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PubMed2026

Vortex-assisted liquid-liquid microextraction based on natural deep eutectic solvents for the determination of pyrethroid pesticides in urine.

A novel, facile, and environmentally friendly analytical method was developed based on vortex-assisted liquid-liquid microextraction and high-performance liquid chromatography with diode-array detection for detecting pyrethroid pesticides (PPs) in urine. Natural deep eutectic solvents (NADESs) were prepared using plant essential oil-derived monoterpenoids (thymol, carvacrol, and menthol) combined with aromatic primary alcohols (benzyl alcohol, phenethyl alcohol, and phenylpropyl alcohol) as hydrogen bond donors and acceptors. These solvents served as environmentally benign extraction media, thereby avoiding the use of conventional volatile, toxic organic solvents. NADESs are naturally derived, easy to prepare, biodegradable, and environmentally friendly solvents. Hydrophobic and π-π interactions between the NADESs and PPs may contribute to enhancing the affinity of PPs toward the NADESs phase. Vortex technology, accelerating mass transfer between the sample and extractant phases, enables fast extraction of PPs. Under optimized conditions, the method achieved a low detection limit (0.002 mg L-1), satisfactory precision with relative standard deviations (0.3%-2.4%), and acceptable recovery (80.7%-86.2%). The method demonstrated excellent performance in urine analysis and was feasible as a facile and green strategy for monitoring the content of PPs in biological matrices and assessing exposure risk.

Liquid Phase Microextraction↗

PubMed2026

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning↗

PubMed2026

The Effect of Slow Deep Breathing Relaxation Exercise on Pain and Anxiety Levels During and Post-Chest Tube Removal After CABG.

Chest tube removal after coronary artery bypass graft is frequently reported by patients as stressful and painful, highlighting the need for effective nonpharmacological interventions. Slow deep breathing relaxation exercises (SDBREs) may serve as a simple nursing strategy to reduce discomfort. In this study, we aimed to evaluate the effect of SDBRE on pain and anxiety during and after chest tube removal following coronary artery bypass grafting in Nablus hospitals. An experimental design was used with 80 patients recruited from 2 hospitals. Participants were randomly assigned to either an intervention group (n = 40) that practiced SDBRE or a control group (n = 40) that received standard care. Data were collected through a self-administered questionnaire, the Numeric Pain Scale, and the Visual Anxiety Scale. Data collection occurred from March to October 2024. The intervention group reported significantly lower pain scores during removal (M: 5.325 vs 7.125, P < .001) and after removal (P < .001). Anxiety scores were significantly lower both during and after removal (P < .001). Pain correlated with duration, with more complex operations and prolonged chest tube insertion linked to higher scores. SDBRE significantly reduced pain and anxiety during and after chest tube removal, supporting its integration into routine postoperative nursing care.

Humans↗

PubMed2026

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries↗

PubMed2026

Diversity and population connectivity of members of the family Eunicidae inhabiting deep-water corals in the North Atlantic.

Eunicid polychaetes are often found in association with Cold Water Corals (CWCs), even establishing symbiotic relationships, such as those described between Desmophyllum pertusum and Eunice norvegica. While genetic connectivity of CWCs across the North Atlantic has been widely studied, little is known about their associated fauna in this regard. Here, we present a study combining a focused analysis of the genetic and genomic connectivity of E. norvegica with a regional assessment of the distribution and evolutionary relationships of three CWC-associated eunicid species from the Cantabrian Sea and the North of the United Kingdom (190-1,230 m depth). An integrative approach using genetic (16S, COI and 18S), morphological and ecological data allowed the identification of the eunicids studied, with new records of Eunice cf. nicidioformis and Leodice cf. antarctica in the Cantabrian Sea, as well as previously undocumented associations with CWC species. In addition, RADseq data contributed to the delimitation of the closely related species E. norvegica and Eunice philocorallia. Moreover, the genetic connectivity of E. norvegica was studied trough a RADseq (1,067 neutral SNPs) approach. Our results indicate a single panmictic population across approximately 2,000 km, suggesting that oceanographic currents facilitate passive dispersal of E. norvegica lecithotrophic larvae, aided by coral host stepping-stones. The connectivity patterns observed for E. norvegica mirror those of D. pertusum, on which the worm is ecologically dependent. Our study highlights the importance of using integrated genetic, morphological and ecological data to characterise and delineate understudied CWC-associated species and improve our understanding of their dispersal capabilities and genetic connectivity to inform future conservation recommendations.

Animals↗

PubMed2026

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves↗

PubMed2026

Integrating genomic distance analyses in the description of a new family, genus, and species of sponge-associated antipatharians (black corals).

Antipatharians (black corals) are among the least studied coral groups, with much of their diversity still undescribed. Here, we present an integrative morphological, phylogenomic and genomic distance study of deep-sea antipatharians sampled in high seas areas of the North Pacific Ocean and from New Zealand's Exclusive Economic Zone. These corals grow on hexactinellid sponges - a unique characteristic in the order Antipatharia. Using a dataset of ultra-conserved elements and exons, combined with morphological analyses, we reconstruct phylogenomic relationships and formally describe a new family (Eidikopathidae fam. nov.), a new genus (Eidikopathesgen. nov.), and two new species (E. korallispongiasp. nov., E. zealandkoralliasp. nov.). Morphologically, the new family is distinguished by a corallum consisting of a network of loose branches that fuse with the sponge skeletal framework. Phylogenomic analyses recovered consistent topologies with strong nodal support, corroborating the distinct evolutionary placement of this sponge-associated lineage. Pairwise genomic distances estimated using the Tamura-Nei model were concordant with patristic genomic distances, identifying Pteridopathidae as the genetically closest family to Eidikopathidae fam. nov., followed by Myriopathidae and Stylopathidae, which were recovered as sister families in the phylogeny. This pattern shows that genomic distance complements, rather than simply mirrors, tree topology by quantifying accumulated sequence divergence among lineages. Together, these results provide the first genomic distance framework for Antipatharia, offering a baseline for future systematic, evolutionary, and biodiversity studies on this fundamental shallow, mesophotic and deep-sea coral group.

Animals↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

Bioprospecting microbial genomes to expand the biocatalytic toolbox of rubber oxygenases.

A set of rubber oxygenases was discovered through phylogenetic analysis and AI-based structural modeling of complexes of the putative enzymes with a substrate mimicking cis-1,4-polyisoprene. Sixteen candidate proteins were selected from thermophilic microorganisms, all sequence-related to the Latex clearing protein from Streptomyces sp. K30 (LcpK30). Sequence truncation and solubility tags were then evaluated to enhance protein expression, with the SUMO tag proving to be the most effective. Including LcpK30, nine heme-containing oxygenases were successfully expressed in E. coli NEB 10-beta cells, purified (35-157 mg L-1 yield) and characterized. Steady-state kinetics revealed significant rubber latex-degrading properties for six of them, with the truncated SUMO-fused LcpK30 (SUMO-LcpK30T) showing activity in agreement with literature. Notably, the catalytic efficiencies of all the expressed homologs lay within one order of magnitude and the oxygenase from Thermomonospora echinospora was found to be particularly promising in terms of activity, especially at high latex concentrations (more than 1% w/v). The analysis of reaction mixtures by both HPLC and HPLC-MS confirmed the oxidation of cis-1,4-polyisoprene to form the expected isoprenoid oligomers (n = 2-12), whose distribution was consistent with the usual endo-type cleavage pattern in all but one case. This bioprospecting effort afforded a platform of new rubber-degrading enzymes with diverse efficiencies and product profiles, capable of adapting to targeted applications.

Oxygenases↗

PubMed2026

AI echo INSIGHT study: A prospective blinded randomized trial of artificial intelligence echocardiogram interpretation.

BACKGROUND: Transthoracic echocardiography (TTE) is the most commonly performed cardiac imaging modality with over 30 million studies annually. Demand for timely expert interpretation continues to outpace capacity, creating diagnostic delays and inter-observer variability that impact patient care. Recent research has suggested computer vision artificial intelligence (AI) models can generate accurate preliminary comprehensive TTE reports, however, prospective evaluation is needed to determine whether AI-assisted TTE interpretation can improve clinician efficiency while preserving diagnostic accuracy. METHODS: AI ECHO INSIGHT is a prospective randomized blinded clinical trial conducted at Kaiser Permanente Northern California that will evaluate 1200 historical TTE studies (1000 consecutive unselected studies plus 200 with moderate or greater valvular disease) interpreted using three workflows: (1) AI-generated preliminary report finalized by a blinded cardiologist (AI-assisted); (2) cardiologist-generated preliminary report finalized by a blinded cardiologist (cardiologist-assisted); and (3) sonographer-generated preliminary report finalized by a blinded cardiologist (sonographer-assisted). The primary outcome is the rate of substantial change between preliminary and final reports, comparing the AI-assisted workflow to the pooled cardiologist-assisted and sonographer-assisted workflows. Secondary outcomes include cardiologist interpretation time for report finalization, superiority testing for diagnostic accuracy, and reporting consistency. CONCLUSION: AI ECHO INSIGHT is a prospective randomized blinded clinical trial evaluating the clinical impact of AI-assisted TTE interpretation on diagnostic accuracy, cardiologist efficiency, and reporting consistency in real-world echocardiography workflows. TRIAL REGISTRATION: ClinicalTrials.gov registration number NCT07229300.

Humans↗

PubMed2025

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans↗

PubMed2026

Repetitive transcranial magnetic stimulation in functional motor disorders: A systematic review of effects and targets.

OBJECTIVE: To evaluate the effectiveness, safety, and potential mechanistic implications of repetitive transcranial magnetic stimulation (rTMS) in adults with functional motor disorders (FMD), focusing on possible phenotype-specific responses and stimulation protocols. METHODS: Seven databases were searched from inception to July 2026. Randomised and non-randomised interventional studies were included. Risk of bias and evidence certainty were assessed using PEDro, RoB 2, JBI tools, and GRADE. Because of substantial clinical and methodological heterogeneity, findings were synthesised qualitatively. RESULTS: Fourteen studies were included. The primary motor cortex was targeted in 11 studies. Functional tremor showed the most consistent evidence with inhibitory stimulation: one small sham-controlled trial found a significant group-by-time effect on tremor severity (p = 0.007), while an uncontrolled prospective series reported 40 % reduction in postural tremor amplitude (p = 0.05). Evidence for functional weakness was conflicting: excitatory M1 stimulation increased objective strength by 25 % versus 10 % with sham (p = 0.004), whereas the largest inhibitory sham-controlled trial found no benefit (p = 0.80). No severe adverse events were reported, but safety reporting was incomplete. GRADE certainty was moderate for tremor and very low for all other outcomes. CONCLUSIONS: Current evidence is insufficient to establish the efficacy of rTMS in FMD or to recommend phenotype-specific protocols. Preliminary findings support further investigation of inhibitory stimulation for functional tremor, whereas evidence for excitatory stimulation in functional weakness remains uncertain. SIGNIFICANCE: The possible interaction between phenotype and stimulation direction is hypothesis-generating. rTMS should currently be considered an experimental, context-sensitive adjunct within multidisciplinary care, pending adequately powered phenotype-stratified sham-controlled trials. Prospero Registration Number: CRD420251250969.

Humans↗

PubMed2026

Continuous theta-burst stimulation over the right DLPFC modulates central executive network connectivity in depression: exploratory analysis of a randomized clinical trial.

Previous studies suggest that transcranial magnetic stimulation exerts antidepressant effects and is associated with alterations in functional connectivity (FC), but the neural correlates remain unclear. This exploratory sham-controlled trial investigated the effect of continuous theta-burst stimulation (cTBS) over the right dorsolateral prefrontal cortex (DLPFC) on FC in major depressive disorder (MDD). Seventy MDD patients were randomized to receive two-week treatment of personalized cTBS or sham stimulation. Resting-state fMRI was performed at baseline and post-treatment. Ultimately, 31 patients in the active cTBS group and 28 patients in the sham group passed imaging quality control and were included in the final analysis. To identify the FC that may have been influenced by cTBS treatment, two complementary FC analyses were conducted: (1) voxel-wise degree centrality (DC) followed by seed-based FC, and (2) an individual FC analysis based on the stimulation targets. Furthermore, correlations between FC changes and clinical symptoms improvement were examined. Both groups exhibited reductions of depression scores, with greater improvement in the active group. Compared to the sham group, active cTBS showed increased DC in the precuneus and elevated FC between the precuneus (within the para-cingulate network) and the right inferior parietal lobule (IPL) and DLPFC. Further stimulation target-based analysis revealed increased FC between stimulation targets and both the precuneus and visual regions following treatment. Our findings reveal neural changes associated with cTBS over the right DLPFC in MDD, notably involving the precuneus and its connectivity with the right IPL/DLPFC, suggesting alterations within the central executive network. TRIAL REGISTRATION: chictr.org.cn; ChiCTR2300068273.

Humans↗

PubMed2026

Effect of transcutaneous auricular vagus nerve stimulation on postoperative pain in patients undergoing thoracoscopic partial lung resection: a randomized, double-blind, controlled clinical trial.

BACKGROUND: Postoperative pain after thoracic surgery remains common and challenging. Transcutaneous auricular vagus nerve stimulation (taVNS) is a noninvasive neuromodulation technique with potential analgesic effects. This study aimed to evaluate the efficacy and safety of taVNS for postoperative pain management in patients undergoing thoracoscopic partial lung resection. METHODS: Adults undergoing thoracoscopic partial lung resection were randomized to active or sham taVNS. The primary outcome was cough pain intensity at 48h post-surgery, assessed by Numeric Rating Scale (NRS). Secondary outcomes included cough pain at 24h and 72h, resting pain, moderate-to-severe pain incidence, opioid consumption, quality of recovery, postoperative pulmonary complications , chest tube duration, hospital stay, postoperative nausea/vomiting, and adverse events. RESULTS: Among 119 analyzed patients (active n = 60, sham n = 59), active taVNS reduced cough pain scores at 24h, 48h, and 72h postoperatively, as well as resting pain (p < 0.05). It also lowered the incidence of moderate-to-severe cough pain at 24h and 48h, reduced cumulative postoperative opioid use at 24h and 72h, and decreased rescue analgesia on postoperative day 3 (p < 0.05). Active taVNS was associated with a lower incidence of postoperative pneumothorax (p < 0.05). No serious adverse events occurred. CONCLUSION: Perioperative taVNS was associated with a modest analgesic benefit and reduced postoperative opioid requirements after thoracoscopic partial lung resection. The observed reduction in postoperative pneumothorax requires cautious interpretation, and further multicenter trials are needed to determine its clinical utility.

Humans↗

PubMed2026

Effect of intraoperative 40-hz gamma-frequency auditory stimulation on postoperative delirium in older adults undergoing major surgery: a randomized clinical trial protocol.

INTRODUCTION: Postoperative delirium (POD) is a common and clinically significant complication among older adults undergoing major surgery under general anesthesia. Gamma-frequency (40-Hz) auditory stimulation has demonstrated potential neuroprotective and cognition-enhancing effects, suggesting a plausible role in perioperative delirium prevention. However, direct clinical evidence supporting intraoperative 40-Hz auditory stimulation in reducing POD remains limited, warranting rigorous evaluation in a randomized trial. PATIENTS AND METHODS: This prospective, parallel-group, randomized controlled trial will enroll 550 older adults scheduled for major noncardiac, nonneurosurgical surgery under general anesthesia. Participants will be randomized in a 1:1 ratio to either the active stimulation group, receiving intraoperative 40-Hz gamma-frequency auditory stimulation delivered via headphones for 2 h following successful anesthesia induction, or the sham stimulation group, wearing headphones without active auditory output. The primary outcome is the incidence of POD on postoperative day 1 though 3, assessed using the Confusion Assessment Method (CAM) or the CAM for the ICU (CAM-ICU). Secondary outcomes include POD severity, sleep quality, pain scores, analgesic consumption, the incidence of postoperative nausea and vomiting (PONV), rescue antiemetic use, duration of post-anesthesia care unit (PACU) stay, length of hospital stay, quality of postoperative recovery, incidence of perioperative adverse events; postoperative morbidity, health-related quality of life, and all-cause 30-day mortality. DISCUSSION: This trial will determine whether intraoperative 40-Hz gamma-frequency auditory stimulation reduces the incidence of POD among older adults undergoing major surgery under general anesthesia. If efficacious, this noninvasive intervention could constitute a feasible perioperative strategy to mitigate delirium risk and enhance postoperative recovery. CLINICAL TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR2500115156).

Humans↗

PubMed2026

Repetitive transcranial magnetic stimulation in substance use disorders is safe and tolerable: A Systematic review of 141 clinical trials including 4299 participants.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuromodulation intervention investigated as a treatment for substance use disorder (SUD) and its co-occurring disorders. As the number of rTMS SUD clinical trials increase, the safety and tolerability profile should be assessed. In this systematic review, we investigate adverse events (AEs) of rTMS in individuals with SUD and factors that may influence their occurrence. METHODS: We performed a systematic PubMed search to identify all controlled trials of rTMS in SUD published up to January 2025. Eligible studies were assessed, and safety information was extracted for analysis. RESULTS: A total of 141 clinical trials with 4299 participants were included in their active arms. rTMS trials recruited participants who were engaged in active substance use, were in the pre-treatment phase, in early recovery, or in sustained recovery. Twenty-two studies explicitly reported no AEs. Sixty-nine studies reported only mild AEs, while only six studies reported moderate AEs. Thirty-five studies did not report safety-outcomes/AEs. As expected, participants reported mild and temporary AEs such as headaches, pain or discomfort under the coil, or dizziness. Only nine studies reported serious AEs (7 studies in active TMS and 2 in sham TMS). Importantly, no seizures attributable to active rTMS were reported in these SUD samples. CONCLUSION: Overall, rTMS in SUD samples is safe and well-tolerated regardless of recovery stage and substance. Most reported side effects were mild, self-limiting, and tolerable. However, AE reporting was incomplete, as 35 of 141 trials reported no safety data, limiting conclusions to reported outcomes. This evidence supports the safety of rTMS as a potential stand-alone or adjunctive treatment for SUD.

Humans↗

PubMed2026

Reducing state anxiety with alpha-frequency transcranial alternating current stimulation.

BACKGROUND: Anxiety reactivity to acute stress is a transdiagnostic vulnerability factor. We tested whether a single session of alpha-frequency transcranial alternating current stimulation (tACS) targeting the frontoparietal control network reduces stress-evoked state anxiety in healthy adults. METHODS: In a randomized, blinded, sham-controlled study, 42 participants (mean age 58.9 years) completed an acute stress task before and after stimulation. The task was an adapted moving-circles paradigm in which circle collisions triggered a brief aversive event (mild electric shock plus unpleasant noise and a white flash). Active stimulation consisted of 20 min of 10-Hz tACS (2.0 mA/channel; 30-s ramp up/down) delivered via electrodes at F3, P3, Cz, and T7 (0° phase at F3/P3; 180° at Cz/T7). Sham stimulation used the same montage and ramp periods but no sustained current. RESULTS: State anxiety showed a significant Time × Protocol interaction (F(1,35) = 4.22, p = .047): STAI-S decreased after active tACS (Δ = -3.16) but increased slightly after sham (Δ = +1.17). Perceived stress appraisal (SAAS) did not change. Resting-state alpha power at F3/P3 showed no reliable pre-post effects. During the task, left-frontal relative alpha differed by protocol and showed a trend toward larger increases following active tACS. Electrodermal and pupil indices changed across sessions in both groups, with no differential stimulation effects. CONCLUSIONS: A single alpha-tACS session produced a modest, selective reduction in stress-evoked state anxiety, supporting oscillatory neuromodulation as a scalable approach to dampen anxiety reactivity.

Humans↗

PubMed2026

Effectiveness of transcranial direct current stimulation with and without positive mood induction on worry and transdiagnostic cognitive-emotional processes: A randomized controlled trial.

The present study investigated the effectiveness of transcranial direct current stimulation (tDCS), with and without positive mood induction, on worry and key transdiagnostic cognitive-emotional processes, including attentional bias, working memory, problem solving, and emotion regulation, in individuals with high levels of worry. This single-blind randomized controlled trial included 45 individuals with high levels of worry. After a structured clinical interview, participants were randomly assigned, with gender balancing, to one of three groups: (1) tDCS alone, (2) tDCS combined with positive mood induction, or (3) a sham control group. Outcome measures were administered at three time points (pretest, posttest, and one-month follow-up) and assessed attentional bias (Dot Probe Task), working memory (1-back task), problem solving (Tower of London task), emotion regulation (Gross's Emotion Regulation Questionnaire), and worry severity (Penn State Worry Questionnaire; PSWQ). Repeated-measures ANOVA showed that both active groups (tDCS alone and tDCS + positive mood induction) significantly improved attentional bias, worry, working memory, problem solving, and emotion regulation compared to controls (p < 0.05). The combined intervention produced significantly greater gains than tDCS alone in working memory, problem solving, emotion regulation (p < 0.05), and reductions in attentional bias and worry (p < 0.001). All effects persisted at one-month follow-up (p < 0.05). tDCS reduces worry and attentional bias and enhances cognition and emotion regulation in individuals with high levels of worry. The combined intervention produced larger and more sustained improvements than tDCS alone across the assessed behavioral outcomes. These findings support further investigation of combining tDCS with structured positive mood induction while the mechanisms underlying the additional benefits remain to be established.

Humans↗