Navigating the complexities of neuronal signaling and targets in neurological disorders: From pathology to therapeutics

Neurological disorders arising from structural and functional disruptions in the nervous system present major global health challenges. This review examines the intricacies of various cellular signaling pathways, including Nrf2/Keap1/HO-1, SIRT-1, JAK/STAT3/mTOR, and BACE-1/gamma-secretase/MAPT, which play pivotal roles in neuronal health and pathology. The Nrf2-Keap1 pathway, a key antioxidant response mechanism, mitigates oxidative stress, while SIRT-1 contributes to mitochondrial integrity and inflammation control. Dysregulation of these pathways has been identified in neurodegenerative and neuropsychiatric disorders, including Alzheimer's and Parkinson's diseases, characterized by inflammation, protein aggregation, and mitochondrial dysfunction. Additionally, the JAK/STAT3 signaling pathway emphasizes the connection between cytokine responses and neuroinflammation, further compounding disease progression. This review explores the crosstalk among these signaling networks, elucidating how their disruption leads to neuronal decline. It also addresses the dual roles of these pathways, presenting challenges in targeting them for therapeutic purposes. Despite the potential benefits of activating neuroprotective pathways, excessive stimulation may cause deleterious effects, including tumorigenesis. Future research should focus on designing multi-targeted therapies that enhance the effectiveness and safety of treatments, considering individual variabilities and the obstacles posed by the blood-brain barrier to drug delivery. Understanding these complex signaling interactions is crucial for developing innovative and effective neuroprotective strategies that could significantly improve the management of neurological disorders.

Therapeutic potential of butyrate against heat Stress-Induced intestinal damage, systemic inflammation, and multiple organ Dysfunction: Insights from in vitro and in vivo experiments

Global warming is a major risk factor for life-threatening heat stroke (HS). Systemic inflammation plays a key role in the pathophysiology of HS, substantially affecting clinical outcomes. Reduced intestinal blood flow during HS causes ischemia-reperfusion injury, compromising the intestinal barrier and triggering systemic inflammation and organ damage. Butyrate, a short-chain fatty acid, plays a multifaceted role in maintaining intestinal health, inhibiting inflammation, and alleviating oxidative stress. Therefore, this study aimed to evaluate butyrate's therapeutic potential against HS and explored the mechanisms underlying its protective effects. Male Wistar rats were divided into 4 groups: control, control + butyrate, HS, and HS + butyrate. Hemodynamic changes, biochemical parameters, coagulation markers, cytokine levels, polymorphonuclear neutrophil infiltration, and survival rates were analyzed. Additionally, ileal samples (from rats) and LS174T cells were used to investigate the effect of butyrate on intestinal function. Heat stress induced cytotoxicity; reduced transepithelial resistance in intestinal goblet cells; and triggered intestinal inflammation, oxidative stress, and apoptosis in HS rats. These rats exhibited systemic inflammation, hypotension, tachycardia, coagulopathy, multiple organ dysfunction, and mortality. Butyrate treatment reduced cytotoxicity and improved transepithelial resistance in LS174T cells. Butyrate also reduced intestinal heat stress, inflammation, oxidative stress, and apoptosis, as well as systemic inflammation in HS rats. Furthermore, butyrate ameliorated hypotension, tachycardia, coagulopathy, and multiple organ dysfunction and increased survival in HS rats. These findings indicate that butyrate is a promising intervention for mitigating heat stress-induced intestinal damage, systemic inflammation, and multiple organ dysfunction.

Effect of probiotic extracellular vesicles and their applications on health and disease

Probiotics have been established to exert a positive impact on the treatment of various diseases. Indeed, these active microorganisms have garnered significant attention in recent years for their potential to prevent and treat illnesses. Their beneficial effects have been hypothesized to be linked to their released extracellular vesicles. These nanoscale structures, secreted during the growth and metabolism of probiotics, possess favorable biocompatibility and targeting properties, thereby promoting intercellular material transport and signaling. This article aimed to review the bioactive components and functions of these probiotics vesicles, highlighting their role in the treatment of various diseases and discussing their potential future applications. By exploring the mechanisms of probiotic extracellular vesicles in disease development, this review aimed to provide a theoretical reference for further research on their therapeutic potential. © 2025 Society of Chemical Industry.

Resveratrol: A Natural Compound Targeting the PI3K/Akt/mTOR Pathway in Neurological Diseases

Neurological diseases (NDs), including neurodegenerative disorders and acute injuries, are a significant global health concern. The PI3K/Akt/mTOR pathway, a crucial signaling cascade, is responsible for the survival of cells, proliferation, and metabolism. Dysregulation of this pathway has been linked to neurological conditions, indicating its potential as a vital target for therapeutic approaches. Resveratrol (RSV), a natural compound found in berries, peanuts, and red grapes, has antioxidant, anti-cancer, and anti-inflammatory effects. Its ability to modulate the PI3K/Akt/mTOR pathway has been interesting in NDs. Studies have shown that RSV can activate the PI3K/Akt pathway, promoting cell survival and inhibiting apoptosis of neuronal cells. Its impact on mTOR, a downstream effector of Akt, further contributes to its neuroprotective effects. RSV's ability to restore autophagic flux presents a promising avenue for therapeutic intervention. Its anti-inflammatory properties suppress inflammatory responses by inhibiting key signaling molecules within the pathway. Additionally, RSV's role in enhancing mitochondrial function contributes to its neuroprotective profile. This study highlights RSV's potential as a multifaceted therapeutic agent in NDs, specifically by PI3K/Akt/mTOR pathway modulation. Additional investigation is required to optimize its therapeutic capacity in diverse neurological conditions.

Advancing osteoarthritis research: the role of AI in clinical, imaging and omics fields

Osteoarthritis (OA) is a degenerative joint disease with significant clinical and societal impact. Traditional diagnostic methods, including subjective clinical assessments and imaging techniques such as X-rays and MRIs, are often limited in their ability to detect early-stage OA or capture subtle joint changes. These limitations result in delayed diagnoses and inconsistent outcomes. Additionally, the analysis of omics data is challenged by the complexity and high dimensionality of biological datasets, making it difficult to identify key molecular mechanisms and biomarkers. Recent advancements in artificial intelligence (AI) offer transformative potential to address these challenges. This review systematically explores the integration of AI into OA research, focusing on applications such as AI-driven early screening and risk prediction from electronic health records (EHR), automated grading and morphological analysis of imaging data, and biomarker discovery through multi-omics integration. By consolidating progress across clinical, imaging, and omics domains, this review provides a comprehensive perspective on how AI is reshaping OA research. The findings have the potential to drive innovations in personalized medicine and targeted interventions, addressing longstanding challenges in OA diagnosis and management.

What Information do Systemic Pathological Changes Bring to the Diagnosis and Treatment of Alzheimer's Disease?

Alzheimer's disease (AD) is regarded as a neurodegenerative disease, and it has been proposed that AD may be a systemic disease. Studies have reported associations between non-neurological diseases and AD. The correlations between AD pathology and systemic (non-neurological) pathological changes are intricate, and the mechanisms underlying these correlations and their causality are unclear. In this article, we review the association between AD and disorders of other systems. In addition, we summarize the possible mechanisms associated with AD and disorders of other systems, mainly from the perspective of AD pathology. Regarding the relationship between AD and systemic pathological changes, we aim to provide a new outlook on the early warning signs and treatment of AD, such as establishing a diagnostic and screening system based on more accessible peripheral samples.

Potential of integrating phytochemicals with standard treatments for enhanced outcomes in TBI

OBJECTIVE

TBI's intricate pathophysiology, which includes oxidative stress, neuroinflammation, apoptosis, and mechanical injury, makes it a serious public health concern. Although stabilization and secondary damage management are the main goals of current treatments, their efficacy is still restricted. The potential for improving patient outcomes by combining phytochemicals with traditional medicines is examined in this review.

METHODS

The study examined the neuroprotective qualities of ginsenosides, ginkgolides, resveratrol, and curcumin as well as their antioxidant and anti-inflammatory activities. Analysis was done on molecular pathways and medication delivery techniques to improve translational outcomes and drug availability for clinical practice.

RESULTS

Phytochemical substances directly influence TBI-related neurogenic pathways and functional restoration while also affecting subsequent neural damage processes. Particle-based medicine delivery platforms enhance therapeutic drug efficacy, emerging as innovative solutions for targeted drug delivery. When traditional medical therapies integrate with phytochemicals, it becomes possible to achieve better patient results through enhanced synergy.

CONCLUSION

This review uniquely integrates phytochemicals with standard TBI treatments, emphasizing advanced drug delivery strategies and their translational potential to enhance neuroprotection and clinical outcomes. Unlike previous studies, it explores novel drug delivery platforms, such as nanoparticle-based systems, and highlights the synergy between phytochemicals and conventional therapies to improve patient recovery.

Population Health in Neurology and the Transformative Promise of Artificial Intelligence and Large Language Models

This manuscript examines the expanding role of population health strategies in neurology, emphasizing systemic approaches that address neurological health at a community-wide level. Key themes include interdisciplinary training in public health, policy reform, biomedical informatics, and the transformative potential of artificial intelligence (AI) and large language models (LLMs). In doing so, neurologists increasingly adopt a holistic perspective that targets the social determinants of health, integrates advanced data analytics, and fosters cross-sector collaborations-ensuring that prevention and early intervention are central to their efforts. Innovative applications, such as predictive analytics for identifying high-risk populations, digital twin technologies for simulating patient outcomes, and AI-enhanced diagnostic tools, illustrate the transition in neurology from reactive care to proactive, data-driven interventions. Examples of transformative practices include leveraging wearable health technologies, telemedicine, and mobile clinics to improve early detection and management of neurological conditions, particularly in underserved populations. These emerging methodologies expand access to care while offering nuanced insights into disease progression and community-specific risk factors. The manuscript emphasizes health disparities and ethical considerations in designing inclusive, data-driven interventions. By harnessing emerging technologies within frameworks that prioritize equity, neurologists can reduce the burden of neurological diseases, improve health outcomes, and establish a sustainable, patient-centered model of care benefiting both individuals and entire communities. This integration of technology, interdisciplinary expertise, and community engagement fosters a future where brain health is preventive, accessible, and equitable.

Associations between oral health measures and cognitive function in middle aged and older Indian adults

Given India's rise in ageing population and emerging epidemiological evidence of the possible association between poor oral health and cognitive impairment, the present study examined associations between oral health measures and cognitive function using a cross-sectional dataset from Longitudinal Aging Study in India, 2017-2018. Analysis included 56,738 participants aged ≥ 45 years old. Self-reported physician-diagnosed oral health measures included loss of teeth (some or all), presence of painful teeth, ulcers, bleeding and swelling gums, loose teeth, dental cavities or caries, and soreness or cracks in the corners of the mouth. Cognitive function was assessed using a battery of neurocognitive tests across five domains: memory, orientation, arithmetic function, executive function, and object naming. Findings from multivariable regression models revealed that participants who lost all their teeth had lower cognition scores by 0.65 points [β= -0.65, 95% CI: -0.97, -0.33] than those who had not lost any teeth. An unexpected positive association was found between three or more oral conditions and cognitive performance [β = 0.53, 95% CI: 0.28, 0.77] that needs further investigation. Findings suggest that oral health is associated with cognitive function and there is a need to promote policies targeted at improving the oral health infrastructure and health education.

Nigrostriatal iron accumulation in the progression of Parkinson's disease

Iron deposition in the nigrostriatal system plays a pivotal role in Parkinson's disease (PD) onset and progression. This study explored the time course of nigrostriatal iron accumulation in 54 PD patients at early to moderately advanced stages and 20 age-matched healthy controls. Using multi-echo T2*-MRI and R2* relaxometry, iron content was assessed in the substantia nigra pars compacta (SNpc) and striatum. In vivo findings were contrasted with histological analyses in a progressive 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced parkinsonism model involving six non-human primates (NHPs) and two controls using Perls' Prussian blue staining. Complementarily, dopaminergic degeneration was quantified by 6-[18F]-fluoro-L-dopa PET in humans and TH immunohistochemistry in NHPs. Results showed progressive iron accumulation in the SNpc correlating with striatal dopaminergic denervation and neuronal loss. Striatal iron followed a V-shaped progression, decreasing initially and increasing later. Iron in the SNpc may serve as a marker of neurodegeneration in PD, while decreased striatal iron may indicate pathological susceptibility to dopaminergic loss.

Mitigating intubation stress, mucosa injury, and inflammatory response in nasogastric tube intubation via suppression of the NF-κB signaling pathway by engineering a hydration lubrication coating

Nasogastric tube (NGT) intubation is a common yet critical clinical procedure. However, complications arising from tube friction result in awful pain and morbidity. Here, we report a straightforward surface modification of slender NGT utilizing highly hydrated micelles that were composed of hyaluronic acid and Pluronic. The strong intermolecular hydrogen bonding facilitated the assembly of the micelles on NGT via a one-step dip coating process. The micelle coating conferred excellent hydrophilic, lubrication, anti-protein adhesive, and biocompatible properties. The in vivo efficacy of the micelle coating in alleviating catheterization irritation and mucosal injury was demonstrated using an NGT intubation model of rabbits. More importantly, compared to the paraffin oil coating (the current clinical means), the micelle coating possessed superior capability to reduce the inflammatory reaction caused by NGT intubation. The underlying mechanism was attributed to the suppression of the TLR4-IKBα-NF-κB inflammatory signaling pathway. This work provides a promising solution for developing lubricant medical coatings.

Impact of antipsychotics on prolactin levels in youth with psychiatric disorders: A cross-sectional study

OBJECTIVE

The increasing prescription of antipsychotics for children and adolescents raises concerns regarding abnormal prolactin levels. However, prolactin monitoring is rarely conducted (0.1-10 %), and the prevalence and characteristics of abnormal prolactin levels remain unclear. This study aimed to investigate the prevalence of abnormal prolactin levels and identify the factors influencing serum prolactin levels in pediatric and adolescent patients treated with antipsychotics in a real-world clinical setting.

METHOD

This retrospective cross-sectional study was conducted at Nagoya University Hospital and included consecutive 489 patients with psychiatric disorders aged <18 years who underwent serum prolactin monitoring. Because all hospitalized patients were included, sampling bias was minimized. Data on patient demographics, psychiatric diagnoses, medications, and prolactin levels were extracted and analyzed. Multiple regression analysis was performed to identify the factors influencing serum prolactin levels. Analysis of covariance was used to assess the effects of different antipsychotics on prolactin levels.

RESULTS

Hyperprolactinemia was observed in 23.0 % of patients treated with antipsychotics, whereas hypoprolactinemia was observed in 13.7 % of patients. Domperidone, sulpiride, and antipsychotics significantly increased prolactin levels. Risperidone, olanzapine, and blonanserin were associated with significantly increased serum prolactin levels, whereas aripiprazole was associated with hypoprolactinemia.

CONCLUSION

Approximately 40 % of pediatric patients treated with antipsychotics exhibited abnormal prolactin levels. Clinicians should routinely monitor prolactin levels and consider prolactin-related side effects when prescribing antipsychotics to children and adolescents. These findings emphasize the importance of tailored antipsychotic therapy to minimize the adverse effects in this vulnerable population.

Impact of Disease-Modifying Antirheumatic Drugs on Cognitive Function in Older Adults with Rheumatoid Arthritis

Cognitive impairment poses significant challenges for aging populations. Systemic inflammation, a hallmark of rheumatoid arthritis (RA), has been implicated in neurodegeneration through mechanisms including blood-brain barrier disruption, microglial activation, and cytokine-mediated neuronal damage. This review examines the potential impact of disease-modifying antirheumatic drugs (DMARDs) on cognitive function in RA, focusing on the inflammatory pathways linking systemic inflammation to neuroinflammation and cognitive decline. DMARDs, categorized into conventional synthetic (csDMARDs), biologic (bDMARDs), and targeted synthetic (tsDMARDs) classes, modulate immune responses through distinct mechanisms. Evidence suggests that DMARDs, particularly bDMARDs targeting proinflammatory cytokines such as TNF-α and IL-6, may mitigate neuroinflammatory processes and preserve cognitive function. However, the cognitive impact of csDMARDs such as methotrexate is complex, with conflicting reports regarding its role in vascular dementia. Emerging therapies such as Janus kinase inhibitors (JAK-i) offer promise in modulating central inflammation, though clinical evidence remains limited. While some studies highlight protective effects of DMARDs against dementia, findings are inconsistent, hindered by heterogeneity in study design, patient demographics, and cognitive assessment methods. This review underscores the need for personalized treatment strategies, integrating RA management with cognitive health considerations. Future research should prioritize robust, prospective studies with long-term follow-up, incorporating neuroimaging and biomarker analysis to elucidate the mechanisms underpinning DMARD-associated cognitive outcomes. A better understanding of the involved inflammatory pathways in RA and the potential effects of DMARDs could lead to improved therapeutic approaches, enhancing quality of life for patients with RA and potentially benefiting broader strategies in preventing or treating dementia.

Whispers in the Brain: Extracellular Vesicles in Neuropathology and the Diagnostic Alchemy of Neurological Diseases

Extracellular vesicles (EVs) have emerged as pivotal mediators in neurological diseases, showcasing multifaceted potential roles ranging from pathogenesis to diagnosis. These nano-sized membranous structures, released by various cell types including neurons, astrocytes, and microglia, encapsulate a diverse cargo of proteins, lipids, RNA species, and even DNA fragments. In neuropathology, EVs contribute significantly to intercellular communication within the central nervous system (CNS), influencing physiological or pathological cascades. Through the transfer of bioactive molecules, EVs modulate neuroinflammation, neuronal survival, synaptic plasticity, and the propagation of protein aggregates characteristic of neurodegenerative disorders. Moreover, their presence in biofluids such as cerebrospinal fluid (CSF), blood, and urine reflects the pathophysiological state of the CNS, offering a window into the diagnosis, monitoring and treatment of neurological diseases. Recent advancements in EV isolation techniques, coupled with high-throughput omics technologies, have facilitated the profiling of EV cargo, enabling the identification of disease-specific biomarkers with high sensitivity and specificity. This review explores the intricate roles of EVs in neuropathology, highlighting their involvement in Alzheimer's disease, Parkinson's disease, multiple sclerosis, and other neurological disorders. Furthermore, it delves into the diagnostic potential of EVs, discussing current challenges and prospects in harnessing EV-derived biomarkers for precision medicine in neurology. Ultimately, understanding the biology of EVs in neurological contexts promises transformative insights into disease mechanisms and therapeutic strategies, paving the way for innovative diagnostic tools and targeted interventions in clinical practice.

Siddha medicine and modern neuroscience: a synergistic approach to neurological care

Neurological disorders burden modern healthcare causing cognitive and emotional issues. The Siddha system offers a promising herbal and non-invasive-based therapy. This present review explores the neuromodulatory and neuroprotective effects of the Siddha system integrating herbal and non-invasive interventions with modern neuroscience for a comprehensive treatment strategy against neurological disorders. A detailed literature review was conducted using sources, such as Google search engine, Web of Science, and published databases, focusing on keywords related to 'Siddha herbal, non-invasive, traditional approach for neurological disorders'. The findings indicate that Siddha-based herbal medicines exhibit significant pharmacological activities, which help slow the progression of neurological diseases. Additionally, Siddha-based non-invasive therapies, such as yoga, meditation, Varma (traditional pressure point therapy), massage, and other external manipulations, have been reported to significantly increase brain activity, improve cognitive function, and enhance the patient's quality of life. The findings suggest that complementing Siddha-based therapy with modern neuroscience could enhance personalized neurological care in patients. Although Siddha has a rich history in traditional medicine, a significant research gap remains in large-scale clinical trials, treatment standardization, pharmacological validation, and mechanistic understanding. Addressing these gaps could enhance clinical utility in contemporary healthcare, ultimately benefitting brain health and overall well-being. Integrating Siddha medicine with modern neuroscience holds promise for advancing neurological care.

Multimodal convolutional neural network-based algorithm for real-time detection and differentiation of malignant and inflammatory biliary strictures in cholangioscopy: a proof-of-concept study (with video)

BACKGROUND AND AIMS

Deep learning algorithms gained attention for detection (computer-aided detection [CADe]) of biliary tract cancer in digital single-operator cholangioscopy (dSOC). We developed a multimodal convolutional neural network (CNN) for detection (CADe), characterization and discriminating (computer-aided diagnosis [CADx]) between malignant, inflammatory, and normal biliary tissue in raw dSOC videos. In addition, clinical metadata were included in the CNN algorithm to overcome limitations of image-only models.

METHODS

Based on dSOC videos and images of 111 patients (total of 15,158 still frames), a real-time CNN-based algorithm for CADe and CADx was developed and validated. We established an image-only model and metadata injection approach. In addition, frame-wise and case-based predictions on complete dSOC video sequences were validated. Model embeddings were visualized, and class activation maps highlighted relevant image regions.

RESULTS

The concatenation-based CADx approach achieved a per-frame area under the receiver-operating characteristic curve of .871, sensitivity of .809 (95% CI, .784-.832), specificity of .773 (95% CI, .761-.785), positive predictive value of .450 (95% CI, .423-.467), and negative predictive value of .946 (95% CI, .940-.954) with respect to malignancy on 5715 test frames from complete videos of 20 patients. For case-based diagnosis using average prediction scores, 6 of 8 malignant cases and all 12 benign cases were identified correctly.

CONCLUSIONS

Our algorithm distinguishes malignant and inflammatory bile duct lesions in dSOC videos, indicating the potential of CNN-based diagnostic support systems for both CADe and CADx. The integration of non-image data can improve CNN-based support systems, targeting current challenges in the assessment of biliary strictures.

Effects of Prolonged Proton-Pump Inhibitor Use on Renal Dysfunction and Bone Fragility

BACKGROUND

Proton-pump inhibitor (PPI) use for management of gastroesophageal reflux disease (GERD) consists of a short-duration trial, according to guidelines. Long-term usage is appropriate under certain indications. Literature has increasingly documented an adverse effect profile of PPIs, including kidney disease and bone fragility.

OBJECTIVE

To investigate the rate of occurrence of osteopenia, osteoporosis, and chronic kidney disease (CKD) in patients using PPI therapy for longer than the recommended trial period of 8 weeks.

METHODS

Retrospective cohort analysis of a single-site primary care clinic. Patients aged 18 to 65 years with PPI prescriptions longer than 8 weeks were included. Information regarding PPI prescriptions, demographics, and medical diagnoses was collected.

RESULTS

The search discovered 293 PPI-users and 1908 never-PPI-users. Demographics varied, with a P-value <0.05 in age, body mass index (BMI), and black population (higher in PPI group). The PPI cohort featured higher rates of osteoporosis/osteopenia and CKD (P < 0.001). The odds ratios (ORs) of diagnosis with PPI use was 2.91 (95% CI = [1.692, 4.979]) in osteoporosis/osteopenia. The OR was 1.14 (95% CI = [1.141, 2.229]) in CKD and PPI use but higher with diabetes, elevated BMI, black race, and male gender.

CONCLUSIONS AND RELEVANCE

We observed increased occurrence rates of osteoporosis, or osteopenia, and CKD in patients with prolonged PPI use. Demographics varied in age, BMI, and black race proportion. A logistic regression revealed increased likelihood of kidney disease and osteoporosis/osteopenia in association with PPI use. These results add to the evidence regarding long-term PPI use and the development of these conditions, but additional studies are needed.

Association Between Gastroesophageal Reflux Disease and Hypertension: A Systematic Review and Meta-Analysis

Background

Gastroesophageal reflux disease (GERD) and hypertension (HTN) are common conditions with substantial health burdens. While prior studies suggest a link between GERD and HTN, findings remain inconsistent. This systematic review and meta-analysis aimed to clarify the relationship between GERD and HTN.

Method

A systematic search of PubMed, Web of Science, and Embase was conducted to identify observational studies published through December 2024. Studies evaluating the prevalence and association between GERD and HTN were included. Screening and data extraction were performed using Nested Knowledge software, with quality assessed via the Modified Newcastle-Ottawa Scale. Random-effects meta-analyses were used to calculate pooled prevalence and risk estimates, while heterogeneity was quantified using the I 2 statistic. Publication bias was evaluated using DOI and funnel plots.

Results

Twelve studies, with sample sizes ranging from 71 to 12  960 participants, were included. The pooled prevalence of HTN among GERD patients was 16.80% (95% CI: 6.28%-31.02%) with high heterogeneity (I 2 = 99%). The pooled risk ratio (RR) for HTN was 1.381 (95% CI: 0.992-1.922) and heterogeneity (I 2 = 76%) highlighted variability. Sensitivity analyses and publication bias were evident.

Conclusion

GERD is a potential risk factor for HTN, with GERD patients demonstrating an elevated likelihood of developing HTN. Future research is required to investigate the underlying mechanisms and confounding factors that may influence this association.

A multi-stage multi-modal learning algorithm with adaptive multimodal fusion for improving multi-label skin lesion classification

Skin cancer is frequently occurring and has become a major contributor to both cancer incidence and mortality. Accurate and timely diagnosis of skin cancer holds the potential to save lives. Deep learning-based methods have demonstrated significant advancements in the screening of skin cancers. However, most current approaches rely on a single modality input for diagnosis, thereby missing out on valuable complementary information that could enhance accuracy. Although some multimodal-based methods exist, they often lack adaptability and fail to fully leverage multimodal information. In this paper, we introduce a novel uncertainty-based hybrid fusion strategy for a multi-modal learning algorithm aimed at skin cancer diagnosis. Our approach specifically combines three different modalities: clinical images, dermoscopy images, and metadata, to make the final classification. For the fusion of two image modalities, we employ an intermediate fusion strategy that considers the similarity between clinical and dermoscopy images to extract features containing both complementary and correlated information. To capture the correlated information, we utilize cosine similarity, and we employ concatenation as the means for integrating complementary information. In the fusion of image and metadata modalities, we leverage uncertainty to obtain confident late fusion results, allowing our method to adaptively combine the information from different modalities. We conducted comprehensive experiments using a popular publicly available skin disease diagnosis dataset, and the results of these experiments demonstrate the effectiveness of our proposed method. Our proposed fusion algorithm could enhance the clinical applicability of automated skin lesion classification, offering a more robust and adaptive way to make automatic diagnoses with the help of uncertainty mechanism. Code is available at https://github.com/Zuo-Lihan/CosCatNet-Adaptive_Fusion_Algorithm.

Reversible Watermarking for Electrocardiogram Protection

The electrocardiogram (ECG) is one of the widespread diagnostic methods used in telemedicine. However, in the telemedicine systems, the data transfer process to the end user may suffer from security risks. Reversible watermarking can preserve the security of electrocardiograms and keep their original precision for correct diagnostics. In this paper, we present an extensive investigation of four reversible watermarking methods: prediction error expansion (PEE), reversible contrast mapping difference expansion (RCM), integer transform-based difference expansion (ITB), and compression-based watermarking. We discover new facets of the existing ECG watermarking methods (PEE and compression-based watermarking) and adapt image watermarking methods (RCM and ITB) to ECG signal. We compare different kinds of prediction and compression methods used in the studied methods and provide a watermark capacity comparison for different methods' implementations. The research results will help in watermarking method selection in practice.

A Progressive Risk Formulation for Enhanced Deep Learning based Total Knee Replacement Prediction in Knee Osteoarthritis

We developed deep learning models for predicting Total Knee Replacement (TKR) need within various time horizons in knee osteoarthritis patients, with a novel capability: the models can perform TKR prediction using a single scan, and furthermore when a previous scan is available, they leverage a progressive risk formulation to improve their predictions. Unlike conventional approaches that treat each scan of a patient independently, our method incorporates a constraint based on disease's progressive nature, ensuring that predicted TKR risk either increases or remains stable over time when multiple scans of a knee are available. This was achieved by enforcing a progressive risk formulation constraint during training with patients who have more than one available scan in the studies. Knee radiographs and MRIs from the Osteoarthritis Initiative (OAI) and Multicenter Osteoarthritis Study (MOST) were used in this work and deep learning models were trained to predict TKR within 1, 2, and 4-year time periods. The proposed approach, utilizing a dual-model risk constraint architecture, demonstrated superior performance compared to baseline - conventional models trained with standard binary cross entropy loss. It achieved an AUROC of 0.87 and AUPRC of 0.47 for 1-year TKR prediction on the OAI radiograph test set, considerably improving over the baseline AUROC of 0.79 and AUPRC of 0.34. For the MOST radiograph test set, the proposed approach achieved an AUROC of 0.77 and AUPRC of 0.25 for 1-year predictions, outperforming the baseline AUROC of 0.71 and AUPRC of 0.19. Similar trends were observed in the MRI testsets.

Comparison of brain volume increase in patients with intracranial hypertension after decompressive craniectomy and expansion craniotomy

Intracranial hypertension is a critical condition often resulting from traumatic brain injury or malignant middle cerebral artery ischemia, necessitating surgical intervention when conservative treatments fail. This study compares the efficacy of decompressive craniectomy (DC) and expansion craniotomy (EC) in managing cerebral edema. Sixty-three patients, 52 undergoing DC and 11 undergoing EC, were evaluated for changes in brain volume, midline shift, and other key parameters using pre- and post-operative CT scans. Results indicated that brain volume increased significantly more in the EC group (100 ± 51 cm³) compared to the DC group (72 ± 51 cm³, p < 0.05). Both techniques effectively reduced midline displacement, but EC showed a superior capacity for brain expansion. The findings suggest that EC, which raises the cranial operculum to reduce soft tissue tension and provide hemostatic effects, may offer advantages over DC by allowing greater decompression and reducing the risk of complications such as epidural hematomas. These results support the potential of EC as a promising alternative to DC for treating intracranial hypertension. Future research should investigate long-term outcomes to further validate these findings.

Case Report: Posterior reversible encephalopathy syndrome after lenvatinib treatment for hepatocellular carcinoma

Background

Posterior reversible encephalopathy syndrome (PRES) is characterized by headaches, vision loss, confusion, encephalopathy, seizures, and reversible focal edema on neuroimaging. Early recognition and treatment of PRES are essential to prevent severe complications. Lenvatinib is a multi-targeted kinase inhibitor that is used as a first-line treatment for patients with hepatocellular carcinoma (HCC). Lenvatinib-induced PRES is a less commonly recognized side effect.

Case presentation

A 72-year-old female patient with HCC, who had no history of hypertension, received lenvatinib therapy. The patient exhibited symptoms such as confusion, altered mental status, headaches, and severe hypertension during treatment. Neuroimaging revealed characteristic findings of vasogenic edema in the white matter of the brain. The patient's neurological symptoms gradually improved after lenvatinib discontinuation, and follow-up imaging showed a reduction in the white matter abnormalities.

Conclusion

The underlying mechanisms of PRES induced by lenvatinib remain unclear, but hypertension is considered a crucial factor in its pathogenesis. This case report adds to the understanding of the potential adverse effects associated with lenvatinib in patients with HCC, emphasizing the need for vigilance in monitoring and managing such complications to ensure the safety and wellbeing of patients undergoing this treatment.

Gallstones as a predictor of elevated cardiovascular disease risk: A meta-analysis and meta-regression of over 7.4 million participants

INTRODUCTION

Gallstone disease (GD) is a prevalent condition frequently encountered in surgical units worldwide. The objective of this comprehensive systematic review and meta-analysis study was to examine the relationship between gallstones and the risk of cardiovascular diseases (CVDs).

METHODS

To conduct our study, we performed a systematic review and meta-analysis. We gathered relevant studies from reputable databases, including Web of Science, Scopus, PubMed, Cochrane, Google Scholar, and Embase. The quality of the articles was assessed using the Newcastle-Ottawa Scale checklist. To assess heterogeneity among the studies, we utilized statistical tests such as the Chi-square test, I² statistic, and forest plots. Meta-regression analysis considered variables such as the year of the study, study design, sample size, study quality assessment score, geographical region, average age of subjects, and follow-up duration. Additionally, we evaluated publication bias using Begg's and Egger's tests.

RESULTS

Data from 22 studies conducted between 1985 and 2023 were analyzed. The combined number of participants across these studies was 7,496,303. The meta-analysis results revealed that individuals with GD had a higher risk of CVDs (Risk Ratio (RR): 1.29; 95% CI: 1.22-1.36; P <  0.001). Subgroup analysis showed consistent results across good quality studies (RR: 1.20, 95% CI: 11.12-1.28; P <  0.001), moderate quality studies (RR: 1.41, 95% CI: 1.15-1.74; P <  0.001), and low-quality studies (RR: 1.22, 95% CI: 1.15-1.30; P <  0.001). In the meta-regression analysis, none of the variables had a significant relationship with the observed heterogeneity (P-value > 0.10). In a sensitivity analysis, the estimated RR remained consistent, confirming the robustness of the meta-analysis results.

CONCLUSION

Our findings suggest an association between gallstone disease and an increased risk of CVDs. It seems that one of the important factors of this relationship is having common causes for the formation of gallstones and cardiovascular diseases. However, gallstones can be considered an important sign of increased risk of cardiovascular diseases.

Effectiveness of wearable activity trackers on physical activity among adolescents in school-based settings: a systematic review and meta-analysis

BACKGROUND

While inactivity and sedentarism among adolescents are increasing globally, technology-based interventions incorporating wearable activity trackers (WATs) demonstrate the potential to combat the situation. With a focus on schools as critical environments in which to perform interventions among adolescents, this meta-analytic review of literature aimed to examine the effectiveness of wearable trackers in objectively measured physical activity (PA).

METHODS

A systematic search was conducted across six databases-PubMed, CENTRAL, Scopus, SPORTDiscus, the Web of Science Core Collection, and PsycINFO-between January 2012 and March 2024. The language was restricted to English only. Both randomized controlled trials and quasi-experiment studies were included. Risk of bias was assessed using Cochrane RoB2 and ROBINS-I tools. Subgroup analyses and sensitivity analyses were performed. Effect direction for a narrative synthesis was also conducted. GRADE criteria were applied to assess quality of evidence.

RESULTS

Fifteen studies were finally included in the literature review, and ten were adopted for meta-analysis. No statistical significance was found in intervention outcomes involving WATs' effect on PA, whether in terms of total daily steps, moderate-to-vigorous PA (MVPA), or calorie counts. However, the subgroup analysis revealed that one study using research-grade assessment showed a substantial positive effect on steps. There were no data reported regarding the effect of objectively measured sedentary behavior.

CONCLUSION

Further study is needed to explore whether wearable activity trackers raise or decrease PA among adolescents in schools.

REGISTRATION

PROSPERO, registration number: CRD42023421008.

Enhancing Patient Outcome Prediction Through Deep Learning With Sequential Diagnosis Codes From Structured Electronic Health Record Data: Systematic Review

BACKGROUND

The use of structured electronic health records in health care systems has grown rapidly. These systems collect huge amounts of patient information, including diagnosis codes representing temporal medical history. Sequential diagnostic information has proven valuable for predicting patient outcomes. However, the extent to which these types of data have been incorporated into deep learning (DL) models has not been examined.

OBJECTIVE

This systematic review aims to describe the use of sequential diagnostic data in DL models, specifically to understand how these data are integrated, whether sample size improves performance, and whether the identified models are generalizable.

METHODS

Relevant studies published up to May 15, 2023, were identified using 4 databases: PubMed, Embase, IEEE Xplore, and Web of Science. We included all studies using DL algorithms trained on sequential diagnosis codes to predict patient outcomes. We excluded review articles and non-peer-reviewed papers. We evaluated the following aspects in the included papers: DL techniques, characteristics of the dataset, prediction tasks, performance evaluation, generalizability, and explainability. We also assessed the risk of bias and applicability of the studies using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST). We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist to report our findings.

RESULTS

Of the 740 identified papers, 84 (11.4%) met the eligibility criteria. Publications in this area increased yearly. Recurrent neural networks (and their derivatives; 47/84, 56%) and transformers (22/84, 26%) were the most commonly used architectures in DL-based models. Most studies (45/84, 54%) presented their input features as sequences of visit embeddings. Medications (38/84, 45%) were the most common additional feature. Of the 128 predictive outcome tasks, the most frequent was next-visit diagnosis (n=30, 23%), followed by heart failure (n=18, 14%) and mortality (n=17, 13%). Only 7 (8%) of the 84 studies evaluated their models in terms of generalizability. A positive correlation was observed between training sample size and model performance (area under the receiver operating characteristic curve; P=.02). However, 59 (70%) of the 84 studies had a high risk of bias.

CONCLUSIONS

The application of DL for advanced modeling of sequential medical codes has demonstrated remarkable promise in predicting patient outcomes. The main limitation of this study was the heterogeneity of methods and outcomes. However, our analysis found that using multiple types of features, integrating time intervals, and including larger sample sizes were generally related to an improved predictive performance. This review also highlights that very few studies (7/84, 8%) reported on challenges related to generalizability and less than half (38/84, 45%) of the studies reported on challenges related to explainability. Addressing these shortcomings will be instrumental in unlocking the full potential of DL for enhancing health care outcomes and patient care.

TRIAL REGISTRATION

PROSPERO CRD42018112161; https://tinyurl.com/yc6h9rwu.

A genome-wide association study identifies a novel East Asian-specific locus for dementia with Lewy bodies in Japanese subjects

BACKGROUND

Dementia with Lewy bodies (DLB) is the second most common type of degenerative dementia in older patients. As with other multifactorial diseases, the pathogenesis results from interactions of environmental and genetic factors. The genetic basis of DLB is not yet fully understood. Recent genomic analyses of DLB in Caucasian cohorts identified genetic susceptibility loci for DLB, but the comprehensive genomic analysis in Asians was still not performed.

METHODS

We conducted a genome-wide association study (GWAS) in Japanese subjects (211 DLB cases and 6113 controls) to clarify the genetic architecture of DLB pathogenesis.

RESULTS

We identified the East Asian-specific DHTKD1 locus (rs138587229) on chromosome 10 with genome-wide significance (GWS; P = 3.27 × 10-8) and the ICOS/PARD3B locus on chromosome 2 with suggestive significance (P = 3.95 × 10-7) as novel DLB genetic risk loci. We also confirmed the APOE locus (rs429358, P < 5.0 × 10-8), a known risk locus for DLB and Alzheimer's disease in Caucasians. The DHTKD1 locus was associated with the gene expression of SEC61A2 and showed a causal relationship with cholinesterase levels. In a trans-ethnic meta-analysis that included Japanese, UK Biobank, and other Caucasian GWAS, we confirmed the risk for DLB at APOE and SNCA loci with GWS. Transcriptome-wide association analysis identified ZNF155 and ZNF284 in the brain cortex and GPRIN3 in the substantia nigra as putative causal genes for DLB.

CONCLUSIONS

This is the first GWAS for DLB in East Asians, and our findings provide new biological and clinical insights into the pathogenesis of DLB.

One-Year Mortality After Percutaneous Endoscopic Gastrostomy: The Prognostic Role of Nutritional Biomarkers and Care Settings

Background/Objectives: This study aimed to evaluate the clinical outcomes, complications, and one-year mortality of patients undergoing percutaneous endoscopic gastrostomy (PEG) in different care settings (hospital, nursing home, and home). Additionally, we investigated the comparative prognostic role of the prognostic nutritional index (PNI) and the CRP-to-albumin ratio (CAR) in predicting mortality among these patients. Methods: A retrospective analysis of 236 adult patients who underwent PEG placement between January 2022 and December 2023 was performed. Demographic, clinical, and laboratory data were collected. The PNI was calculated according to the following formula: PNI = 10 × (albumin) + 0.005 × (lymphocyte count). The CAR was obtained by the ratio of the CRP level to the albumin level. Patients were categorized based on their post-PEG care settings. Results: Neurologic disorders were the most common indication for PEG (69.9%). The one-year mortality was 32.2%, with a median survival of 38 weeks (95% CI: 35-41). In the multivariable model, a lower PNI (HR = 0.93, 95% CI: 0.89-0.97, p < 0.001), as well as being followed in a hospital setting, emerged as independent predictors of mortality. Patients with timely PEG tube replacement showed a reduced mortality risk. The ROC analysis showed that the PNI had a higher AUROC (0.78 ± 0.04) compared to the CAR (0.69 ± 0.04), indicating superior prognostic accuracy for predicting one-year mortality. Conclusions: Care settings significantly influence survival outcomes, with better mortality rates observed in nursing homes and home environments. The PNI was superior to the CAR in predicting one-year mortality, emphasizing its clinical utility in risk stratification for PEG patients. Proactive tube management and individualized care strategies are critical for improving the prognosis in this population.

Survival status and predictors of mortality among road traffic accident adult patients admitted to intensive care units of referral hospitals in Tigray 2024

BACKGROUND

Globally, road traffic accidents (RTAs) cause over 1.35 million deaths each year, with an additional 50 million people suffering disabilities. Ethiopia has the highest number of road traffic accidents, with over 14,000 people killed and over 45,000 injured annually. This study aimed to assess survival status and predictors of mortality among road traffic accident adult patients admitted to intensive care units of Referral Hospitals in Tigray, 2024.

METHODS

An institution-based retrospective follow-up study design was conducted from January 8, 2019, to December 11, 2023, on 333 patient charts. A bivariable Cox-regression analysis was performed to estimate crude hazard ratios (CHR). Subsequently, a multivariable Cox regression analysis was performed to estimate the Adjusted Hazard Ratios (AHR). Finally, AHR with p-value less than 0.05 was used to measure the association between dependent and independent variables.

RESULT

The incidence of mortality for road traffic accident victims, was 21 per 1000 person-days observation with (95% CI: 16, 27.6) and the median survival time was 14 days. The predictors of mortality in this study were the value of oxygen saturation on admission ≤ 89% (AHR = 4.9; 95%CI: 1.4-17.2), Intracranial hemorrhage (AHR = 3.3; 95% CI: 1.02-11), chest injury (AHR = 3.2; 95%CI: 1.38-7.59), victims with age catgories of 31-45 years (AHR = 0.3; 95% CI: 0.1-0.88) and 46-60 years (AHR = 0.22; 95% CI: 0.06-0.89).

CONCLUSION

A concerningly high mortality rate from car accidents were found in Referral Hospitals of Tigray. To improve the survival rates, healthcare providers should focus on victims with very low oxygen levels, head injuries, chest injuries, and older victims.

Integrative approaches to m6A and m5C RNA modifications in autism spectrum disorder revealing potential causal variants

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that currently affects approximately 1-2% of the global population. Genome-wide studies have identified several loci associated with ASD; however, pinpointing causal variants remains elusive. Therefore, functional studies are essential to discover potential therapeutics for ASD. RNA modification plays a crucial role in the post-transcriptional regulation of mRNA, with m6A and m5C being the most prevalent internal modifications. Recent research indicates their involvement in the regulation of key genes associated with ASD. In this study, we conducted an integrative genomic analysis of ASD, incorporating m6A and m5C variants, followed by cis-eQTL, gene differential expression, and gene enrichment analyses to identify causal variants from a genome-wide study of ASD. We identified 20,708 common m6A-SNPs and 2,407 common m5C-SNPs. Among these, 647 m6A-SNPs exhibited cis-eQTL signals with a p-value < 0.05, while only 81 m5C-SNPs with a p-value < 0.05 showed cis-eQTL signals. Most of these were functional loss variants, with 38 variants representing the most significant common m6A/m5C-SNPs associated with key ASD-related genes. In the gene differential expression analysis, seven proximal genes corresponding to significant m6A/m5C-SNPs were differentially expressed in at least one of the three microarray gene expression profiles of ASD. Key differentially expressed genes corresponding to m6A/m5C cis-variants included KIAA1671 (rs5752063, rs12627825), INTS1 (rs67049052, rs10237910), VSIG10 (rs7965350), TJP2 (rs3812536), FAM167A (rs9693108), TMEM8A (rs1802752), and NUP43 (rs3924871, rs7818, rs9383844, rs9767113). Cell-specific cis-eQTL analysis for proximal gene identification, combined with gene expression datasets from single-cell RNA-seq analysis, would validate the causal relationship of gene regulation in brain-specific regions, and experimental validation in cell lines would achieve the goal of precision medicine.

Association between hemoglobin levels and cerebral white matter volume in a general older Japanese population: the Iki-Iki study

PURPOSE

Although previous studies have reported that hemoglobin levels can affect the brain, very few have focused on the association between hemoglobin levels and brain volume. We aimed to identify the influence of hemoglobin levels on brain volume measured using magnetic resonance imaging (MRI) in a large elderly population.

METHODS

This cross-sectional study included 2153 participants (median age, 69 years; 60.2% female) who underwent 3T brain MRI. Multiple regression analyses were performed after adjusting for potential confounders. In the subgroup analyses, participants were divided into four groups according to sex and age threshold (lower age group [65-74] and higher age group [≥ 75]).

RESULTS

After adjusting for potential confounders, total white matter volume reduction was found to be associated with decreased hemoglobin levels (females: standardized β = 0.059, [95% confidence interval (CI): 0.0032, 0.11], P = 0.038, males: standardized β = 0.069 [95% CI: -0.00023, 0.14], P = 0.051). This relationship was notable in younger age groups of both sexes. After adjustment, the total gray matter and hippocampal volumes were not significantly associated with hemoglobin levels.

CONCLUSION

Low hemoglobin levels may have deleterious effects on white matter volume, which diminishes with age.

Machine learning-based risk prediction of mild cognitive impairment in patients with chronic heart failure: A model development and validation study

Accurate identification of individuals at high risk for mild cognitive impairment (MCI) among chronic heart failure (CHF) patients is crucial for reducing rehospitalization and mortality rates. This study aimed to develop and validate a machine learning model to predict MCI risk in CHF patients. 602 CHF patients were included in this cross-sectional analysis. We constructed four machine learning models and assessed the models using the area under the receiver operating characteristic curve (AUC), calibration curve, and clinical decision curve. Results showed that scores of psychological and social adaptation management, age, free triiodothyronine, Self-rating Depression Scale scores, hemoglobin, sleep duration per night and gender were the best predictors and these factors were used to construct dynamic nomograms. Among all models, eXtreme Gradient Boosting (XGBoost) with an AUC of 0.940 performed the best in predicting the risk of MCI in CHF patients. Dynamic nomogram helps clinicians perform early screening in large populations.

Increased risk of dementia in patients with primary Sjogren's syndrome: a nationwide population-based cohort study

BACKGROUND/AIMS

This nationwide cohort study aimed to evaluate (1) whether primary Sjogren's syndrome (pSS) can contribute to the development of dementia and (2) whether the use of hydroxychloroquine (HCQ) can decrease the incidence of dementia in patients with pSS using the Health Insurance Review and Assessment database.

METHODS

We established a cohort between 2008 and 2020 of 20,160 patients with pSS without a history of dementia. The control group comprised sex- and age-matched individuals with no history of autoimmune disease or dementia. Cox proportional hazard analyses were performed to identify the association between pSS and dementia development. We also assessed the hazard ratio (HR) of dementia in early users of HCQ (within 180 days of the diagnosis of pSS) compared to non-users, adjusted for age, sex, and comorbidities.

RESULTS

The incidence of dementia was 0.68 (95% CI 0.64-0.72) cases per 100 person-years in pSS, and it was 0.58 (0.56-0.60) in the controls. The adjusted HR (aHR) of developing dementia was 1.16 (1.09-1.25) times greater in the pSS group than in the controls. The risk of dementia did not increase in HCQ users (aHR 1.07 [0.94-1.21]), but HCQ non-users had a 1.22 (1.12-1.33) higher risk of developing dementia than the matched controls. The use of HCQ lowered the risk of dementia in comparison with non-users in patients with pSS (aHR 0.82 [0.71-0.94]).

CONCLUSION

Our results suggest that pSS is associated with an increased risk of dementia. HCQ may prevent dementia in patients with pSS.

Anti-ulcerogenic activity of the marine-pearl derived medicine mukta Pishti in Rat model of pylorus ligation-induced peptic ulcer

ETHNOPHARMACOLOGICAL RELEVANCE

Mukta Pishti (MKP) is a traditional Ayurvedic medicine described in classical textbook 'Rasatarangini' and synthesized from marine pearls following classical methodology. MKP is used as therapeutic medicine against hyperacidity, irritable bowel syndrome, and gastric ulcers.

AIM OF THE STUDY

Here, we explored the therapeutic properties of MKP in alleviating peptic ulcer in male Wistar rat model of pylorus ligation.

METHODS

Physicochemical properties of MKP were explored using scanning electron microscope, electron dispersive X-ray, dynamic light scattering, and Fourier-transform-infrared (FTIR)-spectroscopy analysis. Animals were orally treated twice daily with dosages of MKP, over a period of 15 days. The animals underwent 6 h pylorus ligation for the induction of peptic ulcers and analyzed for biochemical changes in gastric content, gross and histopathological changes in the stomach region.

RESULTS

Physicochemical analysis showed 0.1-30 μm particles size for MKP, with elemental composition of oxygen, calcium, silica, carbon, phosphorus, and sodium. FTIR-spectroscopy indicated presence of aragonite crystals in MKP with capability of physically binding to gastric mucin molecules. Additionally, MKP treatment modulated gastric pH in simulated digestion model but did not affect the overall gastric content and total/free acidity levels in the in vivo pylorus ligation model. However, MKP treatment in rats significantly reduced ulcer index in stomach region and protected it against epithelial damages, hemorrhages and edema induced by pylorus ligation.

CONCLUSION

MKP alleviated peptic ulcer induced by pylorus ligation in the male Wistar rats. Further research is warranted to elucidate the precise mode of action and long-term safety of Mukta Pishti.

Prevalence, sub-types, and associated factors of anemia among inpatients at a tertiary psychiatric hospital in Tanzania: a cross-sectional study

BACKGROUND

Anemia has been linked to psychiatric disorders including depression, bipolar disorder, and schizophrenia. Studies have demonstrated an association between anemia and worsening clinical presentation and treatment outcomes of these disorders. This study aimed to assess the prevalence and factors associated with anemia among adult patients admitted at Mirembe National Mental Health Hospital (MNMH) in Dodoma, Tanzania.

METHODS

A cross-sectional analytical study was conducted at MNMH among 265 adults admitted at the hospital. Socio-demographic and clinical variables were collected using a closed-ended questionnaire, and anemia and other hematological indices were assessed via complete blood count (CBC). Data were entered into an Open Data Kit (ODK) app and analyzed using SAS version 9.4. Chi-squared test was used initially to assess association between individual exposures and the outcome, anemia. Variables with a p-value < 0.20 from the chi squared analysis were fitted into a logistic regression model to determine their odds of association with anemia. Odds ratios from adjusted regression analysis were used to identify factors independently associated with anemia. Significance level was set at p value < 0.05.

RESULTS

The prevalence of anemia among adult patients admitted at MNMH was 44% (CI 38.08, 50.36). The majority of participants had mild anemia (74.36%). Microcytic hypochromic and normocytic normochromic were the common types of anemia (47% and 46% respectively). Being male, institutionalization, and using Olanzapine was associated with anemia among participants at bivariate analysis, however, only institutionalization remained as a statistically significant factor associated with anemia at multivariable analysis (AOR:5.742, 95% CI 2.048, 16.105).

CONCLUSIONS

Comprehensive care strategies addressing anemia among psychiatric inpatients are crucial, extending beyond psychiatric symptoms to address factors related to prolonged admission, such as nutritional considerations. It is recommended that regular screening for anemia be implemented among psychiatric inpatients and efforts should be made to investigate and address the underlying causes of anemia among this population.

Bioinformatics analysis reveals key mechanisms of oligodendrocytes and oligodendrocyte precursor cells regulation in spinal cord Injury

Despite extensive research, spinal cord injuries (SCI), which could cause severe sensory, motor and autonomic dysfunction, remain largely incurable. Oligodendrocytes and oligodendrocyte precursor cells (ODC/OPC) play a crucial role in neural morphological repair and functional recovery following SCI. We performed single-cell sequencing (scRNA-seq) on 59,558 cells from 39 mouse samples, combined with microarray data from 164 SCI samples and 3 uninjured samples. We further validated our findings using a large clinical cohort consisting of 38 SCI patients, 10 healthy controls, and 10 trauma controls, assessed with the American Spinal Cord Injury Association (ASIA) scale. We proposed a novel SCI classification model based on the expression of prognostic differentially expressed ODC/OPC differentiation-related genes (PDEODGs). This model includes three types: Low ODC/OPC Score Classification (LOSC), Median ODC/OPC Score Classification (MOSC), and High ODC/OPC Score Classification (HOSC). Considering the relationship between these subtypes and prognosis, we speculated that enhancing ODC/OPC differentiation and inhibiting inflammatory infiltration may improve outcomes. Additionally, we identified potential treatments for SCI that target key genes within these subtypes, offering promising implications for therapy.

Clinical implication of anemia in older patients with dementia with lewy bodies

AIM

This research sought to investigate the possible connection between anemia and various parameters of comprehensive geriatric assessment in elderly individuals diagnosed with Dementia with Lewy Bodies (DLB). To our knowledge, this investigation represents the first attempt to examine how anemia impacts patients suffering from DLB.

METHODS

This cross-sectional study encompassed 147 DLB patients from a single geriatric outpatient clinic. The study defined anemia as hemoglobin levels under 12 g/dL for women and 13 g/dL for men. Patients' demographic information, coexisting medical conditions, and results from comprehensive geriatric evaluations were also recorded.

RESULTS

Participants in the study had an average age of 85.4 ± 7.1 years. Anemia was present in 46.9% of the patients. Significant disparities were noted between individuals with and without anemia regarding the occurrence of congestive heart failure (CHF), polypharmacy, geriatric depression, and insomnia (all p < 0.05). After controlling for age, gender, and CHF in the multivariate analysis, the association between anemia and both the quantity of medications used [OR: 1.15 (95% CI:1.01-1,31)] and Geriatric Depression Scale-15 scores [OR: 0.88, 95% CI: 0.78-0.98] remained statistically significant (p < 0.05) when comparing anemic patients to non-anemic individuals.

CONCLUSION

In the present study almost one in two older patients with DLB were anemic. Anemia is associated with presence of CHF, higher number of drugs and depressive mood in DLB. It is recommended that healthcare providers should recognize the importance of anemia and its associated effects when treating older adults with DLB. This approach may lead to more effective management and treatment of this complex condition.

A Comprehensive AI Framework for Superior Diagnosis, Cranial Reconstruction, and Implant Generation for Diverse Cranial Defects

Cranioplasty enables the restoration of cranial defects caused by traumatic injuries, brain tumour excisions, or decompressive craniectomies. Conventional methods rely on Computer-Aided Design (CAD) for implant design, which requires significant resources and expertise. Recent advancements in Artificial Intelligence (AI) have improved Computer-Aided Diagnostic systems for accurate and faster cranial reconstruction and implant generation procedures. However, these face inherent limitations, including the limited availability of diverse datasets covering different defect shapes spanning various locations, absence of a comprehensive pipeline integrating the preprocessing of medical images, cranial reconstruction, and implant generation, along with mechanical testing and validation. The proposed framework incorporates a robust preprocessing pipeline for easier processing of Computed Tomography (CT) images through data conversion, denoising, Connected Component Analysis (CCA), and image alignment. At its core is CRIGNet (Cranial Reconstruction and Implant Generation Network), a novel deep learning model rigorously trained on a diverse dataset of 2160 images, which was prepared by simulating cylindrical, cubical, spherical, and triangular prism-shaped defects across five skull regions, ensuring robustness in diagnosing a wide variety of defect patterns. CRIGNet achieved an exceptional reconstruction accuracy with a Dice Similarity Coefficient (DSC) of 0.99, Jaccard Similarity Coefficient (JSC) of 0.98, and Hausdorff distance (HD) of 4.63 mm. The generated implants showed superior geometric accuracy, load-bearing capacity, and gap-free fitment in the defected skull compared to CAD-generated implants. Also, this framework reduced the implant generation processing time from 40-45 min (CAD) to 25-30 s, suggesting its application for a faster turnaround time, enabling decisive clinical support systems.

Development of clinical decision support for patients older than 65 years with fall-related TBI using artificial intelligence modeling

BACKGROUND

Older persons comprise most traumatic brain injury (TBI)-related hospitalizations and deaths and are particularly susceptible to fall-induced TBIs. The combination of increased frailty and susceptibility to clinical decline creates a significant ongoing challenge in the management of geriatric TBI. As the population ages and co-existing medical conditions complexify, so does the need to improve the quality of care for this population. Utilizing early hospital admission variables, this study will create and validate a multinomial decision tree that predicts the discharge disposition of older patients with fall-related TBI.

METHODS

From the National Trauma Data Bank, we retrospectively analyzed 11,977 older patients with a fall-related TBI (2017-2021). Clinical variables included Glasgow Coma Scale (GCS) score, intracranial pressure monitor use, venous thromboembolism (VTE) prophylaxis, and initial vital signs. Outcomes included hospital discharge disposition re-categorized into home, care facility, or deceased. Data were split into two sets, where 80% developed a decision tree, and 20% tested predictive performance. We employed a conditional inference tree algorithm with bootstrap (B = 100) and grid search options to grow the decision tree and measure discrimination ability using the area under the curve (AUC) and calibration plots.

RESULTS

Our decision tree used seven admission variables to predict the discharge disposition of older TBI patients. Significant non-modifiable variables included total GCS and injury severity scores, while VTE prophylaxis type was the most important interventional variable. Patients who did not receive VTE prophylaxis treatment had a higher probability of death. The predictive performance of the tree in terms of AUC value (95% confidence intervals) in the training cohort for death, care, and home were 0.66 (0.65-0.67), 0.75 (0.73-0.76), and 0.77 (0.76-0.79), respectively. In the test cohort, the values were 0.64 (0.62-0.67), 0.75 (0.72-0.77), and 0.77 (0.73-0.79).

CONCLUSIONS

We have developed and internally validated a multinomial decision tree to predict the discharge destination of older patients with TBI. This tree could serve as a decision support tool for caregivers to manage older patients better and inform decision-making. However, the tree must be externally validated using prospective data to ascertain its predictive and clinical importance.

Genetic Markers of Postmortem Brain Iron

Brain iron (Fe) dyshomeostasis is implicated in neurodegenerative diseases. Genome-wide association studies (GWAS) have identified plausible loci correlated with peripheral levels of Fe. Systemic organs and the brain share several Fe regulatory proteins but there likely exist different homeostatic pathways. We performed the first GWAS of inductively coupled plasma mass spectrometry measures of postmortem brain Fe from 635 Rush Memory and Aging Project (MAP) participants. Sixteen single nucleotide polymorphisms (SNPs) associated with Fe in at least one of four brain regions were measured (p < 5 × 10-8). Promising SNPs (p < 5 × 10-6) were followed up for replication in published GWAS of blood, spleen, and brain imaging Fe traits and mapped to candidate genes for targeted cortical transcriptomic and epigenetic analysis of postmortem Fe in MAP. Results for SNPs previously associated with other Fe traits were also examined. Ninety-eight SNPs associated with postmortem brain Fe were at least nominally (p < 0.05) associated with one or more related Fe traits. Most novel loci identified had no direct links to Fe regulatory pathways but rather endoplasmic reticulum-Golgi trafficking (SORL1, SORCS2, MARCH1, CLTC), heparan sulfate (HS3ST4, HS3ST1), and coenzyme A (SLC5A6, PANK3); supported by nearest gene function and omic analyses. We replicated (p < 0.05) several previously published Fe loci mapping to candidate genes in cellular and systemic Fe regulation. Finally, novel loci (BMAL, COQ5, SLC25A11) and replication of prior loci (PINK1, PPIF, LONP1) lend support to the role of circadian rhythms and mitochondria function in Fe regulation more generally. In summary, we provide support for novel loci linked to pathways that may have greater relevance to brain Fe accumulation; some of which are implicated in neurodegeneration. However, replication of a subset of prior loci for blood Fe suggests that genetic determinants or biological pathways underlying Fe accumulation in the brain are not completely distinct from those of Fe circulating in the periphery.

How can patients shape digital medicine? A rapid review of patient and public involvement and engagement in the development of digital health technologies for neurological conditions

INTRODUCTION

Patient and Public Involvement and Engagement (PPIE) involves working 'with' or 'by' patients and the public, rather than 'to,' 'about,' or 'for' them, and is integral to neurological and digital health research. This rapid review examined PPIE integration in the development and implementation of digital health technologies for neurological conditions.

METHODS

Key terms were input into six databases. Included articles were qualitative studies or PPIE activities involving patient perspectives in shaping digital health technologies for neurological conditions. Bias was evaluated using the NICE qualitative checklist, with reporting following PRISMA guidelines.

RESULTS

2,140 articles were identified, with 28 included. Of these, 25 were qualitative studies, and only three were focused PPIE activities. Patient involvement was mostly limited to one-off consultations during development.There was little evidence of PPIE during implementation, and minimal reporting on its impact.

CONCLUSIONS

PPIE has been inconsistently reported in this research area, highlighting the need for more guidance and best-practice examples This review used a UK-based definition of PPIE, which may have excluded relevant activities from other countries. Future reviews should broaden terminology to capture PPIE integration globally.

Correlation Between Coagulation Parameters and Dense Fibrin Band Configuration in Tough Intracerebral Hematoma in Anticoagulated Patients

OBJECTIVE

Patients receiving anticoagulation therapy develop intracerebral hematomas, which are difficult to evacuate during endoscopic surgery. Insufficient thrombin activation results in the gradual conversion of fibrinogen to fibrin, forming dense fibrin bands (FBs) that harden the hematoma. We aimed to investigate the factors contributing to hematoma hardness.

METHODS

Eleven men and 11 women (age range: 41-84 years) with hypertensive intracerebral hematomas underwent surgery between 2016 and 2018. Hematoma hardness was measured intraoperatively as the maximum breaking point under compression (Newton [N]) using a bar-type tester. Hematoma samples were graded based on histological FB density. The relationships between hardness, FB grade, and hematological parameters were assessed in patients with and without anticoagulation therapy.

RESULTS

Hematomas were categorized as nonhard (0-3.0 N, n = 16) or hard (3.0-7.0 N, n = 6). Hardness was strongly correlated with FB grade (r = 0.76) and prothrombin time-international normalized ratio (PT-INR) (r = 0.75) and moderately correlated with activated partial thromboplastin time (APTT) (r = 0.65). Three patients with hematoma receiving warfarin and one receiving factor Xa inhibitor demonstrated significantly higher FB grade (P = 0.008) and increased hematoma hardness (6.0 ± 1.4 N) compared with those without anticoagulation treatment (1.3 ± 1.2 N, P = 0.00001). Receiver operating characteristic curve analysis indicated that a PT-INR of 1.81 and an APTT of 32.3 seconds may predict hard hematomas.

CONCLUSIONS

Tough hematomas were histologically characterized by high FB density. Preoperative PT-INR and APTT may predict the presence of tough hematomas.

A Scoping Review of the Methodologies and Reporting Standards in Recent Applications of Artificial Intelligence in Radiomics for Chronic Subdural Hematoma Imaging

Chronic subdural hematoma (cSDH) is the accumulation of blood in the subdural space, primarily affecting older adults. Radiomics is a rapidly emerging field that integrates artificial intelligence (AI) with imaging to improve diagnostic precision and prognostic predictions, including hematoma expansion and recurrence. However, the heterogeneous study designs, endpoints, and reporting standards limit its clinical application. This scoping review queried PubMed for studies published before or on December 25, 2024, using terms related to cSDH and AI-based imaging analysis. Inclusion criteria required primary research applying AI to cSDH imaging and reporting prognostic endpoints such as recurrence, expansion, or treatment response. Extracted data included methodological variables, imaging modalities, endpoints of interest, and performance metrics. Most studies used computed tomography (CT) imaging for analysis, with hematoma recurrence being the most frequently evaluated endpoint of interest. However, there was wide inconsistency in the reporting of model performance metrics. Thus, radiomics offers opportunities to improve outcome prediction and treatment planning in cSDH. Future work should focus on defining clinically meaningful endpoints, standardizing metrics, and validating models prospectively to facilitate integration into practice.

Deciphering the role of hepcidin in iron metabolism and anemia management

One of the most common diseases worldwide is anemia, which is characterized by insufficient erythrocyte production. Numerous complex factors, such as chronic diseases, genetic mutations, and nutritional inadequacies, contribute to this widespread syndrome. This review focuses specifically on anemias caused by defective hepcidin production. Hepcidin, a peptide hormone produced primarily by liver cells, plays a crucial role in regulating iron levels by controlling its absorption. Hepcidin's mechanism of action involves binding to the ferroportin iron transporter, causing its internalization. Disturbances in iron metabolism can have far-reaching consequences, affecting not only the blood but also organs like the liver, kidneys, and brain. Iron homeostasis is crucial for maintaining optimal physiological function. Several blood-based markers are employed to assess iron stores. However, these markers have inherent limitations. Hepcidin, a key regulator of iron metabolism, plays a pivotal role in preventing iron release into the plasma from absorptive enterocytes and macrophages. Elucidating the structure and function of hepcidin is essential for understanding its role in iron homeostasis, which has significant implications for the diagnosis and management of various anemia subtypes. A well-established correlation exists between hepcidin dysregulation and iron deficiency. Despite its potential as a biomarker, the clinical application of hepcidin is hindered by the lack of a commercially available, clinically validated assay. This review aims to provide a comprehensive overview of hepcidin's role in regulating blood iron concentrations and elucidate its implications in the pathogenesis of various anemia subtypes, paving the way for its future applications in research and clinical practice.

Viruses and the Brain-A Relationship Prone to Trouble

Neurological disorders, some of which are associated with viral infections, are growing due to the aging and expanding population. Despite strong defenses of the central nervous system, some viruses have evolved ways to breach them, which often result in dire consequences. In this review, we recount the various ways by which different viruses can enter the CNS, and we describe the consequences of such invasions. Consequences may manifest as acute disease, such as encephalitis, meningitis, or result in long-term effects, such as neuromuscular dysfunction, as occurs in poliomyelitis. We discuss evidence for viral involvement in the causation of well-known chronic neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, multiple sclerosis, as well as vascular dementia in the elderly. We also describe the approaches currently available to control a few of the neural viral infections. These include antivirals that are effective against human immunodeficiency virus and herpes simplex virus, as well as vaccines valuable for controlling rabies virus, poliomyelitis virus, and some flavivirus infections. There is an urgent need to better understand, at a molecular level, how viruses contribute to acute and, especially, chronic neurological diseases and to develop more precise and effective vaccines and therapies.

Minimally Invasive Puncture and Drainage Surgery for the Treatment of Thalamic Hemorrhage Guided by a 3D-printed Guide Plate

Thalamic hemorrhage is a type of intracerebral hemorrhage with high disability and mortality rates. Because of its deep bleeding location, irregular shape of the hematoma, and compression of the third ventricle, it is not suitable for craniotomy. This paper reports a case of a 63-year-old male patient who sought medical attention for left-sided basal ganglia and thalamus hemorrhage that broke into the ventricles. Upon admission, the patient exhibited impaired consciousness and was diagnosed with thalamic hemorrhage accompanied by ventricular hemorrhage through the head CT and CTA scan. To address the patient's unique circumstances, a 3D-printed guide plate was utilized to guide the puncture and drainage surgery, thereby ensuring a relatively smooth and less traumatic process. After the surgery, the patient's consciousness recovered well, and there was significant improvement in clinical indicators. This case demonstrates that a 3D-printed guide plate has the advantage of precise localization and minimal trauma in guiding thalamic hemorrhage surgery, showing promising clinical application prospects and being worthy of promotion in future clinical practice.

The correlation between high-sensitivity cardiac troponin levels in diabetic patients' serum and lower limb lesions: based on NHANES data

Objective

To evaluate the association of hypersensitive cardiac troponin (hs-cTnT), a biomarker of myocardial injury, with diabetic lower extremity disease in American adults.

Methods

We conducted a cross-sectional study (unweighted N=1,196) of diabetic patients aged 40 years or older who participated in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2004. Logistic regression was used to assess the association of hs-cTnT with lower extremity disease, including peripheral neuropathy (as assessed by monofilament test), peripheral artery disease (as assessed by ankle-brachial index), history of foot ulcers, or amputation. All analyses are weighted.

Results

The prevalence rate of diabetic lower extremity disease was 41.6%. Adjusted hs-cTnT was significantly associated with lower limb disease in adults with diabetes. There is interaction between chronic kidney disease and hs-cTnT, which strongly interferes with the correlation between hs-cTnT and lower extremity lesions in diabetic patients.

Conclusions

Our study suggests the usefulness of hs-cTnT as a biomarker for lower extremity lesions in adults with diabetes and highlights the potential direct interaction of hs-cTnT with chronic kidney disease.

Advances in chromosomal microarray analysis: Transforming neurology and neurosurgery

Over the past two decades, genomics has transformed our understanding of various clinical conditions, with Chromosomal Microarray Analysis (CMA) standing out as a key technique. Offering unparalleled sensitivity, CMA detects submicroscopic chromosomal imbalances, enabling the examination of DNA for copy number variations, deletions, duplications, and other structural differences. In neurology, CMA has revolutionised diagnoses, personalised treatment plans, and patient outcomes. By identifying genetic anomalies linked to neurological conditions, CMA allows clinicians to tailor treatments based on individual genetic profiles, enhancing precision medicine. CMA's clinical utility spans numerous neurological conditions, providing crucial insights into neurodevelopmental disorders, CNS tumours, neurodegenerative diseases, cerebrovascular diseases, and epilepsy. In neurodevelopmental disorders, CMA aids in diagnosing autism and intellectual disabilities, facilitating early interventions that improve long-term outcomes. In epilepsy, CMA helps identify genetic causes of drug-resistant seizures, enabling more targeted therapies and reducing adverse reactions. CMA also aids in stratifying risk for cerebrovascular diseases, enabling preventive interventions that improve patient prognosis. Despite its potential, challenges remain, such as interpreting variants of uncertain significance (VOUS), the lack of standardised testing guidelines, and issues of cost and accessibility. Addressing these challenges will optimise CMA's impact, advancing personalised medicine and reshaping neurology. This review discusses CMA's pivotal role in bridging the gap between genomics and clinical practice, underscoring its potential to transform neurogenetics and ultimately improve patient care.

Turmeric-black pepper-honey nanoemulsion formulation and antiulcerogenic effect evaluation against ethanol-induced gastric ulcers in rats

Gastric ulcer is a common disorder of the digestive system. The combination of turmeric and honey is known to treat stomach ulcers. However, curcumin, an active component in turmeric, has limitations, i.e., poor water solubility and low oral bioavailability. Therefore, turmeric and honey were formulated into a nanoemulsion with black pepper to enhance curcumin bioavailability. The study followed a systematic approach to optimize the nanoemulsion formula, determine stability, and evaluate ulcer healing activity in rats with ethanol-induced gastric ulcers. Nanoemulsion was prepared using a low-energy emulsification method called emulsion phase inversion (EPI). Two stability evaluations were carried out, i.e., storage and freeze-thaw stability tests. The organoleptic, droplet size, polydispersity index, pH, viscosity, and curcumin content of the nanoemulsion were evaluated. Male Wistar albino rats were induced with 96% ethanol for six days. The rats were divided into six groups, i.e., healthy control, ulcerated control, omeprazole, two different doses of turmeric, honey, and black pepper nanoemulsion (NTBH1 and NTBH2), and turmeric and honey nanoemulsion (NTH). The antiulcer activity was determined by measuring the ulcer area, ulcer index, curative index, ulcer severity score, and histology. The best formula with the smallest droplet size, i.e., 144.6±3.8 nm, was obtained from the nanoemulsion using Tween 80 as surfactant, glycerin as cosolvent, and sodium alginate as viscosity enhancer. The result showed that the nanoemulsion was stable after being stored at 25 and 40°C for four weeks and after six cycles of freeze-thaw test. The ulcer index of the ulcerated rats from the lowest to the highest, i.e., NTBH2, omeprazole, NTH, and NTBH1. In conclusion, the nanoemulsion developed in this study containing turmeric, honey, and black pepper holds promising potential in treating gastric ulcers, offering a hopeful outlook for future treatments.

Association of serum neurofilament light chain with cognitive impairment: findings from the National Health and Nutrition Examination Survey

Background

Serum Neurofilament Light chain (NfL) is a promising biomarker of neuronal damage, used to assess the extent of neuronal injury and neurodegeneration, and it is widely applied in the diagnosis of neurodegenerative disease and monitoring disease progression. This article aims to determine whether serum NfL associated with cognitive level.

Methods

Using NHANES data, we conducted an analysis of cognitive test results for 450 adults aged 60 years and older and examined their correlation with serum NfL levels. When exploring the association between cognitive test scores and serum NfL levels, regression models and restricted cubic spline (RCS) regression models were employed to adjust for potential confounding factors. The least absolute shrinkage and selection operator (LASSO) regression was applied for identifying key cognitive impairment factors, which was then included in the establishment of a risk prediction nomogram model, with the receiver operating characteristic (ROC) curve being built to evaluate its discriminatory power for cognitive impairment.

Results

It was found that there is a strong positive correlation between serum NfL levels and both low total cognitive function (total-CF) OR: 1.028 (95%CI = 1.015-1.041 p < 0.001) and low Digit Symbol Substitution Test (DSST) OR: 1.026 (95%CI = 1.003-1.050, p = 0.027). Furthermore, using the RCS model, we observed a linear trend in the relationship between NfL and low total-CF. The nomogram model based on NfL identified by LASSO regression displayed a considerable predicative value for low total-CF, with an area under the curve [AUC = 85.6% (81.6-89.3%)].

Conclusion

There is a strong correlation between serum NfL levels and cognitive function, especially DSST, which reflects attention and information processing abilities, as well as overall cognitive function, but not memory and language fluency. Thus, NfL may serve as a serum biomarker for dementia monitoring.