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).

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.

Preoperative hs-CRP/HDL ratio is associated with increased risk for postoperative SIRS in elderly patients: a retrospective cohort study.

BACKGROUND: Systemic inflammatory response syndrome (SIRS) greatly affects postoperative lives of afflicted aged patients. This study aimed to determine whether preoperative high hs-CRP/HDL ratio (CHR) was associated with an increased risk of postoperative SIRS in the elderly population. METHODS: This retrospective cohort study included data on patients aged ≥ 65 years who underwent general anesthesia surgery at two clinical centers between January 2015 and September 2020. The primary exposure was preoperative CHR which was divided into two groups (≤ 12.82 and > 12.82) based on its normal range in our hospital, and the primary outcome was the incidence of postoperative SIRS. Targeted maximum likelihood estimation analyses were used to model the exposure-outcome relationship. RESULTS: The analysis included 5595 elderly patients, of whom 1410 (25.20%) developed SIRS within three postoperative days. Targeted maximum likelihood estimation analysis revealed that elderly patients with CHR > 12.82 vs. CHR ≤ 12.82 was associated with increased risk of postoperative SIRS (aOR = 1.40, 95% CI [1.33, 1.48], P < 0.001). Those results were consistent both in subgroup analyses and sensitivity analyses. Compared with patients with CHR ≤ 12.82, patients with CHR > 12.82 had a higher prevalence of postoperative SIRS (49.06% vs. 22.70%), postoperative in-hospital mortality (3.40% vs. 0.65%), a longer hospital stay after surgery [10 (IQR, 6-16) vs. 8 (IQR, 5-11) days] and higher direct medical cost [10070 (IQR, 6878-15577) vs. 7117 (IQR, 4079-10314) euros, all P < 0.001]. CONCLUSIONS: In elderly patients, preoperative CHR > 12.82 was significantly associated with a higher risk of postoperative SIRS.

Reversibility of acute-on-chronic liver failure syndrome in hepatitis B virus-infected patients with and without prior decompensation.

Acute-on-chronic liver failure (ACLF) is a severe clinical syndrome associated with high short-term mortality and reversibility. This study aimed to compare the characteristics of survival and reversibility in hepatitis B virus (HBV)-related ACLF (HBV-ACLF) patients with and without previous decompensation. Overall, 1044 patients who fulfilled the acute hepatic insult criteria of the APASL-ACLF Research Consortium (AARC) definition were enrolled from a prospectively established cohort of HBV-related liver failure patients. These patients were divided into the AARC ACLF group and the non-AARC ACLF group according to prior decompensation. Mortality, reversibility of ACLF syndrome, and predicted factors associated with reversibility were evaluated. Liver transplantation-free mortality of the AARC ACLF group was significantly lower than that of the non-AARC ACLF group (28 days: 28.2% vs. 40.3%, p = .012; 90 days: 41.7% vs. 65.4%, p < .001). The 5-year cumulative reversal rates of ACLF syndrome were 88.0% (374/425) and 66.0% (31/47) in the AARC and non-AARC ACLF groups, respectively, (p = .039). Following reversibility of ACLF syndrome, 340/374 (90.9%) and 21/31 (67.7%) patients in the AARC and non-AARC ACLF groups, respectively, maintained a stable status within 5 years. Although prior decompensation indicated poor reversibility of ACLF syndrome, HBV-infected patients with prior decompensation who fulfilled the acute hepatic insult criteria of the AARC definition showed favourable reversibility and maintained a stable status after receiving nucleoside analogues. The AARC ACLF definition identified HBV-ACLF as a distinct syndrome with good reversibility. HBV-infected patients with prior decompensation could be included in the AARC ACLF management.

Immunosuppressant and neuromyelitis optica spectrum disorder: optimal treatment duration and risk of discontinuation.

BACKGROUND AND PURPOSE: Preventing relapse by immunosuppressants (ISs) is critical for the prognosis of neuromyelitis optica spectrum disorder (NMOSD); however, the optimal duration of IS treatment is still under discussion. The objective was to explore the optimal duration of IS treatment and the risk of IS discontinuation for NMOSD. METHOD: This cohort study was conducted at a major neurological center that housed the largest NMOSD database in South China. Eligible participants were patients with NMOSD undergoing IS treatment. The main outcome measures were changes in relapse risk based on IS treatment duration, clinical outcomes and predictors of relapse following IS discontinuation. RESULTS: In total, 343 patients were included in this study. The duration of IS treatment was strongly associated with a decrease in relapse risk (hazard ratio [HR] 0.53, p < 0.001). Continuous IS treatment resulted in decreased relapse HRs within 5 years of receiving IS medication, with a mild rebound starting at 5 years. Rituximab reduced the risk of NMOSD relapse to approximately zero within 3 years. The rate of relapse after IS withdrawal was high (77.5%). As opposed to other ISs, a delayed relapse following rituximab withdrawal was observed in this study. Longitudinal extensive transverse myelitis (HR = 2.023, p = 0.006) was associated with a higher risk of relapse after IS discontinuation. CONCLUSIONS: Long-term IS medication for NMOSD is generally suitable. Patients with longitudinal extensive transverse myelitis had a higher risk of relapse after IS discontinuation. Future studies should explore individualized strategies of rituximab maintenance treatment.

G-CSF promotes the viability and angiogenesis of injured liver via direct effects on the liver cells.

BACKGROUND: Presently, liver transplantation is the only treatment strategy for liver failure (LF). Although granulocyte-colony stimulating factor (G-CSF) exhibits protective functions in LF, it is not clear whether it directly affects the liver cells. METHODS AND RESULTS: We established an injured liver cell model and observed that G-CSF treatment promoted cell viability and enhanced Ki67 and VEGF-A expression. Thereafter, human umbilical vein endothelial cells (HUVECs) were cultured in a conditioned medium collected from the G-CSF-treated injured liver cells. HUVECs' proliferation and tubule formation were promoted. Furthermore, in an injured liver mouse model, confirmed via haematoxylin-eosin staining, we evaluated serum alanine aminotransferase activity, Ki67 expression, and microvessel density (MVD). G-CSF treatment significantly relieved liver injury, upregulated Ki67 expression, and enhanced MVD in the injured mouse liver tissue. Additionally, AKT and ERK signal targets were explored, and it was demonstrated that the effects of G-CSF on injured liver cells were mediated through the AKT and ERK signalling pathways. CONCLUSIONS: G-CSF promotes injured liver viability and angiogenesis by directly affecting injured liver cells via the AKT and ERK signalling pathways. These findings improve our understanding of the role of G-CSF in recovery from LF.

Serum NfL associated with anti-NMDA receptor encephalitis.

INTRODUCTION: Neurofilament light chains (NfL) have been reported as potential markers for neuronal-axonal injury in neuroinflammatory diseases. In the current study, we describe serum NfL levels as a prognostic marker for anti-N-methyl-D-aspartate receptor encephalitis (NMDARE). METHODS: Serum levels of NfL of 64 patients with anti-NMDARE and 84 healthy controls were measured by Simoa. The anti-NMDAR Encephalitis One-Year Functional Status (NEOS) score, Modified Rankin Scale (mRS) scores, and clinical and cerebrospinal fluid parameters were evaluated in patients with anti-NMDARE. Meanwhile, we performed a receiver-operator characteristic analysis to assess the power of the serum NFL in predicting the 1-year functional status. RESULTS: Serum NfL levels were significantly elevated in patients with anti-NMDARE compared to healthy controls (p < 0.001, padjusted < 0.001), especially in patients with severe impairments (mRS > 3 vs ≤ 3, p = 0.035) or with limited response to treatment (vs. favorable outcome, p = 0.011). Serum NFL was positively associated with the initial admission mRS (r = 0.23, p = 0.072) and 1-year mRS (r = 0.29, p = 0.018). The AUC of serum NfL and NEOS score for 1-year poor functional status was 0.697 (95% CI 0.527-0.866, p = 0.011), 0.753 (95% CI 0.616-0.890, p = 0.001), respectively. Furthermore, AUC of the combination of serum NfL and NEOS was 0.815 (95% CI 0.680-0.950, p < 0.001). CONCLUSION: Our findings show that serum NfL levels evaluated in anti-NMDAR encephalitis may be a good predictor of the risk of 1-year poor functional status.

Basal metabolic rate and risk of multiple sclerosis: a Mendelian randomization study.

To determine the relationship between basal metabolic rate (BMR) and multiple sclerosis (MS) susceptibility, we analyzed genome-wide association study (GWAS) summary statistics data from the International Multiple Sclerosis Genetics Consortium on a total of 115,803 participants of European descent, including 47,429 patients with MS and 68,374 controls. We selected 378 independent genetic variants strongly associated with BMR in a GWAS involving 454,874 participants as instrumental variables to examine a potential causal relationship between BMR and MS. A genetically predicted higher BMR was associated with a greater risk of MS (odds ratio [OR]: 1.283 per one standard deviation increase in BMR, 95% confidence interval [CI]: 1.108-1.486, P = 0.001). Moreover, we used the lasso method to eliminate heterogeneity (Q statistic = 384.58, P = 0.370). There was no pleiotropy in our study and no bias was found in the sensitivity analysis using the leave-one-out test. We provide novel evidence that a higher BMR is an independent causal risk factor in the development of MS. Further work is warranted to elucidate the potential mechanisms.

Meconium-Stained Amniotic Fluid: Impact on Prognosis of Neonatal Bacterial Meningitis.

OBJECTIVES: Clinical data with respect to the impact of meconium on the prognosis of neonatal bacterial meningitis are scarce. Therefore, in this study, we aimed to determine whether meconium-stained amniotic fluid (MSAF) represents a risk factor for poor prognosis of neonatal bacterial meningitis in a confirmed case population. METHODS: This was a retrospective cohort study of 256 neonates diagnosed with bacterial meningitis hospitalized at one of three hospitals in Shantou, China, between October 2013 and September 2018. Clinical manifestation, laboratory test results and treatment were compared between the two groups, with outcomes dichotomized into 'good' or 'poor' prognosis. Multivariate analysis and follow-up logistic regression analysis were used to identify predictive factors of a poor outcome. RESULTS: Of the 256 neonates with BM, 95 (37.1%) had a good prognosis at discharge and 161 (62.9%) had a poor prognosis. In the poor prognosis group, 131/161 (79.4%) neonates had a permanent neurological sequelae and 19 (11.8%) had ≥2 sequelae. Of note, 11 neonates died. The rate of poor prognosis of BM was significantly higher among neonates with than without MSAF (26.1% vs. 12.6%, respectively; p < 0.05). A logistic multivariate analysis to evaluate the prognostic effect of MSAF to BM showed that neonatal with MSAF is more likely to have a worse prognosis of BM [unadjusted odds ratio (OR), 2.44, 95% confidence interval (CI), 1.24-5.10; adjusted OR, 2.31; 95% CI, 1.09-5.17]. CONCLUSION: MSAF is significantly associated with poor prognosis of neonatal bacterial meningitis. Therefore, in case of MSAF, more attention should be paid to neonatal bacterial meningitis.

Serum neurofilament light chain and glial fibrillary acidic protein in AQP4-IgG-seropositive neuromyelitis optica spectrum disorders and multiple sclerosis: A cohort study.

We investigated the serum neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP) levels in a cohort of Chinese patients with neuromyelitis optica spectrum disorders (NMOSD) and multiple sclerosis (MS) in relation to clinical disease course and treatment. sNfL and sGFAP levels were determined by ultrasensitive single molecule array (Simoa) assay in patients with NMOSD (n = 102) and MS (n = 98) and healthy controls (HCs; n = 84). Notably, 13 patients with NMOSD and 27 patients with MS were enrolled in the 1-year follow-up cohort. Levels were compared with data such as clinical course, disease duration, Expanded Disability Status Scale (EDSS) score, and lesions on MRI. Higher levels of sNfL and sGFAP were found in subjects with NMOSD and MS than in HCs (sNfL, median 12.11, 17.5 vs. 8.88 pg/ml, p < .05; sGFAP, median 130.2, 160.4 vs. 80.01 pg/ml, p < .05). Moreover, sNfL levels were higher in the relapse phase of MS than in the relapse phase of NMOSD (30.02 vs. 14.57 pg/ml, p < .05); sGFAP levels were higher in the remission phase of MS than in the remission phase of NMOSD (159.8 vs. 124.5 pg/ml, p < .01). A higher sGFAP/sNfL quotient at relapse differentiated NMOSD from MS. Multivariate analyses indicated that sGFAP levels were associated with the EDSS score in NMOSD (p < .05). At the 1-year follow-up, sNfL and sGFAP levels were both decreased in NMOSD patients in remission, while only sNfL levels were decreased in MS patients in remission. sGFAP and sNfL are potential blood biomarkers for diagnosing and monitoring NMOSD and MS.

An explainable supervised machine learning predictor of acute kidney injury after adult deceased donor liver transplantation.

BACKGROUND: Early prediction of acute kidney injury (AKI) after liver transplantation (LT) facilitates timely recognition and intervention. We aimed to build a risk predictor of post-LT AKI via supervised machine learning and visualize the mechanism driving within to assist clinical decision-making. METHODS: Data of 894 cases that underwent liver transplantation from January 2015 to September 2019 were collected, covering demographics, donor characteristics, etiology, peri-operative laboratory results, co-morbidities and medications. The primary outcome was new-onset AKI after LT according to Kidney Disease Improving Global Outcomes guidelines. Predicting performance of five classifiers including logistic regression, support vector machine, random forest, gradient boosting machine (GBM) and adaptive boosting were respectively evaluated by the area under the receiver-operating characteristic curve (AUC), accuracy, F1-score, sensitivity and specificity. Model with the best performance was validated in an independent dataset involving 195 adult LT cases from October 2019 to March 2021. SHapley Additive exPlanations (SHAP) method was applied to evaluate feature importance and explain the predictions made by ML algorithms. RESULTS: 430 AKI cases (55.1%) were diagnosed out of 780 included cases. The GBM model achieved the highest AUC (0.76, CI 0.70 to 0.82), F1-score (0.73, CI 0.66 to 0.79) and sensitivity (0.74, CI 0.66 to 0.8) in the internal validation set, and a comparable AUC (0.75, CI 0.67 to 0.81) in the external validation set. High preoperative indirect bilirubin, low intraoperative urine output, long anesthesia time, low preoperative platelets, and graft steatosis graded NASH CRN 1 and above were revealed by SHAP method the top 5 important variables contributing to the diagnosis of post-LT AKI made by GBM model. CONCLUSIONS: Our GBM-based predictor of post-LT AKI provides a highly interoperable tool across institutions to assist decision-making after LT.

To Improve Protein Sequence Profile Prediction through Image Captioning on Pairwise Residue Distance Map.

Protein sequence profile prediction aims to generate multiple sequences from structural information to advance the protein design. Protein sequence profile can be computationally predicted by energy-based or fragment-based methods. By integrating these methods with neural networks, our previous method, SPIN2, has achieved a sequence recovery rate of 34%. However, SPIN2 employed only one-dimensional (1D) structural properties that are not sufficient to represent three-dimensional (3D) structures. In this study, we represented 3D structures by 2D maps of pairwise residue distances and developed a new method (SPROF) to predict protein sequence profiles based on an image captioning learning frame. To our best knowledge, this is the first method to employ a 2D distance map for predicting protein properties. SPROF achieved 39.8% in sequence recovery of residues on the independent test set, representing a 5.2% improvement over SPIN2. We also found the sequence recovery increased with the number of their neighbored residues in 3D structural space, indicating that our method can effectively learn long-range information from the 2D distance map. Thus, such network architecture using a 2D distance map is expected to be useful for other 3D structure-based applications, such as binding site prediction, protein function prediction, and protein interaction prediction. The online server and the source code is available at http://biomed.nscc-gz.cn and https://github.com/biomed-AI/SPROF , respectively.

Infection deteriorating hepatitis B virus related acute-on-chronic liver failure: a retrospective cohort study.

BACKGROUND: Infection is common in acute-on-chronic liver failure (ACLF), which may worsen the clinical condition and prognosis. However, the characteristics of infection and its influence on prognosis in hepatitis B virus related ACLF (HBV-ACLF) as defined by the European Association for the Study of the Liver (EASL) have not been clarified. We aimed to investigate the characteristics of infection and its influence on mortality in patients with HBV-ACLF defined by EASL in China. METHODS: We performed a retrospective cohort study in patients with HBV-ACLF defined by EASL in a single center from January 2015 to December 2017. These patients were divided into two groups with and without infection. The incidence, sites of infection, isolated strains, and risk factors associated with mortality were evaluated. RESULTS: A total of 289 patients were included, among them 185 (64.0%) were diagnosed with an infection. The most common type of infection was pneumonia (55.7%), followed by spontaneous bacterial peritonitis (47.6%) and others. The gram-negative bacteria were the most frequent (58.3%). Patients with one, two, and three or more infection sites had a gradually increasing incidence of sepsis (P < 0.01), septic shock (P < 0.001), and ACLF-3 (P < 0.05). Also, patients with infection isolated one, two, and three or more strains showed a growing incidence of sepsis (P < 0.01) and septic shock (P < 0.001). Patients with infection showed a significantly higher 28-day mortality than those without (P < 0.01), especially in patients with ACLF-3. Infection was identified as an independent risk factor for 28-day mortality in all HBV-ACLF patients. Pneumonia and sepsis were identified as independent predictors of 28-day mortality for patients with infection. CONCLUSIONS: Infection is associated with severe clinical course and high mortality in HBV-ACLF defined by EASL. The increased number of infection sites or isolated strains was associated with the occurrence of sepsis and septic shock. Pneumonia and sepsis were independent predictors for mortality in HBV-ACLF patients with infection.

Apolipoprotein B and renal function: across-sectional study from the China health and nutrition survey.

BACKGROUND: Chronic kidney disease (CKD) is a worldwide public health problem characterized by changes in kidney structure and function, usually leading to a loss of kidney function. The identification of risk factors and management of patients with early-stage CKD may slow or prevent the progression to end-stage renal disease. METHODS: This study used the population-based cohort database from the China Health and Nutrition Survey (CHNS). Data from 11,978 patients were collected from the 2009 to 2011 wave of the CHNS. After removing patients with missing data, we finally included 8322 participants. A cross-sectional design was used to assess the association between Apolipoprotein B (Apo-B) levels and CKD. We used overlapping covariates to develop 5 models to evaluate the odds ratios. RESULTS: Among the study participants, patients with estimated glomerular filtration rates (eGFR) < 60 ml/min/1.73m2were more likely to have increased Apo-B levels (> 1.2 mmol/L, 19.41%), likely to be elderly (> 65 years, 61.76%), likely to be female (61.21%), and likely to be less educated (< 6 years and > 6 & ≤12 years, 32.07 and 52.44%, respectively).The significant association between Apo-B and CKD defined by eGFR even after adjusting for confounders including demographic characteristics, nutritional status, comorbidities, biochemical indicators, and lifestyle factors. In addition, stratified analyses showed that young and middle age (< 65 years), being overweight (body mass index [BMI] > 25 kg/m2), and hyperuricemia were associated with higher risks of CKD stages. CONCLUSIONS: The results of this Chinese population-based study revealed a strong positive correlation between Apo-B and CKD stages. The current findings were obtained from an epidemiologic study; therefore, these data cannot directly address the mechanisms of disease progression. The underlying mechanisms require analysis in future independent validation and prospective cohort studies.

Association of living arrangements with depressive symptoms among older adults in China: a cross-sectional study.

BACKGROUND: Depression is regarded as a major public health concern in our society. While living arrangements as a structural factor of social support may contribute to older adults' depression. Our study aims to investigate the association between living arrangements and depressive symptoms among older adults in the whole China, and to explore whether such influences differ by genders. METHODS: Data were obtained from the 2015 China Health and Retirement Longitudinal Study. The sample was comprised of 6001 individuals aged ≥60 years. Depressive symptoms were measured by the 10-item Short-Form Center for Epidemiological Studies Depression. Independent variables were divided into 4 groups, considering living with/without a spouse and living with/without a child. The multivariate logistic regression was used to estimate the relationship between living arrangements and depressive symptoms in four models. RESULTS: Compared with living only with a spouse, people living with a spouse and child, or living alone were more likely to have depressive symptoms (odds ratio = 1.23 95% CI 1.06-1.42 and 1.40 95% CI 1.03-1.92, respectively). Women were more associated with depressive symptoms (odds ratio = 2.13), but there were no significant associations between living arrangements and depressive symptoms among women. Men living with a spouse and a child had stronger positively depressive symptoms (odds ratio = 1.37). CONCLUSIONS: Older adults living alone, or living with both a child and spouse were more likely to have depressive symptoms. It is important to provide more social services for those older adult, particularly for men living with a spouse and child.

MiR-222 targeted PUMA to improve sensitization of UM1 cells to cisplatin.

microRNAs have been shown to play critical roles in regulating the chemosensitivity of cancer cells. As a member of the oncogenic miRNAs (oncomiRs), miR-222 has been reported to drive the oncogenesis of many types of malignancies. However, little is known concerning the specific role of miR-222 in human oral squamous cell carcinoma (OSCC). The present study explored the role and mechanism of miR-222 in increasing the expression of p53 up-regulated modulator of apoptosis (PUMA) and enhancing the sensitivity of OSCC to cisplatin (CDDP). Results showed that antisense (As)-miR-222 inhibits the expression of miR-222. In contrast, PUMA was dramaticallyup-regulated. IC50 values were significantly decreased in cells treated with As-miR-222 combined with CDDP, to a greater extent than in cells treated with CDDP alone. Furthermore, As-miR-222 enhanced apoptosis and inhibited the invasiveness of UM1 cells. Analysis of the above data suggested that, in UM1 cells, there might be a regulatory loop between miR-222 and PUMA, and that miR-222 inhibition increased the chemosensitivity to CDDP. These findings demonstrated that down-regulation of miR-222 could enhance the chemosensitivity of human OSCC cells to CDDP, and that the combination of As-miR-222 and CDDP could be an effective therapeutic strategy by boosting the expression of PUMA for controlling the growth of OSCC.

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.

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.

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.