ROC Curve Research Articles

Oakland score to identify low-risk patients with lower gastrointestinal bleeding performs well among emergency department patients

BackgroundThe Oakland Score predicts risk of 30-day adverse events among hospitalized patients with lower gastrointestinal bleeding (LGIB) possibly identifying patients who may be safe for discharge. The Oakland Score has not been studied among emergency department (ED) patients with LGIB. The Oakland Score composite outcome includes re-bleeding, defined as additional blood transfusion requirements and/or a further decrease in hematocrit (Hct) >/= 20% after 24 h in clinical stability; red blood cell transfusion; therapeutic intervention to control bleeding, including surgery, mesenteric embolization, or endoscopic hemostasis; in-hospital death, all cause; and re-admission with further LGIB within 28 days. Prediction variables include age, sex, previous LGIB admission, systolic blood pressure, heart rate, and hemoglobin concentration, and scores range from 0 to 35 points, with higher scores indicating greater risk.MethodsRetrospective cohort study of adult (≥ 18 years old) patients with a primary ED diagnosis of LGIB across 21 EDs from March 1st, 2018, through March 1st, 2020. We excluded patients who were more likely to have upper gastrointestinal bleeding (esophago-gastroduodenoscopy without LGIB evaluation), patients who left against medical advice or prior to ED provider evaluation, ED patients without active health plan membership, and patients with incomplete Oakland Score variables. We assessed predictive accuracy by reporting the area under the receiver operator curve (AUROC) and sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios at multiple clinically relevant thresholds.ResultsWe identified 8,283 patients with LGIB, 52% were female, mean age was 68, 49% were non-White, and 27% had an adverse event. The AUROC for predicting an adverse event was 0.85 (95% CI 0.84–0.86). There were 1,358 patients with an Oakland Score of </=8; 4.9% had an adverse event, and sensitivity of the Oakland Score at this threshold was 97% (95% CI 96%−98%).ConclusionThe Oakland Score had high predictive accuracy among ED patients with LGIB. Prospective evaluation is needed to understand if the risk score could augment ED decision-making and improve outcomes and resource utilization.

Cerebrospinal Fluid Calcium Balance in Tick-Borne Encephalitis: A Preliminary Study and Future Research Directions

Introduction: Calcium homeostasis is essential for neurophysiological functions, with dysregulation implicated in neurodegenerative diseases. Recent studies suggest that specific viral brain infections, such as tick-borne encephalitis, can initiate neuronal loss and subsequent neurodegenerative changes. This study examines alterations in calcium levels within the cerebrospinal fluid (CSF) of patients with tick-borne encephalitis (TBE). Objectives: To evaluate the concentration of calcium in the CSF of TBE patients and assess its potential as a diagnostic marker for disease severity. Materials and Methods: CSF samples were collected from 42 subjects (11 controls, 20 with TBE, 11 with other forms of meningitis). Calcium levels were measured using the Alinity c analyzer. Statistical analyses included the Shapiro–Wilk test, Mann–Whitney U test, and ROC curve analysis. Results: Calcium levels were significantly lower in TBE patients compared to controls (mean 0.85 mmol/L vs. 0.98 mmol/L). Lower calcium levels were associated with milder cases of TBE. ROC analysis (AUC 0.802, p-value 0.0053) supports the diagnostic utility of calcium concentration in differentiating TBE severity. The optimal cut-off value for calcium was &gt;3.09 mg/dL, with a sensitivity of 84.62% and specificity of 71.43%. These findings further emphasize the potential of calcium as a diagnostic marker for TBEV. Conclusions: The observed differences in CSF calcium levels between mild and severe TBE cases highlight its potential as a diagnostic marker. Further research is warranted to elucidate calcium’s role in TBE, aiming to improve clinical management and reduce complications. We emphasize that this study is one of the first to propose calcium levels as a potential biomarker for assessing the severity of tick-borne encephalitis, offering a new perspective in the diagnostic approach to this infection.

Immunohistochemical Analysis of Inter-Alpha-Trypsin Inhibitor Heavy Chain 2 and Enolase 1 in Canine Mammary Tumors: Associations with Tumor Aggressiveness and Prognostic Significance

Mammary neoplasms in dogs are a common clinical concern, especially in middle-aged and older intact females. These tumors share similarities with human breast cancer in terms of histology, disease progression, and risk factors, making dogs a relevant model for breast cancer research. The search for biomarkers in canine mammary tumors is essential to understand tumor progression and identify potential therapeutic targets. This study investigated the expression of two potential biomarkers—Inter-Alpha-Trypsin Inhibitor Heavy Chain 2 (ITIH2) and Enolase 1 (ENO1)—in the mammary glands of healthy and tumor-bearing dogs using immunohistochemistry. Both proteins were identified in previous proteomic analyses of extracellular vesicles derived from the plasma of healthy and tumor-bearing dogs. A total of fifty-one canine mammary tissue samples were analyzed and categorized into three groups: (i) the control group, composed of five samples of normal mammary tissue without neoplasia; (ii) benign tumors, composed of nineteen samples of benign mixed tumors; and (iii) malignant tumors, which included six carcinomas in grade 1 mixed tumors, five carcinomas in grade 2 mixed tumors, thirteen solid carcinomas of grade 3, one papillary carcinoma, and two tubular carcinomas. Regarding the intensity of staining, quantified by histoscore, there were no significant differences in the comparison between the groups; for ITIH2, the p-value was 0.33, and for ENO1, the p-value was 0.57. Regarding the predictive potential of their respective ROC curves, the proteins demonstrated low predictive power in canine mammary tumors. These findings indicate that neither ITIH2 nor ENO1 demonstrated strong prognostic value in this setting, as demonstrated by their moderate AUC values, wide confidence intervals, and lack of statistical significance. However, this study found distinct tissue localization patterns for ITIH2 and subcellular localization for ENO1. As an additional way to examine possible associations of these proteins with epithelial–mesenchymal transition, the ZEB1 antibody was tested by both single and double immunohistochemistry, demonstrating a tendency to be more intensely expressed in the malignant group and tending to be associated with ENO1 in canine mammary tumors.

Effects of Hsa-miR-4741/LILRB2 on Senescence of Nucleus Pulposus Cells and Their Prognostic Values in Lumbar Disc Herniation

Background The incidence of lumbar disk herniation (LDH) is usually caused by lumbar disk degeneration. Surgery is a common treatment strategy for LDH, but it can recur, resulting in recurrent disk herniation (RDH). Purpose To explore the predictive value of hsa-miR-4741 and LILRB2 in the prognosis of LDH surgery and the mechanism of nucleus pulposus senescence. Method The ROC curves of RDH based on hsa-miR-4741 and LILRB2 were constructed to evaluate their predictive values in the prognosis of LDH surgery. Human nucleus pulposus cells (NPC) was treated by TNF-α to construct a cell senescence model, studying the senescence mechanism. Oxidative stress and senescence markers were detected after overexpression of hsa-miR-4741 and LILRB2 to evaluate their effects on the senescence of NPC. Dual luciferase assay and the transfection of hsa-miR-4741 mimics or inhibitor were used to investigate the targeted regulation of it to LILRB2. Results The combination of hsa-miR-4741 and LILRB2 showed higher accuracy in predicting the outcome of RDH (AUC = 0.9367), compared with a single molecule. Overexpression of hsa-miR-4741 enhanced TNF-α-induced oxidative stress and senescence, while LILRB2 overexpression had the opposite effect. Hsa-miR-4741 mimics attenuated the luciferase activity of NPC transfected with wt-LILRB2 vector and significantly down-regulated LILRB2 expression. In addition, the antioxidant NAC reversed the promotion of hsa-miR-4741 on NPC senescence. Conclusion The combination of hsa-miR-4741 and LILRB2 was a good predictor of LDH prognosis. Hsa-miR-4741 promoted oxidative stress-induced NPC senescence by negatively regulating LILRB2.

Characterization of Novel Sialylation-Associated microRNA Signature for Prognostic Assessment in Breast Cancer and Its Implications for the Tumor Microenvironment.

Sialylation, a key post-translational modification essential for protein function, is regulated by steroid hormones, along with other glycosylations like fucosylation. These modifications influence tumor growth and metastasis by modulating immune activation. MicroRNAs (miRNAs), crucial in gene expression, affect sialylation and are emerging as promising biomarkers in breast cancer, though their prognostic value remains unclear. Sialylation-related miRNAs were identified through Pearson correlation analysis, and an eight-miRNA risk signature was developed using univariate and Least Absolute Shrinkage and Selection Operator (LASSO) regression in the TCGA dataset. The prognostic value was validated in two independent GEO datasets. Multivariate analysis confirmed that the miRNA risk score is an independent predictor of overall survival (OS). A nomogram integrating clinical characteristics and the risk score was created to predict 1-, 3-, and 5-year OS, assessed through calibration curves, ROC curves, and area under the ROC curve (AUC). Biological pathways were explored using GSEA and GSVA, while immune infiltrates were identified through CIBERSORT and TIMER. The eight-miRNA signature effectively predicted OS, recurrence-free survival, and disease-free survival. High-risk patients exhibited increased macrophage and neutrophil levels, indicative of a poor prognosis. High-risk patients, especially those with triple-negative breast cancer, had significantly worse outcomes. This risk score could inform personalized treatment strategies in breast cancer management.

Relative fat mass (RFM) is linked to testosterone deficiency in adult males

PurposeRelative fat mass (RFM) is a novel obesity assessment metric, and we aim to explore the relationship between RFM and testosterone deficiency in US adult males. MethodsThis study included data from adult males aged 20–59 years from the NHANES 2013–2014 and 2015–2016 cycles. RFM was calculated using a linear equation based on height and waist circumference (WC). Testosterone deficiency was defined as a total serum testosterone level of less than 300 ng/dL. Logistic regression, subgroup analysis, and smooth curve fitting were employed to explore the relationship between RFM and the risk of testosterone deficiency. ResultsThis study included 3243 participants, with 771 diagnosed with testosterone deficiency. Testosterone-deficient individuals exhibited significantly higher RFM levels compared to those with normal testosterone levels (31.23 ± 0.23 vs. 27.16 ± 0.19, P < 0.001). After adjusting for confounding variables, a positive correlation emerged between RFM and testosterone deficiency (OR = 1.16, 95 %CI = 1.11–1.22, P < 0.001). Smooth curve fitting further supported this relationship. Subgroup analysis did not identify any special populations. Receiver operating curve (ROC) analysis results indicated that RFM showed greater effectiveness compared to body mass index (BMI) and WC. ConclusionsElevated RFM levels were found to be linked to the risk of testosterone deficiency. Further studies on RFM hold promise to evaluate and address testosterone deficiency.

Translation, Cross-Cultural Adaptation, and Validation of the Kannada Version of the Exercise Adherence Rating Scale (EARS-Kn) Among Head and Neck Cancer (HNC) Survivors in a Tertiary Care Setup in India.

Adherence in rehabilitation services includes attending appointments, regularly performing prescribed exercises, and correct exercise execution. The Exercise Adherence Rating Scale (EARS) has been adapted into several languages, but there is lack of a standardized tool for various Indian languages and cultural contexts, particularly for use with cancer survivors. With the anticipated 57.7% rise in cancer cases by 2040, this study aims to address this gap. To cross-culturally adapt EARS to Kannada (EARS-Kn) and evaluate its validity and reliability amongst HNC survivors enrolled in the Multimodal Oncology Rehabilitation Exercise-MORE© Program. Following Beaton guidelines, the EARS tool was adapted to Kannada. 34 HNC survivors engaged in the MORE© program. Internal consistency (Cronbach's ⍺) and construct validity (Exploratory Factor Analysis, EFA) were assessed. The Receiver Operating Curve (ROC) determined cut-off scores, sensitivity and specificity of the EARS-Kn. The EARS-Kn demonstrated a Cronbach's-⍺ value of .93. The EFA revealed a one-factor solution with eigenvalues exceeding one and 70.1% loading. The area under the curve (AUC) was 0.908. A cut-off score of 17 was established, with 95.83% sensitivity and 80% specificity. The EARS-Kn version showed strong validity and reliability among Kannada-speaking HNC survivors, indicating its potential to enhance the understanding of exercise adherence among them. Future studies could explore the EARS-Kn version among diverse populations prescribed various rehabilitation regimes. Studies could also further investigate psychometric properties of the EARS in different Indian languages among cancer survivors, which would help improve survivorship outcomes.

Histopathological growth patterns of gastric cancer liver metastasis and their association with patient prognosis.

484 Background: The histopathological growth patterns (HGPs) of liver metastasis reflect the complicated and varied interactions between tumor cells and the host microenvironment. We studied HGPs of gastric cancer liver metastasis (GCLM) and sought to predict them using radiomic and clinical variables. Methods: Hepatectomy was performed in 62 patients with GCLM at our university hospital between 2011 and 2021. HGPs were evaluated according to international consensus guidelines, and were classified as either desmoplastic HGP (dHGP) or non-dHGP. CD4, CD8, VEGF and CD31 were analyzed by immunohistochemistry. Eight hundred and fifty-one radiomics features were extracted from CT portal venous phase images and the optimal radiomics signature was determined by univariate analysis and LASSO regression. Multivariable regression analyses and ROC curves were used to assess the predictive performance of HGPs with a radiomic and clinical combined model. Results: Among 62 patients, 14 were categorized as dHGP, and 48 as non-dHGP. Non-dHGP vs. d-HGP was associated with higher tumor N stage and CEA level, and with decreased CD8 + T cells, and lower VEGF and CD31 expression. HGP status was independently associated with patient cancer-specific survival (CSS) (P＜0.05) multivariately.Analysis of percent relative contribution revealed that HGP ranked first for CSS (35.9%), ahead of T (28.9%) and N (28.9%) stage. A model with combined radiomic and clinical features demonstrated robust performance with area under the curve (AUC) values of 0.993 and 0.933 in the training and validation sets, respectively. Conclusions: Non-invasive determination of radiomic and clinical features was shown to predict HGPs types. Compared to dHGP, GCLM with non-dHGP exhibited significantly lower immune cell infiltration and decreased angiogenesis. Among features examined in GCLM, HGP was the most robust for prognostication. Univariate and multivariate analysis of prognostic factors for cancer-specific survival. Characteristics Univariate analysis Multivariate rergression analysis HR (95%CI) P HR (95%CI) P Gender ( Women vs Men ) 1.13(0.61-2.09) 0.71 Age ( &gt;60years vs ≤60years) 1.08(0.60-1.70) 0.98 HGP ( non-desmoplastic HGP vs desmoplastic HGP ) 3.63(1.78-7.41) 0.00 3.48(1.37-8.88) 0.01 T stage ( T3-T4 vs T1-T2 ) 2.03(1.08-3.80) 0.03 2.29(1.15-4.58) 0.02 N stage ( N1-N3 vs N0 ) 3.46(1.66-7.23) 0.00 2.54(1.17-5.56) 0.02 CEA ( &gt;5ng/ml vs ≤5ng/ml ) 2.37(1.25-4.48) 0.01 1.56(0.70-3.48) 0.27

Enhancing prediction of major depressive disorder onset in adolescents: A machine learning approach.

Major Depressive Disorder (MDD) is a prevalent mental health condition that often begins in adolescence, with significant long-term implications. Indicated prevention programs targeting adolescents with mild symptoms have shown efficacy, yet the methods for identifying at-risk individuals need improvement. This study aims to evaluate the utility of Partial Least Squares Regression (PLSR) in predicting the onset of MDD among non-depressed adolescents, compared to traditional screening methods. The study recruited 1462 Portuguese adolescents aged 13-16, who were assessed using various self-report measures and followed for two years. Participants were randomly divided into training (70%, N=1023) and testing (30%, N=439) samples. PLSR models were developed to predict the occurrence of a major depressive episode (MDE) within two years, using 331 variables. The model's performance was compared to the Children's Depression Inventory (CDI) in predicting MDE onset. The best-fitting PLSR model with two components explained 19.1% and 16.9% of the variance in the training and testing samples, respectively, significantly outperforming the CDI, which explained 7.7% of the variance. The area under the ROC curve was 0.78 for PLSR, compared to 0.71 for CDI. An empirically derived cut-off point was used to create dichotomous risk categories, and it showed a significant difference in MDE rates between predicted high-risk and low-risk groups. The balanced accuracy of the PLSR model was 0.77, compared to 0.65 for the CDI method. The PLSR model effectively identified adolescents at risk for developing MDD, demonstrating superior predictive power over the CDI. This study supports the potential utility of ML techniques (e.g., PLSR) in enhancing early identification and prevention efforts for adolescent depression.

Interaction of inflammatory factors related to pulmonary infection and TLR4/NF-κB signaling pathway in patients with spontaneous intracerebral hemorrhage.

To investigate the interaction of inflammatory factors related to pulmonary infection and the TLR4/NF-κB signaling pathway in patients with spontaneous intracerebral hemorrhage (ICH). A total of 325 critically ill ICH patients treated in our hospital from May 2021 to February 2024 were selected for this study. Based on whether the patient developed a pulmonary infection during treatment, they were divided into the infection group (n=86) and the non-infection group (n=239). The distribution characteristics of pathogens were observed, and changes in serum and defensin, hs-CRP, IL-4, TLR4 mRNA, and NF-κB mRNA were compared. Pearson correlation analysis was used to analyze the relationship between serum defensin, inflammatory factors, and the TLR4/NF-κB signaling pathway. A logistic regression model was used to construct a combined prediction model with defensin, hs-CRP, IL-4, HMGB1, TLR4 mRNA, and NF-κB mRNA. ROC curves were drawn to analyze the area under the curve (AUC), sensitivity, and specificity of defensin, hs-CRP, IL-4, HMGB1, TLR4 mRNA, NF-κB mRNA, and the six combined parameters for predicting pulmonary infection in critically ill ICH patients. In 86 ICH patients with pulmonary infection, 94 strains of pathogens were isolated, with 28 (29.79%) Gram-positive bacteria, 58 (61.70%) Gram-negative bacteria, and 8 (8.51%) fungi. The levels of defensin, hs-CRP, IL-4, HMGB1, TLR4 mRNA, and NF-κB mRNA in the infection group were significantly higher than those in the non-infection group (P<0.05). Pearson correlation analysis showed that defensin, hs-CRP, IL-4, and HMGB1 were positively correlated with TLR4 mRNA and NF-κB mRNA (P<0.05). ROC curve analysis showed that the AUC values for defensin, hs-CRP, IL-4, HMGB1, TLR4 mRNA, NF-κB mRNA, and the six combined parameters for predicting pulmonary infection were 0.789, 0.778, 0.690, 0.792, 0.741, 0.750, and 0.870, respectively. The main pathogens causing pulmonary infection in critically ill ICH patients are Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, Staphylococcus aureus, and Streptococcus hemolyticus. Defensin, hs-CRP, IL-4, HMGB1, and other indicators are influenced by the TLR4/NF-κB signaling pathway in patients with secondary pulmonary infection.

Effect of tRF-28-ZJ47D112Z4DZ on the pathogenesis of gastric cancer through targeting cyclin D1/CDK4 and its early diagnostic value.

475 Background: Gastric cancer exhibits high incidence and mortality rates worldwide. Current research on gastric cancer aims to discover stable and effective early diagnostic markers, as well as uncover the disease's pathogenesis. tRNA-derived fragment (tRF) is a newly discovered regulatory non-coding RNA, which plays an important role in tumor diagnosis and treatment. Methods: This study, through transcriptome sequencing and MINTBase v2.0 database, screened out a new molecule tRF-28-ZJ47D112Z4DZ (tRF-28) related to gastric cancer. An absolute quantitative method was established to quantify the level of tRF-28 in plasma. ROC curve, survival curve, Cox regression model were constructed, and clinicopathological factors were collected to analyze the diagnostic value of tRF-28. "Overexpression" and "knockdown" tRF-28 gastric cancer cell models and xenograft tumor models were established to study the effects of tRF-28 on cell proliferation. Using bioinformatics, qRT-PCR, Western blot, dual luciferase reporter gene, fluorescence in situ hybridization, RNA binding protein immunoprecipitation assay, rescue experiment and immunohistochemistry to study the regulatory role of tRF-28 by binding to the 3'UTR of CCND1. Results: This study clarified the tRF-28 levels in the plasma of healthy individuals, and gastric benign and malignant lesions, providing a new candidate biomarker for the early diagnosis of gastric cancer. Through upregulating and downregulating the level of tRF-28 in gastric cancer cells, it was revealed that tRF-28 inhibits the proliferation of gastric cancer cells in vivo and in vitro by regulating key proteins such as Cyclin D1, CDK4, Rb, and p-Rb. In studying specific molecular mechanisms, tRF-28 and CCND1 were co-located in the cytoplasm. tRF-28 combines with Ago2 protein to form a complex and plays a role in silencing the target gene CCND1 in the cytoplasm. The rescue experiments revealed that silencing the target gene CCND1 can reverse the carcinogenesis effect of tRF-28 inhibitors, clarifying the biological functions of tRF-28 by regulating CCND1. Conclusions: Based on a series of research findings, we elucidated that tRF-28 form a complex with Ago2 protein, binding to the 3' UTR of CCND1 to downregulate Cyclin D1, CDK4, and other critical proteins, thereby inhibiting the proliferation of gastric cancer cells. Our study aims to offer new insights into identifying potential early diagnostic markers and therapeutic targets for gastric cancer.

Role of cfDNA and DNA integrity index (DII) in colon cancer in response to surgery.

236 Background: Colorectal cancer diagnosis requires new biomarkers for improved detection and monitoring. cfDNA has shown potential in detecting minimal residual disease, evaluating treatment response, and providing prognostic information. Recent studies highlight cfDNA as a promising molecular marker for early disease detection and progression monitoring. This study aims to evaluate the role of cfDNA and DII in assessing surgical response in CRC patients. The primary objective is to assess cfDNA levels pre- and post-curative resection. Secondary objectives include identifying factors influencing baseline cfDNA levels, evaluating factors affecting DII, and comparing cfDNA and CEA levels in response to surgery. Statistical analyses included descriptive statistics, ROC curve, Student T tests and Fisher's exact test. Methods: The study was designed as a prospective investigation conducted over a period from September 2022 to April 2024 at the Regional Cancer Centre. Forty pathologically proven non metastatic colonic carcinoma planned for primary surgery were included and patients with sepsis and chronic diseases were excluded from the study. Blood samples (10 ml) were collected pre-surgery and at four weeks post-surgery. Plasma cfDNA was extracted, quantified, and analyzed via quantitative real-time PCR using human β-actin as a reference. The DII was calculated as the ratio of 394 bp to 99 bp amplicons of β-actin. Results: The mean age was 62.15 years (range 39-85), with 55% over 60 years. High-risk features included poor differentiation (4.2%), preoperative CEA &gt;5 ng/ml (17.5%), LVI (20.8%), and PNI (6.3%). Surgical approaches included 10 laparoscopic, 29 open, and 1 converted from laparoscopic to open due to excessive bleeding. Overall stage grouping showed 18 patients in Stage III, and 11 each in Stage I and II. Median pre- and postoperative cfDNA levels were 24.2 ng/μl and 29.6 ng/μl (p=0.83), and median DNA integrity index levels were 1.1 and 1.0 (p=0.95). Preoperative cfDNA levels averaged 24.2 ng/μl and postoperative levels 29.6 ng/μl (p = 0.83); DII levels were 1.1 preoperatively and 1.0 postoperatively (p = 0.95). Postoperative cfDNA levels decreased in 21 patients and increased in 19, while DII decreased in 20 and increased in 20. Significant associations were noted for cfDNA changes with surgery type and high-risk features. ROC analysis revealed cfDNA cut-off at 275 ng/μl, DII at 1.5, and CEA at 4 µg/L. Sensitivities for cfDNA and DII were 66.67% and 100%, respectively, with combined sensitivity reaching 100%. Conclusions: Persistent high cfDNA levels post-surgery suggest potential minimal residual disease despite radical resection. The residual disease is a harbinger of systemic failure. Monitoring cfDNA and DII can identify patients at risk for recurrence, guiding intensified adjuvant therapy. Further studies with extended follow-up are recommended to validate these findings. Clinical trial information: CTRI/2023/10/058468 .

Generating 3D brain tumor regions in MRI using vector-quantization Generative Adversarial Networks.

Medical image analysis has significantly benefited from advancements in deep learning, particularly in the application of Generative Adversarial Networks (GANs) for generating realistic and diverse images that can augment training datasets. The common GAN-based approach is to generate entire image volumes, rather than the region of interest (ROI). Research on deep learning-based brain tumor classification using MRI has shown that it is easier to classify the tumor ROIs compared to the entire image volumes. In this work, we present a novel framework that uses vector-quantization GAN and a transformer incorporating masked token modeling to generate high-resolution and diverse 3D brain tumor ROIs that can be used as additional data for tumor ROI classification. We apply our method to two imbalanced datasets where we augment the minority class: (1) low-grade glioma (LGG) ROIs from the Multimodal Brain Tumor Segmentation Challenge (BraTS) 2019 dataset; (2) BRAF V600E Mutation genetic marker tumor ROIs from the internal pediatric LGG (pLGG) dataset. We show that the proposed method outperforms various baseline models qualitatively and quantitatively. The generated data was used to balance the data to classify brain tumor types. Our approach demonstrates superior performance, surpassing baseline models by 6.4% in the area under the ROC curve (AUC) on the BraTS 2019 dataset and 4.3% in the AUC on the internal pLGG dataset. The results indicate the generated tumor ROIs can effectively address the imbalanced data problem. Our proposed method has the potential to facilitate an accurate diagnosis of rare brain tumors using MRI scans.

Diagnostic Value and Thyroid Hormone Variations in Pregnant Women During Pregnancy in Hui'an County in China.

To evaluate the diagnostic value of thyroid hormones in pregnancy-related thyroid conditions and ascertain the reference range of thyroid hormones in Hui'an pregnant women. We examined 760 pregnant women (406 early, 172 mid, and 182 late pregnancy) and 114 non-pregnant controls. A 95% medical reference range was computed based on measurements of thyroid hormone levels (FT3, FT4, and TSH). Group comparisons were conducted, and the diagnostic accuracy was assessed using ROC curves. There were significant differences in thyroid hormone levels between pregnant women at different stages and non-pregnant women (P < 0.05). In contrast to mid-pregnancy and controls, FT3 and FT4 were higher in the early and late stages of pregnancy (P < 0.05), although TSH was decreased during pregnancy. Compared to healthy or hypothyroid pregnant women, the diagnostic positive rate for hyperthyroidism was greater (P < 0.05). TSH, FT3, and FT4 had larger AUCs in ROC analysis for identifying hyperthyroidism than hypothyroidism (P < 0.05), and the combination of these markers improved diagnostic accuracy (P < 0.05). In Hui'an, thyroid hormone levels vary over the weeks of pregnancy and between pregnant and non-pregnant women. By establishing local reference ranges, thyroid problems in pregnancy can be diagnosed, and complications can be avoided.

Using integrative bioinformatics approaches and machine-learning strategies to identify potential signatures for atrial fibrillation.

Atrial fibrillation (AF) is the most common tachyarrhythmia and seriously affects human health. Key targets of AF bioinformatics analysis can help to better understand the pathogenesis of AF and develop therapeutic targets. The left atrial appendage tissue of 20 patients with AF and 10 patients with sinus rhythm were collected for sequencing, and the expression data of the atrial tissue were obtained. Based on this, 2578 differentially expressed genes were obtained through differential analysis. Different express genes (DEGs) were functionally enriched on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), mainly focusing on neuroactive ligand-receptor interactions, neuronal cell body pathways, regulation of neurogenesis, and neuronal death, regulation of neuronal death, etc. Secondly, 14 significant module genes were obtained by analyzing the weighted gene co-expression network of DEGs. Next, LASSO and SVM analyzes were performed on the differential genes, and the results were in good agreement with the calibration curve of the nomogram model for predicting AF constructed by the weighted gene co-expression network key genes. The significant module genes obtained by the area under the ROC curve (AUC) analysis were analyzed. Through crossover, two key disease characteristic genes related to AF, HOXA2 and RND2, were screened out. RND2 was selected for further research, and qPCR verified the expression of RND2 in sinus rhythm patients and AF patients. Patients with sinus rhythm were significantly higher than those in AF patients. Our research indicates that RND2 is significantly associated with the onset of AF and can serve as a potential target for studying its pathogenesis.

Evaluating systemic immune-inflammation indices as predictive markers for endometriosis diagnosis: A retrospective observational study.

Endometriosis is a chronic inflammatory disease for which there is currently no accurate screening test to identify or predict the probability of the disease in individuals. This can often lead to delays in diagnosis. Several systemic immune-inflammation indices are currently used as predictive or supportive markers for several inflammation-associated diseases. In this study, we investigated whether these immune-inflammation indices, such as systemic immune inflammation index (SII), systemic inflammation response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), and pan-immune inflammation value (PIV) could serve as predictive or supplementary markers for diagnosing endometriosis. A total of 434 women with confirmed endometriosis and 517 controls were included in this study. Data on peripheral blood tests, including total counts of white cells, neutrophils, monocytes, lymphocytes, and platelets, were collected, and systemic immune-inflammation indices were calculated. SII, SIRI, NLR, and PIV values were significantly higher in women diagnosed with endometriosis compared to controls. Using the cut-off values of 538 for SII, 0.814 for SIRI, 2.03 for NLR, and 210 for PIV, we achieved 76 % sensitivity and 70 % specificity. When the four indices were combined, the area under the ROC curve (AUC) was 0.796 (95 % CI: 0.766, 0.827), with 76 % sensitivity and 70 % specificity. In conclusion, while ultrasonography or MRI remains the gold standard for visualizing the lesions in diagnosing endometriosis, followed by laparoscopy and histologic verification, routine peripheral blood tests in combination with clinical symptoms, could provide additional clinical diagnostic value for endometriosis as a non-invasive and cost-effective test.

The impact of diabetes on Sepsis-induced cardiomyopathy.

This study investigated the association between diabetes and Sepsis-induced cardiomyopathy (SIC), focusing on how changes in inflammatory response and cardiac function influence SIC prognosis. The aim is to provide clinicians with more accurate treatment and management strategies, ultimately enhancing patient outcomes and quality of life. This retrospective cohort study analyzed 258 Sepsis-induced cardiomyopathy (SIC) patients, stratified by diabetes status and HbA1C levels. Data were collected from electronic medical records. Statistical tests included the Kolmogorov-Smirnov, t-test, Mann-Whitney U, Kruskal-Wallis, chi-square, and Spearman correlation. Univariate and multivariate logistic regression assessed diabetes' impact on SIC severity. Model fit was evaluated with the Hosmer-Lemeshow and negative log-likelihood ratio tests. A nomogram was constructed and validated using ROC curves, calibration curves, and decision curve analysis. Subgroup and interaction analyses were performed (P<0.05). Diabetes worsened inflammation and immune responses in SIC, significantly affecting markers like LVEF, TnI, CK-MB, BNP, NLR, IL-6, PCT, CRP, APACHE II, and SOFA scores (P<0.05). Grouping by HbA1C levels revealed no significant differences in LVEF (P=0.078), Alb (P=0.105), or L/A (P=0.211), but differences were found for TnI, CK-MB, BNP, NLR, IL-6, PCT, CRP, APACHE II, and SOFA (P<0.05). HbA1C strongly correlated with CRP (rs=0.8664). BNP (OR 1.001) and HbA1C (OR 1.302) were significant risk factors for SIC, with the nomogram showing good predictive performance (AUC 0.693). No significant interaction between HbA1C and BNP on SIC severity was observed (P=0.791). Diabetes exacerbates inflammatory and immune responses in Sepsis-induced cardiomyopathy patients, leading to worsened cardiac function.

Hospital frailty risk score predicts postoperative outcomes after endoscopic endonasal resection of non-functioning pituitary adenomas.

Frailty indices are invaluable resources in risk stratification and predicting high-value care outcomes for neurosurgical patients. The Hospital Frailty Risk Score (HFRS) is a recently developed and validated method for evaluating frailty; however, its implementation has yet to be assessed in patients with non-functioning pituitary adenomas undergoing endoscopic endonasal resection. In this study, we aimed to evaluate HFRS's predictive ability for high-value care outcomes, namely postoperative complications, length of stay (LOS), and hospital charges, and to compare it to other traditionally used frailty indices. A retrospective review of electronic medical records from 2017 to 2020. A total of 109 ICD-10 codes corresponding to various frailty-related conditions were used to identify the components of HFRS. These components were then used to calculate the HFRS for each patient, with higher scores indicative of elevated frailty. Standard multivariate logistic regression models were employed to explore the association between HFRS and high-value care outcomes. Model discrimination was assessed using the area under the ROC curves, and the DeLong test was used to compare AUCs. A total of 172 patients were included, with a mean age of 57.27 ± 12.95 years and an average HFRS score of 3.65 3.27. Among patients, 56% were male, 5.2% experience postoperative complications, 23.3% endured extended LOS, 25.0% incurred high hospital charges. In multivariate regression models, greater HFRS was significantly and independently associated with postoperative complications (OR = 1.51, P < 0.001), extended LOS (OR = 1.17, P = 0.006) and high hospital charges (OR = 1.18, P = 0.004). HFRS had the highest AUC compared to other frailty indices and was the most parsimonious model, with AUC values of 0.82, 0.64, and 0.63 for predicting complications, extended LOS, and higher charges, respectively. Higher HFRS scores are significantly associated with postoperative complications, prolonged LOS, and high hospital charges for patients undergoing pituitary surgery.

Correlation of HLA-A and HLA-B/C Expression With ESR1 Expression in Patients With Metastatic Breast Cancer as a Potential Prognosticator of Favorable Distant Disease-free Survival.

The loss of breast cancer cell differentiation during metastatic progression leads to a down-regulation of class 1 human leukocyte antigen (HLA) expression, which in turn hinders cytotoxic T lymphocytes from effectively preventing tumor cell proliferation. Consequently, one would expect that decreased HLA expression would correlate with decreased 5-year survival. However, estrogen receptor alpha (ESR1) is known to be positively associated with overall survival. The study aimed to determine the expression levels of HLA-A, HLA-B/C, and ESR1 and to assess their influence on distant disease-free survival (DDFS). This retrospective subgroup analysis of the initial prospective, single-center, double-blind cohort study included a total of 34 patients who underwent a new treatment line for metastatic breast cancer (MBC). The MBC cells were examined using RT-qPCR. The acquired data and the subsequent survival and ROC analyses indicated a positive association of reduced expression of HLA-A and HLA-B/C with DDFS. A statistically significant association of ESR1 with DDFS could not be shown. A potential positive association between reduced expression of HLA-A and HLA-B/C and DDFS is observed. This contrasts with the generally observed association between HLA expression loss and poor prognosis, as reported in previous protein-based studies. In metastatic settings, reduced expression of particular HLA subsets, measured at the mRNA level, might have a protective effect against disease progression.

Thermographic images for screening oral health problems in older adults: A pilot study

ObjectiveThis pilot study assessed the feasibility of using facial thermography to detect intra-oral problems in older adults with cognitive decline and care-resistant behaviors, who are often unable to communicate pain or early symptoms. MethodsTwenty-three older adults (mean age 73.7 ± 13.2 years) with cognitive decline were enrolled. Thermal images of four facial views were taken using a smartphone-connected FLIR thermal camera. Intra-oral examinations were conducted, and the thermographic data were analyzed to extract temperature values in the regions of interest (ROI). Point-biserial correlations and ROC curve analyses were performed to evaluate associations between temperature data and clinical findings, with a significance level of p<0.05. ResultsIntra-oral issues requiring treatment were found in 12 participants, with six reporting clinical pain. The overall mean temperature in the ROI was 33.5 ± 3.9°C, and significant temperature differences were found between the body and ROI temperatures. Correlations were observed between clinical problems and various temperature metrics, including the minimum and maximum ROI temperatures (rpb=-0.327, p=0.002 and rpb=-0.309, p=0.003). ROC analysis indicated that ROI temperature could predict the presence or absence of clinical problems, with AUC values ranging from 0.651 to 0.796 for different metrics. ConclusionThermographic facial imaging shows significant potential as a non-invasive tool for detecting oral health problems in vulnerable older adults. While promising, further research is essential to enhance image quality, streamline the technique, and incorporate AI for improved diagnostic accuracy and ease of use. Clinical SignificanceThis non-invasive, inexpensive technique is easy to perform, independent of patient compliance and, is promising to detect early oral problems in noncommunicative patients.