Template-based synergy extrapolation analysis for prediction of muscle excitations.

Objective.Accurate prediction of unmeasured muscle excitations can reduce the required wearable surface electromyography (sEMG) sensors, which is a critical factor in the study of physiological measurement. Synergy extrapolation uses synergy excitations as building blocks to reconstruct muscle excitations. However, the practical application of synergy extrapolation is still limited as the extrapolation process utilizes unmeasured muscle excitations it seeks to reconstruct. This paper aims to propose and derive methods to provide an avenue for the practical application of synergy extrapolation with non-negative matrix factorization (NMF) methods.Approach.Specifically, a tunable Gaussian-Laplacian mixture distribution NMF (GLD-NMF) method and related multiplicative update rules are derived to yield appropriate synergy excitations for extrapolation. Furthermore, a template-based extrapolation structure (TBES) is proposed to extrapolate unmeasured muscle excitations based on synergy weighting matrix templates totally extracted from measured sEMG datasets, improving the extrapolation performance. Moreover, we applied the proposed GLD-NMF method and TBES to selected muscle excitations acquired from a series of single-leg stance tests, walking tests and upper limb reaching tests.Main results.Experimental results show that the proposed GLD-NMF and TBES could extrapolate unmeasured muscle excitations accurately. Moreover, introducing synergy weighting matrix templates could decrease the number of sEMG sensors in a series of experiments. In addition, verification results demonstrate the feasibility of applying synergy extrapolation with NMF methods.Significance.With the TBES method, synergy extrapolation could play a significant role in reducing data dimensions of sEMG sensors, which will improve the portability of sEMG sensors-based systems and promotes applications of sEMG signals in human-machine interfaces scenarios.

Screening and modification of (+)-germacrene A synthase for the production of the anti-tumor drug (-)-ß-elemene in engineered Saccharomyces cerevisiae.

(-)-ß-Elemene is a primary bioactive compound derived from Curcuma wenyujin and has been widely utilized as an anti-tumor agent for various types of cancer. Due to the inefficiency of plant extraction methods for ß-elemene, significant efforts have been directed toward the heterogeneous biosynthesis of ß-elemene using microbial cell factories. However, there has been less emphasis on the stereochemical configuration of germacrene A and its rearranged product, ß-elemene. In this study, we constructed a yeast cell factory to produce (-)-ß-elemene by optimizing the mevalonate pathway and screening for germacrene A synthases (GASs) from both plant and microbial sources. Notably, we discovered that the rearranged products of GASs exhibited different conformations, and only (+)-germacrene A produced by plant-derived GASs could rearrange to form (-)-ß-elemene. Building on this discovery, we further investigated the catalytic mechanisms of GASs and developed an efficient catalytic gene module for generating (+)-germacrene A. Ultimately, the engineered yeast produced 1152 mg/L of (-)-ß-elemene, marking the highest titer reported in yeast to date. Overall, this work highlights the differences in the stereoconformations of catalytic products between plant- and microbial-derived germacrene A synthases and establishes a foundation for the green and efficient production of ß-elemene with a specific stereochemical configuration.

"Urological age" as a proxy of healthy longevity: analysis of prospective population-based cohorts in U.S. and China.

BACKGROUND: Assessing urinary symptoms poses a complex challenge for primary care practitioners. In evaluating urological function, our approach involves constructing an urological age through the analysis of laboratory parameters and indicators of the urinary system. METHODS: Based on the National Health and Nutrition Examination Survey (NHANES), urological laboratory tests and age-related symptoms were included in the development of urological age (UA) and urological age acceleration (UAA) through the Klemera Doubal method. In relation to mortality associated with UAA, the metric was categorized into grades (0, 1, 2) as a discrete variable. We investigated the correlation between UAA and its grades with mortality, conducted survival analysis based on UAA grades, and explored the correlation between multisystem ageing-related disorders and UAA grades based on the NHANES and the West China Natural Population Cohort Study. RESULTS: UA was related to age with the r to 0.85 in men and 0.84 in women. Each year the increase in UAA was related to higher 1% and 4% mortality for men and women. Those with UAA grades 1 and 2 were associated with more risk of mortality than individuals with UAA grade 0 (men 8% and 40%, women 24% and 157%). The advanced UAA grades kept pace with multisystem ageing. Healthy diets and lifestyle habits are associated with lower UAA. CONCLUSION: Urological age is related to multisystem ageing and increases mortality risk, and urological age can be used to screen high-risk individuals and inform precision clinical development for ageing intervention.

Dexmedetomidine Promotes NREM Sleep by Depressing Oxytocin Neurons in the Paraventricular Nucleus in Mice.

Dexmedetomidine (DEX) is a highly selective α2-adrenoceptor agonist with sedative effects on sleep homeostasis. Oxytocin-expressing (OXT) neurons in the paraventricular nucleus (PVN) of the hypothalamus (PVNOXT) regulate sexual reproduction, drinking, sleep-wakefulness, and other instinctive behaviors. To investigate the effect of DEX on the activity and signal transmission of PVNOXT in regulating the sleep-wakefulness cycle. Here, we employed OXT-cre mice to selectively target and express the designer receptors exclusively activated by designer drugs (DREADD)-based chemogenetic tool hM3D(Gq) in PVNOXT neurons. Combining chemogenetic methods with electroencephalogram (EEG) /electromyogram (EMG) recordings, we found that cannula injection of DEX in PVN significantly increased the duration of non-rapid eye movement (NREM) sleep in mice. Furthermore, the chemogenetic activation of PVNOXT neurons using i.p. injection of clozapine N-oxide (CNO) after cannula injection of DEX to PVN led to a substantial increase in wakefulness. Electrophysiological results showed that DEX decreased the frequency of action potential (AP) and the spontaneous excitatory postsynaptic current (sEPSC) of PVNOXT neurons through α2-adrenoceptors. Therefore, these results identify that DEX promotes sleep and maintains sleep homeostasis by inhibiting PVNOXT neurons through the α2-adrenoceptor.

Age, sex, and APOE gene-specific associations between dynapenic obesity and dementia in a large cohort.

OBJECTIVE: To investigate the associations between dynapenic obesity and the risk of dementia, and the modifying effects of age, sex, and the APOE gene, using a large population-based cohort. METHODS: 279,884 participants aged 55 and above from the UK Biobank were included. The participants were classified into four categories based on body mass index and hand grip strength: healthy, obesity, dynapenia, and dynapenic obesity. The incident dementia was identified based on linked hospital records and death register data. Cox proportional hazards regression models were used to estimate the associations, followed by age-, sex-, and apolipoprotein E (APOE) gene-stratified analyses. RESULTS: During the median follow-up of 12.4 years, 5,170 (1.8%) participants developed dementia. Compared with the healthy group, participants with dynapenic obesity had 67% higher dementia risk (hazard ratio [HR]: 1.67, 95% confidence interval [CI]: 1.44-1.94). Compared with the healthy group, higher risks of dementia in participants with dynapenic obesity were respectively observed in male (HR: 2.03, 95% CI: 1.65-2.50), younger (<65 years, HR: 1.97, 95% CI: 1.55-2.50), and non-ε4-carrier (HR: 1.97, 95% CI: 1.60-2.44) (all P for interaction <0.05). In participants under 65 years and non-ε4-carrier, those with dynapenic obesity had the highest risk of dementia (HR: 2.63, 95% CI: 1.91-3.62), compared with the healthy group (P for second order interaction = 0.026). CONCLUSIONS: Dynapenic obesity is associated with increased risks of dementia, especially in participants under 65 years and non-ε4-carrier, suggesting the importance of managing dynapenic obesity in the prevention of cognition-related disorders.

Machine learning models reveal the critical role of nighttime systolic blood pressure in predicting functional outcome for acute ischemic stroke after endovascular thrombectomy.

Background: Blood pressure (BP) is a key factor for the clinical outcomes of acute ischemic stroke (AIS) receiving endovascular thrombectomy (EVT). However, the effect of the circadian pattern of BP on functional outcome is unclear. Methods: This multicenter, retrospective, observational study was conducted from 2016 to 2023 at three hospitals in China (ChiCTR2300077202). A total of 407 patients who underwent endovascular thrombectomy (EVT) and continuous 24-h BP monitoring were included. Two hundred forty-one cases from Beijing Hospital were allocated to the development group, while 166 cases from Peking University Shenzhen Hospital and Hainan General Hospital were used for external validation. Postoperative systolic BP (SBP) included daytime SBP, nighttime SBP, and 24-h average SBP. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), Boruta were used to screen for potential features associated with functional dependence defined as 3-month modified Rankin scale (mRS) score ≥ 3. Nine algorithms were applied for model construction and evaluated using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. Results: Three hundred twenty-eight of 407 (80.6%) patients achieved successful recanalization and 182 patients (44.7%) were functional independent. NIHSS at onset, modified cerebral infarction thrombolysis grade, atrial fibrillation, coronary atherosclerotic heart disease, hypertension were identified as prognostic factors by the intersection of three algorithms to construct the baseline model. Compared to daytime SBP and 24-h SBP models, the AUC of baseline + nighttime SBP showed the highest AUC in all algorithms. The XGboost model performed the best among all the algorithms. ROC results showed an AUC of 0.841 in the development set and an AUC of 0.752 in the validation set for the baseline plus nighttime SBP model, with a brier score of 0.198. Conclusion: This study firstly explored the association between circadian BP patterns with functional outcome for AIS. Nighttime SBP may provide more clinical information regarding the prognosis of patients with AIS after EVT.

Risk factors for dysphagia in patients with acute and chronic ischemic stroke: A retrospective cohort study.

Background: Dysphagia is a common and clinically significant complication of ischemic stroke. The prevalence and risk factors for dysphagia may vary at different stages following an ischemic stroke. Methods: This study included patients with acute and chronic ischemic stroke who were treated at the Department of Rehabilitation, First Affiliated Hospital, Zhejiang University School of Medicine from 2019 to 2022. Various demographic, clinical, and laboratory parameters were collected, and statistical analyses were performed to investigate their association with dysphagia. Results: Among the 399 ischemic stroke patients included in the study, 165 (41.4 %) experienced dysphagia, with 72 (38.7 %) in the acute phase and 93 (43.7 %) in the chronic phase. Univariate analysis revealed significant associations (p < 0.05) between dysphagia and factors such as pulmonary infection, aphasia, NIHSS score, ADL score, NLR score, lower extremity Brunnstrom's stages, and sit-to-stand balance. Multiple logistic regression analysis, after adjusting for confounding factors, identified the ADL score as an independent predictor of dysphagia. These findings were consistent across three time-windows: the acute phase, the chronic phase, and 180 days after stroke onset. Additionally, the lymphocyte count and pulmonary infection were identified as potential independent indicators. Conclusions: This study investigated the prevalence and risk factors for dysphagia in ischemic stroke patients at different time-windows. A low ADL score (<40) may serve as a valuable and reliable predictor for poststroke dysphagia in clinical settings.

[Construction of prediction model of severe acute pancreatitis based on serum soluble T cell immunogloblulin and mucin domain-containing protein 3].

OBJECTIVE: To investigate the predictive value of the model based on soluble T cell immunogloblulin and mucin domain-containing protein 3 (sTIM3) for the progression of severe acute pancreatitis (SAP) in patients with acute pancreatitis (AP). METHODS: A retrospective cohort study was conducted. The AP patients admitted to Changzhou First People's Hospital and Changzhou Second People's Hospital from June 1, 2020 to June 30, 2022 were enrolled. Mild AP (MAP) and moderately severe AP (MSAP) patients were classified as non-SAP group, and SAP patients were classified as SAP group according to the progression of AP patients during hospitalization. The basic data, blood biological indicators, serum sTIM3 level, bedside index for severity in acute pancreatitis (BISAP), acute physiology and chronic health evaluation II (APACHE II) score, modified computed tomography severity index (MCTSI) score within 48 hours of admission, and prognosis indicators were collected. Multivariate Logistic regression analysis was conducted to analyze the risk factors of the progression of SAP in patients with AP during hospitalization. Based on the results of multivariate analysis and the best parameters selected based on the minimal Akaike information criterion (AIC), the SAP prediction model based on sTIM3 was constructed. The receive operator characteristic curve (ROC curve) was plotted to analyze the predictive efficacy of the model. RESULTS: A total of 99 AP patients were enrolled, 80 patients in the non-SAP group and 19 patients in the SAP group. Compared with the non-SAP group, body mass index (BMI), drinking history ratio, heart rate (HR), respiration rate (RR), white blood cell count (WBC), red blood cell count (RBC), C-reactive protein (CRP), alanine aminotransferase (ALT), serum creatinine (SCr), procalcitonin (PCT), interleukin-6 (IL-6), sTIM3, BISAP score, APACHE II score and MCTSI score were significantly increased, and pulse oxygen saturation (SpO2), direct bilirubin (DBil) and IL-10 were significantly decreased. The length of intensive care unit (ICU) stay and total length of hospital stay of patients in the SAP group were significantly longer than those in the non-SAP group [length of ICU stay (days): 1.0 (0, 1.5) vs. 0 (0, 0), total length of hospital stay (days): 17.11±9.39 vs. 8.40±3.08, both P < 0.01]. Multivariate Logistic regression analysis showed that HR [odds ratio (OR) = 1.059, 95% confidence interval (95%CI) was 1.010-1.110, P = 0.017], DBil (OR = 0.981, 95%CI was 0.950-0.997, P = 0.043), and sTIM3 (OR = 1.002, 95%CI was 1.001-1.003, P = 0.027) were independent risk factors for predicting the progression of SAP in patients with AP, and the SAP prediction model based on sTIM3 was constructed: Logit(P) = -14.602+0.187×BMI+0.057×HR+0.006×CRP-0.020×DBil+0.002×sTIM3. ROC curve analysis showed that among the aforementioned single factor quantitative indicators, IL-6 was the most effective in predicting the progression of AP patients to SAP during hospitalization, but the predictive performance of prediction model based on the sTIM3 was significantly better than IL-6 [area under the ROC curve (AUC) and 95%CI: 0.957 (0.913-1.000) vs. 0.902 (0.845-0.958), P < 0.05]. CONCLUSIONS: The model based on serum sTIM3 demonstrated good predictive value for the progression of SAP in patients with AP.

Levofloxacin alleviates blood-brain barrier disruption following cerebral ischemia and reperfusion via directly inhibiting A-FABP.

Reperfusion therapy is currently the most effective treatment for acute ischemic stroke, but often results in secondary brain injury. Adipocyte fatty acid-binding protein (A-FABP, FABP4, or aP2) was shown to critically mediate cerebral ischemia/reperfusion (I/R) injury by exacerbating blood-brain barrier (BBB) disruption. However, no A-FABP inhibitors have been approved for clinical use due to safety issues. Here, we identified the therapeutic effect of levofloxacin, a widely used antibiotic displaying A-FABP inhibitory activity in vitro, on cerebral I/R injury and determined its target specificity and action mechanism in vivo. Using molecular docking and site-directed mutagenesis, we showed that levofloxacin inhibited A-FABP activity through interacting with the amino acid residue Asp76, Gln95, Arg126 of A-FABP. Accordingly, levofloxacin significantly inhibited A-FABP-induced JNK phosphorylation and expressions of proinflammatory factors and matrix metalloproteinase 9 (MMP-9) in mouse primary macrophages. In wild-type mice with transient middle cerebral artery occlusion, levofloxacin substantially mitigated BBB disruption and neuroinflammation, leading to reduced cerebral infarction, alleviated neurological outcomes, and improved survival. Mechanistically, levofloxacin decreased MMP-9 expression and activity, and thus reduced degradation of extracellular matrix and endothelial tight junction proteins. Importantly, the BBB- and neuro-protective effects of levofloxacin were abolished in A-FABP or MMP-9 knockout mice, suggesting that the therapeutic effects of levofloxacin highly depended on specific targeting of the A-FABP-MMP-9 axis. Overall, our study demonstrates that levofloxacin alleviates A-FABP-induced BBB disruption and neural tissue injury following cerebral I/R, and unveils its therapeutic potential for the treatment of ischemic stroke.

[Clinical application of retrograde thyroidectomy from top to bottom in retrosternal thyroid surgery].

Objective:To investigate the value of retrograde thyroidectomy from top to bottom in the operation of retrosternal thyroid surgery. Methods:Retrospective analysis was performed on the cases of retrosternal goiter excised by our surgeons from January 2017 to June 2022,the technical points, feasibility and advantages of the operation were summarized. Results:A total of 15 cases of retrosternal goiter treated by retrograde thyroidectomy were collected, including 5 cases of type Ⅰ retrosternal goiter and 10 cases of type Ⅱ retrosternal goiter.The postoperative pathology was benign. The surgical time is 40-60 minutes for unilateral retrosternal goiter and 70-90 minutes for bilateral goiter. All patients were discharged normally within 7 days after operation, and no operative complications were observed such as bleeding, hoarseness or hypoparathyroidism. Conclusion:This surgical excision method of thyroid is suitable for the type Ⅰ and type Ⅱ retrosternal goiter surgery, which can avoid the difficulties in exposing and separating the the inferior thyroid behind the sternum in conventional surgical method, speed up the operation and reduced the difficulty of operation, and has certain promotion value in clinic.

LC-MS/MS based metabolomic analysis of serum from patients with cerebrovascular stenosis.

Cerebrovascular stenosis (CVS) is the main cause of ischemic stroke, which greatly threatens human life. Hence, it's important to perform early screenings for CVS. Metabolomics is an emerging omics approach that has great advantages in disease screening and diagnosis. Therefore, we aim to elucidate the correlation between CVS and metabolomics, which can aid in conducting CVS screening at an early stage. Patients with CVS in Beijing Hospital were included in the study. A total of 36 participants, including 18 patients diagnosed with CVS and 18 healthy individuals, were recruited at Beijing Hospital between May 2022 and October 2021. The serum samples were analyzed for liquid chromatography-tandem mass spectrometry (LC-MS/MS). Then, multivariate statistical methods, including principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed. Differential metabolites were obtained and demonstrated by volcano plot and heatmap. The study recruited 36 participants, including 18 patients with CVS and 18 healthy participants. A total of 150 metabolites were identified. Multivariate statistical analysis revealed significant differences between patients and healthy participants. Furthermore, 30 serum metabolites levels differed significantly between two groups. Differential metabolites were enriched in phenylalanine, tyrosine, and tryptophan biosynthesis; primary bile acid biosynthesis, and other pathways. This study identified differential metabolites in patients with CVS and elucidated the relevant metabolic pathways. Thus, these findings aid in the study of the pathogenesis of CVS and its early diagnosis. DATA AVAILABILITY STATEMENT: The datasets generated for this study are available on request to the corresponding author.

[Analysis of Histologic Transformation and Prognosis for Follicular Lymphoma].

OBJECTIVE: To investigate the related factors of invasive transformation and prognosis for follicular lymphoma. METHODS: A total of 168 patients with follicular lymphoma at First Affiliated Hospital of Zhengzhou University from August 2015 to January 2021 were collected, and the significance of each index in histological transformation (HT) and prognosis were analyzed. RESULTS: Pathology grade3, Ki-67 index ≥40%, ß2MG＞3 mg/L, LDH＞245 U/L, POD24 and non-invasion of bone marrow were associated with HT. Univariate analysis showed that the high risk of FLIPI-2, pathological grade 3, Ki-67≥40%, anemia, ß2MG＞3 mg/L, LDH＞245 U/L and HT had significant adverse effects on PFS; ß2MG＞3 mg/L, LDH＞245 U/L, POD24 and HT had significant adverse effects on OS. Cox multivariate analysis showed that the ß2MG >3 mg/L and HT were independent risk factors of PFS, HT was independent risk factor of OS. CONCLUSION: The pathological grade, Ki-67, ß2MG, LDH, POD24 and bone marrow invasion of FL can predict the risk of HT. Meanwhile, ß2MG >3 mg/L and HT are significantly related to poor prognosis of FL.

Visual stimulation rehabilitation for cortical blindness after vertebral artery interventional surgery: A case report and literature review.

INTRODUCTION AND IMPORTANCE: Cortical blindness (CB) after vertebral artery interventional surgery is not a frequently reported complication. In this study, the efficacy of visual stimulation rehabilitation consisting of visual recovery training and repetitive transcranial magnetic stimulation (rTMS) for cortical blindness was investigated by clinical evaluation, ophthalmologic examination, and electroencephalography (EEG). CASE PRESENTATION: This study reports on a 55-year-old male who showed partial bilateral posterior cerebral artery cortical branch occlusion after timely embolectomy due to thrombus dislodgement during right vertebral artery opening, stenting resulting in basilar artery tip occlusion. The lesions were mainly located in the right cerebellar hemisphere and bilateral occipital lobes, and the patient suffered from bilateral loss of vision, with only light perception preserved. The patient began to receive visual recovery training and 15 sessions of right occipital high-frequency transcranial magnetic stimulation 5 days after the onset. CLINICAL DISCUSSION: After treatment, the patient's capacity to identify things improved, allowing him to watch television, as did the precision and fluency of random hand movements, walking, and self-care. CONCLUSION: Visual stimulation rehabilitation composed of visual recovery training and rTMS is a promising therapy option for cortical blindness, and our case report provides clinical experience with vision recovery for patients with cortical blindness.

Melatonin alleviates intrarenal CaOx crystals deposition through inhibiting LPS-induced non-canonical inflammasome-mediated renal tubular epithelial cells pyroptosis.

Urinary tract infection has long been considered a complication rather than etiology of calcium oxalate (CaOx) nephrolithiasis. This study aimed to explore the role of lipopolysaccharide (LPS), an important component of Gram-negative bacteria, on CaOx nephrolithiasis formation and antagonistic effect of melatonin. Male C57BL/6 mice were intraperitoneally injected with glyoxylate acid (80 mg/kg) daily for 7 days to construct CaOx nephrolithiasis model. A single dose of LPS (2.0 mg/kg) was given 2 h before the second glyoxylate acid treatment in the presence or absence of melatonin (25 mg/kg). Our results found that LPS promoted adhesion of CaOx crystals to renal tubular epithelial cells (RTECs) and intrarenal CaOx crystals deposition. Protein levels of cleaved Caspase-11, N-terminal of cleaved GSDMD (GSDMD-N), NOD-like receptor thermal protein domain associated protein 3 (NLRP3) and cleaved Caspase-1, several markers of non-classical inflammasome activation were upregulated in LPS-treated mouse kidneys and HK-2 cells. Moreover, the number of GSDMD pores was increased in LPS-treated HK-2 cell membrane. Melatonin inhibited Caspase-11 cleavage and antagonized the subsequent LPS-mediated upregulation of GSDMD-N, NLRP3 and cleaved Caspase-1 in kidney tissues and HK-2 cells. In addition, melatonin reduced membrane localization of GSDMD-N and the number of GSDMD pores in LPS-treated HK-2 cells. Accordingly, melatonin inhibited LPS-induced IL-1ß and IL-18 in mouse serum and HK-2 culture supernatant. Importantly, melatonin alleviated LPS-induced crystal-cell interactions and intrarenal CaOx crystals deposition. We provide experimental evidence that LPS promoted CaOx nephrolithiasis formation by inducing non-canonical inflammasome-mediated RTECs pyroptosis. Melatonin alleviated CaOx nephrolithiasis formation through inhibiting LPS-induced non-canonical inflammasome-mediated RTECs pyroptosis.

Non-Contrasted CT Radiomics for SAH Prognosis Prediction.

Subarachnoid hemorrhage (SAH) denotes a serious type of hemorrhagic stroke that often leads to a poor prognosis and poses a significant socioeconomic burden. Timely assessment of the prognosis of SAH patients is of paramount clinical importance for medical decision making. Currently, clinical prognosis evaluation heavily relies on patients' clinical information, which suffers from limited accuracy. Non-contrast computed tomography (NCCT) is the primary diagnostic tool for SAH. Radiomics, an emerging technology, involves extracting quantitative radiomics features from medical images to serve as diagnostic markers. However, there is a scarcity of studies exploring the prognostic prediction of SAH using NCCT radiomics features. The objective of this study is to utilize machine learning (ML) algorithms that leverage NCCT radiomics features for the prognostic prediction of SAH. Retrospectively, we collected NCCT and clinical data of SAH patients treated at Beijing Hospital between May 2012 and November 2022. The modified Rankin Scale (mRS) was utilized to assess the prognosis of patients with SAH at the 3-month mark after the SAH event. Based on follow-up data, patients were classified into two groups: good outcome (mRS ≤ 2) and poor outcome (mRS > 2) groups. The region of interest in NCCT images was delineated using 3D Slicer software, and radiomic features were extracted. The most stable and significant radiomic features were identified using the intraclass correlation coefficient, t-test, and least absolute shrinkage and selection operator (LASSO) regression. The data were randomly divided into training and testing cohorts in a 7:3 ratio. Various ML algorithms were utilized to construct predictive models, encompassing logistic regression (LR), support vector machine (SVM), random forest (RF), light gradient boosting machine (LGBM), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and multi-layer perceptron (MLP). Seven prediction models based on radiomic features related to the outcome of SAH patients were constructed using the training cohort. Internal validation was performed using five-fold cross-validation in the entire training cohort. The receiver operating characteristic curve, accuracy, precision, recall, and f-1 score evaluation metrics were employed to assess the performance of the classifier in the overall dataset. Furthermore, decision curve analysis was conducted to evaluate model effectiveness. The study included 105 SAH patients. A comprehensive set of 1316 radiomics characteristics were initially derived, from which 13 distinct features were chosen for the construction of the ML model. Significant differences in age were observed between patients with good and poor outcomes. Among the seven constructed models, model_SVM exhibited optimal outcomes during a five-fold cross-validation assessment, with an average area under the curve (AUC) of 0.98 (standard deviation: 0.01) and 0.88 (standard deviation: 0.08) on the training and testing cohorts, respectively. In the overall dataset, model_SVM achieved an accuracy, precision, recall, f-1 score, and AUC of 0.88, 0.84, 0.87, 0.84, and 0.82, respectively, in the testing cohort. Radiomics features associated with the outcome of SAH patients were successfully obtained, and seven ML models were constructed. Model_SVM exhibited the best predictive performance. The radiomics model has the potential to provide guidance for SAH prognosis prediction and treatment guidance.

Impact of qualifying artery on the efficacy of stenting plus medical therapy versus medical therapy alone in patients with symptomatic intracranial stenosis: a post-hoc analysis of the CASSISS trial.

BACKGROUND: A recent trial failed to show any benefit of stenting plus medical therapy over medical therapy alone in patients with symptomatic intracranial stenosis. We aimed to examine whether the symptomatic qualifying artery modifies the effect of stenting plus medical therapy. METHODS: This is a post-hoc analysis of the CASSISS trial that included patients with symptomatic intracranial stenosis, randomly assigned to undergo stenting plus medical therapy or medical therapy alone; 358/380 patients were included. Multivariable logistic regression analysis was used with an interaction term to estimate the altered treatment effect by the qualifying artery. The primary outcome was a composite of stroke or death within 30 days or stroke in the qualifying artery territory beyond 30 days through 1 year. The five secondary outcomes included stroke or death related to the qualifying artery territory at 2 and 3 years. RESULTS: No significant treatment allocation-by-stenosis site interaction was observed (Pinteraction=0.435). Compared with medical therapy alone, the adjusted ORs for stenting plus medical therapy were 2.73 (95% CI 0.42 to 17.65) for internal carotid artery stenosis, 1.20 (95% CI 0.29 to 4.99) for M1 stenosis, 0.23 (95% CI 0.02 to 2.31) for vertebral artery stenosis, and 1.33 (95% CI 0.34 to 5.28) for basilar artery stenosis. Of the five secondary outcomes, none showed a significant treatment allocation-by-stenosis site interaction including stroke in the qualifying artery territory at 2 years (Pinteraction=0.659) and 3 years (Pinteraction=0.493). CONCLUSIONS: Among patients with transient ischemic attacks or ischemic stroke due to severe intracranial atherosclerotic stenosis, there was no evidence that the symptomatic qualifying artery could determine the addition of stenting to medical therapy.

Computed tomography angiography-based radiomics model for predicting carotid atherosclerotic plaque vulnerability.

Vulnerable carotid atherosclerotic plaque (CAP) significantly contributes to ischemic stroke. Neovascularization within plaques is an emerging biomarker linked to plaque vulnerability that can be detected using contrast-enhanced ultrasound (CEUS). Computed tomography angiography (CTA) is a common method used in clinical cerebrovascular assessments that can be employed to evaluate the vulnerability of CAPs. Radiomics is a technique that automatically extracts radiomic features from images. This study aimed to identify radiomic features associated with the neovascularization of CAP and construct a prediction model for CAP vulnerability based on radiomic features. CTA data and clinical data of patients with CAPs who underwent CTA and CEUS between January 2018 and December 2021 in Beijing Hospital were retrospectively collected. The data were divided into a training cohort and a testing cohort using a 7:3 split. According to the examination of CEUS, CAPs were dichotomized into vulnerable and stable groups. 3D Slicer software was used to delineate the region of interest in CTA images, and the Pyradiomics package was used to extract radiomic features in Python. Machine learning algorithms containing logistic regression (LR), support vector machine (SVM), random forest (RF), light gradient boosting machine (LGBM), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and multi-layer perception (MLP) were used to construct the models. The confusion matrix, receiver operating characteristic (ROC) curve, accuracy, precision, recall, and f-1 score were used to evaluate the performance of the models. A total of 74 patients with 110 CAPs were included. In all, 1,316 radiomic features were extracted, and 10 radiomic features were selected for machine-learning model construction. After evaluating several models on the testing cohorts, it was discovered that model_RF outperformed the others, achieving an AUC value of 0.93 (95% CI: 0.88-0.99). The accuracy, precision, recall, and f-1 score of model_RF in the testing cohort were 0.85, 0.87, 0.85, and 0.85, respectively. Radiomic features associated with the neovascularization of CAP were obtained. Our study highlights the potential of radiomics-based models for improving the accuracy and efficiency of diagnosing vulnerable CAP. In particular, the model_RF, utilizing radiomic features extracted from CTA, provides a noninvasive and efficient method for accurately predicting the vulnerability status of CAP. This model shows great potential for offering clinical guidance for early detection and improving patient outcomes.

Flow diversion for posterior circulation aneurysms: a multicenter retrospective study.

Background: The prevalence of intracranial aneurysms is approximately 3% worldwide. Posterior circulation (PC) aneurysms have a higher risk of treatment complications than anterior circulation aneurysms. Improving the survival rate and quality of life of patients with PC aneurysms remains one of the most important issues in the field. Objectives: Flow diverter (FD) treatment of PC aneurysms remains controversial. We aimed to investigate the effects of FD treatment and analyze differences among different application methods or aneurysm types in PC aneurysms. Design: This is a multicenter retrospective study. Methods: Patients with PC aneurysms treated with the pipeline embolization device (PED) or Tubridge embolization device (TED) between 2015 and 2020 in five neurovascular centers were retrospectively enrolled. The primary outcomes were major perioperative complication, clinical outcome, and aneurysm occlusion rates. Univariable and multivariable logistic regression analyses were used to determine the risk factors of each outcome. Results: In total, 252 aneurysms were included. Major perioperative complication, favorable clinical outcome, and complete occlusion rates were 7.5%, 91.0%, and 79.1%, respectively. Compared with other types of aneurysms, dissecting aneurysms had the best clinical outcome and highest occlusion rate. Both clinical and angiographic outcomes were independently associated with the aneurysm location at the basilar artery. Aneurysm size was not associated with any outcome. TED had similar clinical and angiographic outcomes compared with PED but more perioperative major complications. Tandem treatment and coiling assistance may have poorer clinical outcomes but similar occlusion rates. Single- and multiple-stent treatments had similar outcomes. Conclusion: FD treatment of PC aneurysms achieved favorable clinical outcomes and long-term aneurysm occlusion rates with acceptable perioperative complication rates, especially in dissecting and non-basilar artery aneurysms. There was no additional improvement in outcomes with coiling assistance, multi-stent application, or tandem treatment. Therefore, the use of PC aneurysms should be carefully considered.

CT-based thrombus radiomics nomogram for predicting secondary embolization during mechanical thrombectomy for large vessel occlusion.

Background and aims: Secondary embolization (SE) during mechanical thrombectomy (MT) for cerebral large vessel occlusion (LVO) could reduce the anterior blood flow and worsen clinical outcomes. The current SE prediction tools have limited accuracy. In this study, we aimed to develop a nomogram to predict SE following MT for LVO based on clinical features and radiomics extracted from computed tomography (CT) images. Materials and methods: A total of 61 patients with LVO stroke treated by MT at Beijing Hospital were included in this retrospective study, of whom 27 developed SE during the MT procedure. The patients were randomly divided (7:3) into training (n = 42) and testing (n = 19) cohorts. The thrombus radiomics features were extracted from the pre-interventional thin-slice CT images, and the conventional clinical and radiological indicators associated with SE were recorded. A support vector machine (SVM) learning model with 5-fold cross-verification was used to obtain the radiomics and clinical signatures. For both signatures, a prediction nomogram for SE was constructed. The signatures were then combined using the logistic regression analysis to construct a combined clinical radiomics nomogram. Results: In the training cohort, the area under the receiver operating characteristic curve (AUC) of the nomograms was 0.963 for the combined model, 0.911 for the radiomics, and 0.891 for the clinical model. Following validation, the AUCs were 0.762 for the combined model, 0.714 for the radiomics model, and 0.637 for the clinical model. The combined clinical and radiomics nomogram had the best prediction accuracy in both the training and test cohort. Conclusion: This nomogram could be used to optimize the surgical MT procedure for LVO based on the risk of developing SE.

Lateral flow immunoassay for rapid and sensitive detection of dsRNA contaminants in in vitro-transcribed mRNA products.

High purity is essential in mRNA-based therapeutic applications. A major contaminant of in vitro-transcribed (IVT) mRNA manufacturing is double-stranded RNA (dsRNA), which can induce severe anti-viral immune responses. Detection methods, such as agarose gel electrophoresis, ELISA, and dot-blot assay, are used to detect the existence of dsRNA in IVT mRNA products. However, these methods are either not sensitive enough or time-consuming. To overcome these challenges, we develop a rapid, sensitive, and easy-to-implement colloidal gold nanoparticle-based lateral flow strip assay (LFSA) with sandwich format for the detection of dsRNA from IVT process. dsRNA contaminant can be determined visually on the test strip or quantitatively with a portable optical detector. This method allows for a 15 min detection of N1-methyl-pseudouridine (m1Ψ)-containing dsRNA with a detection limit of 69.32 ng/mL. Furthermore, we establish the correlation between the LFSA test results and the immune response caused by dsRNA in mice. The LFSA platform allows the rapid, sensitive, and quantitative monitoring of purity in massive IVT mRNA products and aids for the prevention of immunogenicity by dsRNA impurities.