Complex Nature Research Articles

Parkinson's disease mutant Miro1 causes mitochondrial dysfunction and dopaminergic neuron loss

Abstract The complex and heterogeneous nature of Parkinson’s disease (PD) is still not fully understood, however, increasing evidence supports mitochondrial impairment as a major driver of neurodegeneration. Miro1, a mitochondrial GTPase encoded by the RHOT1 gene, is involved in mitochondrial transport, mitophagy and mitochondrial calcium buffering, and is therefore essential for maintaining mitochondrial homeostasis. Recently, Miro1 has been linked genetically and pathophysiologically to PD, further supported by the identification of heterozygous variants of Miro1 in patients. Herein, we used patient-derived cellular models alongside knock-in mice to investigate Miro1-dependent pathophysiological processes and molecular mechanisms underlying neurodegeneration in PD. Experimental work performed in induced pluripotent stem cells (iPSC)-derived models, including midbrain organoids and dopaminergic neuronal cell cultures from a PD patient carrying the p.R272Q Miro1 mutation as well as healthy and isogenic controls, indicated that the p.R272Q Miro1 mutation leads to increased oxidative stress, disrupted mitochondrial bioenergetics and altered cellular metabolism. This was accompanied by increased α-synuclein levels and a significant reduction of dopaminergic neurons. Moreover, the p.R272Q Miro1 mutation – located in the calcium-binding domain of the GTPase – disrupted calcium homeostasis. This resulted in the calcium-dependent activation of calpain proteases and the subsequent cleavage of α-synuclein. Knock-in mice expressing p.R285Q Miro1 (the orthologue of the human p.R272Q mutation) displayed accumulation of phosphorylated α-synuclein in the striatum and a significant loss of dopaminergic neurons in the substantia nigra, accompanied by behavioral alterations. These findings demonstrate that mutant Miro1 is sufficient to comprehensively model PD-relevant phenotypes in vitro and in vivo, reinforcing its pivotal role in PD pathogenesis.

Painful Left Bundle Branch Block Syndrome: A Systematic Review of Treatment Strategies in Case Reports.

Painful left bundle branch block (PLBBB) syndrome remains a poorly understood cardiac anomaly. This systematic review consolidates case report evidence to elucidate effective management strategies and patient outcomes. Databases including PubMed, Scopus, Web of Science, and Scielo were searched without restrictions on language or publication date. Following PRISMA guidelines, 128 articles were identified, with 31 meeting inclusion criteria. Data were extracted on patient demographics, clinical presentation, treatment regimens, and outcomes using Microsoft Excel and assessed for bias with the Joanna Briggs Institute's tool. The analysis included 45 patients with a mean age of 55.46 ± 12.23. Predominantly, LBBB episodes occurred during exercise (73.3%). Initial treatments comprised beta-blockers/calcium channel blockers (55.56%), pacemaker implantation (13.3%), antianginal medications (13.3%), and other modalities (17.7%). Refractoriness to initial treatment was observed in 66.7% of patients, with subsequent pacemaker implantation resolving symptoms in most cases. An overall satisfactory response was seen in 73.3% of patients post-treatment adjustments. The diverse approaches in treatment highlight the necessity for tailored therapeutic strategies. While pacemakers have demonstrated efficacy in controlling symptoms in several reported cases, it is essential to recognize the complex nature of this intervention. Pacemaker implantation, being a surgical procedure, carries long-lasting implications for patients. Hence, the continuation of pharmacological treatments might still be preferable until more definitive research is available. This review emphasizes the urgent need for further research to establish evidence-based guidelines, particularly concerning the selection of first line of treatment, to optimize outcomes for PLBBB syndrome.

The politics of digital sovereignty and the European Union’s legislation: navigating crises

In recent years, the resistance of member states to the strengthening of the European Union and its ambition to extend the powers of nation states has become a dominant political element, especially in the countries of the Central and Eastern European region. At the same time, both nation states and the EU are facing a number of global challenges, one of the most significant of which, alongside climate change, is digitalization. At the dawn of the digital age, technological innovation and the free flow of information promised unprecedented opportunities. However, as digital technologies have increasingly permeated all aspects of economic, social and political life, they have created new crises and challenges, particularly with regard to digital sovereignty. This research explores the complex and interdisciplinary nature of digital sovereignty, with a particular focus on the crises that digitalization has triggered and caused. These crises manifest themselves in various forms, including cybersecurity threats, privacy issues and the economic dominance of global technology companies. The European Union’s legislative initiatives, including the Digital Services (DSA), Digital Markets (DMA) and European Media Freedom (EMFA) regulations, as well as the efforts to regulate artificial intelligence, are designed to address the crises inherent in the digital age, while at the same time posing new challenges to the sovereignty and perception of sovereignty of individual states. The research examines the EU’s legislative efforts in navigating the politics of digital crises. It sheds light on the interplay between national self-determination and the EU’s overall regulatory framework, highlighting the ongoing struggle to balance control and cooperation in a rapidly changing digital environment. The analysis will provide a deeper understanding of how digital sovereignty is shaped by and responds to crisis policy, and insights into the future of digital governance in an increasingly interconnected world. It also seeks to assess the extent to which recently introduced EU legislation can be harmonized with the policy objective of strengthening the autonomy of nation states. This is particularly important in the context of the legislation and practices observed in countries with relatively small populations, such as Hungary, Slovakia and the Czech Republic.

Uncovering Deterministic Behavior of Black Hole IGR J17091–3624: A Twin of GRS 1915+105

Abstract Understanding the nonlinear properties in accreting systems, particularly for black holes, from observation is illuminating as they are expected to be general relativistic magnetohydrodynamic flows that are nonlinear. Two commonly used features associated with nonlinear systems are chaos, which is deterministic, and randomness, which is stochastic. The differentiation between chaotic and stochastic systems is often considered to quantify the nonlinear properties of an astrophysical system. Particular emphasis is given to the fact that data are often noise contaminated and finite. We examine the dual nature of the black hole X-ray binary IGR J17091–3624, whose behavior has been closely studied in parallel to GRS 1915+105. Certain similarities in the temporal classes of these two objects have been explored in the literature. However, this has not been the case with their nonlinear dynamics: GRS 1915+105 shows signs of both determinism and stochasticity, while IGR J17091–3624 was found to be predominantly stochastic. Here, we confront the inherent challenge of noise contamination faced by previous studies, particularly Poisson noise, which adversely impacts the reliability of nonlinear results. We employ several denoising techniques to mitigate noise effects, and employ methods like principal component analysis, singular value decomposition, and correlation integrals to isolate the deterministic signatures. We find signs of determinism in IGR J17091–3624, thus supporting the hypothesis of it being similar to GRS 1915+105, even as a dynamical system. Our findings not only shed light on the complex nature of IGR J17091–3624 but also pave the way for future research employing noise-reduction techniques to analyze nonlinearity in observed dynamical systems.

Retrieving Continuous-Time Event Sequences Using Neural Temporal Point Processes with Learnable Hashing

Temporal sequences have become pervasive in various real-world applications such as finance, spatial mobility, health records, and so on. Consequently, the volume of data generated in the form of continuous-time event sequence(s) or CTES(s) has increased exponentially in the past few years. Thus, a significant fraction of the ongoing research on CTES datasets involves designing models to address downstream tasks such as next-event prediction, long-term forecasting, sequence classification, and so on. The recent developments in predictive modeling using marked temporal point processes (MTPP) have enabled an accurate characterization of several real-world applications involving the CTESs. However, due to the complex nature of these CTES datasets, the task of large-scale retrieval of temporal sequences has been overlooked by the past literature. In detail, by CTES retrieval we mean that for an input query sequence, a retrieval system must return a ranked list of relevant sequences from a large corpus. To tackle this, we propose NeuroSeqRet , a first-of-its-kind framework designed specifically for end-to-end CTES retrieval. Specifically, NeuroSeqRet introduces multiple enhancements over standard retrieval frameworks and first applies a trainable unwarping function on the query sequence which makes it comparable with corpus sequences, especially when a relevant query-corpus pair has individually different attributes. Next, it feeds the unwarped query sequence and the corpus sequence into MTPP-guided neural relevance models. We develop four variants of the relevance model for different kinds of applications based on the tradeoff between accuracy and efficiency. We also propose an optimization framework to learn binary sequence embeddings from the relevance scores, suitable for the locality-sensitive hashing leading to a significant speedup in returning top- K results for a given query sequence. Our experiments with several datasets show the significant accuracy boost of NeuroSeqRet beyond several baselines, as well as the efficacy of our hashing mechanism.

Textual evidence systematic reviews series paper 3: critical appraisal of evidence from narrative, opinion, and policy.

JBI has long held the view that an inclusive approach to the conceptualization of what counts as evidence is important to the evidence-based movement. JBI's approach for appraising textual evidence had encompassed all forms of text (narrative, opinion, and policy), with one general tool used to guide critical appraisal. The proliferation of textual evidence and increase in textual evidence reviews demonstrate the need to reconceptualize JBI's methodological approach to critically appraising textual evidence. The objective of this paper is to outline the updated methodological approach to systematic reviews of textual evidence, especially in relation to the development of 3 separate critical appraisal tools for narrative, expert opinion, and policy text. Using an adapted Delphi approach, the JBI Textual Evidence Methodology Group convened over several rounds of meetings and discussions with international experts to reach consensus toward the reconceptualization of critical appraisal tools for textual evidence sources. Strategies to effectively interrogate the legitimacy and authenticity of sources were found to be dependent upon the type of textual evidence under review. Therefore, 3 separate critical appraisal tools for narrative, expert opinion, and policy text were developed. This paper provides an overview of the development of 3 separate critical appraisal tools, highlighting the complex nature of textual evidence data sources.

Does conservative or arthroscopic management of canine medial coronoid disease lead to improved outcomes?

Question In dogs diagnosed with medial coronoid disease, does arthroscopic surgical intervention, compared with conservative management, result in improved mobility and reduced pain? Clinical bottom line Category of research: Treatment. Number and type of study designs reviewed: Three studies were identified directly addressing the PICO question. One paper was a retrospective cohort study, another study was a prospective randomised control trial, and the third was a non-randomised non-blinded observational study. Strength of evidence: Weak. Outcomes reported: The first study was a prospective non-randomised study that did not identify a difference in gait evaluation at the 52 week recheck in dogs treated conservatively compared to those treated arthroscopically, with lameness exacerbated in the arthroscopic treatment group until the 26 week recheck. The second study, a retrospective non-randomised cohort study, showed greater, but not statistically different, owner-reported clinical metrology scores in dogs treated arthroscopically compared to those treated conservatively. Liverpool Osteoarthritis in Dogs (LOAD) and Pain Severity Scores (PSS) were higher but not statistically significant, yet Pain Interference Scores (PIS) were statistically significantly higher at 52 weeks in arthroscopically treated dogs compared to conservatively treated dogs. Age at diagnosis and at time of questionnaire completion were statistically significant for LOAD, PSS, and PIS, with older dogs having higher scores. The third study performed a non-blinded observational study assessing canine patients with bilateral medial coronoid disease, with unilateral arthroscopic subtotal coronoidectomy performed on the most clinically affected limb. Radiographs and computed tomography (CT) imaging were performed at diagnosis, with radiographs taken at follow-up. At the time of follow-up, arthroscopically treated limbs had a higher radiographic score than those treated conservatively, although a significant improvement in lameness was seen at the walk in arthroscopically treated limbs. Conservatively managed dogs showed an unchanged (non-significant) gait. Radiographic changes did not appear to correlate to severity of clinical signs. Conclusion: The quality of the published evidence available to answer the PICO question is weak, due to the design of the three reviewed studies. Low patient populations in these three studies also hinder the statistical power of any recommendations made. None of the three studies assesses the complex nature of medial coronoid disease to clearly answer the question posed. The decision to recommend arthroscopy over conservative management therefore depends on the judgement and experience of the veterinary surgeon attending the case. Additionally, assessment of the imaging findings is important when discussing prospective treatment options.

Adolescent girls' explanations of high rates of low mood and anxiety in their population: a co-produced qualitative study.

From early adolescence, girls face greater risk of experiencing low mood and anxiety relative to boys, with recent evidence that this may be worsening. There is a paucity of mental health research that meaningfully progresses understanding of these gender disparities, including that engages adolescent girls' own perspectives, limiting our ability to direct further research and enhance intervention approaches. We examined low mood and anxiety from the perspective of adolescent girls, asking: What do adolescent girls perceive to be causing their population's high rates of low mood and anxiety? We adopted a co-produced qualitative design, guided by ecological systems theory, conducting focus groups in 2022 with 32 adolescent girls aged 16 to 18 years in England. Data were analysed using reflexive thematic analysis. Participants framed low mood and anxiety among adolescent girls as "normal", and discussed potential explanations including persistent reiteration and expectation of gendered norms, intense educational pressures in ways that can be gendered, difficulties within peer relationships, and comparison and insecurity in social media contexts. Throughout, participants highlighted how complex these issues are, including nuances around individual differences, sociodemographic contexts, and societal contexts. The study offers a critically important contribution to evidence on gendered inequalities in low mood and anxiety, drawing attention to the interwoven and complex nature of girls' lives and illuminating various aspects that would benefit from greater research. The insights gained through exploration with girls themselves hold policy and practical relevance to enhance systems to meet girls' needs.

Thyroid function during COVID-19 and post-COVID complications in adults: a systematic review

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, has presented multifaceted health challenges. COVID-19 primarily targets the respiratory system but also affects multiple organ systems, including the endocrine system. Emerging evidence suggests interactions between thyroid function, the acute phase of COVID-19, and the prolonged symptoms known as post-COVID sequalae or long COVID. Several studies have reported that COVID-19 can induce thyroid dysfunction, leading to conditions such as thyroiditis and alterations in thyroid hormone levels. The mechanisms through which SARS-CoV-2 affects the thyroid include direct viral infection of thyroid cells, leading to viral thyroiditis, which causes inflammation and transient or sustained thyroid dysfunction, as well as an excessive systemic immune response (cytokine storm). This is associated with elevated levels of cytokines, such as IL-6, that disrupt thyroid function and lead to nonthyroidal illness syndrome (NTIS). Medications administered during the acute illness phase, such as corticosteroids and antiviral drugs, can also impact thyroid hormone actions. The involvement of the thyroid gland in long COVID, or postacute sequelae of SARS-CoV-2 infection, is an area not well defined, with potential implications for understanding and managing this condition. Persistent low-grade inflammation affecting thyroid function over time can lead to ongoing thyroiditis or exacerbate pre-existing thyroid conditions. Viral infections, including SARS-CoV-2, can trigger or worsen autoimmune thyroid diseases, such as Hashimoto’s thyroiditis and Graves’ disease. Long COVID may disrupt the hypothalamic–pituitary–adrenal (HPA) axis, which can, in turn, affect the hypothalamic-pituitary-thyroid (HPT) axis, leading to abnormal thyroid function. This review was designed to systematically capture recent literature on COVID-19-related thyroid dysfunction in the adult population, the prognostic consequences of thyroid dysfunction during COVID-19, and the effects of thyroid dysfunction on patients with long COVID. A comprehensive search of PubMed and EMBASE databases was conducted. The systematic review was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Study quality was assessed using the Critical Appraisal Skills Programme (CASP). A total of 53 studies met the inclusion criteria. The review summarises recent findings and provides an update of the current understanding of thyroid dysfunction in COVID-19-related spectrum of disorders, underscoring the complex nature of SARS-CoV-2 infection and its far-reaching impacts on human health.

A Study on Consumer-Centric Health Information Provision Strategy Using SWOT-AHP -Focusing on the National Health Information Portal.

Approximately 70% of Koreans access health and medical information online. Health information providers play a crucial role in enhancing public health by ensuring that individuals can effectively consume and utilize this information according to their information-seeking behaviors. However, existing tools for evaluating health information websites have significant limitations. These tools are often one-size-fits-all and lack strategic recommendations for delivering consumer-centered health information. There is a clear need for alternative approaches beyond merely identifying the quality factors that satisfy consumers. A Strengths, Weaknesses, Opportunities, and Threats-Analytic Hierarchy Process (SWOT-AHP) evaluates both internal and external environmental factors of a health information website, which provides strategies based on the prioritization and weighting of quality factors. Specifically, the 'National Health Information Portal,' a platform provided by the Korea Disease Control and Prevention Agency, was assessed through a comprehensive review of prior research and a SWOT analysis, followed by an AHP survey involving 15 experts specializing in health information websites. The findings of the analysis indicate that the most effective development strategy is the SO (Strengths-Opportunities) strategy. This study highlights the need to move beyond uniform evaluation tools and consider the dynamic and complex nature of the Internet, emphasizing the importance of developing prioritized strategies based on evaluations from both consumers and providers.

“Rat race” or “lying flat”? The influence of performance pressure on employees' work behavior

IntroductionPerformance pressure refers to employees' subjective perception of the necessity to achieve expected goals, accompanied by a sense of urgency and tension. This study explores how employees cope with performance pressure, focusing on two contrasting strategies: the “rat race” (proactive work behavior) or “lying flat” (work withdrawal). Grounded in the transactional theory of stress and affective event theory, this research aims to uncover the mechanisms through which performance pressure influences work behavior.MethodsA moderated dual-mediation model was developed to examine the dual pathways of challenge appraisal and workplace anxiety as mediators in the relationship between performance pressure and work behavior. Data were collected through a two-stage survey involving 356 employees from various industries. Statistical analyses, including structural equation modeling, were used to test the hypothesized relationships.ResultsThe findings reveal that performance pressure has a dual effect: it simultaneously stimulates challenge appraisal, promoting proactive work behavior, and induces workplace anxiety, leading to work withdrawal behavior. Additionally, learning goal orientation moderates these effects. Specifically, it strengthens the positive relationship between performance pressure and challenge appraisal while weakening the link between performance pressure and workplace anxiety.DiscussionThis study highlights the complex and dual nature of performance pressure in influencing employee behavior. By identifying learning goal orientation as a critical moderator, organizations can better understand how to harness the positive aspects of performance pressure while mitigating its negative effects. These insights provide practical guidance for managing performance pressure and minimizing associated risks in the workplace.

Correlation between traumatic brain injury, obesity and insulin-resistance – a case report

Introduction: Traumatic brain injury is a significant global health concern. It often results from high-velocity accidents and leads to diffuse axonal injury, causing consciousness disorders and potentially permanent cognitive and behavioural changes. Individuals with traumatic brain injury often exhibit weight gain, potentially leading to obesity. This weight increase is influenced by cognitive dysfunction, reduced physical activity and metabolic changes. Case report: A 23-year-old woman suffered a traumatic brain injury after a traffic accident, with an initial Glasgow Coma Scale score of 5/15. Positive neurological improvement was observed during her stay in the intensive care unit and the neurosurgical department. Subsequently, she was transferred to the rehabilitation department, where she faced significant challenges, including mood fluctuations, cognitive impairments and substantial weight gain. Her body mass index (BMI) increased from 23 kg/m2 pre-accident to a maximum of 36 kg/m2, despite interventions like medications and lifestyle changes. Blood tests revealed insulin-resistance and metformin initiated a successful weight reduction. Conclusion: Managing weight gain following traumatic brain injury requires effective interventions that acknowledge its complexity and multifaceted nature, including lifestyle modifications, behavioural therapy and potentially pharmacotherapy or bariatric surgery. Further research is essential to better understand underlying mechanisms and evaluate intervention effectiveness in this specific patient population.

Vibroarthrographic Signal Classification for Knee Joint Disorder Detection using Tunable Q-factor Wavelet Transform based on Entropy Measures

Research on Vibroarthrographic (VAG) signals presents a promising means for the early diagnosis of knee joint disorders. However, the classification problem for these signals faces serious issues due to their complex and dynamic nature. This study proposes a novel method for decomposing and analyzing VAG signals based on a Tunable Q-factor Wavelet Transform (TQWT) and entropy-based measures. TQWT is used to preprocess and decompose VAG signals recorded during knee motion into subbands. Different entropy metrics, such as approximate entropy, sample entropy, fuzzy entropy, slope entropy, and so on, were computed over different subbands of the signal to capture significant signal features. Effective features were selected using Recursive Feature Elimination (RFE) and then classified using ensemble classifiers such as XGBoost, Ensemble Random Forest (ERF), and RF-logistic regression. The classification accuracy of the proposed sample entropy method was 87.64% and had 90% sensitivity, 86.36% specificity, and 0.88 AUC-ROC. These results demonstrate the ability of the TQWT-based approach to discriminate knee joint abnormalities. Future work will explore performance scaling with larger datasets and apply it to other joint disorders.

DNA-Assembled Size-Permeable Microcapsule Bioreactor Enables Direct and Rapid Sensing of Trace Circulating MicroRNA Biomarkers in Undiluted Cancer Patient Serum.

Sensitive and direct detection of circulating microRNAs (miRNAs) in undiluted human serums can significantly facilitate the diagnosis of different diseases in the early stages; however, the achievement of such a goal is highly challenged by the extremely complex sample matrix nature of serums. Here, we show that sensitive and rapid detection of the circulating let-7a miRNA biomarker in undiluted cancer patient serums can be realized by a new size-permeable microcapsule bioreactor. The Cas13a/crRNA-dsDNA@polyethylene glycol core/shell biomicrocapsules are synthesized by simple encapsulation and etching steps. Such biomicrocapsules exhibit high stability, enhanced protein antifouling capability, and size-selective permeability that only allows short miRNA sequences to enter the core cavities, thereby enabling highly sensitive and direct detection of let-7a miRNA in undiluted serums down to 0.21 pM within 20 min via signal amplification by Cas13a/crRNA and near-infrared (NIR) fluorescence signals. The biomicrocapsule also allows unambiguous discrimination of the clear cell renal cell carcinoma patients from the healthy groups via direct detection of let-7a miRNA in the serum samples, thereby highlighting its robust clinical potential for early disease diagnoses.

An Integrated 3D DEM Modeling Process for Bimrocks Considering Post‐Peak Behavior and Block Breakage

ABSTRACTBimrocks, a complex rock mass commonly found in geotechnical engineering, are often analyzed through the discrete element method (DEM) to understand their mechanical behavior from both macro and micro perspectives. However, there is limited research addressing the post‐peak behavior of bimrocks, particularly in terms of the uniaxial compression stress–strain curve and failure characteristics, with many studies overlooking the complex nature of their post‐peak behavior. This study proposes a comprehensive method for constructing three‐dimensional (3D) numerical samples of bimrocks and selecting appropriate parameters, focusing on accurately capturing both the post‐peak curve shape and failure characteristics. By combining laboratory tests with CT scanning techniques, numerical samples with structures matching those of the physical samples are created, addressing the issue of block stone breakage in traditional discrete element simulations. The study introduces the selection criteria for matrix and block stone parameters and analyzes the microscopic factors influencing the post‐peak curve and failure characteristics. Results indicate that the damping coefficient and loading rate are crucial in shaping the post‐peak curve, with complex curves requiring multiple damping coefficients. Additionally, the radius multiplier influences crack propagation direction, while the strength ratio affects crack penetration and secondary cracking, with these factors being dependent on the matrix strength.

Efficient Liver Segmentation using Advanced 3D-DCNN Algorithm on CT Images

According to the latest global cancer statistics for 2022, liver cancer ranks as the ninth most common disease in women. Segmenting the liver and distinguishing it from tumors within it pose a significant challenge due to the complex nature of liver imaging. Common imaging methods such as Magnetic Resonance Imaging (MRI), Computer Tomography (CT), and Ultrasound (US) are employed to distinguish liver tissue from liver tumors after collecting a sample. Attempting to partition the liver and tumor based on grayscale shades or shapes in abdominal CT images is not ideal because of the overlapping intensity levels and the variability in the location and shape of soft tissues. To address this issue, this study introduces an effective method for liver image segmentation using a 3D deep Convolutional Neural Network (3D-DCNN). The process involves several stages. First, liver images undergo preprocessing to enhance image quality, including median filtering, adaptive filtering, and converting them to grayscale. The feature extraction phase focuses on extracting four sets of features, such as the Local Binary Pattern (LBP) and the Gray-Level Co-occurrence Matrix (GLCM). Additionally, an Iterative Region Growing (IRG) technique is developed to improve the Dice Similarity Coefficient (DSC) prediction by enhancing the quality of the input images obtained from segmented images. This method enables the segmentation of the liver in abdominal CT image volumes and can subsequently be used to segment liver tumor images to evaluate the performance of the proposed 3D-DLNN approach. This method was implemented in MATLAB, and its performance was evaluated using various metrics. In experimental analysis, the proposed technique outperformed other methods, including Jaccard with JISTS-FCM, Fuzzy C-Means (FCM), and FCM with Cluster Size Adjustment (FCM-CSA).

Serum choline, leptin and interleukin-6 levels in fibromyalgia syndrome-induced pain: a case–control study

BackgroundFibromyalgia Syndrome (FMS) predominantly affects middle-aged women, characterized by musculoskeletal pain, fatigue, and cognitive issues. Choline, an endogenous molecule, may influence FMS due to its analgesic and anti-inflammatory properties. This study compared choline, leptin, and interleukin-6 (IL-6) levels in FMS patients and controls and examining their association with pain severity.MethodsVolunteers with FMS were clinically diagnosed at a Physical Medicine and Rehabilitation Department. The control group included pain-free volunteers. Pain severity was gauged using a numeric scale, dietary choline intake through a questionnaire. Serum choline, leptin and (interleukin)IL-6 levels were measured from fasting blood samples of volunteers with enzyme-linked immunosorbent assays (ELISA).ResultsAll FMS patients (n = 38) and healthy volunteers (n = 38) were female. Pain score in patients with FMS was 7.6 ± 0.2. Dietary choline intake was lower in patients with FMS than the controls (p = 0.036). Serum choline and leptin levels were lower in the FMS group compared to control (p = 0.03). Serum IL-6 levels were higher in the FMS group than in the control (p < 0.001). There was weak positive correlation between IL-6 levels and pain scores and there were no correlation between leptin levels and pain scores in FMS.ConclusionsThis research highlights FMS's complex nature, involving neurochemical, immunological, and nutritional factors. It suggests the significance of choline's anti-inflammatory effect, leptin's metabolic function, and IL-6's role in FMS pathology. The results suggest that reduced dietary choline might influence serum choline, leptin, and IL-6 levels, potentially impacting FMS-related pain. This points to the potential of supplementary choline intake in FMS management.Trial registrationNot applicable (Non-interventional study).

Evaluation of the effects of amitraz on the enzyme activity and stability of lysozyme: Spectroscopic and MD simulation approach.

The binding interaction of food preservatives and pesticides has emerged as a matter of paramount importance as it not only presents potential health hazards but also carries substantial consequences for food processing and preservation. Herein, the mechanism of interaction between lysozyme and Amitraz was explored through spectroscopic and computational techniques. Spectral investigations indicated the spontaneous nature and stability of the lysozyme-Amitraz complex. The corresponding CD and FT-IR studies proved the structural changes of lysozyme. The presence of amitraz led to a notable decrease in both the enzymatic activity and thermal stability of lysozyme. Molecular docking demonstrated the preferred mode of interaction, and molecular dynamics simulations confirmed the stability of the resultant complex. In conclusion, the alarming findings of the lysozyme-Amitraz interaction underscore its detrimental impact on food safety and human health. Accordingly, urgent measures are imperative to address and mitigate the potential hazards posed by such interactions in food production.

Hyaluronic acid regulated facile synthesis of size-tunable multifunctional nanomedicine for effective cancer therapy.

The complex and heterogeneous nature of cancer necessitates the development of innovative multifunctional nanomedicines (MN). Hyaluronic acid (HA) is a functional carbohydrate polysaccharide that is widely used in various biomedical fields. In this study, we employed HA as a stabilizer and regulator for the synthesis of a size-tunable nanomedicine comprising ferric ions, doxorubicin, and epigallocatechin gallate (EGCG), referred to as HDE-MN, for cancer therapy. A change in the HA ratio can yield HDE-MNs with sizes varying from ~20nm to over 100nm. Modified HA can respond to hyaluronidase (HAase) to provide controllable pH/HAase dual-responsive drug release for improved cancer therapy. Moreover, HA can mediate the targeted delivery of HDE-MNs both in vitro and in vivo to cancer cells. In addition, HDE-MNs reversed multidrug resistance owing to the incorporation of EGCG, inducing ferroptosis due to the involvement of ferric ions. More importantly, HDE-MNs have a photothermal conversion effect, enabling photothermal therapy, photothermally enhanced drug release, and ferroptosis, which collectively contribute to significantly improved cancer therapy. Therefore, the HDE-MNs with laser irradiation achieved full ablation of the in vivo tumors. Together with its good biocompatibility, HDE-MNs may be promising for effective cancer therapy.

Evaluating the Mental Health (MH) impact of the COVID-19 pandemic for stable patients with HIV

ABSTRACT People living with HIV (PLWH) have a higher prevalence of mental ill health compared to the general population. We aimed to understand the impact of the COVID-19 pandemic and omitting routine HIV appointments on the mental health (MH) of PLWH. Between April 2020 and March 2021, routine appointments for “stable” PLWH were replaced by virtual consultations. MH assessments using standardised questionnaires were compared before and during the pandemic. Full data were available for 426 individuals after excluding those with incomplete data and those requiring early review for non-MH-related issues. The results showed that 277 (65%) experienced no/minimal MH symptoms throughout, indicating robust MH. For depression, scores worsened in 59 (13.8%), improved in 62 (14.6%) and remained stable in 305 (71.6%). For anxiety, scores worsened in 55 (12.9%), improved in 64 (15%) and remained stable in 307 (72.1%). A total of 98.4% of individuals remained virally suppressed, with 7 developing a detectable viral load. One person stopped antiretroviral treatment secondary to an MH crisis. Findings suggest that the COVID-19 pandemic did not significantly impact the overall MH in our cohort of PLWH. It also demonstrates an effective implementation of virtual consultations. The complex nature of MH in PLWH highlights the need for individualised MH care.