Vitexicarpin suppresses malignant progression of colorectal cancer through affecting c-Myc ubiquitination by targeting IMPDH2.

BACKGROUND: Colorectal cancer (CRC) is the second most common cause of cancer-related mortality and is characterised by extensive invasive and metastatic potential. Previous studies have shown that vitexicarpin extracted from the fruits of Vitex rotundifolia can impede tumour progression. However, the molecular mechanisms involved in CRC treatment are still not fully established. PURPOSE: Our study aimed to investigate the anticancer activity, targets, and molecular mechanisms of vitexicarpin in CRC hoping to provide novel therapies for patients with CRC. STUDY DESIGN/METHODS: The impact of vitexicarpin on CRC was assessed through various experiments including MTT, clone formation, EDU, cell cycle, and apoptosis assays, as well as a tumour xenograft model. CETSA, label-free quantitative proteomics, and Biacore were used to identify the vitexicarpin targets. WB, Co-IP, Ubiquitination assay, IF, molecular docking, MST, and cell transfection were used to investigate the mechanism of action of vitexicarpin in CRC cells. Furthermore, we analysed the expression patterns and correlation of target proteins in TCGA and GEPIA datasets and clinical samples. Finally, wound healing, Transwell, tail vein injection model, and tissue section staining were used to demonstrate the antimetastatic effect of vitexicarpin on CRC in vitro and in vivo. RESULTS: Our findings demonstrated that vitexicarpin exhibits anticancer activity by directly binding to inosine monophosphate dehydrogenase 2 (IMPDH2) and that it promotes c-Myc ubiquitination by disrupting the interaction between IMPDH2 and c-Myc, leading to epithelial-mesenchymal transition (EMT) inhibition. Vitexicarpin hinders the migration and invasion of CRC cells by reversing EMT both in vitro and in vivo. Additionally, these results were validated by the overexpression and knockdown of IMPDH2 in CRC cells. CONCLUSION: These results demonstrated that vitexicarpin regulates the interaction between IMPDH2 and c-Myc to inhibit CRC proliferation and metastasis both in vitro and in vivo. These discoveries introduce potential molecular targets for CRC treatment and shed light on new mechanisms for c-Myc regulation in tumours.

Real-time analgesic efficacy and factors determining drug requirements of combined spinal-epidural analgesia for labor: a prospective cohort study.

PURPOSE: Combined spinal-epidural analgesia (CSEA) is effective but not sufficient for labor pain. This study was conducted to assess the real-time analgesic efficacy, side effects of anesthetic drug dosage, and maternal satisfaction in labor to provide reference for the optimization of labor analgesia. METHODS: This was a prospective, cohort, single-center study that included 3020 women who received CSEA for labor analgesia. The visual analogue scale (VAS) for labor pain, real-time anesthetic drug dosage, side effects, adverse labor outcomes, factors influencing average drug dosage, and maternal satisfaction with CSEA were assessed. RESULTS: Overall, the VAS labor pain score was lowest at the first hour after the anesthesia was given. After 4 h for primiparas and 3 h for multiparas, the VAS score was greater than 3 but the anesthetic drug dosage did not reach the maximum allowed dosage at the same time. The average anesthetic drug dosage was positively correlated with fever, urinary retention, uterine atony, prolonged active phase, prolonged second stage, assisted vaginal delivery, and postpartum hemorrhage. The average anesthetic drug dosage was the highest in women ≤ 20 years old, those with a body mass index (BMI) ≥ 24.9 kg/m2, and those with a primary or secondary education level. CONCLUSION: Appropriate age guidance and emphasis on education of labor analgesia, weight management during pregnancy, and real-time anesthetic dosage adjustment during labor based on VAS pain score may have positive effects on the satisfaction of labor analgesia. CLINICAL TRIAL NUMBER AND REGISTRY: Clinicaltrials.gov (ChiCTR2100051809).

A machine learning model to predict spontaneous vaginal delivery failure for term nulliparous women: An observational study.

OBJECTIVE: This study aims to construct and evaluate a model to predict spontaneous vaginal delivery (SVD) failure in term nulliparous women based on machine learning algorithms. METHODS: In this retrospective observational study, data on nulliparous women without contraindications for vaginal delivery with a singleton pregnancy ≥37 weeks and before the onset of labor from September 2020 to September 2021 were divided into a training set and a temporal validation set. Transperineal ultrasound was performed to collect angle of progression, head-perineum distance, subpubic arch angle, and their levator hiatal dimensions. The cervical length was measured via transvaginal ultrasound. The delivery methods were later recorded. Through LASSO regression analysis, indicators that can affect SVD failure were selected. Seven common machine learning algorithms were selected for model training, and the optimal algorithm was selected based on the area under the curve (AUC) to evaluate the effectiveness of the validation model. RESULTS: Four indicators related to SVD failure were identified through LASSO regression screening: angle of progression, cervical length, subpubic arch angle, and estimated fetal weight. The Gaussian NB algorithm was found to yield the highest AUC (0.82, 95% confidence interval [CI] 0.65-0.98) during model training, and hence it was chosen for verification with the temporal validation set, in which an AUC of 0.79 (95% CI 0.64-0.95) was obtained with accuracy, sensitivity, and specificity rates of 80.9%, 72.7%, and 75.0%, respectively. CONCLUSION: The Gaussian NB model showed good predictive effect, proving its potential as a clinical reference for predicting SVD failure of term nulliparous women before actual delivery.

Cardiopulmonary Coupling Spectrogram as an Ambulatory Method for Assessing Sleep Disorders in Patients With Autoimmune Encephalitis.

BACKGROUND AND OBJECTIVES: Sleep disorders are a common and important clinical feature in patients with autoimmune encephalitis (AE); however, they are poorly understood. We aimed to evaluate whether cardiopulmonary coupling (CPC), an electrocardiogram-based portable sleep monitoring technology, can be used to assess sleep disorders in patients with AE. METHODS: Patients fulfilling the diagnostic criteria of AE were age- and sex-matched with recruited healthy control subjects. All patients and subjects received CPC testing between August 2020 and December 2022. Demographic data, clinical information, and Pittsburgh Sleep Quality Index (PSQI) scores were collected from the medical records. Data analysis was performed using R language programming software. RESULTS: There were 60 patients with AE (age 26.0 [19.8-37.5] years, male 55%) and 66 healthy control subjects (age 30.0 [25.8-32.0] years, male 53%) included in this study. Compared with healthy subjects, patients with AE had higher PSQI scores (7.00 [6.00-8.00] vs 3.00 [2.00-4.00], p < 0.001), lower sleep efficiency (SE 80% [71%-87%] vs 92% [84%-95%], p < 0.001), lower percentage of high-frequency coupling (25% [14%-43%] vs 45% [38%-53%], p < 0.001), higher percentage of REM sleep (19% ± 9% vs 15% ± 7%, p < 0.001), higher percentage of wakefulness (W% 16% [11%-25%] vs 8% [5%-16%], p = 0.074), higher low-frequency to high-frequency ratio (LF/HF 1.29 [0.82-2.40] vs 0.91 [0.67-1.29], p = 0.001), and a higher CPC-derived respiratory disturbance index (9.78 [0.50-22.2] vs 2.95 [0.40-6.53], p < 0.001). Follow-up evaluation of 14 patients showed a decrease in the PSQI score (8.00 [6.00-9.00] vs 6.00 [5.00-7.00], p = 0.008), an increased SE (79% [69%-86%] vs 89% [76%-91%], p = 0.030), and a decreased W% (20% [11%-30%] vs 11% [8%-24], p = 0.035). Multiple linear regression indicated that SE (-7.49 [-9.77 to -5.21], p < 0.001) and LF/HF ratio (0.37 [0.13-0.6], p = 0.004) were independent factors affecting PSQI scores in patients with AE. DISCUSSION: Sleep disorders with autonomic dysfunction are common in patients with AE. Improvements in the PSQI score and SE precede the restoration of sleep microstructural disruption in the remission stage. CPC parameters may be useful in predicting sleep disorders in patients with AE.

Combination of serum markers with optical coherence tomography angiography for evaluating neuromyelitis optica spectrum disorders and multiple sclerosis.

BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS), autoimmune inflammatory diseases of the central nervous system, affect the optic nerve and brain. A lumbar puncture to obtain biomarkers is highly invasive. Serum biomarkers and optical coherence tomography angiography (OCTA) are more accessible and less expensive than magnetic resonance imaging and provide reliable, reproducible measures of neuroaxonal damage. This study investigated the association between serum neurofilament light chain (sNfL), serum glial fibrillary acidic protein (sGFAP), and OCTA metrics. Serum sNfL and sGFAP levels, OCTA values, and clinical characteristics were compared among 91 patients with NMOSD, 81 patients with MS, and 34 healthy controls (HCs) at baseline and 1-year follow-up. RESULTS: sNfL and sGFAP levels were higher while the sGFAP/sNfL quotients were significantly lower in NMOSD and MS patients than those in HCs. At baseline, the average thicknesses of the peripapillary retinal nerve fibre layer (pRNFL) and macular ganglion cell-inner plexiform layer (mGC-IPL) were significantly smaller in NMOSD and MS patients than those in HCs (pRNFL: MS 92.0 [80.2; 101] µm, NMOSD 80.0 [59.0; 95.8] µm, vs HC 99.0 [92.0; 104] µm, p < 0.001; mGC-IPL: MS 74.5 [64.2; 81.0] µm, NMOSD 68.0 [56.0; 81.0] µm, vs HC 83.5 [78.0; 88.0] µm, p < 0.001). The vessel density (VD) and perfusion density (PD) were increased in MS patients without optic neuritis compared to HCs (VD: MS 16.7 [15.6; 17.9] HC 15.3 [13.4; 16.9], p = 0.008; PD: MS 0.41 [0.38; 0.43], HC 0.37 [0.32; 0.41], p = 0.017). In NMOSD patients without optic neuritis, sNfL was significantly associated with PD at baseline (r = 0.329, q = 0.041). The baseline and follow-up values of the sNfL level and average pRNFL and mGC-IPL thicknesses in MS patients showed significant differences. NMOSD patients showed significant differences between baseline and follow-up sNfL and sGFAP levels but not OCTA metrics. CONCLUSION: Changes in retinal microvasculature might occur earlier than those in retinal structure and may therefore serve as a promising diagnostic marker for early NMOSD. The combination of serum markers and OCTA metrics could be used to evaluate and differentiate between MS and NMOSD.

Causal association between genetically predicted circulating immune cell counts and frailty: a two-sample Mendelian randomization study.

Background: Despite the recognized link between immune responses and frailty, the association between immune cell counts and frailty based on previous observational studies remains disputed, with uncertain causal nexus. This study aimed to elucidate causal association between genetically predicted circulating immune cell counts and frailty. Methods: We conducted the two-sample Mendelian randomization (MR) study with independent genetic variants associated with six immune cell subtype counts from genome-wide association studies in 563,946 European individuals. Frailty summary data, assessed via frailty index (FI), was obtained from study comprising 175,226 subjects. Univariate MR, reverse MR and multivariate MR were conducted to comprehensive investigate the association between immune cell counts and FI, with two-step MR analysis for mediation analysis. Results: Univariate MR evidence indicated that among six leukocyte subtype counts, only elevated eosinophil count was significantly correlated with higher FI (ß = 0.059, 95% confidence interval [CI], 0.042-0.078, P=5.63E-11), with no reverse causal relationship identified in reverse MR. In multivariate MR, the causal effect of eosinophil count retained statistical significance (ß = 0.063, 95% CI, 0.021-0.104, P = 0.003). Ultimately, the two-step MR analysis demonstrated two mediators in this causal pathway: asthma (ß= 0.019, 95% CI, 0.013-0.025, P = 35.84E-10, mediated proportion, 31.732%) and rheumatoid arthritis (ß= 0.004, 95% CI, 0.001-0.006, P=1.75E-03, mediated proportion, 6.411%). Conclusions: Within immune cell subtypes, MR evidence indicated only genetically predicted circulating eosinophil count had irreversible and independent causal effect on frailty, with asthma and rheumatoid arthritis possibly serving as partial mediators. The finding stressed the need for further exploring physiological functions of eosinophils in order to develop effective strategies against frailty.

Development and validation of machine learning based prediction model for postoperative pain risk after extraction of impacted mandibular third molars.

Background: Predicting postoperative pain risk in patients with impacted mandibular third molar extractions is helpful in guiding clinical decision-making, enhancing perioperative pain management, and improving the patients' medical experience. This study aims to develop a prediction model based on machine learning algorithms to identify patients at high risk of postoperative pain after tooth extraction. Methods: We conducted a prospective cohort study. Outpatients with impacted mandibular third molars were recruited and the outcome was defined as the NRS (Numerical Rating Scale) score of peak postoperative pain within 24 h after the operation ≥7, which is considered a high risk of postoperative pain. We compared the models built using nine different machine learning algorithms and conducted internal and time-series external validations to evaluate the model's predictive performances in terms of the area under the curve (AUC), accuracy, sensitivity, specificity, and F1-value. Results: A total of 185 patients and 202 cases of impacted mandibular third molar data were included in this study. Five modeling variables were screened out using least absolute selection and shrinkage operator regression, including physician qualification, patient self-reported maximum pain sensitivity, OHI-S-CI, BMI, and systolic blood pressure. The overall performance of the random forest model was evaluated. The AUC, sensitivity, and specificity of the prediction model built using the random forest method were 0.879 (0.861-0.891), 0.857, and 0.846, respectively, for the training set and 0.724 (0.673-0.732), 0.667, and 0.600, respectively, for the time series validation set. Conclusions: This study developed a machine learning-based postoperative pain risk prediction model for impacted mandibular third molar extraction, which is promising for providing a theoretical basis for better pain management to reduce postoperative pain after third molar extraction.

Cerebrospinal fluid uric acid levels associated with disease severity in patients with anti-N-methyl-d-aspartate receptor encephalitis.

INTRODUCTION: Uric acid (UA) is an important natural antioxidant and strong peroxynitrite scavenger, but little is known about central nervous system (CNS) levels of UA in patients with anti-N-methyl-d-aspartate receptor encephalitis (NMDARE). METHODS: Cerebrospinal fluid (CSF) and serum levels of UA were determined in 72 patients with anti-NMDARE and 111 controls with non-inflammatory neurological diseases (NINDs). Serum UA levels were also evaluated in 132 healthy controls (HCs). CSF neuron-specific enolase (NSE) and blood-brain barrier (BBB) index were evaluated in patients with anti-NMDARE. The association of CSF UA levels with anti-NMDARE and its clinical parameters were evaluated in the patients. RESULTS: CSF UA levels were lower in patients with anti-NMDARE than in patients with NINDs, especially in patients with severe impairments (modified Rankin Scale [mRS] scores >3 vs. ≤ 3, p = 0.006). Furthermore, serum UA levels in patients with anti-NMDARE were significantly lower than in patients with NINDs and HCs. CSF UA levels were significantly associated with mRS scores, and serum UA levels in patients with anti-NMDARE. Furthermore, CSF/serum UA ratio was significantly associated with BBB index. CONCLUSIONS: CSF UA levels associated with disease severity and serum UA levels in patients with anti-NMDARE. And CSF/serum UA ratio correlated with BBB index, indicating that CSF and serum UA levels change similarly with BBB permeability in anti-NMDARE patients.

Development and validation of a machine learning model to predict prognosis in HIV-negative cryptococcal meningitis patients: a multicenter study.

PURPOSE: To predict prognosis in HIV-negative cryptococcal meningitis (CM) patients by developing and validating a machine learning (ML) model. METHODS: This study involved 523 HIV-negative CM patients diagnosed between January 1, 1998, and August 31, 2022, by neurologists from 3 tertiary Chinese centers. Prognosis was evaluated at 10 weeks after the initiation of antifungal therapy. RESULTS: The final prediction model for HIV-negative CM patients comprised 8 variables: Cerebrospinal fluid (CSF) cryptococcal count, CSF white blood cell (WBC), altered mental status, hearing impairment, CSF chloride levels, CSF opening pressure (OP), aspartate aminotransferase levels at admission, and decreased rate of CSF cryptococcal count within 2 weeks after admission. The areas under the curve (AUCs) in the internal, temporal, and external validation sets were 0.87 (95% CI 0.794-0.944), 0.92 (95% CI 0.795-1.000), and 0.86 (95% CI 0.744-0.975), respectively. An artificial intelligence (AI) model was trained to detect and count cryptococci, and the mean average precision (mAP) was 0.993. CONCLUSION: A ML model for predicting prognosis in HIV-negative CM patients was built and validated, and the model might provide a reference for personalized treatment of HIV-negative CM patients. The change in the CSF cryptococcal count in the early phase of HIV-negative CM treatment can reflect the prognosis of the disease. In addition, utilizing AI to detect and count CSF cryptococci in HIV-negative CM patients can eliminate the interference of human factors in detecting cryptococci in CSF samples and reduce the workload of the examiner.

Nitrogen and sulfur co-doped carbon quantum dots as "on-off-on" fluorescence probes to detect Hg2+ and MnO4- and improving the photostability of Rhodamine B.

BACKGROUND: Carbon quantum dot (CQDs) are zero-dimensional carbon nanomaterials with a size of less than 10 nm CQDs are widely used in the field of ion detection by virtue of their fluorescence characteristics such as strong fluorescence intensity, good optical stability and tunable emission wavelength. Although the traditional atomic absorption method, electrochemical method and other metal ion detection methods are highly sensitive, the operation is complex, expensive and limited by the site. Therefore, we prepared the N, S-CQDs capable of detecting Hg2+ and MnO4- in water with the advantages of simple operation, low cost, and direct visual signal. RESULTS: N, S-CQDs with high-quantum yield (77.68%), uniform particle size (0.4 nm-2.6 nm) and green fluorescence were created utilizing a one-pot hydrothermal process with the precursors ASDA-Na4 and m-phenylenediamine. N, S-CQDs has good optical properties such as high fluorescence intensity, wavelength independence, up-conversion luminescence and fluorescence stability. We examined 27 common ions in water and found that the fluorescence of N, S-CQDs could be selectively quenched by Hg2+ and MnO4-, and the detection limits are 0.41 µM and 1.2 µM, respectively. The mechanism of quenching is further investigated. The fluorescence of N, S-CQDs-Hg2+ system can be restored by halogen ions (Cl-, Br-, I-), while the fluorescence of N, S-CQDs-MnO4- system can be partially restored by Fe2+. This forms an "on-off-on" mode of fluorescent probes. In addition, we also studied that trace amounts of N, S-CQDs can improve the photostability of RhB. SIGNIFICANCE: The N, S-CQDs are fluorescent probes in an "on-off-on" mode. N, S-CQDs with green fluorescence (on) can be quenched by Hg2+ and MnO4- (off). The fluorescence quenched by Hg2+ can be restored by halogen ions again, while the fluorescence quenched by MnO4- can partially be restored (on). This ion detection method can be used to visually detect the two ions in the field, with the advantages of low cost, simple operation and visual intuition.

Cerebrospinal Fluid Chloride Is Associated with Disease Activity of Relapsing-Remitting Multiple Sclerosis: A Retrospective Cohort Study.

BACKGROUND: Blood-brain barrier dysfunction in active multiple sclerosis (MS) lesions leads to pathological changes in the cerebrospinal fluid (CSF). This study aimed to investigate the possible association between routine CSF findings, especially CSF chloride, at the time of the first lumbar puncture and the relapse risk and disability progression of relapsing-remitting MS (RRMS). METHODS: This retrospective study included 77 patients with RRMS at the MS Center of our institution from January 2012 to December 2020. The Anderson and Gill (AG) model and Spearman correlation analysis were used to explore predictors of relapse and disability during follow-up. RESULTS: In the multivariate AG model, patients with elevated CSF chloride level (hazard ratio [HR], 1.1; 95% confidence interval [CI]: 1.06-1.22; p = 0.001) had a high risk of MS relapse. Using median values of CSF chloride (123.2 mmol/L) as a cut-off, patients with CSF chloride level ≥ 123.2 mmol/L had a 120% increased relapse risk compared with those with CSF chloride level < 123.2 mmol/L (HR = 2.20; 95% CI: 1.19-4.05; p = 0.012). CONCLUSIONS: Elevated CSF chloride levels might be a biologically unfavorable predictive factor for disease relapse in RRMS.

Development and validation of a patient-specific model to predict postoperative SIRS in older patients: A two-center study.

Introduction: Postoperative systemic inflammatory response syndrome (SIRS) is common in surgical patients especially in older patients, and the geriatric population with SIRS is more susceptible to sepsis, MODS, and even death. We aimed to develop and validate a model for predicting postoperative SIRS in older patients. Methods: Patients aged ≥65 years who underwent general anesthesia in two centers of Third Affiliated Hospital of Sun Yat-sen University from January 2015 to September 2020 were included. The cohort was divided into training and validation cohorts. A simple nomogram was developed to predict the postoperative SIRS in the training cohort using two logistic regression models and the brute force algorithm. The discriminative performance of this model was determined by area under the receiver operating characteristics curve (AUC). The external validity of the nomogram was assessed in the validation cohort. Results: A total of 5,904 patients spanning from January 2015 to December 2019 were enrolled in the training cohort and 1,105 patients from January 2020 to September 2020 comprised the temporal validation cohort, in which incidence rates of postoperative SIRS were 24.6 and 20.2%, respectively. Six feature variables were identified as valuable predictors to construct the nomogram, with high AUCs (0.800 [0.787, 0.813] and 0.822 [0.790, 0.854]) and relatively balanced sensitivity (0.718 and 0.739) as well as specificity (0.718 and 0.729) in both training and validation cohorts. An online risk calculator was established for clinical application. Conclusion: We developed a patient-specific model that may assist in predicting postoperative SIRS among the aged patients.

Multimorbidity of Allergic Conditions in Urban Citizens of Southern China: A Real-World Cross-Sectional Study.

BACKGROUND: Extensive knowledge of allergic multimorbidities is required to improve the management of allergic diseases with the industrialization of China. However, the demography and allergen distribution patterns of allergic multimorbidities in China remain unclear, despite the increasing prevalence of allergies. METHODS: This was a real-world, cross-sectional study of 1273 outpatients diagnosed with one or more allergic diseases in Guangzhou, the most populated city of southern China, with leading industrial and commercial centers, between April 2021 and March 2022. Seven allergic diseases (allergic rhinitis (AR), asthma (AS)/cough variant asthma (CVA), atopic dermatitis (AD)/eczema, food allergy (FA), allergic conjunctivitis (AC), drug allergy (DA), and anaphylaxis) were assessed. Positive rates of sensitization to different allergens were measured using an allergen detection system of the UniCAP (Pharmacia Diagnostics, Sweden) instrument platform to compare the groups of allergic multimorbidities against a single entity. RESULTS: There were 659 (51.8%) males and 614 (48.2%) females aged from 4 months to 74 years included in the analysis. The study participants who were diagnosed with allergic diseases had an average of 1.6 diagnoses. Overall, 46.5% (592 of 1273) of the patients had more than one allergic condition, and allergic rhinitis was the most common type of multimorbidity. Women were more likely to suffer from an allergic disease alone, whereas allergic multimorbidities were more likely to be diagnosed in men (p = 0.005). In addition, allergic multimorbidities were common in all age groups, with an incidence ranging from 37.1% to 57.4%, in which children and adolescents were more frequently diagnosed with allergic multimorbidities than adults (18-60 years old) (all p < 0.05). Allergic multimorbidity was observed throughout the year. A difference in the positive rate of allergens sensitization and total immunoglobulin E (tIgE) levels between different allergic multimorbidities was observed. CONCLUSIONS: Allergic multimorbidities were very commonly found in nearly half of all patients with allergies. The proportion of allergic multimorbidities varied with the type of disease, sex, age, and allergen distribution pattern. These findings may help clinicians to develop "One health" strategies for the clinical management of allergic diseases.

Novel highly selective fluorescence sensing strategy for Mercury(â ¡) in water based on nitrogen-doped carbon quantum dots.

In this work, a fluorescent signal-closing probe of nitrogen-doped carbon quantum dots (NCQDs) was developed for quantitative detection of mercury ions (Hg2+). In this detection system, the NCQDs with high quantum yield (QY, 63.80 %) were synthesized via simple hydrothermal method with Methyl Glycine Diacetic acid Trisodium Salt (MGDA) and m-phenylenediamine (MPD) as carbon and nitrogen sources. The NCQDs have a typical surface structure and exceptional fluorescence stability, and their fluorescence zones are centered on excitation wavelengths of 440 nm and emission wavelengths of 510 nm. Under optimal conditions, the NCQDs have outstanding anti-interference ability to various ions and high selectivity to mercury ions. The fluorescence intensity of the detection system is weakened due to the generation of non-fluorescent groups caused by the static quenching effect. The fluorescence quenching efficiency shows a fascinating linear relationship with Hg2+ ions at 0-100 µM (y = 0.0051x-0.015, R2 = 0.9943), and the detection limit is 0.9 µM. Acute toxicity test shows that NCQDs have low toxicity and little harm to environment. The detection system can be used for the quantification of mercury ions in environmental water samples, and the recovery rate is between 99.64 % and 103.43 %, indicating that it is a simple and economical fluorescence detection method.

Natural Killer Cells Disrupt Nerve Fibers by Granzyme H in Atheriosclerotic Cerebral Small Vessel Disease.

Natural killer (NK) cells are enriched in the central nervous system in aging-related atheriosclerotic cerebral small vessel disease (aCSVD), but their roles and underlying mechanism remain to be elucidated. To identify potential cytotoxic molecules released by NK cells in aCSVD lesions, proteomic analysis of cerebrospinal fluid (CSF), plasma, and peripheral NK cells from patients with aCSVD were performed. We found that integrin ß2 (ITGB2), cathepsin D (CTSD), and granzyme H (GZMH) were highly expressed in NK cells. ITGB2 interacted with intercellular adhesion molecule 1 in vascular endothelial cells. As assessed by immunofluorescence and scanning electron microscopy of the blood-brain barrier model, transwell membranes covered with primary human brain microvascular endothelial cells and astrocytes, we demonstrated that the CTSD-mediated degradation of collagen in the blood-brain barrier depended on the cytotoxicity of NK cells in aCSVD. With the immunostaining in vitro and in vivo, GZMH disruption of demyelinated nerve fibers was reversed by cotreatment with the inhibitor 3,4-DCIC during white matter hyperintensity (WMH) in aCSVD. Our results indicate that NK cells contribute to CTSD-induced damage to the blood-brain barrier and GZMH-induced disruption of nerve fibers during WMH in aCSVD.

Cortical gradient of a human functional similarity network captured by the geometry of cytoarchitectonic organization.

Mapping the functional topology from a multifaceted perspective and relating it to underlying cross-scale structural principles is crucial for understanding the structural-functional relationships of the cerebral cortex. Previous works have described a sensory-association gradient axis in terms of coupling relationships between structure and function, but largely based on single specific feature, and the mesoscopic underpinnings are rarely determined. Here we show a gradient pattern encoded in a functional similarity network based on data from Human Connectome Project and further link it to cytoarchitectonic organizing principles. The spatial distribution of the primary gradient follows an inferior-anterior to superior-posterior axis. The primary gradient demonstrates converging relationships with layer-specific microscopic gene expression and mesoscopic cortical layer thickness, and is captured by the geometric representation of a myelo- and cyto-architecture based laminar differentiation theorem, involving a dual origin theory. Together, these findings provide a gradient, which describes the functional topology, and more importantly, linking the macroscale functional landscape with mesoscale laminar differentiation principles.

Prevalence of multiple sclerosis in Guangzhou, China: A population-based case-finding prospective study.

BACKGROUND: Multiple sclerosis (MS) is rare in China, and the prevalence previously reported may be biased. Currently, few studies that have investigated the prevalence of MS in China based on the latest diagnostic criteria. METHODS: Through a population-based survey from August 8, 2021 to December 31, 2021, we calculated the prevalence of multiple sclerosis in 18,676,605 residents of Guangzhou, China. MS patients were identified through the health insurance system of the Guangzhou Health Insurance Bureau, and we surveyed 17 large tertiary hospitals using a case-finding approach. All MS patients were diagnosed according to the 2017 McDonald criteria. RESULTS: A total of 143 patients in the resident population of Guangzhou were diagnosed with MS, with a crude prevalence of 0.77 per 100,000 (95% confidence interval (CI): 0.65-0.90), and the prevalence was higher in in females (1.14/100,000) than in males (0.44/100,000). The age-adjusted prevalence was 0.92 per 100,000 (95% CI: 0.77-1.10). The prevalence peaked at the age of 25-29 years (2.86/100,000) for both males and females (1.44/100,000 and 4.42/100,000, respectively). CONCLUSIONS: This is the first study to report the prevalence of MS in Guangzhou, China, according to the criteria. Our study shows that the prevalence of MS in Guangzhou is lower than that in other cities in China.

Cerebrospinal fluid cystatin C levels in patients with anti-NMDAR encephalitis and other neurological diseases.

BACKGROUND: Cystatin C has neuroprotective and immunomodulatory effects on the central nervous system. However, the role of cerebrospinal fluid (CSF) cystatin C in anti-N-methyl-d-aspartate receptor encephalitis (anti-NMDARE) remains unknown. METHODS: In this study, CSF levels of cystatin C were determined in 73 patients with anti-NMDARE; 496 patients with other neurological diseases, comprising 108 with neuromyelitis optica, 77 with multiple sclerosis, 71 with schizophrenia, 68 with cryptococcus meningitis or meningoencephalitis, 43 with tuberculous meningitis or meningoencephalitis, 43 with bacterial meningitis or meningoencephalitis (BM), 35 with Guillain-Barré syndrome, 23 with spinal cord injury (SCI), 14 with amyotrophic lateral sclerosis (ALS), and 14 with idiopathic epilepsy; and 136 control patients with non-inflammatory diseases. The associations of CSF cystatin C with anti-NMDARE and its clinical parameters were evaluated. RESULTS: CSF cystatin C levels were significantly lower in patients with anti-NMDARE than in patients with BM, SCI, and ALS, especially among those with poor functional status (modified Rankin Scale [mRS] ≥4). CSF cystatin C levels were also significantly lower in anti-NMDARE patients with poor functional status (mRS ≥4) than in those with good functional status (mRS <4). CSF cystatin C levels were significantly associated with mRS scores and CSF white blood cell counts in anti-NMDARE patients. CONCLUSIONS: CSF levels of cystatin C are decreased in anti-NMDARE patients and negatively associated with disease severity.

Single-particle fluorescence tracking combined with TrackMate assay reveals highly heterogeneous and discontinuous lysosomal transport in freely orientated axons.

Axonal transport plays a significant role in the establishment of neuronal polarity, axon growth, and synapse formation during neuronal development. The axon of a naturally growing neuron is a highly complex and multifurcated structure with a large number of bends and branches. Nowadays, the study of dynamic axonal transport in morphologically complex neurons is greatly limited by the technological barrier. Here, a sparse gene transfection strategy was developed to locate fluorescent mCherry in the lysosome of primary neurons, thus enabling us to track the lysosome-based axonal transport with a single-particle resolution. Thereby, several axonal transport models were observed, including the forward or backward transport model, stop-and-go model, repeated back-and-forth transport model, and cross-branch transport model. Then, the accurate single-particle velocity quantification by TrackMate revealed a highly heterogeneous and discontinuous transportation process of lysosome-based axonal transport in freely orientated axons. And, multiple physical factors, such as the axonal structure and the size of particles, were disclosed to affect the velocity of particle transporting in freely orientated axons. The combined single-particle fluorescence tracking and TrackMate assay can be served as a facile tool for evaluating axonal transport in neuronal development and axonal transport-related diseases.