Search Results (313)

Background: Transcranial direct current stimulation (tDCS) has emerged as a promising neuromodulatory tool for language rehabilitation in chronic aphasia. However, the effects of bi-hemispheric, multisite stimulation remain largely unexplored, especially in people with chronic and treatment-resistant language impairments. The goal of this study is to look at the effects on behavior and brain activity of an individualized language training program that combines bi-hemispheric multisite anodal tDCS with personalized language training for Albert, a patient with long-standing, treatment-resistant non-fluent aphasia. Methods: Albert, a right-handed retired physician, had transcortical motor aphasia (TCMA) subsequent to a left-hemispheric ischemic stroke occurring more than six years before the operation. Even after years of traditional treatment, his expressive and receptive language deficits remained severe and persistent despite multiple rounds of traditional therapy. He had 15 sessions of bi-hemispheric multisite anodal tDCS aimed at bilateral dorsal language streams, administered simultaneously with language training customized to address his particular phonological and syntactic deficiencies. Psycholinguistic evaluations were performed at baseline, immediately following the intervention, and at 1, 2, 3, and 6 months post-intervention. Resting-state fMRI was conducted at baseline and following the intervention to evaluate alterations in functional connectivity (FC). Results: We noted statistically significant enhancements in auditory sentence comprehension and oral reading, particularly at the 1- and 3-month follow-ups. Neuroimaging showed decreased functional connectivity (FC) in the left inferior frontal and precentral regions (dorsal stream) and in maladaptive right superior temporal regions, alongside increased FC in left superior temporal areas (ventral stream). This pattern suggests that language networks may be reorganizing in a more efficient way. There was no significant improvement in phonological processing, which may indicate reduced connectivity in the left inferior frontal areas. Conclusions: This case underscores the potential of combining individualized, network-targeted language training with bi-hemispheric multisite tDCS to enhance recovery in chronic, treatment-resistant aphasia. The convergence of behavioral gains and neuroplasticity highlights the importance of precision neuromodulation approaches. However, findings are preliminary and warrant further validation through controlled studies to establish broader efficacy and sustainability of outcomes. Full article

Some children with autism may require additional support to meet academic expectations for comprehension. Because an extensive set of research links oral narration to listening and reading comprehension, the promotion of narrative-based skills may be a viable intervention approach. The purpose of this study was to examine the effect of narrative intervention with explicit strategy instruction on the listening and reading retells of children with autism after hearing and decoding novel stories. Four children with autism aged 7 and 9 years old participated in this multiple baseline across participants single-case experimental design study. Behavioral therapists delivered the narrative intervention, which included explicit instruction on the use of story grammar icons, to each child individually within the course of their therapy. Results showed that all participants improved their listening (TauU ES range = 0.64–1.06) and reading (TauU ES range = 0.72–1.15) retells, but they required extended use of the icon strategy to achieve the most benefit. When icons were completely removed, three of the four participants performed above baseline levels on the listening and reading comprehension measures. Full article

Spinal muscular atrophy (SMA) is a fatal motor neuron disease characterized by five clinical subtypes, each presenting with different rates of disease progression and varying responses to recently approved therapies. The identification of reliable biomarkers is essential for improving diagnosis and prognosis, monitoring disease progression, enabling personalized treatment strategies, and evaluating therapeutic responses. In this review, we conducted a comprehensive literature search using PubMed and Web of Science with the keywords “spinal muscular atrophy”, “biomarker” and advanced technologies such as “single-cell omics”, “nanopore and long-read sequencing” and “epigenetics” to identify and summarize current advances in SMA biomarker discovery and application. We begin with a brief overview of SMA and its current treatment barriers. We then conclude with well-established and emerging molecular and non-molecular biomarkers, followed by a conclusion of emerging technologies in biomarker discovery. In the meantime, we highlight the application of biomarkers in key areas, including early diagnosis and disease stratification, monitoring of disease progression, and prediction of treatment response. Finally, we summarize biomarker-targeted therapies, addressing current challenges in biomarker research, with the goal of improving clinical outcomes for patients with SMA. Full article

Background: Hypotension following epidural labor analgesia (ELA) is its most common complication, affecting approximately 20% of patients and posing risks to both maternal and fetal health. As digital tools and predictive analytics increasingly shape perioperative and obstetric anesthesia practices, real-world implementation data are needed to guide their integration into clinical care. Current monitoring practices rely on intermittent non-invasive blood pressure (NIBP) measurements, which may delay recognition and treatment of hypotension. The Hypotension Prediction Index (HPI) algorithm uses continuous arterial waveform monitoring to predict hypotension for potentially earlier intervention. This clinical trial evaluated the feasibility, acceptability, and efficacy of continuous HPI-guided treatment in reducing time-to-treatment for ELA-associated hypotension and improving maternal hemodynamics. Methods: This was a prospective randomized controlled trial design involving healthy pregnant individuals receiving ELA. Participants were randomized into two groups: Group CM (conventional monitoring with NIBP) and Group HPI (continuous noninvasive blood pressure monitoring). In Group HPI, hypotension treatment was guided by HPI output; in Group CM, treatment was based on NIBP readings. Feasibility, appropriateness, and acceptability outcomes were assessed among subjects and their bedside nurse using the Acceptability of Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), and Feasibility of Intervention Measure (FIM) instruments. The primary efficacy outcome was time-to-treatment of hypotension, defined as the duration between onset of hypotension and administration of a vasopressor or fluid therapy. This outcome was chosen to evaluate the clinical responsiveness enabled by HPI monitoring. Hypotension is defined as a mean arterial pressure (MAP) < 65 mmHg for more than 1 min in Group CM and an HPI threshold < 75 for more than 1 min in Group HPI. Secondary outcomes included total time in hypotension, vasopressor doses, and hemodynamic parameters. Results: There were 30 patients (Group HPI, n = 16; Group CM, n = 14) included in the final analysis. Subjects and clinicians alike rated the acceptability, appropriateness, and feasibility of the continuous monitoring device highly, with median scores ≥ 4 across all domains, indicating favorable perceptions of the intervention. The cumulative probability of time-to-treatment of hypotension was lower by 75 min after ELA initiation in Group HPI (65%) than Group CM (71%), although this difference was not statistically significant (log-rank p = 0.66). Mixed models indicated trends that Group HPI had higher cardiac output (β = 0.58, 95% confidence interval −0.18 to 1.34, p = 0.13) and lower systemic vascular resistance (β = −97.22, 95% confidence interval −200.84 to 6.40, p = 0.07) throughout the monitoring period. No differences were found in total vasopressor use or intravenous fluid administration. Conclusions: Continuous monitoring and precision hypotension treatment is feasible, appropriate, and acceptable to both patients and clinicians in a labor and delivery setting. These hypothesis-generating results support that HPI-guided treatment may be associated with hemodynamic trends that warrant further investigation to determine definitive efficacy in labor analgesia contexts. Full article

Contemporary phonetics and speech therapy continuously seek new techniques and methods that could contribute to improving verbal communication for individuals with speech disorders. One such phenomenon, Delayed Auditory Feedback (DAF), involves the speaker hearing their own voice with a specific delay relative to real-time speech. Although the research presented in this study was conducted on healthy individuals, it offers valuable insights into the mechanisms controlling speech, which may also apply to individuals with speech disorders. This article introduces a novel method and measurement setup, focusing on selected key speech signal parameters. To characterize the impact of Delayed Auditory Feedback (DAF) on fluent speakers, speech signal parameters were measured in 5 women and 5 men during spontaneous speech and reading. Parameters such as speech rate, fundamental frequency, formants, speech duration, jitter, and shimmer were analyzed both during and prior to the application of DAF. The results of this study may find practical applications in the field of telecommunications, especially in improving the efficiency and quality of human communication. Full article

Background: This retrospective, multi-reader, blinded, pivotal trial assessed the performance of artificial intelligence (AI)-based clinical decision support system used to improve the clinician detection of emergent large vessel occlusion (ELVO) using brain non-contrast computed tomography (NCCT) images. Methods: We enrolled 477 patients, of which 112 had anterior circulation ELVO, and 365 served as controls. First, patients were evaluated by the consensus of four clinicians without AI assistance through the identification of ELVO using NCCT images. After a 2-week washout period, the same investigators performed an AI-assisted evaluation. The primary and secondary endpoints in ELVO prediction between unassisted and assisted readings were sensitivity and specificity and AUROC and individual-level sensitivity and specificity, respectively. The standalone predictive ability of the AI system was also analyzed. Results: The assisted evaluations resulted in higher sensitivity and specificity than the unassisted evaluations at 75.9% vs. 92.0% (p < 0.01) and 83.0% vs. 92.6% (p < 0.01) while also resulting in higher accuracy and AUROC at 81.3% vs. 92.5%, (p < 0.01) and 0.87 [95% CI: 0.84–0.90] vs. 0.95 [95% CI: 0.93–0.97] (p < 0.01). Furthermore, the AI system improved sensitivity and specificity for three and four readers, respectively, and had a standalone sensitivity of 88.4% (95% CI: 81.0–93.7) and a specificity of 91.2% (95% CI: 87.9–93.9). Conclusions: This study shows that an AI-based clinical decision support system can improve the clinical detection of ELVO using NCCT. Moreover, the AI system may facilitate acute stroke reperfusion therapy by assisting physicians in the initial triaging of patients, particularly in thrombectomy-incapable centers. Full article

The integration of artificial intelligence (AI) into next-generation sequencing (NGS) has revolutionized genomics, offering unprecedented advancements in data analysis, accuracy, and scalability. This review explores the synergistic relationship between AI and NGS, highlighting its transformative impact across genomic research and clinical applications. AI-driven tools, including machine learning and deep learning, enhance every aspect of NGS workflows—from experimental design and wet-lab automation to bioinformatics analysis of the generated raw data. Key applications of AI integration in NGS include variant calling, epigenomic profiling, transcriptomics, and single-cell sequencing, where AI models such as CNNs, RNNs, and hybrid architectures outperform traditional methods. In cancer research, AI enables precise tumor subtyping, biomarker discovery, and personalized therapy prediction, while in drug discovery, it accelerates target identification and repurposing. Despite these advancements, challenges persist, including data heterogeneity, model interpretability, and ethical concerns. This review also discusses the emerging role of AI in third-generation sequencing (TGS), addressing long-read-specific challenges, like fast and accurate basecalling, as well as epigenetic modification detection. Future directions should focus on implementing federated learning to address data privacy, advancing interpretable AI to improve clinical trust and developing unified frameworks for seamless integration of multi-modal omics data. By fostering interdisciplinary collaboration, AI promises to unlock new frontiers in precision medicine, making genomic insights more actionable and scalable. Full article

Background: Advances in the treatment of type 2 diabetes (T2D) in recent decades have been primarily focused on its broader understanding in the context of the possibility of preventing the development and progression of the disease and of cardiovascular (CV) complications. Nevertheless, worldwide research indicates that individuals with T2D are still under-regulated, both in terms of glycemic control and in preventing CV complications. The aim of this study was to examine Croatian general practitioners (GPs)’ practice and patterns in prescribing antidiabetic medications and their understanding of guidelines. Methods: Research was conducted using a self-designed anonymous survey, which was delivered to the e-mail addresses of GPs throughout Croatia in digital format. Respondents were solely GPs, without any restrictions with regard to their characteristics. Data on the number of individuals diagnosed with T2D and prescribed a specific medication were based on declarations by respondents from their e-health records. Results: Approximately 59% of individuals with T2D are cared for solely by GPs. In terms of achieving targeted values of HbA1c, 47% of individuals with T2D are well regulated. Almost all the respondents claim that they review prescribed T2D therapy at least once a year. A total of 47.6% of respondents have read and entirely understood the EASD/ADA guidelines, but 58.3% apply the dual principles of controlling HbA1c levels and CV risk in the treatment of T2D. In individuals with associated CV comorbidity, SGLT2ins were the most frequently prescribed. Conclusions: The results indicate that Croatian GPs are still inclined to apply outdated paradigms of T2D treatment but that they are gradually accepting new regimens of care and recommendations for prescribing novel, more effective medications. Full article

Background/Objectives: Patients with New York Heart Association (NYHA) class III heart failure (HF) suffer from frequent hospitalizations. Non-invasive pulmonary artery pressure (PAP) sensor-guided HF care has been shown to reduce hospitalizations. However, it is unknown whether the PAP changes prior to hospitalization differ between clinical right, left or global cardiac decompensation. Methods: Sensor-derived PAP data and HF hospitalization records from 41 patients with NYHA class III HF were classified retrospectively into predominantly left, right or global decompensation. Linear mixed-effect regression models were used for statistical evaluations of the PAP in selected hospitalizations for which admission was at least 28 days after the last admission and 14 days after the last hospital discharge and with readings in between. Results: During 24.4 months of follow-up, 127 hospitalizations in 38 patients were evaluated. The global cardiac decompensation (n = 13) had the highest PAP before hospitalization, followed by left-sided (n = 20) decompensation. Patients with right-sided decompensation (n = 9) had comparable PAP values before hospitalization to the cohort without any cardiac decompensation (n = 85). The diastolic PAP showed a significant increase of 0.035 mmHg/day (p = 0.0097) in left-sided decompensation and of 0.13 mmHg/day (p < 0.0001) in global cardiac decompensation, whereas no significant change in the diastolic PAP occurred prior to the right-sided decompensation. The baseline right ventricular function and right ventricle–pulmonary arterial coupling (TAPSE/PASP ratio) were impaired in patients with subsequent global cardiac decompensation. Conclusion: PAP telemonitoring-guided therapy can reliably detect early signs of left and global cardiac decompensation but may be limited in detecting right-sided cardiac congestion. The routine assessment of RV–PA coupling may improve the detection of global cardiac decompensation, as severe impairments could indicate impending deterioration. In contrast, monitoring the RV contractility may aid in identifying isolated right-sided congestion and imminent decompensation. Full article

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive loss of upper and lower motor neurons, leading to muscle weakness, paralysis, and ultimately respiratory failure. Despite advances in understanding its genetic basis, particularly mutations in Chromosome 9 Open Reading Frame 72 (C9orf72), superoxide dismutase 1 (SOD1), TAR DNA-binding protein (TARDBP), and Fused in Sarcoma (FUS) gene, current diagnostic methods result in delayed intervention, and available treatments offer only modest benefits. This review examines innovative approaches transforming ALS research and clinical management. We explore emerging biomarkers, including the fluid-based markers such as neurofilament light chain, exosomes, and microRNAs in biological fluids, alongside the non-fluid-based biomarkers, including neuroimaging and electrophysiological markers, for early diagnosis and patient stratification. The integration of multi-omics data reveals complex molecular mechanisms underlying ALS heterogeneity, potentially identifying novel therapeutic targets. We highlight current gene therapy strategies, including antisense oligonucleotides (ASOs), RNA interference (RNAi), and CRISPR/Cas9 gene editing systems, alongside advanced delivery methods for crossing the blood–brain barrier. By bridging molecular neuroscience with bioengineering, these technologies promise to revolutionize ALS diagnosis and treatment, advancing toward truly disease-modifying interventions for this previously intractable condition. Full article

Background: Colorectal cancer (CRC) remains one of the most prevalent and fatal malignancies globally, with radiotherapy playing a crucial role in the treatment of locally advanced rectal cancer (LARC). However, the efficacy of radiotherapy is limited by significant resistance, with only a small proportion of patients achieving a pathologic complete response (PCR) to neoadjuvant chemoradiotherapy (nCRT). This study aims to uncover the genetic and molecular factors contributing to radiotherapy resistance in CRC through an integrated analysis of germline mutations, transcriptomic data, and immune microenvironment characteristics. Methods: Whole-exome sequencing (WES) was performed on tumor samples from 12 LARC patients. Transcriptomic data from the TCGA-READ and GSE150082 (LARC with chemoradiotherapy) cohorts were integrated with WES findings. The independent cohort GSE190826 (neoadjuvant therapy in rectal cancer) dataset was utilized to validate the WES data. Single-cell RNA sequencing (scRNA-seq) analysis of GSE132465 (primary CRC) resolved cellular heterogeneity. A random forest algorithm was employed to develop a predictive gene signature. Results: Our findings reveal a mutational landscape associated with radiotherapy resistance, identifying specific germline mutations linked to treatment outcomes. Differential gene expression analysis highlighted pathways involved in DNA replication, DNA repair, and immune regulation, with a focus on the tumor immune microenvironment (TIME). A gene signature, including CDCA4, FANCA, PBRM1, RPL13, and C12orf43, was developed to predict radiotherapy response. Notably, CDCA4 expression was significantly associated with tumor mutation burden (TMB) and microsatellite instability (MSI), and it plays a crucial role in regulating B cell infiltration in the tumor microenvironment. Conclusions: Our study provides novel insights into the molecular mechanisms of radiotherapy resistance in CRC and proposes CDCA4 and B cell-related immune features as potential biomarkers for patient stratification and personalized treatment strategies. Full article

Metabolism is a complex network of biochemical pathways that break down macromolecules to produce energy essential for cellular function. Disruptions in metabolic homeostasis are closely linked to noncommunicable diseases (NCDs) such as cardiovascular disease, type 2 diabetes, and cancer, which are leading causes of death worldwide. Many NCD-associated conditions, including obesity and insulin resistance, stem from metabolic dysfunction, and current therapies often fall short in preventing disease progression, highlighting the need for novel therapeutic targets. Microproteins, small proteins of ≤100–150 amino acids, have recently emerged as important regulators of metabolism. Encoded by short open reading frames (sORFs), many of these proteins were historically overlooked due to their small size and misclassification as noncoding RNAs. Advances in genomics and proteomics have revealed that these sORFs can encode functional proteins with critical roles in metabolic pathways. In this review, we highlight the microproteins involved in energy metabolism, mitochondrial function, and nutrient signaling. We discuss their emerging roles in the pathogenesis of NCDs and explore their potential as novel therapeutic targets. As microprotein biology continues to evolve, these small but powerful regulators may offer new strategies for treating metabolic dysfunction and reducing the global burden of NCDs. Full article

Allergic diseases share a type 2 immune reaction and elevated oxidative stress, contributing to disease pathogenesis and exacerbations. Vitamin C (ascorbic acid), a fundamental exogenous antioxidant, has been hypothesized to attenuate these pathological mechanisms. This narrative review critically examined the most recent evidence concerning the role of vitamin C in preventing and managing allergic diseases, including asthma, allergic rhinitis, and atopic dermatitis. This narrative review consisted of three steps: conducting the search, reviewing abstracts and full texts, and discussing results. For this reason, we consulted the PubMed database to detect the pertinence of studies according to the review’s conduct. The final search ended in March 2025 and included English-language-based international articles, online reports, and electronic books. The keywords “vitamin C and allergic disease” and “vitamin C and immune system” were used. After the complete search, we read the abstracts to ensure that they concerned the topic of interest. Recent evidence suggests a protective role for vitamin C in asthma, with several studies reporting reduced oxidative stress markers, improved lung function, and decreased airway inflammation following regular intake or supplementation. Higher dietary vitamin C intake correlates with lower asthma prevalence and severity, particularly in pediatric populations. Conversely, the findings regarding allergic rhinitis and atopic dermatitis are heterogeneous. While topical ascorbic acid derivatives show promise in atopic dermatitis models, oral vitamin C intake does not appear to affect allergic rhinitis or dermatitis risk significantly. Vitamin C demonstrates potential as an add-on therapy in asthma management by attenuating oxidative stress and type 2 respiratory inflammation. However, its role in allergic rhinitis and atopic dermatitis remains less clear. Further multicentric, well-designed clinical trials are necessary to establish definitive guidelines for vitamin C supplementation in allergic disease management. Full article

Objectives: The primary objective of this review is to analyze the effects on body weight of discontinuing therapy with glucagon-like peptide-1 receptor agonists (GLP-1 RAs) or tirzepatide in patients treated for obesity. In recent months, there has been a considerable increase in the utilization of GLP-1 RAs and GIP/GLP-1 RAs. However, the paucity of available data regarding their medium- to long-term safety remains a salient concern. Of particular significance is the observation of the weight curve following their suspension, a subject that has received scant attention to date. Methods: For this, a bibliographic search was carried out in three electronic databases: PubMed, Cochrane Library and Google Scholar. The following filters were applied: in the last 10 years, Randomized Controlled Trial, Adult: 19+ years. The review was restricted to randomized controlled trials to reduce bias and ensure the high quality of the studies examined. A total of 427 references were identified, 178 articles were read in full, and 13 articles were included in the analysis. Results and Conclusions: The analysis showed a rapid regain of weight after cessation of therapy, regardless of the duration of the treatment with GLP-1 RA or GIP/GLP-1 RA. This rebound is likely to substantially mitigate the metabolic benefits attained through weight loss. Given the efficacy of these drugs, it is essential for future research to focus on elucidating the optimal duration of these treatments or identifying techniques or schemes that involve a reduction in dosages to prevent weight regain. Full article

CLN2 disease (neuronal ceroid lipofuscinosis type 2) is an ultra-rare lysosomal storage disorder caused by mutations in the TPP1/CLN2 gene, resulting in impaired tripeptidyl peptidase 1 (TPP1) activity. The timely initiation of enzyme replacement therapy is pivotal for attenuating progressive and irreversible neurodegeneration. This study aimed to benchmark the performance of Oxford Nanopore long-read sequencing (ONT-LRS) for targeted TPP1 mutation detection in a Turkish CLN2 cohort and to assess its concordance with orthogonal validation methods, including Sanger sequencing and enzymatic activity assays. Using a custom-designed primer panel, the entire TPP1 gene (6846 bp) was sequenced on the Oxford Nanopore (ONT) MinIon platform in seven clinically confirmed CLN2 index patients and sixteen unaffected family members. Detected variants were validated via Sanger sequencing and correlated with TPP1 enzyme activity in leucocytes and dried blood spots. Four pathogenic or likely pathogenic TPP1 variants were identified: c.622C>T (p.Arg208*), c.857A>G (p.Asn286Ser), c.1204G>T (p.Glu402*), and c.225A>G (p.Gln75=), along with fourteen additional benign variants. Variant allele frequencies were 50% for c.622C>T, 28.6% for c.1204G>T, 14.3% for c.857A>G, and 7.1% for c.225A>G. Notably, this is the first report to document the homozygous state of the c.857A>G variant and the compound heterozygous configuration of the c225A>G and c.622C>T variants in CLN2 patients, thereby expanding the known mutational landscape. In contrast, the globally common variant c.509-1G>C was not observed, suggesting regional variation in TPP1 mutation patterns. Consistent with the prior Turkish studies, c.622C>T (p.Arg208*) was the most prevalent variant, followed by c.1204G>T (p.Glu402*). TPP1 enzymatic activity was significantly reduced in all affected individuals (p < 0.0001), supporting the functional relevance of the identified variants. ONT-LRS offers a robust, cost-effective platform for high-resolution analysis of the TPP1 gene. Integrating molecular and biochemical data improves diagnostic precision and supports timely, targeted interventions for CLN2 disease, particularly in regions with high consanguinity and limited diagnostic infrastructure. Full article