with lung and breast cancer and associated with poor outcomes. While there is some intracranial activity with systemic therapies, most chemotherapies are minimally effective. Etirinotecan pegol (EP), a PEGylated chemotherapy with favorable pharmacokinetics over irinotecan, was administered at a dose of 145 mg/m2 IV every 3 weeks to patients with previously treated metastatic non-small cell lung cancer (NSCLC, n=12), small cell lung cancer (SCLC, N=3) and breast cancer (MBC, n=12), having progressive brain metastases after brain-directed radiotherapy or refusal. The primary endpoint was a 25% or greater disease control rate, defined as CR, PR + SD, in the central nervous system (CNS) at 12 weeks; secondary endpoints included toxicity and systemic disease control. Prior whole brain radiotherapy had been administered to 3 patients with NSCLC and 8 patients with MBC. The CNS control rate at 12 weeks in NSCLC and MBC was 17% (2 patients in each cohort) and 0% in SCLC. The median overall progression free survival for NSCLC was 2.7 months (95% CI: 1.3, 6.7) and MBC was 1.4 months (95% CI: 1.3, 6.9). The most common adverse events were diarrhea (48%), nausea (48%) and fatigue (26%). Six patient deaths occurred on this study. Dehydration/diarrhea (1) and neutropenic sepsis (3) from study treatment was at least possibly related to these deaths. This study demonstrates that EP did not meet the threshold of clinical efficacy in patients with refractory CNS metastasis from lung or breast cancer.

Thiamine (vitamin B1) is an essential coenzyme and catalyses various reactions in central metabolic pathways. Since mammals have lost the ability to synthesize thiamine de novo, this micronutrient has to be imported via the high affinity solute carriers SLC19A2 and A3 across the plasma membrane. Perturbations of these transport systems have severe effects on human health. Recent structural work on SLC19A2 and A3 have provided molecular insights into substrate and drug recognition and conformational changes during transport. Based on the analysis of the available SLC19A3 structures, we hypothesise that the binding site is rather promiscuous, allowing different small molecules to interact and potentially inhibit this transporter. To explore this, we employed a computational approach, by which 538 approved and investigational drugs were docked into an ensemble of SLC19A3 cryo-EM structures, followed by binding and transport inhibition assays. Eight novel compounds were identified that bind and inhibit SLC19A3. To visualise such a new drug interaction, we determined the cryo-EM structure of SLC19A3 bound to domperidone, a dopamine D2 receptor antagonist used for the treatment of nausea and gastrointestinal disorders. Our computational work together with biochemical and cellular transport assays expands the understanding of SLC19A3-drug interactions, highlights the power of virtual screening approaches using structural ensembles and provides a first pharmacophore model for SLC19A3 inhibitors. These findings offer a basis for addressing drug-induced thiamine deficiencies and our approach can be used to optimise pharmacological strategies involving SLC19A3-interacting compounds in the future.

Background: Diabetic nephropathy (DN), affects 30% diabetic, presents significant global healthcare challenges. Despite advancements in current therapies, their adverse effects underscore demand for safer options. Recent research has indicated that the gut microbiota as a promising therapeutic target for DN. Cornus officinalis, a traditional Chinese medicinal herb widely used for DN management, contains bioactive polysaccharides with gut microbiota-modulating potential. However, the precise mechanisms underlying their therapeutic effects remain poorly understood. Purpose: This study aims to elucidate the mechanisms by which Cornus officinalis polysaccharides (COP) ameliorate DN through microbiota modulation. Methods: DN was induced in Sprague-Dawley rats via streptozotocin injection and high-fat diet. Animals were randomly assigned to receive COP (120, 240, or 480 mg/kg/day), valsartan (positive control), or vehicle. Effects were evaluated through biochemical parameters, renal histopathology, immunofluorescence, and Western blotting. Gut microbiota composition was analyzed via 16S rRNA sequencing. Integrated metabolomic/transcriptomic analyses for critical metabolites and pathways, with in vitro mechanistic validation. Results: COP administration significantly ameliorated renal damage while restoring glomerular filtration function. It enhanced the abundance of Akkermansia muciniphila and restored bile acid (BA) metabolic homeostasis. In vitro studies revealed that Akkermansia muciniphila modulated lithocholic acid (LCA) metabolism. Transcriptomics identified PPAR signaling as the core mechanism, with LCA derivatives mitigating podocyte injury through the Slc27a2-PPARα-Angptl4 axis, defining the nephroprotective pathway. Conclusion: COP ameliorates DN though a multi-mechanistic approach involving gut microbiota modulation, restoration of BA metabolism, and repair of glomerular function via the Slc27a2-PPARα-Angptl4 axis. These findings provide a novel multi-target strategy for DN management.

This short communication develops a variational formulation for modeling a protium hydrogen molecular ionization obtained through a high temperature scalar field and an appropriate electric one action. The results are based on standard tools of calculus of variations and optimization theory.

A document by Abhishek Bansal . Click on the document to view its contents.

Influenza, respiratory syncytial virus (RSV) and SARS-CoV-2 are among the main viruses circulating in the population, with a significant burden on public health. While individuals at higher risk are more likely to develop severe symptoms leading to hospitalization, viral circulation in the community remains less extensively monitored. This study compared viral circulation between RELAB, a recently established community-based laboratory surveillance network (n=22,843 tested patients) and hospital surveillance at the Hospices Civils de Lyon, France (n=23,046 tested patients), for the season 2023-2024. For influenza and SARS-CoV-2, similar trends were observed in at-risk populations (children under five years and adults over 65 years) in both settings. Circulation of these two viruses was first detected in the community and insights from the young adult population (19-64 years) were only captured in the community network. Circulation of RSV was more intense in terms of number of cases and started in the pediatric population, which was more represented in the hospital. In conclusion, this study highlighted the complementarity between community and hospital surveillance, as different populations and periods of viral circulation were observed.

Sepsis-associated encephalopathy (SAE) is a diffuse brain dysfunction caused by sepsis, with an unclear pathogenesis and limited treatment options. This study aimed to investigate the therapeutic effects of glutathione (GSH) in a lipopolysaccharide (LPS)-induced sepsis model and to elucidate its underlying mechanism of action. Adult C57BL/6 mice were intraperitoneally injected with LPS (25 mg/kg) to induce sepsis. Prior to LPS administration, GSH (100 mg/kg) was administered intraperitoneally for four consecutive days. Remarkably, GSH treatment significantly reduced mortality in the sepsis model. Behavioral experiments showed notable improvements in locomotor activity in GSH-treated mice, including increased total distance covered and more frequent crossings in the light/dark field test. Additionally, GSH treatment enhanced exploration, as indicated by an increased number of entries into the open arms of the elevated plus maze. In the tail suspension test, GSH treatment reduced resting time and instances of immobility, suggesting potential antidepressant effects. Histological analyses, including Nissl, HE, and immunofluorescence staining, revealed enhanced neuronal survival in the hippocampal CA1 and DG regions following GSH treatment. To explore the molecular mechanisms, Western blot analysis demonstrated that GSH reduced the release of inflammatory markers (IL-1β, IL-6, IL-10) and apoptosis-related proteins (Caspase-3 and cleaved Caspase-3). Furthermore, GSH downregulated PKA, phosphorylated PKA, and NF-κB, suggesting modulation of the PKA and NF-κB signaling pathways. These findings suggest that GSH mitigates neurological damage in sepsis by reducing inflammation and apoptosis, while also improving depressive behavior and cognitive function. GSH may represent a promising therapeutic approach for reducing mortality in SAE.

The article considers artificial neural networks as a means of intelligent data analysis. The relevance of using such networks is due to the active growth of data volumes, which occurs as a result of the automation of various technological processes. The primary methods of data analysis in the field of security science are identified, along with an examination of their respective advantages and disadvantages. As a result, an important conclusion is substantiated: the use of artificial neural networks for the purpose of intelligent analysis of accumulated data is fully justified and expedient, primarily for practical reasons. The areas of application for intelligent data analysis and existing systems are examined. A comparative analysis of the use of neural network architecture within the context of security science conditions is conducted. An approach to a neural network for data selection with the allocation of the relevant stages is proposed. Building on this, a practical demonstration of the simplest recurrent neural network is proposed, with an exploration of the stages involved in this process. An algorithm for constructing the proposed system is outlined. Conclusions are drawn about the promising areas for applying data mining methods.

Optimisation algorithms are critical methods and tools that can improve engineering and science fields. However, researchers are confronting challenges in the subject due to a lack of a major approach for comparisons and effective benchmarking. This requires human implementation of the algorithms, such as configuration and execution, which is time-consuming and prone to errors. This paper proposes OptimUse, a user-friendly Graphical User Interface (GUI) software built primarily to address the issues that researchers experience in this sector. OptimUse includes both single-object and multi-objective metaheuristic optimisation algorithms that can operate seemingly while providing parameter adjustment and execution. Users of OptimUse do not need programming experience or coding abilities because the software's design allows them to select algorithms from dropdown lists and parameter tunings, allowing them to acquire the results of their desired algorithm without writing any code. Furthermore, it includes standard benchmark test functions as well as real-world functions, such as the beam problem, providing a large study field for researchers. OptimUse can also be extended further because it is an open-source platform that allows users to integrate new optimisation methods. Before launching OptimUse, the software underwent many testing procedures, including white box testing and black box testing, which hampered it further. This paper proposes a solution to the problem of a unified software package that includes all the optimization methods in one place. OptimUse improves time efficacy, portability, accessibility, and repeatability, resulting in a strong and versatile solution that may be used in research studies to compare algorithms more easily. The open-source framework is available at: https://github.com/Tarik4Rashid4/OptimUse.git

not-yet-known not-yet-known not-yet-known unknown Unveiling the self-assembly mechanism of amphiphilic peptide is crucial for the development of functional supramolecular biomaterials. The chemical properties of hydrophilic amino acids play an essential role in this process. Our multiscale molecular dynamic (MD) simulations indicated that the hydrophilic residue, threonine (T) was an excellent candidate to balance the hydrophobicity of the peptide, which could enhance the peptide self-assembly performance. In addition, simulations demonstrated that the number of hydrogen bonds in peptide aggregates was irrelevant to the peptides self-assembly. Avoiding hydrophilic side chains from disrupting the hydrogen bond network between the peptide backbones can improve self-assembly stability. Together with the experimental validation, we believe that T is a promising amino acid to balance the hydrophobicity of amphiphilic peptides. This work highlighted the importance of hydrophilic amino acids in peptide self-assembly, which could be further utilized in designing amphiphilic peptides with different functions.

not-yet-known not-yet-known not-yet-known unknown Amusement turned out to be a deadly encounter: a unique case of severe alcoholic ketoacidosis Esmail Sangey1, Frank Minja1, Shaffin Rajan1, Hilary Chipongo1 1 Critical Care Department Shree Hindu Mandal Hospital, P.O BOX 581, Dar es Salaam, Tanzania Corresponding author: esangey@hotmail.com

Background Intraductal papilloma (IDP) is a benign lesion, rarely exceeding 10 cm in diameter, which may be associated with carcinoma in situ or invasive carcinoma components, leading to difficult diagnostic imaging or puncture biopsy pathology. Case We describe the case of a middle-aged woman with a giant IDP of the breast

The significance of cybersecurity in today's globally linked world is paramount. Cybercriminals are finding new and more sophisticated ways to compromise fleet management systems, which regulate and track giant groupings of cars. The potential for cyberattacks is rising exponentially due to the increasing data-driven integration of various systems. Security threats, such as cyber vulnerabilities (CVs), have grown in tandem with the potential uses of extensive data-based communication in multiple sectors, including the autonomous car business. Data transmission between autonomous vehicles and Internet of Things devices may be more susceptible to cyberattacks because of the symmetry of extensive data communication networks employed by these vehicles. Both symmetric and asymmetric algorithms can encrypt the data associated with CVs. Proactive cybersecurity solutions for autonomous vehicles, power-based cyberattacks, and dynamic responses are among the many new concerns and opportunities presented by technological breakthroughs and shifting security threats. A lot of big data research has gone into finding ways to lessen the impact of CVs and big data breaches by implementing security solutions. Big data communication, autonomous vehicular networks (AVNs), and DCAVs will face future security challenges, primarily from CVs in data communication, vulnerabilities in AVMs, and cyber threats to network functioning. For this reason, security algorithms and countermeasure models must be efficient if CVs and data breaches are to be minimized. Integrating CV policies and rules with proxy and DMZ servers strengthened the countermeasure's effectiveness. Here, the energy levels of individual attacks are established to determine the information security measures that are reliant on the increasing degrees of assaults and CVs.

Software-defined networking, sometimes known as SDN for short, is an intriguing method of networking that combines centralized management with network programming. When software-defined networking (SDN) is utilized, the control plane and the data plane are separated, and the network management is transferred to a central place known as the controller. In addition to being able to be programmed, this controller acts as the brain of the network. Over the past few years, the research community has shown a rising tendency to reap the benefits of current discoveries in artificial intelligence (AI) to increase their capacity for learning and decision-making in software-defined networking (SDN). It has been established that they have this propensity to boost their capacity to learn and to make judgments. This paper comprehensively overviews recent initiatives undertaken to incorporate AI into SDN. According to our research findings, the most often discussed topics in artificial intelligence were machine learning, meta-heuristics, and fuzzy inference systems. This study aims to evaluate the potential advantages of introducing AI-based approaches into the SDN paradigm and the possible uses and applications for these methodologies.

This article employs Critical Discourse Analysis (CDA) to examine the works of Ernst Jünger and Martin Heidegger, arguing that their philosophical metaphors on war, death, and existential authenticity have not only reflected post-World War I crises but have also inadvertently contributed to the normalization of violence in modern political discourse. By analyzing key texts (such as *Storm of Steel* and *Being and Time*) and their indirect influence on authoritarian movements of the 21st century, it is demonstrated how the "aesthetics of darkness" in philosophy can become a tool for justifying destructive ideologies. This research warns that uncritical readings of these texts risk reproducing a "sanctified madness." 

BACKGROUND: Acute bronchiolitis is the first episode of respiratory distress in children under 24 months, characterised by wheezing and crackling rales. Diagnosis is clinical, with no routine supplementary tests recommended. This study aims to determine the utility of lung ultrasound in predicting the course of acute bronchiolitis in patients that require hospitalisation. METHODS: A prospective observational and analytical study was conducted with 100 patients aged 0-2 years, hospitalised in the Infant Hospitalisation Unit, Neonatology, or Neonatal Intensive Care Unit (NICU) with a diagnosis of acute bronchiolitis. Two lung ultrasounds were performed, one at admission and one at discharge, scored using the Pulmonary Score by Zoido Garrote et al 3. RESULTS: A threshold of 12.5 points (Sensitivity 90%, Specificity 89.7%, AUC 0.96) was set for initiating respiratory support and 17.5 points for ICU admission (S 83.3%, E 93.9%, AUC 0.95). There was a significant correlation between the Pulmonary Score and clinical severity scales, days of respiratory support, hospitalisation duration, and FiO2 requirement. CONCLUSIONS: The Pulmonary Score could be a useful indicator for predicting the need for respiratory support or intensive care in acute bronchiolitis patients. More multicenter studies with larger sample sizes are needed to further investigate the utility of lung ultrasound and the Pulmonary Score in acute bronchiolitis.

Objectives Automatic capture confirmation (ACC) algorithms monitor the pacing capture threshold (PCT) and adjust energy output to deliver a tailored safety margin over the PCT, while providing a high-output backup safety pulse in the event of non-capture. Advantages of these algorithms include increased device longevity, enhanced patient safety, and improved remote monitoring capabilities. While such algorithms have been validated for conventional right ventricular pacing (RVP) locations, there is limited information on their performance for pacing in the increasingly utilized location of the left bundle branch area (LBBA). Our objective was to evaluate the longitudinal performance and stability of the Abbott AutoCapture™ algorithm in patients with left bundle branch area pacing (LBBAP). Methods De-identified remote device data were retrospectively analyzed from consecutive patients in our hospital who received AutoCapture enabled Abbott pacemakers with LBBAP from June 2021 to August 2023. Device stored AutoCapture PCT measurements were then evaluated incrementally over an approximate 2-year period, to evaluate longer-term trends and performance, and also compared with the original, manual PCT at the time of initial implant. Results A total of 619 patients with either single chamber (model 1272, n= 89) or dual-chamber Abbott devices (model 2272, n= 530) were identified. AutoCapture and manually measured PCTs at implant were within 0.25 V in 600/615 (97.6%) patients, with average PCTs of 0.76 V ± 0.28 and 0.80 V ± 0.26 respectively, at a pulse width of 0.5 ms. At 1, 3, 6, 12, and 24-month remote follow-up, average AutoCapture PCTs were 0.67 V ± 0.29 (n=594), 0.66 V ± 0.25 (n=560), 0.71 V ± 0.29 (n=543), 0.77 V ± 0.29 (n=447) and 0.81 V ± 0.28 (n=112), respectively. At the last remote follow-up, lead impedances were 536 ohms ±60, and sensed R-wave amplitude were 11 mV ± 3. AutoCapture was found to be effective in assessing PCT and was activated in the majority of patients (619/644, 97%) without complications related to its activation or usage during the follow-up period. Conclusion The AutoCapture algorithm measured accurate PCTs at implant and showed a stable trend during follow-up out to approximately 2 years in patients with LBBAP.

This letter critically examines the study titled ”Catheter Ablation Improves Ventilatory Efficiency in Atrial Fibrillation‐Mediated Cardiomyopathy” by Ahluwalia et al., which investigates the impact of catheter ablation (CA) on ventilatory efficiency in atrial fibrillation (AF)-mediated cardiomyopathy. While the study presents valuable findings, we raise concerns regarding the oversimplification of the relationship between left atrial volume reduction and improvements in exercise oscillatory ventilation (EOV). We argue that the factors influencing EOV, such as peripheral muscle deconditioning, altered chemoreceptor sensitivity, and systemic inflammation, were not adequately addressed. Additionally, the study’s limited electrophysiological analysis does not fully explore the arrhythmic mechanisms contributing to ventilatory inefficiency. Our letter calls for a more comprehensive evaluation of the complex interactions involved in ventilatory efficiency and the electrophysiological effects of CA.

Post-implant infections of pacemakers or defibrillators represent a significant complication, impacting patient morbidity and mortality. This case report describes a 75-year-old man with multiple comorbidities who developed pocket erosion of a previously implanted biventricular defibrillator, complicated by Staphylococcus Haemolyticus infection. Following device extraction and targeted antibiotic therapy, an extravascular implantable cardioverter defibrillator (EV-ICD) Aurora EV-ICD™ was implanted. The procedure was successfully performed, with a two-month follow-up showing no signs of infection or device displacement. EV-ICD emerges as a safe and effective alternative in high-risk patients, minimizing complications associated with vascular access and endocardial lead implantation.