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PubMed2026

A single session of high-definition transcranial direct current stimulation does not modulate effects of knee two-point discrimination training or sensorimotor function in healthy adults: Double-blind randomised controlled trial.

BACKGROUND: Benefits of sensory-training interventions on sensorimotor outcomes are inconsistent, and it is unclear whether transcranial direct current stimulation (tDCS) can enhance proprioception, which is fundamental to neuromuscular control. Existing evidence is dominated by upper-limb studies, so transferability to the knee is unclear. This study investigated whether a single session of anodal high-definition (HD)-tDCS, alone or combined with brief two-point discrimination (TPD) training, enhances knee sensorimotor function and performance in healthy adults. METHODS: In a double-blind randomised-controlled trial, 57 healthy participants received (1) 20-min, 1 mA anodal HD-tDCS over the knee primary somatosensory (S1) map or sham stimulation, and (2) 15-min knee TPD training or no training. Knee somatosensory, sensorimotor, and functional performance measures were assessed pre- and immediately post-intervention. Three-way mixed-design ANOVAs, equivalence testing (smallest effect size of interest η2 = 0.02), Bayes factors, and linear mixed-effects models quantified effects. RESULTS: HD-tDCS, TPD training, and their sequential combination had no effect on any outcome measure (p ≥ 0.05; η2 ≤ 0.015). Confidence intervals spanned equivalence bounds, and equivalence testing results were non-significant (p ≥ 0.05). Bayes factors (<0.33) showed moderate evidence for the null (no effect). Mixed-effects modelling attributed ≤8% of total variance to intervention fixed effects, with the remainder captured by participant-level random effects. CONCLUSION: A single 20-minute session of 1 mA HD-tDCS, with or without brief TPD training, does not acutely modify knee somatosensory, sensorimotor, or functional performance in healthy adults. Existing evidence at the hand may not translate to the lower limb. Future work should investigate higher-dose, multi-session, task-concurrent, or network-targeted strategies in clinical populations.

Humans↗

PubMed2026

Transcriptomic responses of gill and intestinal tissues in Nile tilapia (Oreochromis niloticus) to bacterial infection following sequential nanoimmersion and hydrogel-based multivalent vaccination.

Bacterial pathogens, including Flavobacterium oreochromis, Aeromonas veronii, Streptococcus agalactiae, and Edwardsiella tarda, represent major infectious threats to Nile tilapia (Oreochromis niloticus). A multivalent vaccination strategy integrating cationic nanoemulsion immersion with oral hydrogel boosters was developed to investigate tissue-specific immune responses at the transcriptomic level. Gill tissues were collected following immersion challenge and intestinal tissues following intraperitoneal injection challenge, reflecting the physiologically relevant infection biology of each pathogen and the mechanistic rationale of each delivery platform. RNA sequencing (RNA-seq) generated high-quality datasets (mapping rate > 81.64%) with strong concordance to quantitative real-time PCR (qRT-PCR) validation (r = 0.83). Comparative transcriptomic analysis revealed distinct yet complementary immune signatures between tissues. Gill transcriptomes were enriched in phagosome, focal adhesion, extracellular matrix-receptor interaction (ECM-receptor interaction), and cytokine-cytokine receptor interaction pathways, accompanied by increased expression of major histocompatibility complex class I/II (MHC class I/II), mannose receptor, αVβ3 integrin, and calnexin, indicating innate activation, enhanced phagocytic capacity, epithelial barrier reinforcement, and adaptive immune coordination. Intestinal transcriptomes showed predominant enrichment of adaptive immune pathways, including the intestinal immune network for immunoglobulin (Ig) production, Forkhead box O (FoxO) signaling, and mitogen-activated protein kinase (MAPK) signaling, with increased expression of T-cell receptor (TCR), inducible T-cell co-stimulator ligand (ICOS-L), C-X-C chemokine receptor type 4 (CXCR4), and polymeric immunoglobulin receptor (pIgR), reflecting T and B cell coordination, lymphocyte trafficking, and mucosal immunoglobulin transport, alongside innate engagement through phagosome pathway enrichment. Shared upregulation of MHC class II, B-cell receptor (BCR) signaling, integrin alpha M (ITGAM), and immunoglobulin-associated components across both tissues suggests coordinated mucosal immune activation through a conserved immune module, warranting direct experimental validation. Collectively, these findings provide transcriptomic evidence that this vaccination strategy elicits an integrated, tissue-specialized immune response, advancing mechanistic understanding of gill and intestinal immunity in vaccine-induced protection of teleost fish.

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PubMed2026

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting ACL injuries, evaluating their methodological quality, performance, and reliability. METHOD: A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases, supplemented by Google Scholar for grey literature, covering articles published between January 1, 2015, and August 30, 2025. Eligible studies were appraised using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST) for methodological quality and risk of bias, and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines for quality of evidence. RESULTS: Ten studies were included. PROBAST showed eight studies had moderate risk of bias and two low risk. TRIPOD found only two studies met quality criteria. ML models included logistic regression (n = 5), support vector machines (n = 4), k-nearest neighbor (n = 3), decision trees (n = 3), random forests (n = 5), neural networks (n = 2), linear discriminant analysis (n = 1), and pre-trained CNNs (n = 1). AUC ranged from 0.63 to 0.98. Accuracy (reported in six studies) ranged from 26% to 95%; however, these values should be interpreted with caution due to the absence of confidence intervals, lack of class imbalance handling, and limited external validation across studies. Tree-based ensemble methods such as random forest achieved competitive accuracy (74-86%), while SVM, a non-ensemble classifier, reported accuracy ranging from 71% to 95%; however, the highest values were obtained in studies with notably small sample sizes (n = 12 to n = 39), raising concerns about overfitting and generalizability. CONCLUSION: Current ML algorithms show promise for identifying athletes at high ACL injury risk and detecting relevant risk factors. Although study quality was generally satisfactory, future research should prioritize external validation and model interpretability to support clinical translation.

Humans↗

PubMed2026

Transpulmonary proteomic gradient analysis in women with pulmonary arterial hypertension associated with systemic sclerosis.

This study investigated proteomic alterations in the pulmonary circulation of patients with pulmonary arterial hypertension associated with systemic sclerosis (PAH-SSc) by analyzing the transpulmonary protein gradient and comparing the proteomic profiles with systemic sclerosis (SSc) without PAH. Twenty women were included (10 PAH-SSc, 64.6 ± 10.8 years; 10 SSc, 62.8 ± 11.5 years). The transpulmonary gradient was defined as the difference in biomarker concentrations between wedge-position and pulmonary artery blood samples. Peptides were analysed using liquid chromatography-mass spectrometry, and differentially abundant proteins were identified with Proteome Discoverer. Protein-protein interaction networks were generated with STRING and visualized in Cytoscape. A total of 270 proteins were detected, with no significant transpulmonary gradient alterations. However, patients with PAH-SSc showed distinct proteomic profiles compared to SSc. Multivariate analysis identified 48 differentially abundant proteins in pulmonary artery plasma, with 15 overrepresented and 33 downregulated in PAH-SSc. Among these, the downregulation of transforming growth factor-beta-induced protein ig-h3 (TGFβI/ig-h3) points to a potential involvement of the TGF-β-related extracellular matrix remodelling pathway in PAH-SSc. However, further validation in larger and independent cohorts is required before its relevance as a biomarker or therapeutic target can be established. In conclusion, while no transpulmonary proteomic gradient was observed, the proteomic profiles of PAH-SSc and SSc were different. The profile in PAH-SSc was characterized by differences in immune response, lipid metabolism, and hemostatic proteins. SIGNIFICANCE: This study offers the first proteomic characterization of the transpulmonary gradient in PAH-SSc and SSc. Although no differences in the gradient were found, the pulmonary artery plasma proteome of PAH-SSc patients showed a distinct pattern compared to SSc. Several proteins associated with immune function, haemostasis, and cellular processes were altered, which may indicate specific pathophysiological features of PAH-SSc or suggest how lung dysfunction develops in SSc. Targeting dysregulated proteins like TGFβI/ig-h3 or addressing immune-coagulation imbalances may support future research studies. Overall, these findings refine the molecular profile of PAH-SSc and provide a basis for future large-scale studies aimed at clarifying disease mechanisms and identifying clinically relevant molecular signatures.

Humans↗

PubMed2026

Clinical efficacy and brain mechanism characteristics of guide chi and regulate spirit tuina therapy in the treatment of post-stroke walking dysfunction: A randomized controlled trial based on fNIRS.

BACKGROUND: This study aims to preliminarily evaluate the role of Guide Chi and Regulate Spirit(GCRS) Tuina in enhancing walking function in post-stroke patients with walking dysfunction; secondly, by using functional near-infrared spectroscopy (fNIRS), it investigates the effect of GCRS Tuina on the restoration of brain function in this patient population. METHODS: Participants in the control group received 4-week rehabilitation treatment, while those in the Combined Tuina Group (CTG) additionally received GCRS Tuina therapy for another 4 weeks on this basis. Functional Ambulation Category (FAC), Fugl - Meyer Assessment Scale for Lower Extremity Motor Function (FMA - LE), and Modified Barthel Index (MBI) were evaluated at the baseline and after 4 treatment weeks. A gait and motion analysis system was used to measure step length, stride, walking speed, and step frequency. FNIRS was used to measure the resting-state functional connectivity(FC) strength, as well as the β - value and HbO2 concentration mean during the walking task. RESULTS: A total of 60 participants completed the randomized, and 53 completed the trial and entered the statistical analysis. Compared with the Single Rehabilitation Group(SRG), the CTG group had higher FAC, FMA-LE, and MBI scores after 4 weeks. After the treatment course, the standardized step length, stride, walking speed, and step frequency of the CTG were higher than SRG. At the Region of Interest(ROI) level, the CTG exhibited 13 inter-ROI FC strengths that were higher than SRG, and the differences could survive the FDR correction (PFDR<0.05). Under the walking task, the CTG group had higher β values in 18 channels and higher Oxyhemoglobin(HbO2) concentrations in 19 channels than the SRG (PFDR <0.05). CONCLUSION: GCRS Tuina therapy can significantly improve patients' walking function, enhance lower limb motor ability and daily living ability. It can improve walking efficiency. Tuina can significantly increase the FC and enhance the activation levels and HbO2 concentrations. The stimulation of Tuina may help reconstruct the brain's motor control network, restore impaired motor function, promote the occurrence of neural plasticity, strengthen the neural circuits in the cognitive-motor-sensory cortex to improve walking function. TRIAL REGISTRATION: This study has been registered with the International Traditional Medicine Clinical Trial Registry (ITMCTR2024000654).

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PubMed2026

Predictive Models for Hypoglycemia Risk in Haemodialysis Patients With Diabetic Kidney Disease: Systematic Review and Meta-Analysis.

AIM: To provide evidence for selecting and developing reliable clinical assessment tools for hypoglycemia in diabetic kidney disease patients during haemodialysis. DESIGN: Review. METHODS: Systematic searches were performed in 9 Chinese and English databases to collect literature regarding the development of hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease. Two reviewers independently performed literature screening, data extraction, risk-of-bias assessment, and applicability evaluation. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability of the included studies. Meta-analysis was conducted using R software. DATA SOURCES: CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, EMbase, Web of Science, and CINAHL. The search period covered from the establishment date of each database to December 2025. RESULTS: Six studies, comprising six prediction models, were included. Two studies performed internal validation, and three conducted external validation. All models reported the area under the curve, ranging from 0.813 to 0.866, and calibration measures. Four studies were rated as having a high risk of bias, while all six demonstrated good overall applicability. The meta-analysis showed that the pooled AUC value of the six studies was 0.846 (95% CI: 0.823-0.867). CONCLUSION: Research on hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease remains in the developmental stage. Although the included prediction models exhibited satisfactory apparent discriminatory ability and clinical applicability, most of the original studies suffered from a high risk of bias and lacked adequate validation. The true predictive performance and clinical application value of these models remain to be further verified. Accordingly, routine and unconditional clinical application is not recommended at this stage. Future studies should include more high-quality, multicenter external validation and develop models with high generalizability, favourable clinical applicability, and robust predictive performance to facilitate early identification of hypoglycemia risk in this population. IMPACT: This study systematically evaluated the hypoglycemia risk prediction models for diabetic kidney disease patients during haemodialysis, and the research on hypoglycemia risk prediction models for maintenance haemodialysis patients during dialysis is still in the development stage. This study provides a reference for clinical medical staff to select or develop hypoglycemia risk prediction and assessment tools for diabetic kidney disease patients during haemodialysis. REPORTING METHOD: This study was conducted in accordance with the relevant guidelines of the EQUATOR Network and followed the TRIPOD-SRMA Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. TRIAL REGISTRATION: PROSPERO: CRD420251243352.

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PubMed2026

Relationships between cannabis and cocaine use in a randomized trial of combined buprenorphine and naltrexone for DSM-IV cocaine dependence.

BACKGROUND: Cannabis is the most commonly used drug in the United States, and among people who use cannabis, polysubstance use is common and understudied. We aimed to examine the association of tetrahydrocannabinol (THC) positive urine drug screen (+UDS) with the odds of submitting a cocaine + UDS during cocaine use disorder treatment. METHODS: We conducted a secondary data analysis of a previously reported double-blind, placebo-controlled clinical trial, CTN0048. Participants meeting criteria for opioid abuse/dependence were assigned to receive extended-release naltrexone and one of three conditions of buprenorphine (placebo, 4 mg/day, 16 mg/day) for 8 weeks. Generalized estimating equations (GEE) were used to analyze urine samples (Liu et al., 2018) collected over time, examining the association between THC + UDS and cocaine + UDS during treatment. RESULTS: Participants (n = 301) averaged 46 (SD = 8.64) years of age, were majority male (78.41 %), non-Hispanic (89.70 %), and African American (66.45 %). GEE results indicated that patients who submitted THC + UDS had significantly higher odds of submitting cocaine + UDS compared to participants who submitted THC-negative UDS across the 25 time points examined (OR = 1.47, 95 % CI = 1.21-1.79, p = 0.00). Time (OR = 0.9998, 95 % CI: 0.9997, 0.9999, p = 0.018) and the covariate of sex assigned at birth (OR = 1.77, 95 % CI = 1.13-2.77, p = 0.013) were also significant in the model, indicating very small decreases in the odds of submitting a cocaine + UDS over time for all patients and 77 % higher odds of submitting cocaine + UDS for females. CONCLUSION: THC + UDS was associated with increased odds of submitting a cocaine + UDS during treatment. Further investigation is needed to discern whether decreasing THC use will result in reduced cocaine use; however, these results suggest that it may be beneficial to counsel patients on cannabis use cessation both before and during treatment for cocaine use, as it is related to cocaine use treatment outcomes. TRIAL REGISTRATION: Secondary data analysis of ClinicalTrials.gov, TRN: NCT01402492 ("A randomized study to test the safety and effectiveness of buprenorphine in the presence of naltrexone for the treatment of cocaine dependence"; National Drug Abuse Treatment Clinical Trials Network (CTN) clinical trial: CTN0048), Registration date: 27 July 2011.

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PubMed2026

Multi-omics integrative analysis provides insight into potential molecular responses to sustained high water flow in common carp (Cyprinus carpio) cultured in recirculating aquaculture.

To investigate the potential molecular responses by which water flow intensity affects the growth of common carp (Cyprinus carpio) in a recirculating aquaculture system (RAS), a control group (CG, actual water velocity 0.3 cm/s) and three sustained flow treatment groups were established, including a low-flow group (LF, 1 body length per second, bl/s), a medium-flow group (MF, 2 bl/s), and a high-flow group (HF, 3 bl/s). After 12 weeks of culture in the RAS, growth performance was compared among groups under different flow intensities. The best-performing group and the control group were then selected for the determination of intestinal digestive enzyme activities, as well as transcriptomic and whole-genome bisulfite sequencing analyses of muscle tissue. The results showed that the specific growth rate and feed intake of the HF group were significantly higher than those of the other groups (P < 0.05), whereas no significant difference in feed conversion ratio was observed among groups. Compared with the CG group, lipase activity was significantly higher in the HF group (P < 0.05), while α-amylase and trypsin activities showed increasing trends without significant differences. RNA-seq identified a total of 273 differentially expressed genes, including 72 upregulated genes and 201 downregulated genes in the HF group relative to the CG group. These genes were mainly enriched in glycolysis, pyruvate metabolism, ATP metabolism, the pentose phosphate pathway, the insulin signaling pathway, the PPAR signaling pathway, and the adipocytokine signaling pathway, indicating that sustained high water flow induced a muscle transcriptional response characterized by remodeling of energy metabolism and substrate utilization. Whole-genome bisulfite sequencing analysis showed that DNA methylation in common carp muscle occurred predominantly in the CpG context. Differentially methylated regions between the HF and CG groups were mainly distributed in transcription-related regulatory regions, including promoters, CpG islands, and CpG island shores. In promoter regions, the number of hypermethylated regions in the HF group relative to the CG group was markedly higher than that of hypomethylated regions. Integrated analysis further identified two candidate genes showing both promoter differential methylation and differential expression, namely LOC109094644 and bcorl1, suggesting that adaptation to high water flow may involve IGF-related growth regulation and remodeling of upstream transcriptional programs. The qPCR results were consistent with the transcriptomic data. Taken together, within the tested range, a sustained water flow of 3 bl/s was more conducive to the growth of common carp in the RAS, which may be associated with enhanced lipid digestion and utilization, remodeling of the muscle energy metabolic network, changes in promoter methylation, and the coordinated regulation of key candidate genes. This study provides a theoretical basis for clarifying the exercise adaptation mechanism of common carp in recirculating aquaculture and for optimizing flow velocity parameters.

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PubMed2026

Aflibercept With Versus Without Reduced-Fluence Photodynamic Therapy for Polypoidal Choroidal Vasculopathy: Optical Coherence Tomography Angiographic Changes From a Randomized Clinical Trial.

OBJECTIVES: To report the longitudinal optical coherence tomography angiography (OCTA) changes in polypoidal choroidal vasculopathy (PCV) treated with intravitreal aflibercept monotherapy or in combination with reduced-fluence PDT. DESIGN: Image analysis of a double-masked, sham-controlled, randomized clinical trial. SUBJECTS: 55 eyes of 55 treatment-naïve participants with symptomatic macular PCV completing 52 weeks of follow-up. METHODS: Participants underwent protocolized, multimodal imaging, including OCT, OCTA, fluorescein angiography, and indocyanine green angiography at baseline, week 12, and week 52. Quantitative OCTA parameters included total lesion area, branching neovascular network (BNN) area, and BNN vessel density (VD). Qualitative features included trunk vessel presence and OCTA signal within the polypoidal lesion (PL). Eyes were categorized by treatment arm and PL closure at week 52. MAIN OUTCOME MEASURES: Longitudinal OCTA changes and predictors of PL closure at week 52. RESULTS: We included 55 eyes (28 combination therapy and 27 monotherapy). Total lesion area decreased at week 12 but returned toward baseline at week 52 (combination: 3.72 ± 3.01mm2 at baseline, 2.86 ± 2.50mm2 at week 12, 3.59 ± 3.26mm2 at week 52; monotherapy: 3.77 ± 2.23mm2 at baseline, 3.27 ± 2.36mm2 at week 12, and 3.47 ± 2.58mm2 at week 52). BNN area decreased at week 12 and remained reduced at week 52 in both treatment arms (combination: 2.29 ± 2.08 mm2 at baseline, 1.46 ± 1.36mm2 at week 12, and 1.53 ± 1.32mm2 at week 52; monotherapy: 2.39 ± 1.85mm2 at baseline, 1.87 ± 1.68mm2 at week 12, and 1.82 ± 1.38mm2 at week 52). BNN VD reduction was greater in the combination arm at week 12 (-10 ± 15% vs - 3 ± 12%, P = .02). The proportion of eyes with trunk vessels increased over time in both arms (combination: 35.7% at baseline, 59.3% at week 12, and 67.8% at week 52; monotherapy: 25.9% at baseline, 44.4% at week 12, and 71.4% at week 52). In multivariable analysis, baseline BCVA predicted BCVA change at week 52 (β=-0.96 [-1.21 to -0.72], P < .01), and baseline CST predicted CST change (β=0.93 [0.75 to 1.10], P < .01). Greater reduction in BNN VD at week 12 was independently associated with PL closure at week 52 (OR 0.62 [0.39 to 0.97], P = .03). CONCLUSIONS: Early reduction in BNN vessel density, rather than reduction in lesion size, was associated with subsequent PL closure. OCTA-derived vascular changes may serve as noninvasive biomarkers for predicting treatment response in PCV.

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.

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