Search Results (3,139)

Background: The intracranial space has limited capacity; thus, volume changes in any component can raise intracranial pressure and cause mass effect. This mechanism underlies many neurological disorders. Artificial Intelligence, increasingly applied in medicine and diagnostic imaging, may support the evaluation of such conditions. This systematic review investigates AI-based models for cerebrospinal fluid segmentation and analysis on computed tomography. Methods: In December 2024, a systematic review was conducted across MEDLINE (PubMed), Scopus, Web of Science, Embase, and Cochrane Library. From 559 identified studies, 14 were included after independent review by two evaluators. Extracted data covered study characteristics, AI model design, dataset composition, and performance metrics for CSF segmentation. Quality assessment followed PRISMA 2020 and used JBI, AMSTAR 2, and CASP checklists. Results: The 14 studies demonstrated applications of AI in CSF segmentation and volumetric assessment, primarily for hydrocephalus diagnosis, mass effect evaluation, and stroke outcome prediction. Convolutional Neural Networks and Random Forests were the most frequent approaches. Reported segmentation accuracy was high, with Dice Similarity Coefficient values ranging from 0.75 to 0.95 and strong volumetric correlations (r up to 0.99) between AI-based and manual measurements. Conclusions: AI-assisted CSF segmentation from CT images shows promising accuracy and efficiency, with potential to enhance neurological diagnostics. Remaining challenges include dataset variability, inconsistent algorithm performance, and limited clinical validation. Future research should prioritize standardization of methods, larger and more diverse training datasets, and integration of AI tools into clinical workflows. Full article

Background/Objectives: Central nervous system (CNS) infections remain a significant public health challenge and require rapid and accurate diagnosis to guide clinical management. Although the incidence of bacterial meningitis has declined owing to widespread vaccination, viral etiologies continue to dominate CNS infections. The aim of this study was to assess the epidemiological trends, age distribution, and seasonality of CNS infections using multiplex PCR. Methods: A retrospective analysis was conducted on cerebrospinal fluid (CSF) samples collected between January 2021 and December 2022 from patients with CNS infections at King Abdulaziz Medical City. A BioFire FilmArray Meningitis/Encephalitis (ME) panel was used to detect pathogens. Patient demographics, pathogen distribution, and seasonal trends were analyzed. Results: A total of 2,460 CSF samples were tested, of which 130 (5%) were positive for at least one pathogen. Viral pathogens accounted for 82.3% of the infections, with human herpesvirus-6 (HHV-6) (31%) and enterovirus (EV) (20%) being the most common. Bacterial pathogens represented 17.7% of the cases, with Streptococcus pneumoniae (6%) and Escherichia coli K1 (5%) being the predominant bacterial agents. The highest infection burden was observed in infants aged 0–6 months, with a marked male predominance. Seasonal analysis revealed multiple peaks in viral infections, particularly of HHV-6 and EVs, whereas bacterial infections were sporadic, with Streptococcus agalactiae and Streptococcus pneumoniae peaking in October and November. Conclusions: Viral infections, particularly HHV-6 and EVs, dominated CNS infections, with distinct seasonal and age-related variations. These findings underscore the value of multiplex PCR in improving the rapid diagnosis of CNS infections and aiding in timely treatment and antimicrobial stewardship. Full article

Background: While diabetes is a recognized risk factor for asthma, the shared genetic components between diabetes/glycemic traits and asthma remain unclear. This study investigates the genetic associations, causal relationships, and underlying mechanisms linking these conditions. Methods: We assessed global genetic correlations using linkage disequilibrium score regression (LDSC), high-definition likelihood analysis (HDL), and genetic covariance analysis (GNOVA). Trait pairs with significant correlations subsequently underwent genetic overlap analysis (Genetic analysis integrating Pleiotropy and functional Annotation, GPA) and local genetic correlation analysis (Local Genetic Variant Association Analysis, LAVA). Cross-phenotype association (CPASSOC) and multitrait analysis of GWAS (MTAG) identified potential pleiotropic loci, followed by colocalization and functional annotation. Proteome-wide association study (PWAS) revealed proteins and pathways shared between diabetes/glycemic traits and asthma. Generalized summary-data-based Mendelian randomization (GSMR) was used to evaluate causal effects between diabetes/glycemic traits and asthma. Results: Significant genetic correlations were observed between body mass index (BMI) and asthma (rg = 0.280–0.397; FDR < 0.05), type 2 diabetes mellitus (T2DM) and asthma (rg = 0.240–0.289; FDR < 0.05) across all three methods. GPA revealed significant genome-wide genetic overlap, highest for BMI and asthma (pleiotropy association ratio [PAR] = 0.377) and T2DM-asthma (PAR = 0.353). LAVA identified 111 significant local correlation regions, predominantly between T2DM and asthma (70 regions). Colocalization analysis identified 24 shared pleiotropic loci, predominantly on chromosome 8. Local genetic correlation analysis revealed extensive correlations between T2DM and asthma. PWAS identified 46 shared proteins, with IL6R, MAPK3, and CSF2 being key hubs. Protein–protein interaction analysis highlighted enrichment in JAK-STAT signaling, Th1/Th2 differentiation, and IL-17 pathways. GSMR demonstrated causal effects of BMI (OR = 1.47, 95% CI: 1.42–1.53, FDR < 0.05) and T2DM (OR = 1.06, 95% CI: 1.04–1.08, FDR < 0.05) on increased asthma risk, with no evidence of reverse causality. Conclusions: Obesity (BMI) and T2DM exert causal effects on asthma risk via shared genetic loci and inflammatory pathways, particularly involving IL6R, MAPK3, CSF2, and JAK-STAT signaling. Targeting these colocalized proteins may offer potential therapeutic strategies. Full article

Background/Objectives: Anterior cervical meningocele (ACM) is a rare congenital condition characterized by the herniation of the meninges through a defect in the anterior vertebral column. ACM clinical management is not standardized because this condition is rare, and guidelines are missing. Hereby, a systematic literature review is performed to determine management options and outcomes. Methods: The case of a 62-year-old patient with incidental diagnosis of C3-C5 ACM is presented. A systematic review was conducted using standard PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines for all cases of anterior cervical meningocele from 1837 to 2025. Results: The review provided nine clinical cases and our illustrative case. The median age was 47 years, with a predominance of female patients (70%). The most common presenting symptom was neck pain (60%), followed by paresthesia and hypoesthesia in the upper limbs. Four patients underwent conservative management with clinical and radiological follow-up, while four patients underwent neurosurgical intervention. Surgical treatment was complicated by cerebrospinal fluid (CSF) leak in two patients, and one of them developed meningitis. Conclusions: ACM is typically associated with mesodermal dysplasia and dural ectasia. ACM usually has a benign clinical course, requiring neurological follow-up and conservative management alone. However, a surgical approach should be considered in cases of vertebral instability or symptoms related to upper airway compression or upper gastrointestinal tract compression despite the high risk of CSF leak when surgical repair is attempted. Full article

For drug-susceptible TB, the WHO-endorsed first-line regimen (isoniazid, rifampicin, ethambutol, pyrazinamide) remains the global reference. Therapy must always be tailored to drug susceptibility, especially in MDR- and XDR-TB. HIV-associated mycobacterial infections—including Mycobacterium tuberculosis (TB), disseminated Mycobacterium avium complex (MAC), and Mycobacterium leprae (M. leprae)—remain leading causes of morbidity and mortality in people living with HIV (PLWH). TB continues to account for the highest burden of AIDS-related deaths worldwide, while MAC and leprosy complicate care in advanced immunosuppression. This review synthesizes current evidence on epidemiology, clinical features, and management challenges of HIV–mycobacterial co-infections. We discuss drug-susceptible and drug-resistant TB therapies, drug–drug interactions with antiretroviral therapy (ART), and the clinical impact of immune reconstitution inflammatory syndrome (IRIS). Beyond established regimens, we highlight host-directed strategies such as metformin, glutathione augmentation, mTOR modulation, and vitamin D; immunotherapies including interferon-γ, GM-CSF, and IL-7; and therapeutic vaccines (M72/AS01E, MTBVAC, VPM1002) as promising adjuncts. Distinct from guideline-focused overviews, this review emphasizes non-tuberculous mycobacterial disease (NTM, including MAC) and leprosy in PLWH and synthesizes host-directed and adjunctive strategies with their translational prospects, including ART compatibility and IRIS. By integrating TB, NTM, and leprosy across the HIV care continuum, we highlight opportunities not treated in detail elsewhere—particularly HDT-enabled approaches and implementation considerations in PLWH. Full article

(1) Background: To report two cases of severe tick-borne encephalitis (TBE) in elderly patients presenting with a previously undescribed subarachnoid T2/FLAIR hyperintensity on repeated MRI examinations, which may serve as an early imaging biomarker of disease severity. (2) Methods: Two unvaccinated 82-year-old patients (one male and one female) presented with acute encephalitis and required intensive care. Serial brain MRI, EEG, CSF analysis, and neurophysiological assessments were performed. (3) Results: Both patients showed rapid progressive neurological deterioration in the context of TBE, confirmed by elevated serum and CSF IgM and IgG titers. Early follow-up MRI revealed striking sulcal hyperintensities on T2/FLAIR sequences, interpreted as protein-rich subarachnoid inflammatory changes. These changes paralleled clinical worsening and resolved on follow-up imaging. The male patient developed meningoencephalomyeloradiculitis, remained comatose, and died from respiratory failure (the brain and spinal cord were examined postmortem). The female patient had meningoencephaloradiculitis with severe dysphagia and was discharged with a modified Rankin Scale score of four. Both patients demonstrated epileptiform EEG activity. The CSF analysis revealed markedly elevated total protein, lactate, tau protein, and CXCL13, as evidence of blood–brain barrier disruption and inflammatory neurodegeneration. (4) Conclusions: We describe acute subarachnoid T2/FLAIR hyperintensity in TBE as an imaging feature that may correlate with severe systemic inflammation and a poor prognosis. This radiological finding could serve as a potential early prognostic marker in TBE. Full article

In the past decade, research on recombinant oncolytic viral agents in the treatment of solid tumors has evolved from the initial stage of simple genetic engineering to the current stage of multiple pipelines of parallel clinical application and combination therapy. Compared with T-VEC, the classical therapeutic agent that only expresses GM-CSF, which was approved in 2015, most new oncolytic virus designs include diverse gene constructs to reduce toxic effects, enhance multiple antitumor immunity, avoid immune clearance, or enhance tumor targeting. The single route of administration that activates the inflammatory tumor immune microenvironment by intratumoral injection is no longer sufficient to meet the treatment needs of refractory solid tumors. In this review, we illustrated the construction patterns of typical recombinant oncolytic viral agents and their latest clinical trial progress. Secondly, we summarized the underlying mechanisms of the combined application of antiviral and antitumor immunity in the field of solid tumor immunotherapy. Finally, we explored the feasibility of the intravenous application of oncolytic viruses and their future development directions. We believe that the diversified treatment design of oncolytic viruses will bring more surprises to the immunotherapy of refractory tumors. Full article

Patients with systemic lupus erythematosus (SLE) and lupus nephritis (LN) are at increased risk of severe infections, making effective vaccination strategies essential. While antibody responses to SARS-CoV-2 vaccination have been studied in SLE, less is known about innate immune correlates. Therefore, we evaluated cytokines with a particular emphasis on interferon and chemokine profiles. To fulfill the immunological picture, we also assessed neutralizing antibodies against SARS-CoV-2 variants, lymphocyte subpopulations, and selected gene expression signatures in 33 patients stratified by vaccination status: fully vaccinated (FV, n = 23) and partially vaccinated (PV, n = 10). Serum analyses showed that FV patients exhibited increased type I (IFN-α2, IFN-β) and type III (IFN-λ1, IFN-λ2/3) interferons, as well as elevated pro-inflammatory cytokines (IL-1β, IL-6, TNF-α, and IL-12p70) and IL-10, whereas neutralizing antibody (Neut. Ab.) titers against wild-type and variant strains, including Omicron, were comparable between groups. Immunophenotyping demonstrated preserved T- and B-cell subset distributions, except for reduced CD8⁺CD197⁺CD45RA⁻ (central memory) T cells in FV patients. ISG15 gene expression was upregulated in the T cells of FV patients. Correlation analyses linked IL-6 with disease activity and IL-8, GM-CSF, IFN-β, IL-10, and Alpha Neut. Ab. with organ damage. Complement C3 correlated inversely with IFN-α2 and IFN-γ, while C4 correlated positively with Alpha and Omicron Neut. Ab. These findings highlight that vaccination in SLE induces distinct interferon and cytokine signatures without consistent enhancement of neutralizing antibodies against SARS-CoV-2, underscoring the importance of integrated immune correlates in assessing vaccine responses in this population. Full article

Background/Objectives: Classical swine fever (CSF) is listed by the World Organisation for Animal Health as a highly devastating and contagious pig disease, causing severe economic losses to the swine industry. In spite of the successful elimination of CSF in Taiwan, preparedness against potential reintroduction remains essential. The live attenuated vaccines have been effective in disease control, but are not capable of a viable strategy that differentiates infected from vaccinated animals (DIVA). Subunit vaccines are recognized for their safety and ability to induce protective immunity against infectious diseases. Methods: In this study, the recombinant CSF virus (CSFV) E2 proteins were formulated with a CpG motif as an adjuvant to produce the E2-CpG subunit vaccine. Its efficiency in specific-pathogen-free (SPF) pigs was compared with a commercially available E2 subunit vaccine (Bayovac^® CSF-E2; Bayer Taiwan Co., Ltd., Taipei City, Taiwan). Results: Significantly higher titers of anti-E2 antibodies were induced in pigs immunized with a single dose of the E2-CpG vaccine, particularly the reduced E-0.5A formulation, than those immunized with a dose of the commercialized E2 subunit vaccine adjusted to double dosage. This designed subunit vaccine showed high efficacy in protection against clinical symptoms and significant pathological alterations in pigs after a highly virulent CSFV (genotype 1.1) challenge. Viral shedding was not detected in vaccinated pigs before completion of the challenge study, and the viral load in their spleens remained undetectable. Conclusions: These results could support the potential of the E2-CpG vaccine as a cost-effective, single-dose subunit vaccine capable of inducing robust CSFV-specific immunity and providing 100% protection against lethal CSFV challenges. Full article

As smart manufacturing environments continue to evolve, operational technology systems are increasingly integrated with external networks and cloud-based platforms. However, many manufacturing facilities still use legacy systems running on end-of-support/life operating systems with discontinued security updates. It is difficult to mitigate the cyber threats and risks for these systems using perimeter-based security models that isolate them from other networks. To address these constraints, a Zero Trust-based security architecture tailored for legacy manufacturing environments with practical field applicability is proposed. Our architecture builds upon the six core functions outlined in National Institute of Standards and Technology Cybersecurity Framework 2.0—identify, protect, detect, respond, recover, and govern—adapting them specifically to manufacturing environment security challenges. To achieve this, the architecture combines asset identification, policy-driven access control, secure SMB gateway transfers, automated anomaly detection and response, clean image recovery, and organizational governance procedures. This study validates the effectiveness and scalability of the proposed architecture through scenario-based simulations. When combining the EoSL defense hardening and gateway-based perimeter control, the architecture achieves approximately 99% overall threat suppression and a 98% reduction in critical-asset infection rates, demonstrating its strong resilience and scalability in large-scale legacy OT environments. Full article

Colony-stimulating factor 3 (CSF3), additionally called granulocyte colony-stimulating factor (G-CSF), is the major cytokine regulating neutrophil production and also impacting their function. The actions of this cytokine are mediated through its unique receptor, the colony-stimulating factor 3 receptor (CSF3R). Several classes of pathogenic mutations in the CSF3R gene have been identified that have distinct biological properties and clinical impacts. This review provides an overview of CSF3R, the various pathogenic CSF3R mutations/variants and their biological effects. It also details the diseases to which they contribute, notably including chronic neutrophilic leukemia (CNL) and other myeloproliferative neoplasms (MPNs), myelodysplastic neoplasms (MDS), combined MDS/MPN disorders such as atypical chronic myeloid leukemia (aCML) and chronic myelomonocytic leukemia (CMML), as well as acute myeloid leukemia (AML) and lymphoid malignancies. Full article

Background: Early diagnosis of Alzheimer’s disease (AD) is constrained by invasive and costly tests. Aggregation of $\beta$-amyloid and the A$\beta$42/A$\beta$40 ratio in cerebrospinal fluid (CSF) and blood are key biomarkers. Fluorescent probes can report aggregate states, and artificial intelligence (AI) can extract subtle patterns from spectral and blood data. This review synthesizes how probes and AI can identify aggregates and assess the A$\beta$42/A$\beta$40 ratio in body fluids to facilitate earlier AD diagnosis. Methods: PRISMA-compliant searches were conducted in Scopus, PubMed, Web of Science, and IEEE Xplore. Results: Twenty-eight studies met inclusion criteria. Plasma A$\beta$42/A$\beta$40 was lower in PET-positive individuals by ∼7–18%, with higher performance for mass spectrometry (mean AUC ≈ 0.80) than immunoassays (AUC ≈ 0.71). CSF A$\beta$42/A$\beta$40 showed larger group differences (∼50% reductions in PET+) and stronger PET concordance, outperforming plasma. Fluorescent probes—including AN-SP and CRANAD-28—were sensitive to early aggregates and showed in vivo imaging potential, but evidence is largely preclinical or from small cohorts. AI/ML approaches frequently achieved within-study accuracies >90% (e.g., 94–100% in spectral tasks), yet external validation and head-to-head tests of ratio alone versus ratio + AI remain scarce. Conclusions: Plasma A$\beta$42/40 —particularly by mass spectrometry—currently provides the most reproducible fluid approximation to amyloid PET (mean AUC ≈ 0.80). Fluorescent probes sensitively detect oligomeric A$\beta$ species and show in vivo potential, but evidence remains largely preclinical or from small cohorts. AI/ML methods can extract additional signal from spectral and multivariate blood data, yet consistent incremental gains over optimized Aβ42/40 assays have not been demonstrated due to limited external validation and head-to-head comparisons. Full article

Background/Objectives: Meningoencephalitis (ME) is a life-threatening infectious disease; therefore, prompt and accurate diagnosis is lifesaving. Traditional diagnostic methods, such as culture, have several limitations related to sensitivity and specificity. Emerging multiplex ME-PCR panels are a comprehensive and rapid tool in a single test. The Bio-Speedy Meningitis/Encephalitis RT-qPCR MX-17 panel (Bioeksen R&D Technologies Inc., Turkey) enables testing for 17 targets. To evaluate the performance of the panel compared to clinical and CSF parameters. Methods: A total of 403 patients with a preliminary diagnosis of ME were reviewed between January 2019 and September 2023. Following revision, 72 patients with clinical, CSF, and laboratory findings were included. The tested panel was used to detect targeted pathogens in CSF samples. The 30-day survival rate and prolonged stay were analyzed. Results: The median CSF protein value was 59.5 mg/dL (14.2–1471 mg/dL) and glucose was 61.95 mg/dL (0.083–165 mg/dL). Forty-one (56.9%) ME panel results were positive, among which 38.9% (28) were viral and 19.4% (14) were bacterial. HHV-6 ranked first with a rate of 15.3%. The Bio-Speedy panel test results outperformed the CSF culture (p < 0.001). The correlation of the Bio-Speedy panel with impaired consciousness was statistically significant (p = 0.004). Six (8.3%) patients from the study group died within 30 days. Conclusions: Compared to traditional methods, Bio-Speedy panel was effective in identifying the causative agents of ME. The Bio-Speedy ME RT-qPCR MX-17 panel offers accurate detection of ME-causing pathogens. The implementation of the panel in clinical practice can impact patient management and improve outcomes. Full article

Human granulocyte colony-stimulating factor (hG-CSF) is primarily used to treat neutropenia induced by cancer chemotherapy and bone marrow transplantation. The current identification test for hG-CSF relies on Western blot (WB), a labor-intensive and technically demanding method. This study aimed to screen and prepare an anti-hG-CSF nanobody to identify and quantify hG-CSF, with the ultimate goal of developing colloidal gold-labeled nanobody test strips for rapid identification. An alpaca was immunized with hG-CSF, and the VHH gene sequence encoding the anti-hG-CSF nanobody was obtained through sequencing following phage display library construction and multiple rounds of biopanning. The nanobody C68, obtained from screening, was expressed by E. coli, and its physicochemical properties such as molecular weight, isoelectric point, and affinity were characterized after purification. WB analysis demonstrated excellent performance of the nanobody in identification tests in terms of specificity, limit of detection (LOD), applicability with products from various manufacturers, and thermal stability. Additionally, we established an ELISA method for hG-CSF quantification utilizing the nanobody C68 and conducted methodological validation. Finally, colloidal gold-based test strips were constructed using the nanobody C68, with a LOD of 30 μg/mL, achieving rapid identification for hG-CSF. This study represents a novel application of nanobodies in pharmaceutical testing and offers valuable insights for developing identification tests for other recombinant protein drugs. Full article

Background/Objectives: Cerebrospinal fluid erythrocyte load (CTRED) reflects occult red-blood-cell ingress into brain/CSF and consequent heme–iron exposure, a toxic pathway relevant to Alzheimer’s disease (AD). We aimed to develop explainable machine learning (ML) models that classify high vs. low CTRED from routine, largely non-invasive inputs, and to position a blood-first workflow leveraging contemporary plasma amyloid–tau biomarkers. Methods: Twenty-six ADNI participants were analyzed. Inputs were age, sex, mean arterial pressure (MAPres), amyloid (Aβ42), total tau, phosphorylated tau, and hippocampal atrophy rate (APC) derived from longitudinal MRI. APC was computed from normalized hippocampal volumes. CTRED was binarized at the median (0 vs. >0). Data were split into train (n = 20) and held-out test (n = 6). Five classifiers (linear SVM, ridge, logistic regression, random forests, and MLP) were trained in leakage-safe pipelines with stratified five-fold cross-validation. To provide a comprehensive assessment, we presented the contribution AUC, thresholded performance metrics, summarized model performance, and the permutation feature importance (PFI). Results: On the test set, SVM, ridge, logistic regression, and random forests achieved AUC = 1.00, while the MLP achieved AUC = 0.833. Across models, PFI consistently prioritized p-tau/tau, Aβ42, and MAPres; age, sex, and APC contributed secondarily. The attribution profile aligns with mechanisms linking BBB dysfunction and amyloid-related microvascular fragility with tissue vulnerability to heme–iron. Conclusions: In this proof-of-concept study, explainable ML predicted CTRED from routine variables with biologically coherent drivers. Although ADNI measurements were CSF-based and the sample was small, the framework is non-invasive by adding plasma p-tau217/Aβ1–42 for amyloid, tau inputs, and integrating demographics, hemodynamic context, and MRI. External, plasma-based validation in larger cohorts is warranted, alongside extension to MCI and multimodal correlation (QSM, DCE-MRI) to establish clinically actionable CTRED thresholds. Full article