Development and validation of a deep learning-based survival prediction model for pediatric glioma patients: A retrospective study using the SEER database and Chinese data.

OBJECTIVE: Develop a time-dependent deep learning model to accurately predict the prognosis of pediatric glioma patients, which can assist clinicians in making precise treatment decisions and reducing patient risk. STUDY DESIGN: The study involved pediatric glioma patients from the Surveillance, Epidemiology, and End Results (SEER) Registry (2000-2018) and Tangdu Hospital in China (2010-2018) within specific time frames. For training, we selected two neural network-based algorithms (DeepSurv, neural multi-task logistic regression [N-MTLR]) and one ensemble learning-based algorithm (random survival forest [RSF]). Additionally, a multivariable Cox proportional hazard (CoxPH) model was developed for comparison purposes. The SEER dataset was randomly divided into 80 % for training and 20 % for testing, while the Tangdu Hospital dataset served as an external validation cohort. Super-parameters were fine-tuned through 1000 repeated random searches and 5-fold cross-validation on the training cohort. Model performance was assessed using the concordance index (C-index), Brier score, and Integrated Brier Score (IBS). Furthermore, the accuracy of predicting survival at 1, 3, and 5 years was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and the area under the ROC curves (AUC). The generalization ability of the model was assessed using the C-index of the Tangdu Hospital data, ROC curves for 1, 3, and 5 years, and AUC values. Lastly, decision curve analysis (DCA) curves for 1, 3, and 5-year time frames are provided to assess the net benefits across different models. RESULTS: A total of 9532 patients with pediatric glioma were included in this study, comprising 9274 patients from the SEER database and 258 patients from Tangdu Hospital in China. The average age at diagnosis was 9.4 ± 6.2 years, and the average survival time was 96 ± 66 months. Through comprehensive performance comparison, the DeepSurv model demonstrated the highest effectiveness, with a C-index of 0.881 on the training cohort. Furthermore, it exhibited excellent accuracy in predicting the 1-year, 3-year, and 5-year survival rates (AUC: 0.903-0.939). Notably, the DeepSurv model also achieved remarkable performance and accuracy on the Chinese dataset (C-index: 0.782, AUC: 0.761-0.852). Comprehensive analysis of DeepSurv, N-MTLR, and RSF revealed that tumor stage, radiotherapy, histological type, tumor size, chemotherapy, age, and surgical method are all significant factors influencing the prognosis of pediatric glioma. Finally, an online version of the pediatric glioma survival predictor based on the DeepSurv model has been established and can be accessed through https://pediatricglioma-tangdu.streamlit.app. CONCLUSIONS: The DeepSurv model exhibits exceptional efficacy in predicting the survival of pediatric glioma patients, demonstrating strong performance in discrimination, calibration, stability, and generalization. By utilizing the online version of the pediatric glioma survival predictor, which is based on the DeepSurv model, clinicians can accurately predict patient survival and offer personalized treatment options.

Evaluating TRAIL and IP-10 alterations in vaccinated pregnant women after COVID-19 diagnosis and their correlation with neutralizing antibodies.

Background: This study evaluates tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and interferon-γ-induced protein-10 (IP-10) in pregnant women with COVID-19 and their newborns, exploring the effects of antiviral treatments and vaccine-induced neutralizing antibody (Nab) inhibition on these key viral infection biomarkers. Methods: We studied 61 pregnant women with past COVID-19 and either three (n=56) or four (n=5) doses of vaccination, and 46 without COVID-19 but vaccinated. We analyzed them and their newborns' blood for TRAIL, IP-10, and Nab levels using enzyme-linked immunosorbent assays (ELISA), correlating these with other clinical factors. Results: Our study found lower TRAIL but higher IP-10 levels in maternal blood than neonatal cord blood, irrespective of past COVID-19 diagnosis. Cases diagnosed with COVID-19 < 4 weeks previously had higher maternal blood TRAIL levels (16.49 vs. 40.81 pg/mL, p=0.0064) and IP-10 (154.68 vs. 225.81 pg/mL, p=0.0170) than those never diagnosed. Antiviral medication lowered TRAIL and IP-10 in maternal blood without affecting Nab inhibition (TRAIL: 19.24 vs. 54.53 pg/mL, p=0.028; IP-10: 158.36 vs. 255.47 pg/mL, p=0.0089). TRAIL and IP-10 levels were similar with three or four vaccine doses, but four doses increased Nab inhibition (p=0.0363). Previously COVID-19 exposed pregnant women had higher Nab inhibition (p < 0.0001). No obvious correlation was found among TRAIL, IP-10, and Nab inhibition level. Conclusions: Our study suggests that lower maternal TRAIL and higher IP-10 levels compared to neonatal cord blood coupled with a rise in both markers following COVID-19 diagnosis that could be reduced by antivirals indicates a correlation to infection severity. Higher vaccine doses enhance Nab inhibition, irrespective of antiviral medication use and independent of TRAIL or IP-10 levels, highlighting the significance and safety of adequate vaccination and antiviral use post-diagnosis in pregnant women.

Catheter and Non-Catheter-Related Venous Thromboembolism in Cancer Patients: Survival, Anticoagulation Efficacy, and Safety.

PURPOSE: To investigate the differences in survival after venous thromboembolism (VTE) and anticoagulation efficacy and safety between catheter (CRVTE) and non-catheter-related VTE (NCRVTE) in cancer patients. METHODS: A retrospective research was conducted, and consecutive cancer (digestive, respiratory, genitourinary, blood and lymphatic, and the other cancers) patients with VTE were enrolled. The anticoagulation therapies included low-molecular-weight heparin (LMWH), warfarin, new type of direct oral anticoagulants (NDOACs), LMWH combined with warfarin, and LMWH combined with NDOACs. Data were collected from the electronic medical record database of our hospital and were analyzed accordingly by Kruskal-Wallis H Test, Chi-square test, Fisher's exact test, Logistic regressions, Kaplan-Meier analysis, and Cox regressions. RESULTS: 263 patients were included, median age in years (interquartile range) was 64(56-71) and 60.5% were male. VTE recurrence rate was 16.7% in CRVTE group which was significantly lower than 34.8% in NCRVTE group (P = .032). Heart diseases were independently associated with VTE recurrence (P = .025). Kaplan-Meier survival estimates at 1, 2, and 3 years for CRVTE group were 62.5%, 60.0%, and 47.5%, respectively, compared with 47.9% (P = .130), 38.7% (P = .028), and 30.1% (P = .046), respectively, for NCRVTE group. Cox regression showed surgery (P = .003), anticoagulation therapy types (P = .009), VTE types (P = .006) and cancer types (P = .039) were independent prognostic factors for 3-year survival after VTE. Nonmajor and major bleeding were not significantly different (P = .417). Anticoagulation therapy types were independently associated with the bleeding events (P = .030). CONCLUSIONS: Cancer patients with CRVTE potentially have a better anticoagulation efficacy and survival compared to NCRVTE, and the anticoagulation safety seems no significant difference.

Transcriptional activation of PINK1 by MyoD1 mediates mitochondrial homeostasis to induce renal calcification in pediatric nephrolithiasis.

This study aims to uncover the molecular mechanisms underlying pediatric kidney stone formation induced by renal calcium deposition by utilizing high-throughput sequencing data to reveal the regulation of PINK1 by MyoD1. We performed transcriptome sequencing on peripheral blood samples from healthy children and children with kidney stones to obtain differentially expressed genes (DEGs). Genes related to mitochondrial oxidative stress were obtained from the Genecards website and intersected with DEGs to obtain candidate target genes. Additionally, we conducted protein-protein interaction (PPI) analysis using the STRING database to identify core genes involved in pediatric kidney stone disease (KSD) and predicted their transcription factors using the hTFtarget database. We assessed the impact of MyoD1 on the activity of the PINK1 promoter using dual-luciferase reporter assays and investigated the enrichment of MyoD1 on the PINK1 promoter through chromatin immunoprecipitation (ChIP) experiments. To validate our hypothesis, we selected HK-2 cells and established an in vitro kidney stone model induced by calcium oxalate monohydrate (COM). We evaluated the expression levels of various genes, cell viability, volume of adherent crystals in each group, as well as mitochondrial oxidative stress in cells by measuring mitochondrial membrane potential (Δψm), superoxide dismutase (SOD) activity, reactive oxygen species (ROS), and malondialdehyde (MDA) content. Mitochondrial autophagy was assessed using mtDNA fluorescence staining and Western blot analysis of PINK1-related proteins. Apoptosis-related proteins were evaluated using Western blot analysis, and cell apoptosis was measured using flow cytometry. Furthermore, we developed a rat model of KSD and assessed the expression levels of various genes, as well as the pathologic changes in rat renal tissues using H&E and von Kossa staining, transmission electron microscopy (TEM), and the expression of creatinine, blood urea nitrogen, neutrophil gelatinase-associated lipocalin (NGAL), and kidney injury molecule-1 (KIM-1) to evaluate the mitochondrial oxidative stress in vivo (through measurement of Δψm, SOD activity, ROS, and MDA content). Mitochondrial autophagy was evaluated by Western blot analysis of PINK1-associated proteins. Apoptosis-related proteins were detected using Western blot analysis, and cellular apoptosis was examined using cell flow cytometry and TUNEL staining. Bioinformatics analysis revealed that the PINK1 gene is upregulated and vital in pediatric kidney stone patients. Our in vitro and in vivo experiments demonstrated that silencing PINK1 could inhibit kidney stone formation by suppressing mitochondrial oxidative stress both in vitro and in vivo. We identified MyoD1 as an upstream transcription factor of PINK1 that contributes to the occurrence of pediatric kidney stones through the activation of PINK1. Our in vivo and in vitro experiments collectively confirmed that silencing MyoD1 could inhibit mitochondrial oxidative stress, mitochondrial autophagy, and cellular apoptosis in a rat model of kidney stones by downregulating PINK1 expression, consequently suppressing the formation of kidney stones. In this study, we discovered that MyoD1 may promote kidney stone formation and development in pediatric patients by transcriptionally activating PINK1 to induce mitochondrial oxidative stress.

Paper-Based procalcitonin and Interleukin-6 test strip with Spectrum-Based optical reader for enterovirus severity differentiation in children.

Infectious diseases significantly impact global health, necessitating prompt diagnosis to mitigate life-threatening sepsis risk. Identifying patients at risk of severe neurological complications from enterovirus infections is challenging due to nonspecific initial presentations. Point-of-care testing (POCT) has emerged as a transformative tool, with low-cost lateral-flow colorimetric assays showing promise in deployable POCT devices. We developed a PCT/IL-6 rapid diagnostic system integrating lateral flow assay (LFA) test strips and a portable optical spectrum reader, allowing simultaneous semi-quantitative measurement of serum PCT and IL-6 within 30 min at the point of care. The system demonstrated a strong correlation with traditional ELISA and effectively differentiated severe pediatric enterovirus cases using serum samples. IL-6 showed superior discriminatory ability over PCT in identifying patients with severe neurological complications. This novel diagnostic platform holds great potential for early sepsis recognition and infectious disease management, especially in resource-limited settings.

Predicting the Risk of In-Hospital Mortality in Traumatic Brain Injury Patients on Invasive Mechanical Ventilation in the Intensive Care Unit: Construction and Validation of an Online Nomogram.

OBJECTIVE: To explore mortality risk factors and to construct an online nomogram for predicting in-hospital mortality in traumatic brain injury (TBI) patients receiving invasive mechanical ventilation (IMV) in intensive care unit (ICU). METHODS: We retrospectively analyzed TBI patients on IMV in ICU from Medical Information Mart for Intensive Care IV database and 2 hospitals. Least absolute shrinkage and selection operation regression and multiple logistic regression were used to detect predictors of in-hospital mortality and to construct an online nomogram. The predictive performance of nomogram was evaluated using area under the receiver operating characteristic curves (AUC), calibration curves, decision curve analysis, and clinical impact curves. RESULTS: Five hundred ten from Medical Information Mart for Intensive Care IV database were enrolled for nomogram construction (80%, n = 408) and internal validation (20%, n = 102). One hundred eighty-five from 2 hospitals were enrolled for external validation. Least absolute shrinkage and selection operation-logistic regression revealed predictors of in-hospital mortality among TBI patients on IMV in ICU included Glasgow Coma Scale (GCS) after ICU admission, Acute Physiology Score III (APS III) after ICU admission, neutrophil and lymphocyte ratio after IMV, blood urea nitrogen after IMV, arterial serum lactate after IMV, and in-hospital tracheotomy. The AUC, calibration curves, decision curve analysis, and clinical impact curves indicated the nomogram had good discrimination, calibration, clinical benefit, and applicability. The multimodel comparisons revealed the nomogram had higher AUC than GCS, APS III, and Simplified Acute Physiology Score II. CONCLUSIONS: We constructed and validated an online nomogram based on routinely recorded factors at admission to ICU and at the beginning of IMV to target prediction of in-hospital mortality among TBI patients on IMV in ICU.

Single-cell dissection of the human blood-brain barrier and glioma blood-tumor barrier.

The blood-brain barrier (BBB) serves as a crucial vascular specialization, shielding and nourishing brain neurons and glia while impeding drug delivery. Here, we conducted single-cell mRNA sequencing of human cerebrovascular cells from 13 surgically resected glioma samples and adjacent normal brain tissue. The transcriptomes of 103,230 cells were mapped, including 57,324 endothelial cells (ECs) and 27,703 mural cells (MCs). Both EC and MC transcriptomes originating from lower-grade glioma were indistinguishable from those of normal brain tissue, whereas transcriptomes from glioblastoma (GBM) displayed a range of abnormalities. Among these, we identified LOXL2-dependent collagen modification as a common GBM-dependent trait and demonstrated that inhibiting LOXL2 enhanced chemotherapy efficacy in both murine and human patient-derived xenograft (PDX) GBM models. Our comprehensive single-cell RNA sequencing-based molecular atlas of the human BBB, coupled with insights into its perturbations in GBM, holds promise for guiding future investigations into brain health, pathology, and therapeutic strategies.

Logistic regression analysis of risk factors influencing childhood enuresis: a comprehensive survey study.

OBJECTIVE: To identify risk factors associated with childhood enuresis. METHODS: We conducted a retrospective analysis of 146 children aged 6 to 13 years diagnosed with enuresis at Anhui Province Children's Hospital between June 2020 and June 2023. Children were categorized based on bedwetting frequency: those with less frequent episodes (once a week to twice a month) were placed in the mild group (60 cases), and those with frequent episodes (two or more times per week) were placed in the severe group (86 cases). We compared demographic data, family histories, and personal characteristics between the groups and performed logistic regression to determine significant risk factors. RESULTS: The analysis revealed that a stubborn personality, nocturnal polyuria, sleep-wake disorders, and bladder dysfunction significantly increased the risk of enuresis (P < 0.05). These findings underscore the importance of a holistic approach in evaluating psychological aspects, nocturnal urination patterns, sleep quality, and bladder health in managing enuresis. CONCLUSION: The study identifies stubborn personality, nocturnal polyuria, sleep-wake disorders, and bladder dysfunction as independent risk factors for childhood enuresis. Understanding these factors is crucial for developing targeted interventions that can enhance the management and outcomes of enuresis. Future research should explore the interrelationships among these factors to refine preventive and therapeutic strategies for early childhood enuresis.

Case report: Cytokine and miRNA profiling in multisystem inflammatory syndrome in children.

Multisystem inflammatory syndrome in children (MIS-C) is an imperative pediatric inflammatory condition closely linked to COVID-19, which garners substantial attention since the onset of the pandemic. Like Kawasaki illness, this condition is characterized by an overactive immune response, leading to symptoms including pyrexia, cardiac and renal complications. To elucidate the pathogenesis of MIS-C and identify potential biomarkers, we conducted an extensive examination of specific cytokines (IL-6, IL-1ß, IL-6R, IL-10, and TNF-α) and microRNA (miRNA) expression profiles at various intervals (ranging from 3 to 20 days) in the peripheral blood sample of a severely affected MIS-C patient. Our investigation revealed a gradual decline in circulating levels of IL-6, IL-1ß, IL-10, and TNF-α following intravenous immune globulin (IVIG) therapy. Notably, IL-6 exhibited a significant reduction from 74.30 to 1.49 pg./mL, while IL-6R levels remained consistently stable throughout the disease course. Furthermore, we observed an inverse correlation between the expression of hsa-miR-596 and hsa-miR-224-5p and the aforementioned cytokines. Our findings underscore a robust association between blood cytokine and miRNA concentrations and the severity of MIS-C. These insights enhance our understanding of the genetic regulatory mechanisms implicated in MIS-C pathogenesis, offering potential avenues for early biomarker detection and therapy monitoring through miRNA analysis.

Cognitive impairment in patients with bipolar disorder alone versus those with bipolar disorder comorbid with borderline personality disorder.

BACKGROUND: Bipolar disorder (BD) is a severe mental illness. BD often coexists with borderline personality disorders, making the condition more complex. AIM: To explore the differences in cognitive impairment between patients with BD and those with BD comorbid with borderline personality disorder. METHODS: Eighty patients with BD and comorbid borderline personality disorder and 80 patients with BD alone were included in groups A and B, respectively, and 80 healthy volunteers were included as controls. Cognitive function in each group was evaluated using the Chinese version of the repeatable battery for the assessment of neuropsychological status (RBANS), the Stroop color-word test, and the Wechsler intelligence scale-revised (WAIS-RC). RESULTS: The indices of the RBANS, Stroop color-word test, and WAIS-RC in groups A and B were significantly lower than those of the control group (P < 0.05). Group A had significantly longer Stroop color-word test times for single-character, single-color, double-character, and double-color, lower scores of immediate memory, visual breadth, verbal function dimensions and total score of the RBANS, as well as lower scores of verbal IQ, performance IQ, and overall IQ of the WAIS-RC compared with group B (P < 0.05). Compared to group B, group A exhibited significantly longer single-character time, single-color time, double-character time, and double-color time in the Stroop color-word test (P < 0.05). CONCLUSION: The cognitive function of patients with BD complicated with borderline personality disorder is lower than that of patients with BD.

Intermittent lysis on a single paper-based device to extract exosomal nucleic acid biomarkers from biological samples for downstream analysis.

As the role of exosomes in physiological and pathological processes has been properly perceived, harvesting them and their internal components is critical for subsequent applications. This study is a debut of intermittent lysis, which has been integrated into a simple and easy-to-operate procedure on a single paper-based device to extract exosomal nucleic acid biomarkers for downstream analysis. Exosomes from biological samples were captured by anti-CD63-modified papers before being intermittently lysed by high-temperature, short-time treatment with double-distilled water to release their internal components. Exosomal nucleic acids were finally adsorbed by sol-gel silica for downstream analysis. Empirical trials not only revealed that sporadically dropping 95 °C ddH2O onto the anti-CD63-modified papers every 5 min for 6 times optimized the exosomal nucleic acids extracted by the anti-CD63 paper but also verified that the whole deployed procedure is applicable for point-of-care testing (POCT) in low-resource areas and for both in vitro (culture media) and in vivo (plasma and chronic lesion) samples. Importantly, downstream analysis of exosomal miR-21 extracted by the paper-based procedure integrated with this novel technique discovered that the content of exosomal miR-21 in chronic lesions related to their stages and the levels of exosomal carcinoembryonic antigen originated from colorectal cancer cells correlated to their exosomal miR-21.

Evaluation of a novel vaginal cells self-sampling device for human papillomavirus testing in cervical cancer screening: A clinical trial assessing reliability and acceptability.

Cervical cancer is a significant public health concern, particularly in low- and middle-income countries where resources for prevention and treatment are limited. Routine screening, such as the Papanicolaou test (Pap smears) and human papillomavirus (HPV) testing, plays a crucial role in the early detection and prevention of cervical cancer. However, the participation rate in cervical cancer screening programs remains below optimal levels due to various factors. This study aimed to evaluate the reliability and acceptability of the HygeiaTouch Self Sampling Kit for Women in collecting vaginal samples for HPV typing, comparing the results with samples collected by physicians. The study included 1210 women aged 21-65 from three medical centers in Taiwan. The findings indicated that the self-sampling kit was as effective as physician-collected specimens in terms of obtaining valid samples and identifying HPV. The agreement between the two methods was 88%, with a κ value of 0.75. Furthermore, the study assessed the mechanical characteristics of the self-sampling applicator through tensile, bending, and torque tests, and determined that it was safe for intravaginal use. Additionally, the study evaluated the safety and satisfaction of self-sampling and found a low rate of adverse events (0.7%) and high levels of satisfaction (over 90%) among participants. Overall, we demonstrated that the HygeiaTouch Self Sampling Kit for Women is a reliable and acceptable device for HPV testing and cervical screening, providing a convenient, safe, and effective alternative for women.

Risk Factors and Predictive Nomogram for Survival in Elderly Patients with Brain Glioma.

OBJECTIVE: To determine the factors that contribute to the survival of elderly individuals diagnosed with brain glioma and develop a prognostic nomogram. METHODS: Data from elderly individuals (age ≥65 years) histologically diagnosed with brain glioma were sourced from the Surveillance, Epidemiology, and End Results (SEER) database. The dataset was randomly divided into a training cohort and an internal validation cohort at a 6:4 ratio. Additionally, data obtained from Tangdu Hospital constituted an external validation cohort for the study. The identification of independent prognostic factors was achieved through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, enabling the construction of a nomogram. Model performance was evaluated using C-index, ROC curves, calibration plot and decision curve analysis (DCA). RESULTS: A cohort of 20 483 elderly glioma patients was selected from the SEER database. Five prognostic factors (age, marital status, histological type, stage, and treatment) were found to significantly impact overall survival (OS) and cancer-specific survival (CSS), with tumor location emerging as a sixth variable independently linked to CSS. Subsequently, nomogram models were developed to predict the probabilities of survival at 6, 12, and 24 months. The assessment findings from the validation queue indicate a that the model exhibited strong performance. CONCLUSION: Our nomograms serve as valuable prognostic tools for assessing the survival probability of elderly glioma patients. They can potentially assist in risk stratification and clinical decision-making.

The Force-Frequency Characteristics of Quartz Wafers under a Cantilever Beam Structure.

This study investigated the force-frequency characteristics of quartz wafers inside a cantilever beam frame. Firstly, the force-frequency coefficient formula of quartz wafers with fixed ends under axial force was analyzed. Firstly, the formula for the force-frequency coefficient of quartz wafers with fixed ends under axial force was analyzed. A force-frequency coefficient formula suitable for cantilever beam structures was derived by considering the changes in surface stress and stiffness of quartz wafers with fixed ends and one end under force on the other. Subsequently, the formula's accuracy was verified by experiments, and the accuracy was more than 92%. In addition, strain simulation analysis was performed on three different shapes of quartz wafers, and experimental verification was carried out on two of them. The results revealed that trapezoidal quartz wafers and cantilever beam structures exhibited superior stress distribution to rectangular chips. Furthermore, by positioning electrodes at various locations on the surface of the quartz chip, it was observed that, as the electrodes moved closer to the fixed end, the force-frequency coefficient of the rectangular quartz chip increased, along with an increase in chip strain under the cantilever structure. In summary, this study provides a new approach for designing cantilever quartz resonator sensors in the future.

A retrospective study of uropathogen and its antibiotic resistance among children with urinary tract infection from a single center in China.

Urinary tract infection (UTI) is a well-known bacterial infection posing serious health problem in children. A retrospective study was conducted to explore the uropathogen and its antibiotic resistance in children with UTI. Data of urine culture and antimicrobial susceptibility test was collected. Consequently, 840 children were included. The overall culture-positive UTI was 458 (54.52 %) with Escherichia coli 166 (36.24 %), followed by Enterococcus faecalis 59 (12.88 %), Enterococcus faecium 70 (15.28 %) and others. They were highly resistant to the most commonly used antibiotics. In 694 children with complicated UTI, there were 8 children with fungal infection. Multiple drug resistance (MDR) was recorded in 315 (80.98 %). The overall proportion of Extended Spectrum ß-Lactamase (ESßL) production was 25 (6.43 %). In 146 children with simple UTI, MDR were also detected in 47 (77.05 %). There were 6 (9.84 %) positive for ESßL production. Our study found that complicated UTI was relatively common. Escherichia coli was the most prevalent isolate, followed by Enterococcus faecium and Enterococcus faecalis. These organisms were highly resistant to the most commonly used antibiotics. Relatively high prevalence of MDR and low ESßL-producing organisms were observed.

COVID-19 Vaccination in Pregnancy: Pilot Study of Plasma MicroRNAs Associated with Inflammatory Cytokines after COVID-19 mRNA Vaccination.

BACKGROUND: The impact of mRNA COVID-19 vaccines on the immunological profiles of pregnant women remains a crucial area of study. This research aims to explore the specific immunological changes triggered by these vaccines in this demographic. METHODS: In a focused investigation, we examined the effects of mRNA COVID-19 vaccination on microRNA expression in pregnant women. Key microRNAs, including miR-451a, miR-23a-3p, and miR-21-5p, were analyzed for expression changes post-vaccination. Additionally, we assessed variations in S1RBD IgG levels and specific cytokines to gauge the broader immunological response. RESULTS: Post-vaccination, significant expression shifts in the targeted microRNAs were observed. Alongside these changes, we noted alterations in S1RBD IgG and various cytokines, indicating an adapted inflammatory response. Notably, these immunological markers displayed no direct correlation with S1RBD IgG concentrations, suggesting a complex interaction between the vaccine and the immune system in pregnant women. CONCLUSIONS: Our pilot study provides valuable insights into the nuanced effects of the mRNA COVID-19 vaccine on immune dynamics in pregnant women, particularly emphasizing the role of microRNAs. The findings illuminate the intricate interplay between vaccines, microRNAs, and immune responses, enhancing our understanding of these relationships in the context of pregnancy. This research contributes significantly to the growing body of knowledge regarding mRNA COVID-19 vaccines and their specific impact on maternal immunology, offering a foundation for further studies in this vital area.

Fluorescence-based reagent and spectrum-based optical reader for lactoferrin detection in tears: differentiating Sjögren's syndrome from non-Sjögren's dry eye syndrome.

Identification of an early biomarker and effective testing device to differentiate dry eye disease secondary to autoimmune disease (Sjögren's syndrome dry eye disease) from non-Sjögren's dry eye disease are prerequisites for appropriate treatment. We aimed to demonstrate the capacity of a new photo-detection device to evaluate tear lactoferrin levels as a tool for differentiating systemic conditions associated with dry eye disease. Patients with non-Sjögren's and Sjögren's syndrome dry eye disease (n = 54 and n = 52, respectively) and controls (n = 11) were enrolled. All participants completed the Ocular Surface Disease Index questionnaire. Tear collection was performed with Schirmer test, and tear break-up time was examined using a slit lamp. Tear lactoferrin was evaluated using our newly developed photo-detection device. The average lactoferrin concentration was significantly lower in samples from patients with non-Sjögren's dry eye disease (0.337 ± 0.227 mg/mL, n = 54) and Sjögren's syndrome dry eye disease (0.087 ± 0.010 mg/mL, n = 52) than in control samples (1.272 ± 0.54 mg/mL, n = 11) (p < 0.0001). Further, lactoferrin levels were lower in patients with Sjögren's syndrome dry eye disease than in those with non-Sjögren's dry eye disease (p < 0.001). Our cost-effective, antibody-free, highly sensitive photo-detection device for evaluating tear lactoferrin levels can assist ophthalmologists in differentiating different types of dry eye diseases.

Unilateral boundary time series forecasting.

Time series forecasting is an essential tool across numerous domains, yet traditional models often falter when faced with unilateral boundary conditions, where data is systematically overestimated or underestimated. This paper introduces a novel approach to the task of unilateral boundary time series forecasting. Our research bridges the gap in existing methods by proposing a specialized framework to accurately forecast within these skewed datasets. The cornerstone of our approach is the unilateral mean square error (UMSE), an asymmetric loss function that strategically addresses underestimation biases in training data, improving the precision of forecasts. We further enhance model performance through the implementation of a dual model structure that processes underestimated and accurately estimated data points separately, allowing for a nuanced analysis of the data trends. Additionally, feature reconstruction is employed to recapture obscured dynamics, ensuring a comprehensive understanding of the data. We demonstrate the effectiveness of our methods through extensive experimentation with LightGBM and GRU models across diverse datasets, showcasing superior accuracy and robustness in comparison to traditional models and existing methods. Our findings not only validate the efficacy of our approach but also reveal its model-independence and broad applicability. This work lays the groundwork for future research in this domain, opening new avenues for sophisticated analytical models in various industries where precise time series forecasting is crucial.