Immune control in Kawasaki disease knowledge mapping: a bibliometric analysis.

BACKGROUND: Kawasaki disease is a systemic vascular disease with an unclear pathophysiology that primarily affects children under the age of five. Research on immune control in Kawasaki disease has been gaining attention. This study aims to apply a bibliometric analysis to examine the present and future directions of immune control in Kawasaki disease. METHODS: By utilizing the themes "Kawasaki disease," "Kawasaki syndrome," and "immune control," the Web of Science Core Collection database was searched for publications on immune control in Kawasaki disease. This bibliometric analysis was carried out using VOSviewers, CiteSpace, and the R package "bibliometrix." RESULTS: In total, 294 studies on immune control in Kawasaki disease were published in Web of Science Core Collection. The three most significant institutions were Chang Gung University, the University of California San Diego, and Kaohsiung Chang Gung Memorial Hospital. China, the United States, and Japan were the three most important countries. In this research field, Clinical and Experimental Immunology was the top-referred journal, while the New England Journal of Medicine was the most co-cited journal. The Web of Science Core Collection document by McCrindle BW et al. published in 2017 was the most cited reference. Additionally, the author keywords concentrated on "COVID-19," "SARS-CoV-2," and "multisystem inflammatory syndrome in children" in recent years. CONCLUSION: The research trends and advancements in immune control in Kawasaki disease are thoroughly summarised in this bibliometric analysis, which is the first to do so. The data indicate recent research frontiers and hot directions, making it easier for researchers to study the immune control of Kawasaki disease.

Knowledge mapping of neonatal electroencephalogram: A bibliometric analysis (2004-2022).

BACKGROUND: Electroencephalography (EEG), a widely used noninvasive neurophysiological diagnostic tool, has experienced substantial advancements from 2004 to 2022, particularly in neonatal applications. Utilizing a bibliometric methodology, this study delineates the knowledge structure and identifies emergent trends within neonatal EEG research. METHODS: An exhaustive literature search was conducted on the Web of Science Core Collection (WoSCC) database to identify publications related to neonatal EEG from 2004 to 2022. Analytical tools such as VOSviewer, CiteSpace, and the R package "bibliometrix" were employed to facilitate this investigation. RESULTS: The search yielded 2501 articles originating from 79 countries, with the United States and England being the predominant contributors. A yearly upward trend in publications concerning neonatal EEG was observed. Notable research institutions leading this field include the University of Helsinki, University College London, and University College Cork. Clinical Neurophysiology is identified as the foremost journal in this realm, with Pediatrics as the most frequently co-cited journal. The collective body of work from 9977 authors highlights Sampsa Vanhatalo as the most prolific contributor, while Mark Steven Scher is recognized as the most frequently co-cited author. Key terms such as "seizures," "epilepsy," "hypoxic-ischemic encephalopathy," "amplitude-integrated EEG," and "brain injury" represent the focal research themes. CONCLUSION: This bibliometric analysis offers the first comprehensive review, encapsulating research trends and progress in neonatal EEG. It reveals current research frontiers and crucial directions, providing an essential resource for researchers engaged in neonatal neuroscience.

A publicly available newborn ear shape dataset for medical diagnosis of auricular deformities.

Early and accurate diagnosis of ear deformities in newborns is crucial for an effective non-surgical correction treatment, since this commonly seen ear anomalies would affect aesthetics and cause mental problems if untreated. It is not easy even for experienced physicians to diagnose the auricular deformities of newborns and the classification of the sub-types, because of the rich bio-metric features embedded in the ear shape. Machine learning has already been introduced to analyze the auricular shape. However, there is little publicly available datasets of ear images from newborns. We released a dataset that contains quality-controlled photos of 3,852 ears from 1,926 newborns. The dataset also contains medical diagnosis of the ear shape, and the health data of each newborn and its mother. Our aim is to provide a freely accessible dataset, which would facilitate researches related with ear anatomies, such as the AI-aided detection and classification of auricular deformities and medical risk analysis.

Ultrasound activated probe for disease imaging and therapy In-Vivo.

Sonodynamic therapy (SDT) is the use of ultrasound (US) to excite sonosensitizers to produce reactive oxygen species (ROS) to induce tumor cell death, thereby achieving therapeutic purposes. Based on the strong tissue penetration ability of ultrasound, SDT can realize the treatment of deeper tumors, and it is targeted, can be specifically concentrated at the tumor site, and has little impact on surrounding normal tissues. It has broad clinical transformation prospects. Therefore, sonosensitizers are the key to SDT, and the exploration of sonosensitizers with excellent therapeutic performance has received great attention. We reviewed the development of ultrasound-inspired sound sensitizers for imaging and treatment. First, different types of sonosensitizers are introduced, the construction and performance of inorganic, organic and hybrid types of sonosensitizers are evaluated, followed by a review of different image-guided SDT, and finally the key problems and solutions in this field are discussed in detail.

Genetic analysis of potential biomarkers and therapeutic targets associated with ferroptosis from bronchopulmonary dysplasia.

Ferroptosis is a recently identified form of cell death that is distinct from the conventional modes such as necrosis, apoptosis, and autophagy. Its role in bronchopulmonary dysplasia (BPD) remains inadequately understood. To address this gap, we obtained BPD-related RNA-seq data and ferroptosis-related genes (FRGs) from the GEO database and FerrDb, respectively. A total of 171 BPD-related differentially expressed ferroptosis-related genes (DE-FRGs) linked to the regulation of autophagy and immune response were identified. Least absolute shrinkage and selection operator and SVM-RFE algorithms identified 23 and 14 genes, respectively, as marker genes. The intersection of these 2 sets yielded 9 genes (ALOX12B, NR1D1, LGMN, IFNA21, MEG3, AKR1C1, CA9, ABCC5, and GALNT14) with acceptable diagnostic capacity. The results of the functional enrichment analysis indicated that these identified marker genes may be involved in the pathogenesis of BPD through the regulation of immune response, cell cycle, and BPD-related pathways. Additionally, we identified 29 drugs that target 5 of the marker genes, which could have potential therapeutic implications. The ceRNA network we constructed revealed a complex regulatory network based on the marker genes, further highlighting their potential roles in BPD. Our findings offer diagnostic potential and insight into the mechanism underlying BPD. Further research is needed to assess its clinical utility.

Perinatal characteristics and neonatal outcomes of singletons and twins in Chinese very preterm infants: a cohort study.

BACKGROUND: The prevalence of preterm birth has been rising, and there is a paucity of nationwide data on the perinatal characteristics and neonatal outcomes of twin deliveries of very preterm infants (VPIs) in China. This study compared the perinatal characteristics and outcomes of singletons and twins admitted to neonatal intensive care units (NICUs) in China. METHODS: The study population comprised all infants born before 32 weeks in the Chinese Neonatal Network (CHNN) between January 2019 and December 2019. Three-level and population-average generalized estimating equation (GEE)/alternating logistic regression (ALR) models were used to determine the association of twins with neonatal morbidities and the use of NICU resources. RESULTS: During the study period, there were 6634 (71.2%) singletons and 2680 (28.8%) twins, with mean birth weights of 1333.70 g and 1294.63 g, respectively. Twins were significantly more likely to be delivered by caesarean section (p < 0.01), have antenatal steroid usage (p = 0.048), have been conceived by assisted reproductive technology (ART) (p < 0.01), have a higher prevalence of maternal diabetes (p < 0.01) and be inborn (p < 0.01) than singletons. In addition, twins had a lower prevalence of small for gestational age, maternal hypertension, and primigravida mothers than singletons (all p < 0.01). After adjusting for potential confounders, twins had higher mortality rates (adjusted odds ratio [AOR] 1.28, 95% confidence interval [CI] 1.10-1.49), higher incidences of short-term composite outcomes (AOR 1.28, 95% CI 1.09-1.50), respiratory distress syndrome (RDS) (AOR 1.30, 95% CI 1.12-1.50), and bronchopulmonary dysplasia (BPD) (AOR 1.10, 95% CI 1.01-1.21), more surfactant usage (AOR 1.22, 95% CI 1.05-1.41) and prolonged hospital stays (adjusted mean ratio 1.03, 95% CI 1.00-1.06), compared to singletons. CONCLUSION: Our work suggests that twins have a greater risk of mortality, a higher incidence of RDS and BPD, more surfactant usage, and longer NICU stays than singletons among VPIs in China.

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OBJECTIVES: To identify the perinatal risk factors for the occurrence of singleton apparently stillborn infants. METHODS: This was a case-control study. A total of 154 singleton neonates with gestational age ≥28 weeks and Apgar score of 0-1 who were subsequently successfully resuscitated in the Obstetrics and Gynecology Hospital of Fudan University from January 2006 to December 2015 were enrolled as the case group (apparently stillborn group). A total of 616 singleton infants born from January 2006 to December 2015 (1-minute Apgar score >1) were randomly selected in a 1:4 ratio as the control group. Univariate analysis and multivariate logistic regression were used to analyze the perinatal risk factors for the occurrence of apparently stillborn infants. RESULTS: The gestational age and birth weight in the apparently stillborn group were significantly lower than those in the control group (P<0.05). The incidences of fetal hydrops, cord prolapse, grade III meconium-stained amniotic fluid, placental abruption, breech presentation, severe pre-eclampsia, maternal general anesthesia at delivery, abnormal antenatal fetal heart monitoring and decreased fetal movement were significantly higher in the apparently stillborn group than those in the control group (P<0.05). The multivariate logistic analysis showed that the mother had general anesthesia at delivery (OR=34.520), decreased antenatal fetal movement (OR=28.168),placental abruption (OR=15.641), grade III meconium-stained amniotic fluid (OR=6.365), abnormal antenatal fetal heart monitoring (OR=5.739), and breech presentation (OR=2.614) were risk factors for the occurrence of apparently stillborn infants (P<0.05), while higher gestational age was a protective factor (OR=0.686, P<0.05). CONCLUSIONS: Attention needs to be paid to mothers with abnormal prenatal fetal heart monitoring, decreased fetal movement, preterm labor, placental abruption, breech presentation, grade III meconium-stained amniotic fluid, and general anesthesia. Preparations for resuscitation should be done to rescue apparently stillborn infants.

Characterization of Fatty Acid Metabolism-Related Genes Landscape for Predicting Prognosis and Aiding Immunotherapy in Glioma Patients.

Glioma is a highly malignant brain tumor with a poor survival rate. The involvement of fatty acid metabolism in glioma was examined to find viable treatment options. The information was gathered from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases. A prognostic signature containing fatty acid metabolism-dependent genes (FAMDs) was developed to predict glioma outcome by multivariate and most minor absolute shrinkage and selection operator (LASSO) regression analyses. In the TCGA cohort, individuals with a good score had a worse prognosis than those with a poor score, validated in the CGGA cohort. According to further research by "pRRophetic" R package, higher-risk individuals were more susceptible to crizotinib. According to a complete study of the connection between the predictive risk rating model and tumor microenvironment (TME) features, high-risk individuals were eligible for activating the immune cell-associated receptor pathway. We also discovered that anti-PD-1/PD-L1 and anti-CTLA4 immunotherapy are more effective in high-risk individuals. Furthermore, we demonstrated that CCNA2 promotes glioma proliferation, migration, and invasion and regulates macrophage polarization. Therefore, examining the fatty acid metabolism pathway aids our understanding of TME invasion properties, allowing us to develop more effective immunotherapies for glioma.

Carbon Dioxide Conversion Synergistically Activated by Dielectric Barrier Discharge Plasma and the CsPbBr3@TiO2 Photocatalyst.

Carbon dioxide utilization activated by the integration of plasma and photocatalyst is a promising approach to achieve the mitigation of the greenhouse effect. In this paper, for the first time, the dielectric barrier discharge (DBD) plasma and halide perovskite photocatalysts were synergistically used to facilitate the carbon dioxide conversion. After introducing the photocatalyst into the plasma reactor, the plasma discharge characteristics were improved by the photocatalyst while the active photons, electrons, and vibrationally excited molecules in plasma also enhanced the photocatalytic activity of the photocatalyst. Compared with pure CsPbBr3 and Al2O3, the CsPbBr3@TiO2 with the best photocatalytic activity also exhibited the best performance in plasma. The carbon dioxide conversion rate of the DBD plasma filled with CsPbBr3@TiO2 was found to be 29.6% higher than the sum of sole plasma and photocatalysis, illustrating the achievement of the synergistic effect between the plasma and photocatalyst. This work brings up new opportunities for efficient large-scale conversion and utilization of carbon dioxide by the coupling of nonthermal plasma and photocatalysis.

Biallelic p.V37I variant in GJB2 is associated with increasing incidence of hearing loss with age.

PURPOSE: This study aimed to quantitatively assess the incidence of hearing loss in relation to age in individuals with biallelic p.V37I variant in GJB2. METHODS: Population screening of the biallelic p.V37I variant was performed in 30,122 individuals aged between 0 and 97 years in Shanghai. Hearing thresholds of the biallelic p.V37I individuals and the controls were determined by click auditory brainstem response or pure tone audiometry. RESULTS: Biallelic p.V37I was detected in 0.528% (159/30,122) of the subjects. Of the biallelic p.V37I newborns, 43.91% (18/41) passed their distortion-product otoacoustic emissions-based newborn hearing screening or had hearing thresholds lower than 20 decible above normal hearing level. The older newborns had elevated hearing thresholds, with increasing incidence of 9.52%, 23.08%, 59.38%, and 80.00% for moderate or higher grade of hearing loss in age groups of 7 to 15 years, 20 to 40 years, 40 to 60 years, and 60 to 85 years, respectively. Their hearing deteriorated at a rate of 0.40 dB hearing level per year on average; males were more susceptible, and deterioration occurred preferentially at higher sound frequencies. CONCLUSION: The biallelic p.V37I variant is associated with steadily progressive hearing loss with increasing incidence over the course of life. Most of the biallelic p.V37I individuals may develop significant hearing loss in adulthood and, can benefit from early diagnosis and intervention through wide-spread genetic screening.

The accuracy of transcutaneous bilirubin to identify hyperbilirubinemia in jaundiced neonates.

OBJECTIVE: To compare transcutaneous bilirubin (TcB) to total serum bilirubin (TSB) in jaundiced neonates by using a JM-103 bilirubinometer. METHODS: We conducted a retrospective study in jaundiced infants ≥35 weeks' gestation. Infants' and maternal information, TcB measurements, and TSB levels were collected. The correlation and consistency between TcB and TSB were analyzed by Pearson's correlation analysis and the Bland-Altman plot. Multivariate regression analysis was used to identify characteristics associated with the difference between TcB and TSB, underestimation by TcB and overestimation by TcB. RESULTS: A total of 787 paired samples were collected. There was a strong correlation between TcB and TSB with a Pearson correlation coefficient of 0.708 (p < .001). In preterm infants, outpatients and infants with high TSB levels, the TcB measurements were less precise. The TcB-TSB difference was significantly associated with gender, maternal hypertension disease, ABO hemolytic disease, and outpatient setting (p < .05). Only the outpatient setting had statistical significance in the underestimation of TSB ≥2 mg/dL. CONCLUSIONS: Generally, TcB by a JM-103 bilirubinometer had a good correlation and consistency with the TSB values. However, small for gestational age, postnatal age of hour, ABO hemolytic disease, and outpatient setting may lead to inconsistencies between the TcB and TSB.

An Autophagy-related Long Non-coding RNA Signature for Breast Cancer.

BACKGROUND: The most prevalent malignant tumor in women is breast cancer (BC). As autophagic therapies have been identified to contribute to BC cell death, the potential prognostic role of long non-coding RNA (lncRNA) related to autophagy in patients with BC was examined. METHODS: The lncRNAs expression profiles were derived from The Cancer Genome Atlas (TCGA) database. Throughout univariate Cox regression and multivariate Cox regression test, lncRNA with BC prognosis have been differentially presented. We then defined the optimal cut-off point between high and low-risk groups. The receiver operating characteristic (ROC) curves were drawn to test this signature. In order to examine possible signaling mechanisms linked to these lncRNAs, the Gene Set Enrichment Analysis (GSEA) has been carried out. RESULTS: Based on the lncRNA expression profiles for BC, a 9 lncRNA signature associated with autophagy was developed. The optimal cut-off value for high-risk and low-risk groups was used. The high-risk group had less survival time than the low-risk group. The result of this lncRNA signature was highly sensitive and precise. GSEA study found that the gene sets have been greatly enriched in many cancer pathways. CONCLUSION: Our signature of 9 lncRNAs related to autophagy has prognostic value for BC, and these lncRNAs related to autophagy may play an important role in BC biology.

Genome-wide exploration of a pyroptosis-related gene module along with immune cell infiltration patterns in bronchopulmonary dysplasia.

Pyroptosis plays a crucial role in bronchopulmonary dysplasia (BPD) and is associated with various lung injury illnesses. However, the function of pyroptosis-related genes (PRGs) in BPD remains poorly understood. The gene expression omnibus (GEO) database was searched for information on genes associated with BPD. Twenty-five BPD-related DE-PRGs were identified, all of which were closely associated with pyroptosis regulation and immunological response. LASSO and SVM-RFE algorithms identified CHMP7, NLRC4, NLRP2, NLRP6, and NLRP9 among the 25 differentially expressed PRGs as marker genes with acceptable diagnostic capabilities. Using these five genes, we also generated a nomogram with excellent predictive power. Annotation enrichment analyses revealed that these five genes may be implicated in BPD and numerous BPD-related pathways. In addition, the ceRNA network showed an intricate regulatory link based on the marker genes. In addition, CIBERSORT-based studies revealed that alterations in the immunological microenvironment of BPD patients may be associated with the marker genes. We constructed a diagnostic nomogram and gave insight into the mechanism of BPD. Its diagnostic value for BPD must be evaluated in further research before it can be used in clinical practice.

Identification and immunological characterization of endoplasmic reticulum stress-related molecular subtypes in bronchopulmonary dysplasia based on machine learning.

Introduction: Bronchopulmonary dysplasia (BPD) is a life-threatening lung illness that affects premature infants and has a high incidence and mortality. Using interpretable machine learning, we aimed to investigate the involvement of endoplasmic reticulum (ER) stress-related genes (ERSGs) in BPD patients. Methods: We evaluated the expression profiles of endoplasmic reticulum stress-related genes and immune features in bronchopulmonary dysplasia using the GSE32472 dataset. The endoplasmic reticulum stress-related gene-based molecular clusters and associated immune cell infiltration were studied using 62 bronchopulmonary dysplasia samples. Cluster-specific differentially expressed genes (DEGs) were identified utilizing the WGCNA technique. The optimum machine model was applied after comparing its performance with that of the generalized linear model, the extreme Gradient Boosting, the support vector machine (SVM) model, and the random forest model. Validation of the prediction efficiency was done by the use of a calibration curve, nomogram, decision curve analysis, and an external data set. Results: The bronchopulmonary dysplasia samples were compared to the control samples, and the dysregulated endoplasmic reticulum stress-related genes and activated immunological responses were analyzed. In bronchopulmonary dysplasia, two distinct molecular clusters associated with endoplasmic reticulum stress were identified. The analysis of immune cell infiltration indicated a considerable difference in levels of immunity between the various clusters. As measured by residual and root mean square error, as well as the area under the curve, the support vector machine machine model showed the greatest discriminative capacity. In the end, an support vector machine model integrating five genes was developed, and its performance was shown to be excellent on an external validation dataset. The effectiveness in predicting bronchopulmonary dysplasia subtypes was further established by decision curves, calibration curves, and nomogram analyses. Conclusion: We developed a potential prediction model to assess the risk of endoplasmic reticulum stress subtypes and the clinical outcomes of bronchopulmonary dysplasia patients, and our work comprehensively revealed the complex association between endoplasmic reticulum stress and bronchopulmonary dysplasia.

Maternal-Neonatal Serum Albumin Level and Neonatal Respiratory Distress Syndrome in Late-Preterm Infants.

Background: To determine the correlation between maternal-neonatal serum albumin level and respiratory distress syndrome (RDS) in late-preterm infants. Methods: This case-control study included 112 late-preterm newborns admitted to the neonatal intensive care unit of our hospital between January 2018 and July 2019. Those infants were divided into the RDS group (n = 56) and the non-RDS group (n = 56). Levels of maternal-neonatal serum albumin, pregnancy complications, and baseline information of the infants were compared between the two groups. Results: 1. There was no correlation between maternal and neonatal serum albumin measures. The maternal albumin level in the RDS group was lower than that in the control group (33.38 ± 3.31 vs. 33.60 ± 3.31, P > 0.05), but the difference was not statistically significant. The neonatal albumin level in the RDS group was significantly lower than that in the control group (32.70 ± 2.48 vs. 35.66 ± 3.27, P < 0.05). To predict RDS in late-preterm infants, using the albumin cutoff level of 34 g/L provides a sensitivity of 83.9% with a specificity of 62.5%. 2. Gestational age, primipara, placenta previa, antenatal corticosteroid therapy, delivery mode, and neonatal serum albumin level were associated with RDS in the late-preterm infant. 3. After adjustment for gestational age, logistic regression analysis showed that neonatal serum albumin level, placenta previa, and delivery mode were independent risk factors for RDS in late-preterm infants. However, albumin level did not related to the severity of RDS. Conclusion: The decrease in serum albumin within the first day after birth was closely related to the occurrence of RDS in late-preterm infants.

A hypoxia risk signature for the tumor immune microenvironment evaluation and prognosis prediction in acute myeloid leukemia.

Acute myeloid leukemia (AML) is the most prevalent form of acute leukemia. Patients with AML often have poor clinical prognoses. Hypoxia can activate a series of immunosuppressive processes in tumors, resulting in diseases and poor clinical prognoses. However, how to evaluate the severity of hypoxia in tumor immune microenvironment remains unknown. In this study, we downloaded the profiles of RNA sequence and clinicopathological data of pediatric AML patients from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, as well as those of AML patients from Gene Expression Omnibus (GEO). In order to explore the immune microenvironment in AML, we established a risk signature to predict clinical prognosis. Our data showed that patients with high hypoxia risk score had shorter overall survival, indicating that higher hypoxia risk scores was significantly linked to immunosuppressive microenvironment in AML. Further analysis showed that the hypoxia could be used to serve as an independent prognostic indicator for AML patients. Moreover, we found gene sets enriched in high-risk AML group participated in the carcinogenesis. In summary, the established hypoxia-related risk model could act as an independent predictor for the clinical prognosis of AML, and also reflect the response intensity of the immune microenvironment in AML.

Ambient fine particulate matter air pollution and the risk of preterm birth: A multicenter birth cohort study in China.

Preterm birth (PTB), defined as live birth before the 37th week of gestation, is believed to have profound impacts on the infant's health in later life. Air pollution has been suggested to be a potential risk factor of PTB, but the evidence was inconsistent. In this multicenter birth cohort study, we aimed to examine the association between fine particulate matter (PM2.5) exposure during pregnancy and PTB in China. A total of 5976 live births were identified between Jan. 2009 and Feb. 2011 from 8 provinces in China. Residential exposures to PM2.5 were assigned based on satellite remote sensing estimates. Cox proportional hazards regressions were employed to explore the correlation for each trimester as well as the entire pregnancy. A total of 443 (7.4%) preterm births were observed. The average PM2.5 during pregnancy was 57.2 ± 8.8 µg/m3. We found exposure to PM2.5 during the whole pregnancy (hazard ratio, HR = 1.262; 95% CI: 1.087-1.465) and in the first trimester (HR = 1.114; 95% CI: 1.007-1.232) was associated with higher risk of PTB. The associations of PM2.5 were stronger for subjects with older maternal or paternal age, lower maternal pre-pregnancy BMI, and lower family income. This study adds supports to the cumulating evidence linking PM2.5 exposure and elevated PTB risk. Measures of air pollution reduction are needed during pregnancy, especially at early stage of pregnancy to prevent adverse birth outcomes.

Development and Validation of a RNA Binding Protein-Associated Prognostic Model for Hepatocellular Carcinoma.

BACKGROUND: Dysregulation of RNA binding proteins (RBPs) has been identified in multiple malignant tumors correlated with tumor progression and occurrence. However, the function of RBPs is not well understood in hepatocellular carcinoma (HCC). METHODS: The RNA sequence data of HCC was extracted out of the Cancer Genome Atlas (TCGA) database and different RBPs were calculated between regular and cancerous tissue. The study explored the expression and predictive value of the RBPs systemically with a series of bioinformatic analyzes. RESULTS: A total of 330 RBPs, including 208 up-regulated and 122 down-regulated RBPs, were classified differently. Four RBPs (MRPL54, EZH2, PPARGC1A, EIF2AK4) were defined as the forecast related hub gene and used to construct a model for prediction. Further study showed that the high-risk subgroup is poor survived (OS) compared to the model-based low-risk subgroup. The area of the prognostic model under the time-dependent receiver operator characteristic (ROC) curve is 0.814 in TCGA training group and 0.729 in validation group, indicating a strong prognostic model. We also created a predictive nomogram and a web-based calculator (https://dxyjiang.shinyapps.io/RBPpredict/) based on the 4 RBPs and internal validation in the TCGA cohort, which displayed a beneficial predictive ability for HCC. CONCLUSIONS: Our results provide new insights into HCC pathogenesis. The 4-RBP gene signature showed a reliable HCC prediction ability with possible applications in therapeutic decision making and personalized therapy.

A Simple-to-Use Nomogram for Predicting Survival in Children with Acute Myeloid Leukemia.

BACKGROUND: The research analyzed a group of patients to develop a statistical nomogram and a web-based survival rate predictor for the comprehensive estimate of the overall survival (OS) of children with acute myeloid leukemia. METHODS: Between 1999 to 2015, we used the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database to evaluate and randomly divide 440 children diagnosed with AML into the population of training (n = 309) and validation (n = 131). The analysis of Lasso Cox was used to identify separate predictive variables. We have used essential forecasting considerations to construct a nomogram and a web-based calculator focused on Cox regression analysis. Nomogram validation was tested through discrimination and calibration. RESULTS: Compared to the multivariate training cohort models, a nomogram integrating gender, age of diagnose, WBC at diagnosis, bone marrow leukemic blast percentage, and chromosomal abnormalities [t(8; 21), inv(16)] were designed for the prediction of OS. We also developed a predictive survival nomogram and a web-based calculator. C-indexes validated internally and checked externally were 0.747 and 0.716. The calibration curves have shown that the nomogram might accurately forecast 3-year and 5-year OS. CONCLUSIONS: A nomogram effectively predicts survival in children with AML. This prognostic model can be used in clinical practice.

Ultrasound performed shortly after birth can predict the respiratory support needs of late preterm and term infants: A diagnostic accuracy study.

BACKGROUND: Late preterm and term infants may develop respiratory issues with severe outcomes. Early identification of these diseases shortly after infants' birth can improve their management. Lung ultrasound (LUS) has been used to diagnose neonatal respiratory diseases. However, few LUS methods have been reported to predict the need for respiratory support, the basis of infant respiratory diseases management. METHODS: We conducted a prospective diagnostic accuracy study following the Standards for the Reporting of Diagnostic Accuracy Studies guidelines at a tertiary academic hospital between 2019 and 2020. A total of 310 late preterm and term infants with mild respiratory symptoms were enrolled. The LUS assessment was performed for each participant at one of the following times: 0.5, 1.0, 2.0, or 4.0 h after birth. Predictive reliability was tested by receiver operating characteristic curve analysis. The main outcome was the need for any respiratory support determined according to international guidelines. RESULTS: Seventy-four infants needed respiratory support, and 236 were healthy according to a 3-day follow-up confirmation. Six LUS imaging patterns were found. Two "high-risk" patterns were strongly correlated with respiratory support needs (area under the curve [AUC] = 0.95; 95% confidence interval [CI]: 0.92-0.98, p < .001). The optimal cut-off value for "high-risk" patterns was 2 (sensitivity = 87.8% and specificity = 91.1%). The predictive value of LUS was greater than that of a symptom-based method (the Acute Care of at-Risk Newborns assessment score) (AUCs' p < .01). CONCLUSIONS: LUS can be used to predict the need for respiratory support in late preterm and term infants and is more reliable than tools based on respiratory symptoms.