Search Results (2,668)

Early detection of cancer is crucial for improving patient outcomes. Traditional modalities such as mammography and low-dose computed tomography are effective but exhibit inherent limitations, including radiation exposure and accessibility challenges. This review explores innovative, non-invasive cancer screening methods, focusing on liquid biopsy and volatile organic compound (VOC)-based detection platforms. Liquid biopsy analyzes circulating tumor DNA and other biomarkers in bodily fluids, offering potential for early detection and monitoring of treatment response. VOC-based detection leverages unique metabolic signatures emitted by cancer cells, detectable in exhaled breath or other bodily emissions, providing a rapid and patient-friendly screening option. We provide a comprehensive overview of these advanced multi-cancer detection techniques to enhance diagnostic accuracy, accessibility, and patient adherence, and ultimately enhance survival rates and patient outcomes. Full article

Background/Objectives: The understanding of the mechanisms involved in the etiopathogenesis and maintenance of Bipolar Disorder (BD) should be a priority to identify potential early clinical markers that could help in improving treatment strategies and prevention. The aim of this study was to investigate the potential correlation between hopelessness, alexithymia, mind wandering, and rumination in patients with a primary diagnosis of BD, evaluating whether these psychopathological aspects could negatively affect bipolar illness. Methods: A semi-structured interview was used to collect sociodemographic and clinical characteristics. Several psychometric tools were administered: the Beck Hopelessness Scale; Toronto Alexithymia Scale; Rumination Response Scale; Mind Wandering Questionnaire; Mind Wandering: Deliberate; Mind Wandering: Spontaneous; and the Daydreaming Frequency Scale. Results: Patients with high levels of hopelessness have a greater number of psychiatric and medical comorbidities and are more frequently on polypharmacotherapy. Additionally, patients with high levels of hopelessness show a greater likelihood of having attempted suicide during their lifetime. The presence of alexithymia is associated with longer hospitalization and psychiatric comorbidities. Higher levels of rumination correlate with a greater number of psychiatric and medical comorbidities, and with the presence of residual symptoms. Mind wandering is associated with the presence of medical comorbidities and residual symptoms. Conclusions: Hopelessness, alexithymia, mind wandering, and rumination should be identified as important proxies of impaired subjective well-being that should be carefully monitored because they could further worsen the clinical course of BD and suicidal risk in this vulnerable population. Full article

Multifunctional hydrogels represent an emerging technological advancement in cancer therapeutics, integrating diagnostic imaging capabilities with therapeutic modalities into comprehensive, multifunctional systems. These hydrogels exhibit exceptional biocompatibility, biodegradability, high water retention capacity, and tunable mechanical properties, enabling precise drug delivery while minimizing systemic side effects. Recent innovations in stimuli-responsive components facilitate intelligent, controlled drug release mechanisms triggered by various stimuli, including changes in pH, temperature, magnetic fields, and near-infrared irradiation. Incorporating diagnostic imaging agents, such as magnetic nanoparticles, fluorescent dyes, and radiolabeled isotopes, substantially improves tumor visualization and real-time therapeutic monitoring. Multifunctional hydrogels effectively integrate chemotherapy, photothermal therapy, photodynamic therapy, immunotherapy, and their synergistic combinations, demonstrating superior therapeutic outcomes compared to conventional methods. Particularly, injectable and in situ-forming hydrogels provide sustained local drug delivery postoperatively, effectively reducing tumor recurrence. However, challenges persist, including initial burst release, mechanical instability, regulatory barriers, and scalability concerns. Current research emphasizes advanced nanocomposite formulations, biofunctionalization strategies, and innovative manufacturing technologies like 3D bioprinting to facilitate clinical translation. This review comprehensively summarizes recent advancements, clinical applications, and future perspectives of multifunctional hydrogel systems for enhanced cancer treatment, underscoring their potential to revolutionize personalized oncology. Full article

Hepatocellular carcinoma (HCC) remains one of the most lethal cancers globally, driven by chronic liver disease and a complex tumor microenvironment (TME). Recent advances in spatial omics, single-cell analyses, and AI-driven digital pathology have shed light on the intricate heterogeneity of HCC, highlighting key roles for immune suppression, angiogenesis, and fibrosis in tumor progression. This review synthesizes current epidemiological trends, noting a shift from viral hepatitis to metabolic syndrome as a primary etiology in Western populations, and elucidates how TME components—such as tumor-associated macrophages, cancer-associated fibroblasts, vascular endothelial cells, and immunosuppressive cytokines—contribute to resistance against conventional therapies. We detail the evolution of immunotherapeutic strategies from monotherapy to combination regimens, including dual immune checkpoint blockade and the integration of antiangiogenic agents. Emerging circulating and tissue-based biomarkers offer promise for enhanced patient stratification and real-time monitoring of treatment responses. Collectively, these innovations herald a paradigm shift toward TME-directed precision oncology in HCC, emphasizing the need for multi-targeted approaches to synergistically modulate interacting cellular constituents and ultimately improve clinical outcomes. Full article

Wound healing is a complex, tightly regulated process essential for maintaining skin barrier function. Chronic wounds, often complicated by biofilm-forming bacteria and elevated oxidative stress, pose significant challenges in clinical management. The rise of antibiotic-resistant bacteria has further exacerbated the problem, limiting therapeutic options and complicating wound treatment. Traditional wound care approaches frequently fail to provide real-time accurate insights into wound status, leading to delayed or suboptimal treatments. Recent advancements in modern and smart wound dressings, which integrate various biosensors, different new drug delivery systems, and wireless communication technology, offers promising solutions for monitoring wound progression over time. These innovations enable early detection of adverse events such as bacterial infections and inflammation, facilitating more effective, on-demand treatment. This review highlights the current state of antibiotic-embedded wound dressings, discusses their limitations, and explores the potential of next-generation wound dressings incorporating microelectronic sensors for real-time monitoring and adaptive therapeutic responses to support healing and combat antimicrobial resistance. Full article

Background/Objectives: OCD is a chronic psychiatric disorder, often requiring long-term pharmacological treatment. Although selective serotonin reuptake inhibitors (SSRIs) are considered first-line agents, 40 to 60% of patients show only partial or no response when treated at standard dosages. In such cases, supratherapeutic doses of SSRIs have been proposed as an alternative strategy. However, the evidence supporting this approach remains limited and fragmented. This review aims to evaluate the rationale, clinical efficacy, tolerability, and practical considerations associated with high-dose SSRI use in OCD. Methods: A structured narrative review was conducted using targeted literature searches in PubMed and Scopus. Studies were included if they reported on the use of high-dose SSRIs (citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, or sertraline) in patients with OCD and provided efficacy and/or tolerability data. Clinical trials, observational studies, and case reports were all reviewed. Results: Evidence shows that higher doses of SSRIs are significantly more effective than low or medium doses in reducing OCD symptoms—especially in individuals who have only partially responded to standard treatment. Smaller clinical studies and case reports have also demonstrated that supratherapeutic dosing, beyond typical regulatory limits, can be both effective and well tolerated in treatment-resistant OCD. Conclusions: High-dose SSRI treatment may be a valuable option for selected OCD patients who do not respond to standard therapy. However, careful patient selection, regular monitoring, and further controlled studies are necessary to better define its long-term safety and effectiveness. In this context, increasingly advanced technologies—such as therapeutic drug monitoring and pharmacogenetic testing for relevant polymorphisms—may support more individualized and safer treatment strategies. Full article

Background/Objectives: Patients suffering from inflammatory bowel diseases (IBDs) undergoing treatment with anti-TNF antibodies mount a diminished humoral immune response to vaccination against SARS-CoV-2 compared to healthy controls. The characterization of variant-specific immune responses is particularly warranted among immunosuppressed patients, where reduced responses may necessitate further medical interventions. Methods: This pilot study investigated the humoral immune response of vaccinated IBD patients on anti-TNF medication and a comparable group of healthy individuals against the viral variants Alpha, Beta, Gamma, Delta, and Omicron BA.1 and BA.5. While total IgG antibodies targeting the receptor binding site of the spike protein of SARS-CoV-2 were quantified using a chemiluminescence microparticle immunoassay (CMIA), their potential neutralizing capacity was determined using commercial and variant-specific in-house surrogate virus neutralization tests (sVNTs) against a variant-specific in-house VSV-pseudotyped virus neutralization test (pVNT) as the gold standard. Results: Employing variant-specific assays recapitulated the immune escape functions of virus variants. Conspicuously, antibody reactivity against Alpha and Omicron BA.1 and BA.5 was strikingly poor in IBD patient sera post-initial vaccination compared to healthy individuals. A comparison of the diagnostic performance of assays with the pVNT revealed that identification of patients with inadequate humoral responses by CMIA and sVNT may require adjustments to cut-off values and end-point titration of sera. Following adaptation of cut-off values, patient sera exhibited reduced reactivity against all tested variants. The assay panel used substantiated the impact of anti-TNF therapy in IBD patients as to reduced strength, function, and breadth of the immune response to several SARS-CoV-2 variants. The immune response measured following the second vaccination was comparable to the antibody response observed in healthy individuals following the first vaccination. Conclusion: Variant-specific sVNTs and pVNTs have the potential to serve as valuable tools for evaluating the efficacy of adapted vaccines and to inform clinical interventions in the care of immunosuppressed patients. Anti-TNF-treated individuals with antibody levels below the optimized CMIA threshold should be considered for early booster vaccination and/or close immunological monitoring. Full article

Traumatic brain injury (TBI) remains a critical global health issue with limited effective treatments. Traditional care of TBI patients focuses on stabilization and symptom management without regenerating damaged brain tissue. In this review, we analyze the current state of treatment of TBI, with focus on novel therapeutic approaches aimed at reducing secondary brain injury and promoting recovery. There are few innovative strategies that break away from the traditional, biological target-focused treatment approaches. Precision medicine includes personalized treatments based on biomarkers, genetics, advanced imaging, and artificial intelligence tools for prognosis and monitoring. Stem cell therapies are used to repair tissue, regulate immune responses, and support neural regeneration, with ongoing development in gene-enhanced approaches. Nanomedicine uses nanomaterials for targeted drug delivery, neuroprotection, and diagnostics by crossing the blood–brain barrier. Brain–machine interfaces enable brain-device communication to restore lost motor or neurological functions, while virtual rehabilitation and neuromodulation use virtual and augmented reality as well as brain stimulation techniques to improve rehabilitation outcomes. While these approaches show great potential, most are still in development and require more clinical testing to confirm safety and effectiveness. The future of TBI therapy looks promising, with innovative strategies likely to transform care. Full article

Advancements in immune monitoring and modulation technologies are driving transformative changes in cancer immunotherapy. These innovations are crucial for assessing patient-specific immune responses, enabling more accurate predictions of therapeutic efficacy and enhancing treatment outcomes. This review provides a comprehensive overview of current technologies used in immune monitoring, such as flow cytometry, single-cell RNA sequencing, and multiplex cytokine profiling. It also explores cutting-edge immune modulation methods, such as biomaterials that activate immune cells and genetically engineered cell-based therapies. We examine the strengths and limitations of these techniques and identify areas where further progress is needed. In particular, we explore how personalized therapies, real-time monitoring systems, and artificial intelligence shape the future of immune-based treatments. Through a comparative analysis of existing platforms and emerging solutions, this paper underscores the importance of integrating diverse scientific approaches—from immunology and bioengineering to data science—in advancing safer, more effective cancer treatments. This interdisciplinary approach promises to enhance the precision and accessibility of immune-based therapies, offering new hope for improved cancer care. Full article

Background/Objectives: Ovarian cancer is the most lethal gynecologic malignancy due to its late diagnosis, aggressive disease course, and high likelihood of recurrence. In the last few years, with the advent of high-throughput genomic methodologies, our understanding of ovarian cancer genetics and biology has grown. In this review, we discuss current monitoring techniques, as well as biomarker-directed therapies, recently developed for ovarian cancer treatment. Methods: The primary literature and review articles were obtained through PUBMED searches of “ovarian cancer”, “biomarkers”, “CA125”, “circulating tumor DNA”, “BRCA”, “HER2”, “TROP2”, and “FOLR1.” Results and Conclusions: The detection and quantification of CA125, a protein biomarker, remains the primary test used in the clinic for ovarian cancer diagnosis and monitoring. However, liquid biopsy techniques involving circulating tumor DNA, used alone or in combination with CA125, are increasingly used to enhance diagnostic accuracy and provide a more comprehensive picture of tumor genomic changes, including single-nucleotide variants, copy number variations, and epigenetic alterations. In the last few years, the use of BRCA, HER2, TROP2, and FOLR1 as biomarkers for targeted treatment has demonstrated promising results, both preclinically and clinically. The detection of BRCA1/2 mutations is routinely used as a strong predictor of response to PARP inhibitors, while HER2, TROP2, and FOLR1 expressions have emerged as primary targets for the treatment of recurrent ovarian cancer patients using novel antibody–drug conjugates (ADCs). Full article

Background/Objectives: AML is a heterogeneous hematological malignancy distinguished by the clonal expansion of immature myeloid progenitor cells. Despite advances in therapy, relapse rates remain high, and outcomes are poor. The WT1 gene has emerged as a potential contributor to leukemogenesis, but its clinical relevance at the transcriptional level is not fully understood. This study employed RNA sequencing as a discovery tool to identify WT1 gene expression in AML and further investigated its role in diagnosis, prognosis, and treatment response. Methods: Between 2020 and 2024, 345 diagnostic, 259 post-induction, and 70 relapse-stage BM or PB samples were prospectively collected from de novo AML patients at AIIMS, New Delhi. RNA sequencing was initially performed on five paired diagnosis-relapse samples to profile transcriptomic changes and assess WT1 expression dynamics. WT1 expression was further validated by qPCR. The relationship between WT1 expression and various clinical parameters was evaluated using Cox regression analysis to determine its impact on prognosis. Results: RNA sequencing and qPCR confirmed WT1 overexpression at diagnosis, which significantly declined following induction therapy. High WT1 expression at diagnosis was linked with adverse clinical characteristics, including elevated WBC counts and higher blast percentages and predicted poor survival outcomes. WT1 expression was identified as a significant prognostic marker, correlating with OS and EFS. Conclusions: By integrating RNA sequencing with targeted validation, this study highlights WT1 expression as a critical biomarker for AML diagnosis, prognosis, and treatment response. The findings suggest that WT1 expression may serve as a valuable tool for monitoring disease status, risk stratification, and guiding treatment decisions in AML, with potential applications for WT1-targeted precision therapies. Full article

Background/Objectives: Serum diagnostic tests for alopecia areata may be used to monitor response to treatment, aiding in the objective assessment of disease activity and helping to change treatment at an earlier point. Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy offers a nondestructive and user-friendly approach for analyzing a wide range of samples. In this study, we evaluated whether ATR-FTIR spectroscopy combined with machine learning can detect alopecia areata and quantify disease activity. We also established whether patient-specific spectral differences correlate with response to therapy, offering molecular insight into treatment response. Methods: Serum samples from 42 patients with alopecia areata and 41 healthy donors were compared. Logistic regression models were developed to separate alopecia areata patients from controls and to monitor treatment response based on clinical scoring. Results: Significant spectral variations were found in the 3000–2800 cm⁻¹ and 1800–1000 cm⁻¹ regions corresponding to the principal biochemical constituents such as proteins, lipids, carbohydrates, and nucleic acids. The AUC of the logistic regression model for distinguishing alopecia areata patients from healthy controls was 0.85 (95% CI: 0.75–0.94) with a sensitivity of 0.89 and a specificity of 0.71. In terms of prediction of treatment response, the model showed discriminative potential (AUC = 0.86, 95% CI: 0.71–0.98), with distinct alterations in the spectrum, particularly in the Amide I band, associated with improvement in the patient’s condition. Conclusions: ATR-FTIR spectroscopy assisted by machine learning offers a serum-based solution for treatment monitoring in alopecia areata patients with clinical applicability. This technique has highly promising potential for the development of rapid, non-invasive, and objective biomarkers in autoimmune dermatology. Additional multi-center trials are required to validate and incorporate these spectral biomarkers into individual treatment regimens. Full article

Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease characterised by systemic inflammation and the progressive damage of joints, significantly impacting patients’ quality of life. Managing this condition requires a complex approach that integrates pharmacological and non-pharmacological therapies, alongside psychosocial support and patient education. Aim: This study aims to highlight the importance of an interdisciplinary approach in the treatment of rheumatoid arthritis, focusing on the role of pharmacological therapies, monitoring treatment response, and the involvement of a multidisciplinary team in the effective management of the disease. Methods: The analysis was based on a review of the specialised literature concerning the role of disease-modifying antirheumatic drugs (DMARDs, both conventional and biological), the use of inflammatory markers (CRP and ESR), advanced imaging techniques, and the contribution of various medical specialities to the holistic management of rheumatoid arthritis. A total of 595,900 records were identified, of which 53 studies were ultimately included in the detailed analysis. Relevant studies from fields such as rheumatology, nutrition, psychology, and physical therapy were included. Results: The findings underline that DMARDs, in combination with other pharmacological therapies, remain essential for slowing disease progression. Monitoring treatment response through inflammatory markers and imaging techniques allows for the adjustment of therapeutic strategies and the prevention of complications. An interdisciplinary approach, involving the rheumatologist, general practitioner, physiotherapist, nutritionist, and psychologist, provides significant benefits, such as reducing inflammation, improving joint function, and offering psychosocial support. Conclusions: The effective management of rheumatoid arthritis requires a personalised interdisciplinary approach. Integrating various specialities, along with patient education and psychosocial support, contributes to better disease management, the prevention of disabilities, and improved quality of life. This review is not registered. Full article

Background/Objectives: Mild Cognitive Impairment (MCI) represents a clinical syndrome characterized by cognitive decline greater than expected for an individual’s age and education level but not severe enough to significantly interfere with daily activities, with variable trajectories that may remain stable, progress to dementia, or occasionally revert to normal cognition. This systematic review examines neurotechnological approaches to cognitive rehabilitation in MCI populations, including neuromodulation, electroencephalography (EEG), virtual reality (VR), cognitive training, physical exercise, and artificial intelligence (AI) applications. Methods: A systematic review following PRISMA guidelines was conducted on 34 empirical studies published between 2014 and 2024. Studies were identified through comprehensive database searches and included if they employed neurotechnological interventions targeting cognitive outcomes in individuals with MCI. Results: Evidence indicates promising outcomes across multiple intervention types. Neuromodulation techniques showed beneficial effects on memory and executive function. EEG analyses identified characteristic neurophysiological markers of MCI with potential for early detection and monitoring. Virtual reality enhanced assessment sensitivity and rehabilitation engagement through ecologically valid environments. Cognitive training demonstrated the most excellent efficacy with multi-domain, adaptive approaches. Physical exercise interventions yielded improvements through multiple neurobiological pathways. Emerging AI applications showed potential for personalized assessment and intervention through predictive modeling and adaptive algorithms. Conclusions: Neurotechnological approaches offer promising avenues for MCI rehabilitation, with the most substantial evidence for integrated interventions targeting multiple mechanisms. Neurophysiological monitoring provides valuable biomarkers for diagnosis and treatment response. Future research should focus on more extensive clinical trials, standardized protocols, and accessible implementation models to translate these technological advances into clinical practice. Full article

Background and Objectives: Neuropsychiatric disorders, including schizophrenia, bipolar disorder, and major depression, constitute a leading global public health challenge due to their high prevalence, chronicity, and profound cognitive and functional impact. This systematic review explores the role of electroencephalography (EEG)-based cognitive biomarkers in improving the understanding, diagnosis, monitoring, and treatment of these conditions. It evaluates how EEG-derived markers can reflect neuro-cognitive dysfunction and inform personalized and scalable mental health interventions. Materials and Methods: A systematic review was conducted following PRISMA guidelines. The databases searched included PubMed, Scopus, PsycINFO, and Web of Science for peer-reviewed empirical studies published between 2014 and 2025. Inclusion criteria focused on EEG-based investigations in clinical populations with neuropsychiatric diagnoses, emphasizing studies that assessed associations with cognitive function, symptom severity, treatment response, or functional outcomes. Of the 447 initially identified records, 132 studies were included in the final synthesis. Results: This review identifies several EEG markers—such as mismatch negativity (MMN), P300, frontal alpha asymmetry, and theta/beta ratios—as reliable indicators of cognitive impairments across psychiatric populations. These biomarkers are associated with deficits in attention, memory, and executive functioning, and show predictive utility for treatment outcomes and disease progression. Methodological trends indicate an increasing use of machine learning and multimodal neuroimaging integration to enhance diagnostic specificity. While many studies exhibit moderate risk of bias, the overall findings support EEG biomarkers’ reproducibility and translational relevance. Conclusions: EEG-based cognitive biomarkers offer a valuable, non-invasive means of capturing the neurobiological underpinnings of psychiatric disorders. Their diagnostic and prognostic potential, as well as high temporal resolution and portability, supports their use in clinical and public health contexts. The field, however, requires further standardization, cross-validation, and investment in scalable applications. Advancing EEG biomarker research holds promise for precision psychiatry and proactive mental health strategies at the population level. Full article