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PubMed2026

Hierarchical modeling of tumor subtypes in cell lines using large-scale genomic datasets.

Cancer cell lines (CLs) are widely used to study tumor biology and drug response, yet their translational relevance is often limited by inaccurate subtype annotations. Existing CL-tumor matching approaches are frequently constrained by flat classification schemes, weak subtype definitions, and the exclusion of normal tissue references, leading to potential confounding of tumor-specific and tissue-of-origin signals. To address these limitations, a hierarchical classification (HC) framework is presented in which CLs are aligned with patient tumors across biological resolutions, from organ to molecular subtype. Gene expression profiles from 802 CLs, 5,612 tumors from The Cancer Genome Atlas (TCGA) , and 8,939 non-cancerous tissues were integrated to separate oncogenic signals from tissue-specific signals. Node-specific features were selected using maximum relevance minimum redundancy, and balanced accuracies of 89% in cross-validation and 75%, and 80% on external datasets were achieved. Through the framework, 43 CLs were reassigned, and clinically relevant underrepresented subtypes were identified.

cancer cell lines↗

PubMed2026

Integrated transcriptomic and metabolomic analysis of fluoride tolerance-related pathways and differentially expressed genes in silkworm strain XSKD.

XueSong KD (XSKD) silkworm strain exhibits prominent fluoride tolerance, yet the underlying molecular mechanisms of fluoride tolerance remains unclear. In the present study, fourth-instar pre-molting XSKD silkworms were used as experimental materials for integrated transcriptomic and untargeted metabolomic analyses. In total, 572 differentially expressed genes and 90 differential metabolites were screened. GO enrichment and KEGG enrichment based on the hypergeometric distribution model revealed that 13-Hydroxy-9Z,11E-octadecadienoic acid (13-(S)-HODE) acts as the core differential metabolite, which is significantly enriched in the linoleic acid metabolism pathway. Within this pathway, LOC101737302 and CYP338A1 display opposite expression trends and show correlations with pathway metabolites. Based on multi-omics data, this study preliminarily characterizes the lipid metabolic response under fluoride stress, providing omics dataset support for further in-depth exploration of the molecular mechanism of fluoride tolerance in silkworms.

Animals↗

PubMed2026

The science of Arabic coffee (Qahwa): from phytochemistry and nutritional profile to health benefits and safety evaluation.

Arabic coffee (Qahwa), a traditional beverage widely consumed in the Middle East, has attracted increasing scientific attention due to its distinctive phytochemical composition and associated health effects. This review provides an integrated analysis of Qahwa's nutritional profile, focusing on its key bioactive constituents, including chlorogenic acids, caffeine, diterpenes (cafestol and kahweol), and phenolic compounds. These constituents contribute to a range of biological activities, notably antioxidant, anti-inflammatory, hepatoprotective, and metabolic regulatory effects. The influence of technological variables, including roasting degree, brewing method, and bean origin, on the chemical composition and functional properties is critically examined. Safety concerns, particularly acrylamide formation and mycotoxin contamination, are also discussed. Although emerging data support Qahwa's potential as a functional beverage, further research is required to clarify dose-response relationships, synergistic interactions, and long-term health outcomes. This work highlights Qahwa as a promising candidate for food and nutraceutical applications, warranting standardized compositional profiling and toxicological evaluation.

Humans↗

PubMed2026

Modelling the effects of biological intervention in a dynamical gene network.

Cellular response to environmental and internal signals can be modeled by dynamical gene regulatory networks (GRN). In the literature, three main classes of gene network models can be distinguished: (1) non-quantitative (or data-based) models which do not describe the probability distribution of gene expressions; (2) quantitative models which fully describe the probability distribution of all genes co-expression; and (3) mechanistic models which allow for a causal interpretation of gene interactions. We propose two rigorous frameworks to model gene alteration in a dynamical GRN, depending on whether the network model is quantitative or mechanistic. We explain how these models can be used for design of experiment, or, if additional alteration data are available, for validation purposes or to improve the parameter estimation of the original model. We apply these methods to the Gaussian graphical model, which is quantitative but non-mechanistic, and to mechanistic models of Bayesian networks and penalized linear regression.

Gene Regulatory Networks↗

PubMed2026

Your story, your brand: A career core competency for nurses.

Intentional management of one's professional story, or narrative discipline , is now a core competency and responsibility for nurses at all career stages. Workforce mobility, interdisciplinary collaboration, broadening career opportunities, and the expansion of digital platforms have elevated the importance of how nurses are perceived by colleagues, organizations, and the public. Increasingly, a nurse's professional story and digital footprint influence professional opportunities, career advancement, and even employment decisions.Many companies invest heavily in brand management to build trust and emotional connection with the people they serve. Importantly, narrative discipline also contributes directly to healthy work environments by reinforcing trust, role clarity, respect, and psychological safety. Drawing from leadership practice, emerging research on nurses' social media use, healthy work environment principles, and guidance from national nurse leadership organizations, this article outlines how nurses can align personal, professional, and enterprise identities; use language deliberately; and engage with discipline and integrity. Practical strategies are provided to help nurses move from passive narrative formation to intentional storytelling that supports career development, workforce engagement, organizational trust, and the sustainability of the nursing profession.

Humans↗

PubMed2026

Multi‑omics approaches to decipher the molecular mechanisms of exercise‑mediated bone protection: From mechanistic insights to personalized exercise prescription (Review).

The global burden of bone metabolic disorders necessitates a shift from generic exercise recommendations toward personalized prescription strategies. Exercise confers skeletal protection through mechanotransduction, yet the underlying molecular networks remain incompletely understood. Multi‑omics technologies, including transcriptomics, proteomics, metabolomics and single‑cell spatial approaches, have revolutionized the capacity to decode exercise‑mediated bone adaptation at the systems level. The present review synthesizes current single‑omics landscapes and integrative multi‑omics analyses that elucidate the core regulatory networks, mechanobiological coupling mechanisms and multiorgan crosstalk that are implicated in the bone response to mechanical loading. Translational applications across clinical scenarios such as osteoporosis, osteoarthritis and disuse bone loss are evaluated, and the technical, analytical and translational challenges limiting clinical implementation are addressed. Finally, the present review provides a framework for translating multi‑omics molecular signatures into personalized exercise prescriptions for optimized skeletal health.

Humans↗

PubMed2026

Molecular mechanisms of natural de novo shoot organogenesis and their applications.

Natural de novo shoot organogenesis (DNSO) is the spontaneous regeneration of shoots from wound sites outside the shoot apical region through endogenous developmental programs. This regenerative capacity enables plants to recover from severe tissue damage by re-establishing the shoot-root axis. Here, we review current knowledge about the molecular mechanisms of natural DNSO, focusing on transcriptomic and physiological studies in model plants. Accumulating evidence suggests that natural DNSO proceeds through three sequential phases: (i) early wound responses, characterized by the activation of the WIND1-ESR1 module and the establishment of apical-basal auxin asymmetry; (ii) cellular proliferation driven by metabolic and cell-cycle reprogramming; and (iii) cytokinin-mediated establishment of shoot apical meristem identity. We also discuss how these mechanistic insights have been harnessed for practical applications, including tissue culture-free transformation systems such as the cut-dip-budding (CDB) method, and developmental reprogramming strategies that employ ectopic expression of developmental regulator (DR) genes to induce DNSO in otherwise recalcitrant species. Together, these advances illustrate how understanding natural regeneration can guide the development of simplified, broadly applicable plant transformation technologies.

Plant Shoots↗

PubMed2026

Final-year nursing students' clinical practice experiences: a reflection study.

OBJECTIVES: This study aimed to explore the most impactful clinical practice experiences of final-year nursing students and the future-oriented actions developed in response to these experiences. METHODS: A retrospective descriptive qualitative design was used. Following reflection training in the internship practice course, 134 final-year nursing students were asked to describe the experience that affected them most during clinical practice. A total of 123 written reflections were analyzed using content analysis. RESULTS: Three themes emerged: near-miss events, incivility behaviors, and positive preceptoring roles. Negative experiences were mainly related to patients, relatives, and nurses and often led students to feel fear and inadequacy. Students reported action plans focused on effective communication, safe patient care, and becoming positive role models. CONCLUSIONS: These findings highlight the importance of supportive clinical learning environments and positive professional socialization during the transition from student to nurse. IMPLICATIONS FOR INTERNATIONAL AUDIENCE: Nursing students worldwide may encounter incivility and near-miss events during clinical practice, potentially adversely affecting their learning experiences and professional development.

Humans↗

PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗

PubMed2026

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence↗

PubMed2026

Teaching Acute Coronary Syndrome High-Risk ECG Interpretation and Clinical Decision-Making Through FOAMed Videos and Podcast Versus Print-Based Materials Among Emergency Care Providers: Randomized Controlled Mixed Methods Trial.

BACKGROUND: Accurate interpretation of high-risk acute coronary syndrome (ACS) electrocardiograms (ECGs) is essential for early diagnosis and timely reperfusion, yet substantial deficits persist across health care professions. Digital self-learning formats such as FOAMed (Free Open Access Medical Education) are widely used, but their effectiveness has rarely been evaluated for complex, high-risk ACS ECG patterns. Existing ECG education studies often focus on students or single professional groups and established ST-segment elevation myocardial infarction (STEMI) criteria, leaving newer guideline-recognized STEMI equivalents, selected emerging occlusion myocardial infarction (OMI)-related patterns, and interprofessional emergency care underrepresented. OBJECTIVE: This study aimed to compare the effectiveness of FOAMed podcast and videos versus traditional print-based materials for teaching high-risk ACS ECG patterns and related clinical decision-making in emergency providers. METHODS: We conducted a prospective, interprofessional, controlled mixed methods trial across 5 training sites in Germany. Paramedics, prehospital emergency physicians, and emergency department clinicians received either a FOAMed multimedia module or print-based materials through concealed allocation; deviations from the intended 1:1 ratio resulted from participant no-shows. The intervention consisted of a 30-minute supervised self-learning session. In total, 103 participants were allocated to FOAMed (n=45) or print-based materials (n=58). Two coprimary outcomes were assessed: ECG interpretation accuracy and text-based ACS clinical decision-making. Secondary outcomes included subjective confidence, learning experience, and exploratory qualitative free-text responses. Outcome assessment was automated and blinded; mixed ANOVA was the primary analysis. The study was not prospectively registered because it assessed educational outcomes in health care professionals rather than patient health outcomes. RESULTS: All 103 participants completed the study. Both groups improved, with greater gains in the FOAMed group: ECG interpretation increased from 55% to 65.5% and text-based ACS clinical decision-making from 45% to 68%, versus 57% to 60% and from 47% to 63%, respectively, in the print-based group. Effect sizes were η²=0.055 for ECG interpretation and η²=0.044 for clinical decision-making. Exploratory subgroup analyses provided no evidence of differential effects across age, gender, or professional background and were likely underpowered. Qualitative responses (46 and 37 entries) provided contextual insights into perceived clarity, engagement, and practical relevance supporting the quantitative findings. CONCLUSIONS: This study is innovative in directly comparing a curated FOAMed multimedia module with selected print-based materials in an interprofessional emergency care population. It differs from existing research by focusing on subtle, emerging ischemic patterns and evaluating realistic, time-limited self-learning formats. The findings provide evidence that curated FOAMed resources can produce greater short-term improvements in ECG interpretation and text-based ACS clinical decision-making than traditional print-based materials in this setting. Although implications for clinical performance remain hypothetical, concise, high-quality digital modules may represent a practical supplement to structured continuing education in emergency care.

Humans↗

PubMed2026

Transcriptomic insights into the molecular mechanism of antifouling agent-induced settlement inhibition in the Pacific oyster Crassostrea gigas.

Marine biofouling remains a persistent challenge to maritime industries and marine ecosystems worldwide. In this study, we systematically evaluated the acute toxicity, settlement inhibitory efficacy, and underlying molecular mechanisms of an N-oleyl-1,3-propanediamine-based antifouling agent using pediveliger larvae of the Pacific oyster Crassostrea gigas. The 96 h-LC50 of the agent was determined to be 0.81 mg/L, and exposure to 1.68 mg/L achieved complete larval settlement inhibition without inducing significant acute toxicity. Transcriptomic analysis identified 791 differentially expressed genes, dominated by downregulated genes associated with ribosomal function, translation, cell adhesion, and cytoskeletal organization. The agent exerts its inhibitory effect primarily through the global suppression of protein synthesis, disruption of cell-substrate adhesion and cytoskeletal integrity, and induction of proteotoxic stress responses. These findings reveal a multi-pathway molecular mechanism underlying antifouling agent-induced settlement inhibition in oyster larvae and provide key molecular biomarkers to support the development of eco-friendly antifouling technologies.

Animals↗

PubMed2026

Physical Appearance Anxiety and Eating Disorders Symptomatology: A Systematic Review and Meta-Analysis.

The present study aimed to assess the link between physical appearance anxiety (PAA) and eating disorder (ED) symptomatology by a meta-analysis of existing literature. Eligible studies were searched across six electronic databases up until November 20, 2025. Pooled effect sizes (r) were calculated using random-effects models. Potential variables that influence effect heterogeneity were analyzed by univariable and multivariable meta-regressions. Influence analyses and a three-parameter selection model (3PSM) were used to assess robustness of the results and publication bias. Twenty-seven effect sizes from 21 studies (N = 5261) were obtained. The results indicated a strong association (i.e., r = 0.559) between the two variables under consideration, which was notably stronger (i) among females compared to males; and (ii) for overall eating disorder symptoms rather than bulimic symptoms. The results of this study advocate for further investigation into the effectiveness of addressing anxiety responses related to personal body traits, particularly among females, within the context of preventing and treating eating disorders.

Humans↗

PubMed2026

Food-derived extracellular vesicles as delivery platforms for medicine-food homology components in metabolic syndrome.

Diet-induced obesity and associated metabolic syndromes have become major global public health challenge, highlighting the urgent need for safe and effective strategies. Recently, food-derived extracellular vesicles (FDEVs) have garnered increasing attention as natural nanocarriers due to their excellent biocompatibility and specific targeted delivery capabilities. FDEVs can efficiently deliver medicine-food homology components (MFHCs) to precisely regulate lipid metabolism, inflammatory responses, and insulin sensitivity, thereby improving obesity and its metabolic abnormalities. This systematic review summarizes recent advances in the use of FDEVs as delivery vehicles for MFHCs to suppress diet-induced obesity and metabolic syndrome, with a particular focus on the underlying molecular mechanisms, including signaling pathway regulation and cellular metabolic remodeling. In addition, the clinical translational potential and industrial application prospects of FDEVs are evaluated, and key challenges related to preparation techniques, safety assessment, and large-scale production are discussed. By integrating current evidence, this review aims to provide theoretical framework and future perspectives for the development of FDEVs as a novel targeted delivery platform and treatment of metabolic diseases.

Extracellular Vesicles↗

PubMed2026

PGPR inoculation and growth enhancement of crops cultivated in hydroponic systems.

Plant growth-promoting rhizobacteria (PGPR) are ubiquitous rhizosphere microorganisms that promote plant health through various mechanisms. Although the study of PGPR inoculants in soil has been done for ages, their application in hydroponic systems has received relatively limited attention. This review identifies PGPR inoculants that are commonly used in hydroponics, methods of application, and their effects on plant growth and nutrient use efficiency. Literature shows that PGPR inoculants improve plant performance in controlled hydroponic systems through the production of growth-stimulating substances, nitrogen fixation, and improved nutrient acquisition. However, the plant growth responses are highly variable depending on the composition of nutrient solutions, environmental factors, crop and microbe species, and the type of hydroponic system. The review identifies various challenges of PGPR inoculation in hydroponic systems and future research directions to address the current gaps. Generally, the productivity of hydroponic systems can be enhanced through advanced inoculation strategies and the development of suitable carrier materials to improve inoculant survival, viability, and functions. Emphasis should also be placed on designing system-specific microbial consortia and Synthetic communities that are tailored to the unique ecological conditions of hydroponic systems.

Hydroponics↗

PubMed2026

A smartphone-integrated Pt@Cu-HCF nanozyme-based paper sensor for on-site determination of total antioxidant capacity in marine oils.

Total antioxidant capacity (TAC) serves as a key indicator for evaluating the nutritional quality of foods. In this study, we designed a platinum-embedded copper hexacyanoferrate (denoted as Pt@Cu-HCF) nanozyme that exhibits high oxidase-like activity, efficiently catalyzing the oxidation of chromogenic substrates to generate robust colorimetric signals. Antioxidants quench hydroxyl radicals (∙OH) produced during the catalytic process, leading to a concentration-dependent suppression of the color signal. Leveraging this mechanism, a smartphone-integrated, colorimetric paper sensor for on-site TAC quantification was developed, using vitamin E as the calibration standard. The sensor was applied to determine TAC in fish oil, algal oil, and krill oil, demonstrating a linear response range of 9.78-312.5 μM and a limit of detection (LOD) of 6.41 μM. Validation using real-world marine oil samples showed excellent agreement with a commercial assay kit, confirming the reliability and practical applicability of this portable sensor for TAC measurement in complex biological matrices.

Antioxidants↗

PubMed2026

A MIL-88@Ru-based molecularly imprinted electrochemiluminescence sensor for highly selective and sensitive detection of enrofloxacin residues in animal-derived foods.

Using a metal-organic framework (MOF) - supported Ru(bpy)32+ (MIL-88@Ru) composite luminescent material, this study innovatively adopted electropolymerization to fabricate a molecularly imprinted polymer-based electrochemiluminescent (MIP-ECL) sensor for enrofloxacin (ENR) detection in animal-derived foods. Systematic investigation of the ECL luminescence and ENR's quenching mechanism confirmed that the sensor integrates ECL's high sensitivity and MIP's high specificity, enabling rapid and accurate recognition of ENR. Experimental results show a good linear response in the range of 1 nmol/L-20 μmol/L (R2 = 0.99), a limit of detection (LOD) as low as 0.28 nmol/L, as well as excellent selectivity and stability. Recoveries of ENR in all investigated matrices ranged from 97.7% to 106.4%, confirming the reliability of the established method. This ECL-MIP coupling strategy provides a new technical approach and application references for the efficient detection of trace pollutants in food safety and environmental monitoring fields.

Enrofloxacin↗

PubMed2026

Comparison of the clinical efficacy, safety and EEG functional connectivity changes between 18-Hz rTMS and iTBS of accelerated dTMS treatment for major depressive disorder: a randomized controlled trial.

Although the antidepressant efficacy of 18-Hz deep transcranial magnetic stimulation (dTMS) has been validated, its prolonged treatment duration has considerable limitations for treatment capacity and patient adherence. Therefore, novel short-course protocols such as accelerated dTMS and intermittent theta burst stimulation (iTBS) present promising alternative options. Here we addressed the question of whether iTBS of accelerated dTMS achieves comparable therapeutic and electrophysiological effects to accelerated dTMS with the conventional 18-Hz rTMS protocol in patients with major depressive disorder (MDD). In a randomized controlled trial (n = 73), participants received either 18-Hz rTMS of accelerated dTMS (rTMS-dTMS group), iTBS of accelerated dTMS (iTBS-dTMS group), or pharmacotherapy alone (drug group). Both dTMS protocols were administered twice daily for 10 days targeting the left lateral prefrontal cortex including the dorsolateral region. Results showed that Hamilton Depression Rating Scale (HAMD) score of the iTBS-dTMS group decreased significantly from 22.5 ± 3.7 before treatment to 8.2 ± 4.1 after treatment (t = 15.900, p < 0.001). HAMD score of the rTMS-dTMS group decreased significantly from 21.3 ± 2.9 before treatment to 8.0 ± 3.8 after treatment (t = 17.232, p < 0.001). The drug group also exhibited significantly improved patients' mood symptoms, and the HAMD score decreased from 24.7 ± 6.8 to 14.0 ± 5.0 (t = 6.363, p < 0.001). The treatment response rate was 85.7% in the iTBS-dTMS group and 76.9% in the rTMS-dTMS group, which was much higher than that of the drug group (42.1%). The remission rate was 50.0% in the iTBS-dTMS group and 42.3% in the rTMS-dTMS group, which was significantly higher than 10.5% of the drug group. We demonstrate here that both accelerated dTMS protocols significantly reduced HAMD scores, improved the response rates, and remission rates, outperforming pharmacotherapy alone. Resting-state EEG analysis further revealed unique frequency-specific functional connectivity (FC) modulation effects: the rTMS-dTMS group primarily exhibited weakened alpha-band functional connectivity within the fronto-occipital, fronto-temporal and fronto-central networks after treatment, whereas the iTBS-dTMS group predominantly demonstrated reduced theta-band functional connectivity within the fronto-parietal, fronto-occipital and fronto-temporal pathways after treatment. These findings indicate that iTBS of accelerated dTMS demonstrates comparable efficacy and tolerability to 18-Hz rTMS of accelerated dTMS, whilst inducing treatment-specific network-level neurophysiological alterations. In the rTMS-dTMS group, relative changes in FC between the frontal and temporal/precentral regions showed significant negative correlation with HAMD score reduction rates, while relative changes in FC between the frontal lobe and parietal lobe showed a significant positive correlation with the rate of HAMD score reduction for the iTBS-dTMS group. This study revealed novel mechanisms by which accelerated dTMS protocols modulate brain networks, providing evidence for the clinical application of accelerated iTBS-dTMS as an efficient, evidence-based treatment for MDD.

Humans↗