Low Score Group Research Articles

The optimal measurement method considering reliability and validity in the anterior knee laxity of anterior cruciate ligament tears.

To seek an optimal measurement method with high reliability and high validity for evaluation of the anterior knee laxity on stress radiographs and comparing the translation values to those of KT-2000 arthrometer. Anterior knee laxity in 77 patients was measured preoperatively using the TelosTM and the KT-2000 arthrometer. Side-to-side difference measurements were taken using three conventional measuring methods and one proposed method (Modified Lateral). The knee position on the stress radiograph was evaluated and scored based on the stress radiograph qualifying criteria depending on stress film correctiveness. Intraclass correlation coefficients were analyzed to evaluate the reliability of the measurement methods and were compared between high (Group H) and low (Group L) radiograph quality score groups for each method. Validity was assessed by comparing the KT-2000 and the TelosTM using Pearson correlation (r value). The Modified Lateral method showed the best Intraclass Correlation Coefficients (ICCs), followed by Center to Center, and Medial to Medial and Lateral to Lateral methods without considering the quality of Telos. In the comparison between groups based on Telos quality for intra-rater reliability, the Medial to Medial (MM) method demonstrated the best reliability in both groups (MM: ICCs, Group H = 0.942, Group L = 0.917, P = 0.693). As for inter-rater reliability, the Modified Lateral (ML) method exhibited the best reliability in both groups (ML: ICCs, Group H = 0.923, Group L = 0.882, P = 0.547). The value measured using the ML method in Telos showed the highest correlation coefficient with the KT-2000 measured value in both groups H and L. There were no statistically significant differences among the correlation coefficient values. The Modified Lateral method is recommended for its high reliability, taking into account the differences in bilateral knee positions and anatomical discriminability on stress radiographs when evaluating anterior knee translation with Telos. It also best reflected the KT-2000 arthrometer. Case Series, Level IV.

Intracranial artery calcification: Frequency, determinants, and modification of outcomes from endovascular thrombectomy

IntroductionIntracranial artery calcification (ICAC) is a common finding on computed tomography (CT) in patients presenting with large vessel occlusion acute ischemic stroke (LVO-AIS) and could serve as a useful biomarker of intracranial atherosclerosis and altered intracranial vessel pliability in patients undergoing endovascular thrombectomy (EVT). MethodsThis was a retrospective cohort study analyzing consecutive patients undergoing CT head prior to EVT between 2016 and 2020. Extent of ICAC proximal to the target vessel was scored using a validated grading scale examining thickness and circumferential extent of calcifications. The relationship between 3 levels of ICAC burden and procedural, clinical, and safety outcomes was analyzed. ResultsAmong 86 patients meeting inclusion criteria, ICAC of any degree was present in 72.1 %. Median ICAC score was 3 [IQR 0-4]. There was a U-shaped association between ICAC score and successful reperfusion: 90.9 %, 65.7 %, and 94.4 % in the low, intermediate, and high ICAC score groups, respectively (p = 0.008). Use of rescue intervention, most often angioplasty and stenting, was greatest in the high ICAC score group: 3.0 % vs. 5.7 % vs. 22.2 % (p = 0.05). Functional independence at 90 days did not differ significantly among groups (41.7 % vs. 31.0 % vs. 15.4 %, p = 0.26), nor did rates of symptomatic intracranial hemorrhage (15.2 % vs. 14.3 % vs. 16.7 %, p = 0.97). ConclusionsICAC is seen on CT in nearly three-quarters of patients with LVO-AIS. Extent of ICAC has a U-shaped association with successful reperfusion, in part due to more frequent use of rescue interventions in patients with extensive ICAC.

Results from a real-world study: a novel glycosyltransferase risk score for prognosis, tumor microenvironment phenotypes and immunotherapy in bladder cancer

BackgroundAlthough immunotherapy shows tremendous potential in the treatment of bladder cancer (BLCA), the overall prognosis and response rates to immunotherapy in BLCA remain suboptimal.MethodsWe performed an extensive evaluation of glycosyltransferase expression patterns in BLCA patients by analyzing 210 glycosyltransferase-related genes. Subsequently, we established correlations between these glycosyltransferase patterns, prognosis, and tumor microenvironment (TME) phenotypes. To offer personalized patient assessments, we developed a glycosyltransferase risk score that accurately predicts prognosis, TME phenotypes, and molecular subtypes. Importantly, we developed a RNA-seq cohort, named Xiangya cohort, to validate our results.ResultsTwo distinct patterns of glycosyltransferase expression were identified, corresponding to inflamed and noninflamed TME phenotypes, and demonstrated the potential to predict prognosis. We developed and validated a comprehensive risk score that accurately predicted individual patient prognosis in the TCGA-BLCA cohort. Additionally, we constructed a nomogram that integrated the risk score with several key clinical factors. Importantly, this risk score was successfully validated in external cohorts, including the Xiangya cohort and GSE48075. Furthermore, we discovered a positive correlation between this risk score and tumor-infiltrating lymphocytes in both the TCGA-BLCA and Xiangya cohorts, suggesting that patients with a higher risk score exhibited an inflamed TME phenotype and were more responsive to immunotherapy. Finally, we observed that the high and low risk score groups were consistent with the luminal and basal subtypes of BLCA, respectively, providing further validation of the risk score’s role in the TME in terms of molecular subtypes.ConclusionsGlycosyltransferase patterns exhibit distinct TME phenotypes in BLCA. Our comprehensive risk score provides a promising approach for prognostic prediction and assessment of immunotherapy efficacy, offering valuable guidance for precision medicine.

A platelet-related signature for predicting the prognosis and immunotherapy benefit in bladder cancer based on machine learning combinations.

Bladder cancer carries a large societal burden, with over 570,000 newly diagnosed cases and 210,000 deaths globally each year. Platelets play vital functions in tumor progression and therapy benefits. We aimed to construct a platelet-related signature (PRS) for the clinical outcome of bladder cancer cases. Ten machine learning techniques were used in the integrative operations to build PRS using the datasets from The Cancer Genome Atlas (TCGA), gene series expression (GSE)13507, GSE31684, GSE32894 and GSE48276. A number of immunotherapy datasets and prediction scores, including GSE91061, GSE78220, and IMvigor210, were utilized to assess how well the PRS predicted the benefit of immunotherapy. Vitro experiment was performed to verify the role of α1C-tubulin (TUBA1C) in bladder cancer. Enet (alpha =0.4) algorithm-based PRS had the highest average C-index of 0.73 and it was suggested as the optimal PRS. PRS acted as an independent risk factor for bladder cancer and patients with high PRS score portended a worse overall survival rate, with the area under the curve of 1-, 3- and 5-year operating characteristic curve being 0.754, 0.779 and 0.806 in TCGA dataset. A higher level of immune-activated cells, cytolytic function and T cell co-stimulation was found in the low PRS score group. Low PRS score demonstrated a higher tumor mutation burden score and programmed cell death protein 1 & cytotoxic T-lymphocyte associated protein 4 immunophenoscore, lower tumor immune dysfunction and exclusion score, intratumor heterogeneity score and immune escape score in bladder cancer, suggesting the PRS as an indicator for predicting immunotherapy benefits. Vitro experiment showed that TUBA1C was upregulated in bladder cancer and knockdown of TUBA1C obviously suppressed tumor cell proliferation. The present study developed an ideal PRS for bladder cancer, which may be used as a predictor of prognosis, a risk classification system, and a therapy guide.

Healthy Lifestyles Modify the Association of Melatonin Receptor 1B Gene and Ischemic Stroke: A Family-Based Cohort Study in Northern China.

Limited research has reported the association between MTNR1B gene polymorphisms and ischemic stroke (IS), and there is insufficient evidence on whether adopting a healthy lifestyle can mitigate genetic risks in this context. This study aimed to investigate the associations between MTNR1B gene variants (rs10830963 and rs1387153) and IS, examining the potential effect of gene-lifestyle interactions on IS risk. Conducted in northern China, this family-based cohort study involved 5116 initially IS-free subjects. Genotype data for rs10830963 and rs1387153 in MTNR1B were collected. Eight modifiable lifestyle factors, including body mass index (BMI), smoking, alcohol consumption, dietary habits, physical activity, sedentary time, sleep duration, and chronotype, were considered in calculating healthy lifestyle scores. Multilevel Cox models were used to examine the associations between MTNR1B variants and IS. Participants carrying the rs10830963-G and rs1387153-T alleles exhibited an elevated IS risk. Each additional rs10830963-G allele and rs1387153-T allele increased the IS risk by 36% (HR = 1.36, 95%CI, 1.12-1.65) and 32% (HR = 1.32, 95%CI, 1.09-1.60), respectively. Participants were stratified into low, medium, and high healthy lifestyle score groups (1537, 2188, and 1391 participants, respectively). Genetic-lifestyle interactions were observed for rs10830963 and rs1387153 (p for interaction < 0.001). Notably, as the healthy lifestyle score increased, the effect of MTNR1B gene variants on IS risk diminished (p for trend < 0.001). This study underscores the association between the MTNR1B gene and IS, emphasizing that adherence to a healthy lifestyle can mitigate the genetic predisposition to IS.

Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score As a Predictor of Prognosis After Hepatectomy.

The hemoglobin, albumin, lymphocyte, and platelet (HALP) score is an immune-nutritional assessment score that is a prognostic indicator for several malignant tumors. This study aimed to investigate its prognostic value in patients who underwent hepatectomy for hepatocellular carcinoma. Data of 685 patients with hepatocellular carcinoma who underwent hepatectomy at Kurume University between 2006 and 2021 were retrospectively analyzed. The patients were classified into high and low HALP score groups based on a cut-off HALP score determined using a receiver operating characteristic curve. To minimize bias, 1:1 propensity score matching was performed. Kaplan-Meier curves were used to estimate survival time, and data were evaluated using the log-rank test. Univariate and multivariate analyses were performed using Cox hazard or logistic regression models for assessing survival time and postoperative outcomes, respectively. Low HALP scores were significantly associated with poor overall survival (p=0.0066). Univariate and multivariate analyses revealed that the HALP score independently predicted overall survival (p=0.005). However, the HALP score was not significantly related to recurrence-free survival or postoperative outcomes. The HALP score is a simple inexpensive tool for predicting prognosis after hepatectomy for hepatocellular carcinoma.

Neutrophil extracellular trap related risk score exhibits crucial prognostic value in skin cutaneous melanoma, associating with distinct immune characteristics.

Neutrophil extracellular traps (NETs) are related to the prognosis of cancer patients. Nevertheless, the potential prognostic values of NETs in skin cutaneous melanoma (SKCM) remains largely unknown. The NET-related gene signature was constructed by LASSO Cox regression analysis using the TCGA-SKCM cohort. The overall survival (OS) and immune status in SKCM patients between the high- and low-NET score (high-score, low-score) groups were explored. The scRNA-seq dataset GSE115978 was used to understand the role of NET score in SKCM at single cell resolution. A five NET genes-based signature (TLR2, CLEC6A, PDE4B, SLC22A4 and CYP4F3) was constructed as the NET-related prognostic model for SKCM. The OS of SKCM patients with low-score was better than that in patients with high-score. Additionally, NET score was negatively associated with infiltration of some immune cells (e.g. type I Macrophages, CD8-T cells, CD4-T cells). Moreover, patients with high-score had low stromal, immune and ESTIMATE scores. Furthermore, drug sensitivity analysis results showed that Lapatinib, Trametinib and Erlotinib may have better therapeutic advantages in patients with high-score. We established a NET-related five gene signature in SKCM and found that the NET-related signature may exhibit a good predictive ability for SKCM prognosis. The NET score may not only predict the survival outcome and drug sensitivity in SKCM, but also reflect the immune conditions of SKCM patients.

Immune infiltration and prognosis in gastric cancer: role of NAD+ metabolism-related markers.

This study endeavored to develop a nicotinamide adenine dinucleotide (NAD+) metabolism-related biomarkers in gastric cancer (GC), which could provide a theoretical foundation for prognosis and therapy of GC patients. In this study, differentially expressed genes (DEGs1) between GC and paraneoplastic tissues were overlapped with NAD+ metabolism-related genes (NMRGs) to identify differentially expressed NMRGs (DE-NMRGs). Then, GC patients were divided into high and low score groups by gene set variation analysis (GSVA) algorithm for differential expression analysis to obtain DEGs2, which was overlapped with DEGs1 for identification of intersection genes. These genes were further analyzed using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses to obtain prognostic genes for constructing a risk model. Enrichment and immune infiltration analyses further investigated investigate the different risk groups, and qRT-PCR validated the prognostic genes. Initially, we identified DE-NMRGs involved in NAD biosynthesis, with seven (DNAJB13, CST2, THPO, CIDEA, ONECUT1, UPK1B and SNCG) showing prognostic significance in GC. Subsequent, a prognostic model was constructed in which the risk score, derived from the expression profiles of these genes, along with gender, emerged as robust independent predictors of patient outcomes in GC. Enrichment analysis linked high-risk patients to synaptic membrane pathways and low-risk to the CMG complex pathway. Tumor immune infiltration analysis revealed correlations between risk scores and immune cell abundance, suggesting a relationship between NAD+ metabolism and immune response in GC. The prognostic significance of our identified genes was validated by qRT-PCR, which confirmed their upregulated expression in GC tissue samples. In this study, seven NAD+ metabolism-related markers were established, which is of great significance for the development of prognostic molecular biomarkers and clinical prognosis prediction for gastric cancer patients.

Prognostic Value of the Controlling Nutritional Status (CONUT) Score in Patients Who Underwent Cytoreductive Surgery Combined with Hyperthermic Intraperitoneal Chemotherapy.

The Controlling Nutritional Status (CONUT) score is a novel nutritional index that integrates the serum albumin level, peripheral blood lymphocyte count, and total cholesterol level. This retrospective study explores its prognostic significance in patients undergoing cytoreductive surgery combined with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC). We included 436 patients who underwent CRS-HIPEC, categorized into low (0-3) and high (4-12) CONUT score groups, and performed logistic regression analysis to predict one-year mortality and postoperative morbidity. Our findings revealed that high CONUT scores correlate with increased one-year mortality (47.1% vs. 20.3%, p < 0.001) and morbidity (39.2% vs. 18.2%, p < 0.001) compared to low CONUT scores. Multivariable regression analysis confirmed high CONUT scores as independent predictors of one-year mortality (odds ratio: 2.253, 95% CI: 1.014-5.005, p = 0.046) and postoperative morbidity (odds ratio: 2.201, 95% CI: 1.066-4.547, p = 0.033). These results underscore the CONUT score's effectiveness as an independent marker for evaluating risks associated with CRS-HIPEC, emphasizing its potential to improve risk stratification.

Spatial transcriptome and single-cell reveal the role of nucleotide metabolism in colorectal cancer progression and tumor microenvironment

BackgroundThe intricacies of nucleotide metabolism within tumor cells specific to colorectal cancer (CRC) remain insufficiently characterized. A nuanced examination of particular tumor clusters and their dynamic interplay with the tumor microenvironment (TME) may yield profound insights into these therapeutically auspicious communicative networks.MethodsBy integrating ten types of single-cell enrichment scoring methods, we carried out enrichment analysis on CRC cell types, which was validated through four additional single-cell cohorts. Groups of tumor cells were determined using the average values of the scores. Using cellphonedb, monocle, inferCNV, SCENIC, and Cytotrace, functional analyses were performed. Utilizing the RCTD approach, single-cell groupings were mapped onto spatial transcriptomics, analyzing cell dependency and pathway activity to distinguish between tumor cell subtypes. Differential expression analysis identified core genes in nucleotide metabolism, with single-cell and spatial transcriptomics analyses elucidating the function of these genes in tumor cells and the immune microenvironment. Prognostic models were developed from bulk transcriptome cohorts to forecast responses to immune therapy. Laboratory experiments were conducted to verify the biological function of the core gene.ResultsNucleotide metabolism is significantly elevated in tumor cells, dividing them into two groups: NUhighepi and NUlowepi. The phenotype NUhighepi was discerned to exhibit pronounced malignant attributes. Utilizing the analytical tool stlearn for cell-to-cell communication assessment, it was ascertained that NUhighepi engages in intimate interactions with fibroblasts. Corroborating this observation, spatial transcriptome cell interaction assessment through MISTy unveiled a particular reliance of NUhighepi on fibroblasts. Subsequently, we pinpointed NME1, a key gene in nucleotide metabolism, affirming its role in thwarting metastasis via in vitro examination. Utilizing multiple machine learning algorithms, a stable prognostic model (NRS) has been developed, capable of predicting survival and responses to immune therapy. In addition, targeted drugs have been identified for both high and low scoring groups. Laboratory experiments have revealed that NME1 can inhibit the proliferation and invasion of CRC tumor cells.ConclusionOur study elucidates the potential pro-tumor mechanism of NUhighepi and the role of NME1 in inhibiting metastasis, further deepening the understanding of the role of nucleotide metabolism in colorectal cancer, and providing valuable targets for disrupting its properties.

Integrating single-cell RNA-seq to identify fibroblast-based molecular subtypes for predicting prognosis and therapeutic response in bladder cancer.

Bladder cancer (BLCA) is a highly aggressive and heterogeneous disease, posing challenges for diagnosis and treatment. Cancer immunotherapy has recently emerged as a promising option for patients with advanced and drug-resistant cancers. Fibroblasts, a significant component of the tumor microenvironment, play a crucial role in tumor progression, but their precise function in BLCA remains uncertain. Single-cell RNA sequencing (scRNA-seq) data for BLCA were obtained from the Gene Expression Omnibus database. The R package "Seurat" was used for processing scRNA-seq data, with uniform manifold approximation and projection (UMAP) for downscaling and cluster identification. The FindAllMarkers function identified marker genes for each cluster. Differentially expressed genes influencing overall survival (OS) of BLCA patients were identified using the limma package. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and chemotherapeutic drug sensitivity between high- and low-risk groups were investigated. RT-qPCR and immunohistochemistry validated the expression of prognostic genes. Fibroblast marker genes identified three molecular subtypes in the testing set. A prognostic signature comprising ten genes stratified BLCA patients into high- and low-score groups. This signature was validated in one internal and two external validation sets. High-score patients exhibited increased immune cell infiltration, elevated chemokine expression, and enhanced immune checkpoint expression but had poorer OS and a reduced response to immunotherapy. Six sensitive anti-tumor drugs were identified for the high-score group. RT-qPCR and immunohistochemistry showed that CERCAM, TM4SF1, FN1, ANXA1, and LOX were highly expressed, while EMP1, HEYL, FBN1, and SLC2A3 were downregulated in BLCA. A novel fibroblast marker gene-based signature was established, providing robust predictions of survival and immunotherapeutic response in BLCA patients.

The relationship between NLR, LDL-C/HDL-C, NHR and coronary artery disease.

Chronic inflammation and dyslipidemia are key risk factors for atherosclerotic cardiovascular diseases. We retrospectively explored the association between the neutrophil to lymphocyte ratio (NLR), the ratio of low-density lipoprotein cholesterol (LDL-C) to high-density lipoprotein cholesterol (HDL-C), and the neutrophil to HDL-C ratio (NHR), and the severity of coronary lesions in patients with acute coronary syndrome (ACS). In June 2023, we selected 1210 patients who were diagnosed with ACS based on chest pain from January 2017 to December 2022. Of these, 1100 patients with abnormal coronary angiography were categorized into the experimental group, and 110 patients with normal coronary angiography were classified as the control group. We collected routine blood tests, lipid profiles, and coronary angiography results at admission (before coronary angiography). Patients were then stratified into a control group (Gensini score = 0) and an experimental group (Gensini score = 0) based on the Gensini score. The experimental group was further divided into a low score group (Gensini score < 69) and a high score group (Gensini score ≥ 69). 1. Statistically significant differences were observed between the control and experimental groups in terms of gender, age, body mass index (BMI), hypertension, diabetes, smoking history, and counts of neutrophils (NEU), lymphocytes (LYM), monocytes (MON), eosinophils (EOS), red cell distribution width (RDW), total cholesterol (TC), HDL-C, LDL-C, NLR, LDL-C/HDL-C, and NHR (P&lt;0.05). Furthermore, differences in BMI, hypertension, diabetes, smoking history, NEU, LYM, MON, TC, triglyceride (TG), HDL-C, LDL-C, NLR, LDL-C/HDL-C, and NHR were significant between the low and high score groups (P&lt;0.05). 2. NEU, LYM, MON, TC, HDL-C, LDL-C, NLR, LDL-C/HDL-C, and NHR showed significant correlations with the Gensini score (r>0.2, P<0.05), with NLR and LDL-C/HDL-C showing the strongest correlations (r = 0.822, P = 0.000). 3. The Receiver Operating Characteristic (ROC) curve indicated that the combination of NLR and LDL-C/HDL-C had superior sensitivity and specificity in predicting the severity of coronary lesions, with a significant difference (P&lt;0.05). The sensitivity was 87.1%, the specificity was 90.9%, and the cut-off point was 2.04. 4. A predictive model was developed based on the ratio of NLR and LDL-C/HDL-C to the Gensini score. The final model score was calculated as 6.803 + 7.029NLR + 13.079LDL-C/HDL-C (R2 = 0.708). Compared to NLR, LDL-C/HDL-C, and NHR, the combined NLR and LDL-C/HDL-C ratio is a more accurate marker for assessing the severity of coronary artery disease in ACS patients. Its convenience and effectiveness make it a promising tool for early assessment, timely risk stratification, and appropriate clinical intervention, ultimately improving clinical outcomes for ACS patients.

P-240 Is the intelligent Data Analysis Score (iDAScore) a reliable tool to predict pregnancy? Our center’s experience

Abstract Study question Is the intelligent Data Analysis Score (iDAScore) reliable in predicting a positive pregnancy test, clinical pregnancy and miscarriage rate after single vitrified-warmed blastocyst transfer (SVBT)? Summary answer There is a significant increase in positive pregnancy test and clinical pregnancy rates as iDAScore increases. The miscarriage rate is lower with increased iDAScore. What is known already With the improvement of assisted reproductive technology (ART), elective single embryo transfer has become a standard. Optimizing embryo selection is a major challenge to increase reproductive outcomes. The Gardner embryo grading system is widely adopted for the evaluation of blastocyst quality, but this tool is subject to inter- and intra-variability. In recent years, artificial intelligence has found diverse applications in healthcare. Based on time-laps sequences of &amp;gt; 180’000 developing embryos, iDAScore is a new deep-learning model for objective and standardized blastocyst scoring. However, its reliability in predicting pregnancy and miscarriage rates remains unknown. Study design, size, duration This monocentric retrospective pilot study was conducted from May 2023 to December 2023. A total of 206 homologous SVBT cycles from 206 patients were analyzed (one patient, one cycle). Exclusion criteria included: cycles involving preimplantation genetic testing, multiple and/or fresh blastocyst transfer, and blastocysts obtained after testicular sperm extraction. All vitrified-warmed blastocysts were scored using iDAScore version 1.0 model, ranging from 1 – 9.9. Participants/materials, setting, methods Scores were stratified into 3 groups: high-score (9.9 – 7.7), medium-score (7.6 – 5.5) and low-score (5.4 – 3.1). For each group, positive pregnancy test, clinical pregnancy and miscarriage rates were analyzed. SVBT cycles were then stratified into four maternal age groups (&amp;lt; 35, 35-37, 38-40, &amp;gt;41 years) and the same outcomes were analyzed. χ2 was used for statistics analysis. Main results and the role of chance Mean maternal age was 36.8 ± 4.9. Among the 206 vitrified-warmed blastocysts, 122 were scored as high-score, 57 as medium-score and 27 as low-score. Positive pregnancy test rate was significantly higher with increased iDAScore with 58% in the high-score group, 36.8% in the medium-score group and 17% in the low-score group (p &amp;lt; 0.0001). Clinical pregnancy rate, defined as the visualization of a fetal heartbeat at ultrasound scan, was also significantly higher with increased iDAScore, with 51.6% in the high-score group, 31.6% in the medium-score group and 17% in the low-score group (p &amp;lt; 0.0001). The miscarriage rate was lower with increased iDAScore, with 8.1% in the high-score group, 16.6% in the medium-score group and 50% in the low-score group, but this difference was not statistically significative (p 0.032). When adjusted to age group however, the miscarriage rate was found to be significantly lower in the high-score group when compared to the medium-score group (p &amp;lt; 0.0001); statistical analysis was not achieved in the low-score group due to the small sample size. Limitations, reasons for caution The major limitation of our study is its small sample size. Data collection is ongoing, to increase the study power. Additionally, many other factors, such as genetic, hormonal, metabolic and/or immunological, may play a role in achieving pregnancy. Wider implications of the findings Our results indicate that iDAScore may be a strong predictor of pregnancy and could be used as a complementary tool to the Gardner embryo grading system in the decision-making process of which blastocyst to transfer. Trial registration number N/A

HER2-negative or low expression as an unfavorable prognostic factor in patients with stage I/II uterine carcinosarcoma.

Uterine carcinosarcoma (UCS) is uncommon high-grade endometrial cancer with limited treatment options. We evaluated the prognostic significance of human epidermal growth factor receptor 2 (HER2) expression and HER2 gene amplification within large cohorts of UCS, and clarify clinicopathologic characteristics of HER2-low UCS. We examined HER2 protein expression in 148 patients of UCS using in vivo diagnostic HER2 immunohistochemistry (IHC) kits and HER2 gene amplification using fluorescence in situ hybridization (FISH) in 72 patients. HER2 IHC score was evaluated according to the latest American Society of Clinical Oncology/College of American Pathologists criteria for gastric cancer, which was negative in 41 patients, low expression of 1+ was observed in 57 patients, and HER2 high expression was observed in 50 patients (2+ in 38 and 3+ in 12 patients). There was no significant statistical difference in clinicopathological characteristics based on HER2 protein expression status. HER2 negative and low expression compared to high expression revealed poor overall survival in stage I/ II. The concordance between IHC and FISH results were relatively low compared to other cancer types (HER2 IHC score 1+, 2+, and 3+ were 5%, 15%, and 50%), and combining these results was not efficient as a prognostic factor in UCS. In contrast, the HER2 IHC score alone was a prognostic factor in stage I/II UCS. HER2 low group did not show specific clinicopathologic features. Since the HER2 IHC score low in advanced UCS is a predictive factor, stratification of UCS using HER2 IHC score for HER2 IHC score low group and developing adjuvant therapy may be proposed in the near future.

Novel Diagnostic Biomarkers Related to Necroptosis and Immune Infiltration in Coronary Heart Disease.

Necroptosis, a monitored form of inflammatory cell death, contributes to coronary heart disease (CHD) progression. This study examined the potential of using necroptosis genes as diagnostic markers for CHD and sought to elucidate the underlying roles. Through bioinformatic analysis of GSE20680 and GSE20681, we first identified the differentially expressed genes (DEGs) related to necroptosis in CHD. Hub genes were identified using least absolute shrinkage and selection operator (LASSO) regression and random forest analysis after studying immune infiltration and transcription factor-miRNA interaction networks according to the DEGs. Quantitative polymerase chain reaction and immunohistochemistry were used to further investigate hub gene expression in vivo, for which a diagnostic model was constructed and the predictive efficacy was validated. Finally, the CHD group was categorized into high- and low-score groups in accordance with the single-sample gene set enrichment analysis (ssGSEA) score of the necroptosis genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, GSEA, and further immune infiltration analyses were performed on the two groups to explore the possible roles of hub genes. Based on the results of the LASSO regression and random forest analyses, four genes were used to construct a diagnostic model to establish a nomogram. Additionally, an extensive analysis of all seventeen necroptosis genes revealed notable distinctions in expression between high-risk and low-risk groups. Evaluation of immune infiltration revealed that neutrophils, monocytes, B cells, and activated dendritic cells were highly distributed in the peripheral blood of patients with CHD. Specifically, the high CHD score group exhibited greater neutrophil and monocyte infiltration. Conversely, the high-score group showed lower infiltration of M0 and M2 macrophages, CD8+ T, plasma, and resting mast cells. TLR3, MLKL, HMGB1, and NDRG2 may be prospective biomarkers for CHD diagnosis. These findings offer plausible explanations for the role of necroptosis in CHD progression through immune infiltration and inflammatory response.

Dental Fear and Caries in 6- to 12-Year-Old Children: a Systematic Review and Meta-analysis.

To investigate the relationship between dental fear and dental caries in children aged 6 to 12 years in a systematic review and meta-analysis. Systematic review search terms were selected according to medical subject headings (MeSH) or non-MeSH. An electronic search of studies published in English assessing the relationship between dental fear (children's fear survey schedule-dental subscale) and dental caries (DMFT or dmft index) was carried out of the Scopus, Web of Science, PubMed, Embase, Cochrane and Proquest databases up to March 2022. Of 5,759 articles retrieved initially, 16 were eligible for inclusion in the study, and 5 of these were included in the quantitative analysis. The quality of studies was evaluated based on the Newcastle-Ottawa scale. Begg tests were employed to assess the publication bias. According to the meta-analysis, the results revealed no statistically significant difference in mean of DMFT score in low and high fear score groups, with a mean difference of 1.28 (95% confidence interval -0.132 to 2.693) (P = 0.076). A statistically significant difference was found in the mean dmft score for the low and high fear score groups, with a mean difference of 0.227 (95% confidence interval 0.058 to 0.395) (P = 0.008). The mean dmft was significantly higher in the high fear score group. Dental fear has a significant relationship with caries in primary teeth, but not in permanent teeth.

Tumor budding -a potential biomarker in low grade salivary gland carcinomas?

Low-grade salivary gland carcinoma is regularly treated with surgical therapy of the salivary gland without elective neck dissection in T1/2 carcinomas, either alone or with adjuvant radiation therapy. However, occult metastasis and locoregional recurrence influence therapy and outcome. Tumor budding is an emerging prognostic pathological factor in many carcinomas, but has not yet been adequately considered in salivary gland carcinomas. We conducted a retrospective single-center study of 64 patients diagnosed with low-grade carcinoma of the major salivary glands treated between 2003 and 2017. Pathological risk factors and TNM classification were thoroughly assessed for each case. All hematoxylin and eosin (HE)-stained histological specimens underwent careful examination, and tumor budding was identified following the guidelines set forth by the International Tumor Budding Consensus Conference in 2016. Tumor budding was not statistically significant concerning 5-year survival rate (5-YSR) (p=0.969) and mean overall survival (log-rank p=0.315). Whereas 5-year disease-free survival rate (5-YDFSR) was 87% in the low tumor budding group and 61.1% in the intermediate and high tumor budding group (p=0.021). Mean disease-free survival accounted for 100.2 months (CI: 88.6;111.9) in the low budding score group and 58.7 months (CI: 42.8;74.6) in the other group (log-rank p=0.032). Notably, pT1/2 showed significantly lower tumor buds than pT3/4 stages (2.43 tumor buds/0.785 mm2 vs. 4.19 tumor buds/0.785 mm2, p=0.034). Similar findings were noted comparing nodal-positive and nodal-negative patients, as well as patients with and without lymphovascular invasion and perineural invasion (each p<0.05). Tumor budding might be used as an additional prognostic factor for recurrence in low-grade salivary gland carcinoma, seemingly associated with a higher nodal metastasis rate and advanced tumor stages and a worse 5-YDFSR. Consequently, the evaluation of tumor budding in resection specimens of low-grade salivary gland tumor may prove valuable in decision-making for neck dissection and follow-up strategy.

Validation of prediction model for successful discontinuation of continuous renal replacement therapy: a multicenter cohort study.

Continuous renal replacement therapy (CRRT) has become the standard modality of renal replacement therapy (RRT) in critically ill patients. However, consensus is lacking regarding the criteria for discontinuing CRRT. Here we validated the usefulness of the prediction model for successful discontinuation of CRRT in a multicenter retrospective cohort. One temporal cohort and four external cohorts included 1,517 patients with acute kidney injury who underwent CRRT for >2 days from 2018 to 2020. The model was composed of four variables: urine output, blood urea nitrogen, serum potassium, and mean arterial pressure. Successful discontinuation of CRRT was defined as the absence of an RRT requirement for 7 days thereafter. The area under the receiver operating characteristic curve (AUROC) was 0.74 (95% confidence interval, 0.71-0.76). The probabilities of successful discontinuation were approximately 17%, 35%, and 70% in the low-score, intermediate-score, and highscore groups, respectively. The model performance was good in four cohorts (AUROC, 0.73-0.75) but poor in one cohort (AUROC, 0.56). In one cohort with poor performance, attending physicians primarily controlled CRRT prescription and discontinuation, while in the other four cohorts, nephrologists determined all important steps in CRRT operation, including screening for CRRT discontinuation. The overall performance of our prediction model using four simple variables for successful discontinuation of CRRT was good, except for one cohort where nephrologists did not actively engage in CRRT operation. These results suggest the need for active engagement of nephrologists and protocolized management for CRRT discontinuation.

Mutational variant allele frequency profile as a biomarker of response to immune checkpoint blockade in non-small cell lung Cancer

IntroductionIdentifying new biomarkers for predicting immune checkpoint inhibitors (ICIs) response in non-small cell lung cancer (NSCLC) is crucial. We aimed to assess the variant allele frequency (VAF)-related profile as a novel biomarker for NSCLC personalized therapy.MethodsWe utilized genomic data of 915 NSCLC patients via cBioPortal and a local cohort of 23 patients for model construction and mutational analysis. Genomic, transcriptomic data from 952 TCGA NSCLC patients, and immunofluorescence (IF) assessment with the local cohort supported mechanism analysis.ResultsUtilizing the random forest algorithm, a 15-gene VAF-related model was established, differentiating patients with durable clinical benefit (DCB) from no durable benefit (NDB). The model demonstrated robust performance, with ROC-AUC values of 0.905, 0.737, and 0.711 across training (n = 313), internal validation (n = 133), and external validation (n = 157) cohorts. Stratification by the model into high- and low-score groups correlated significantly with both progression-free survival (PFS) (training: P < 0.0001, internal validation: P < 0.0001, external validation: P = 0.0066) and overall survival (OS) (n = 341) (P < 0.0001). Notably, the stratification system was independent of PD-L1 (P < 0.0001) and TMB (P < 0.0001). High-score patients exhibited an increased DCB ratio and longer PFS across both PD-L1 and TMB subgroups. Additionally, the high-score group appeared influenced by tobacco exposure, with activated DNA damage response pathways. Whereas, immune/inflammation-related pathways were enriched in the low-score group. Tumor immune microenvironment analyses revealed higher proportions of exhausted/effector memory CD8 + T cells in the high-score group.ConclusionsThe mutational VAF profile is a promising biomarker for ICI therapy in NSCLC, with enhanced therapeutic stratification and management as a supplement to PD-L1 or TMB.

Context-Dependent Regulation of Peripheral Nerve Abundance by the PI3K Pathway in the Tumor Microenvironment of Head and Neck Squamous Cell Carcinoma.

Recent studies have highlighted neurons and their associated Schwann cells (SCs) as key regulators of cancer development. However, the mode of their interaction with tumor cells or other components of the tumor microenvironment (TME) remains elusive. We established an SC-related 43-gene set as a surrogate for peripheral nerves in the TME. Head and neck squamous cell carcinoma (HNSCC) from The Cancer Genome Atlas (TCGA) were classified into low, intermediate and high SC score groups based on the expression of this gene set. Perineural invasion (PNI) and TGF-β signaling were hallmarks of SChigh tumors, whereas SClow tumors were enriched for HPV16-positive OPSCC and higher PI3K-MTOR activity. The latter activity was partially explained by a higher frequency of PTEN mutation and PIK3CA copy number gain. The inverse association between PI3K-MTOR activity and peripheral nerve abundance was context-dependent and influenced by the TP53 mutation status. An in silico drug screening approach highlighted the potential vulnerabilities of HNSCC with variable SC scores and predicted a higher sensitivity of SClow tumors to DNA topoisomerase inhibitors. In conclusion, we have established a tool for assessing peripheral nerve abundance in the TME and provided new clinical and biological insights into their regulation. This knowledge may pave the way for new therapeutic strategies and impart proof of concept in appropriate preclinical models.