The increasing incidence of cardiovascular disease (CVD) is a significant global health concern, affecting millions of individuals each year. Accurate diagnosis of acute CVD poses a formidable challenge, as misdiagnosis can significantly decrease patient survival rates. Traditional biomarkers have played a vital role in the diagnosis and prognosis of CVDs, but they can be influenced by various factors, such as age, sex, and renal function. Soluble ST2 (sST2) is a novel biomarker that is closely associated with different CVDs. Its low reference change value makes it suitable for continuous measurement, unaffected by age, kidney function, and other confounding factors, facilitating risk stratification of CVDs. Furthermore, the combination of sST2 with other biomarkers can enhance diagnostic accuracy and prognostic value. This review aims to provide a comprehensive overview of sST2, focusing on its diagnostic and prognostic value as a myocardial marker for different types of CVDs and discussing the current limitations of sST2.

UNASSIGNED: Non-small cell lung cancer (NSCLC), including the lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) subtypes, is a malignant tumor type with a poor 5-year survival rate. The identification of new powerful diagnostic biomarkers, prognostic biomarkers, and potential therapeutic targets in NSCLC is urgently required.
UNASSIGNED: The UCSC Xena, UALCAN, and GEO databases were used to screen and analyze differentially expressed genes, regulatory modes, and genetic/epigenetic alterations in NSCLC. The UCSC Xena database, GEO database, tissue microarray, and immunohistochemistry staining analyses were used to evaluate the diagnostic and prognostic values. Gain-of-function assays were performed to examine the roles. The ESTIMATE, TIMER, Linked Omics, STRING, and DAVID algorithms were used to analyze potential molecular mechanisms.
UNASSIGNED: NR3C2 was identified as a potentially important molecule in NSCLC. NR3C2 is expressed at low levels in NSCLC, LUAD, and LUSC tissues, which is significantly related to the clinical indexes of these patients. Receiver operating characteristic curve analysis suggests that the altered NR3C2 expression patterns have diagnostic value in NSCLC, LUAD, and especially LUSC patients. Decreased NR3C2 expression levels can help predict poor prognosis in NSCLC and LUAD patients but not in LUSC patients. These results have been confirmed both with database analysis and real-world clinical samples on a tissue microarray. Copy number variation contributes to low NR3C2 expression levels in NSCLC and LUAD, while promoter DNA methylation is involved in its downregulation in LUSC. Two NR3C2 promoter methylation sites have high sensitivity and specificity for LUSC diagnosis with clinical application potential. NR3C2 may be a key participant in NSCLC development and progression and is closely associated with the tumor microenvironment and immune cell infiltration. NR3C2 co-expressed genes are involved in many cancer-related signaling pathways, further supporting a potentially significant role of NR3C2 in NSCLC.
UNASSIGNED: NR3C2 is a novel potential diagnostic and prognostic biomarker and therapeutic target in NSCLC.

Hepatocellular carcinoma (HCC) is a significant contributor to cancer-related deaths in the world. The development and progression of HCC are closely correlated with the abnormal regulation of non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). Important biological pathways in cancer biology, such as cell proliferation, death, and metastasis, are impacted by these ncRNAs, which modulate gene expression. The abnormal expression of non-coding RNAs in HCC raises the possibility that they could be applied as new biomarkers for diagnosis, prognosis, and treatment targets. Furthermore, by controlling the expression of cancer-related genes, miRNAs can function as either tumor suppressors or oncogenes. On the other hand, lncRNAs play a role in the advancement of cancer by interacting with other molecules within the cell, which, in turn, affects processes such as chromatin remodeling, transcription, and post-transcriptional processes. The importance of ncRNA-driven regulatory systems in HCC is being highlighted by current research, which sheds light on tumor behavior and therapy response. This research highlights the great potential of ncRNAs to improve patient outcomes in this difficult disease landscape by augmenting the present methods of HCC care through the use of precision medicine approaches.

Objective. To go beyond the deficiencies of the three conventional multimodal fusion strategies (i.e. input-, feature- and output-level fusion), we propose a bidirectional attention-aware fluid pyramid feature integrated fusion network (BAF-Net) with cross-modal interactions for multimodal medical image diagnosis and prognosis.Approach. BAF-Net is composed of two identical branches to preserve the unimodal features and one bidirectional attention-aware distillation stream to progressively assimilate cross-modal complements and to learn supplementary features in both bottom-up and top-down processes. Fluid pyramid connections were adopted to integrate the hierarchical features at different levels of the network, and channel-wise attention modules were exploited to mitigate cross-modal cross-level incompatibility. Furthermore, depth-wise separable convolution was introduced to fuse the cross-modal cross-level features to alleviate the increase in parameters to a great extent. The generalization abilities of BAF-Net were evaluated in terms of two clinical tasks: (1) an in-house PET-CT dataset with 174 patients for differentiation between lung cancer and pulmonary tuberculosis. (2) A public multicenter PET-CT head and neck cancer dataset with 800 patients from nine centers for overall survival prediction.Main results. On the LC-PTB dataset, improved performance was found in BAF-Net (AUC = 0.7342) compared with input-level fusion model (AUC = 0.6825;p< 0.05), feature-level fusion model (AUC = 0.6968;p= 0.0547), output-level fusion model (AUC = 0.7011;p< 0.05). On the H&N cancer dataset, BAF-Net (C-index = 0.7241) outperformed the input-, feature-, and output-level fusion model, with 2.95%, 3.77%, and 1.52% increments of C-index (p= 0.3336, 0.0479 and 0.2911, respectively). The ablation experiments demonstrated the effectiveness of all the designed modules regarding all the evaluated metrics in both datasets.Significance. Extensive experiments on two datasets demonstrated better performance and robustness of BAF-Net than three conventional fusion strategies and PET or CT unimodal network in terms of diagnosis and prognosis.

UNASSIGNED: To analyze the significance of lung ultrasound score (LUS) combined with serum inflammatory indexes in different severities of severe pneumonia and its clinical value on prognosis.
UNASSIGNED: 100 patients with severe pneumonia treated in the Gansu Provincial Hospital from June 2017 to June 2021 were selected as the research objects. According to the acute physiology and chronic health (APACHE II) score, they were divided into a low-risk group (28 cases), a medium-risk group (39 cases) and a high-risk group (33 cases). The general clinical data of the patients (age, gender, smoking history, and underlying diseases) were collected, the lung ultrasound score (LUS) of the patients was measured, and the serum inflammatory indicators (IL-6, IL-10, TNF-α, CRP and NLR) levels; Pearson correlation analysis to evaluate the correlation between LUS score, serum inflammatory index levels and disease severity; receiver operating characteristic (ROC) curve analysis to evaluate the prognostic value of the combined diagnosis of LUS score and serum inflammatory index for the severity of severe pneumonia.
UNASSIGNED: With the increase in the severity of severe pneumonia, the LUS score and the level of inflammation in the body continued to increase, and LUS combined with serum inflammatory indexes could distinguish the severity of low-risk, medium-risk and high-risk severe pneumonia and had high diagnostic value. In addition, the combined diagnosis of LUS and serum inflammatory markers is also closely related to the prognosis of patients with severe pneumonia, which can distinguish the prognosis.
UNASSIGNED: LUS combined with serum inflammatory indicators (IL-6, IL-10, TNF-α, CRP and NLR) can differentiate the severity and prognosis of severe pneumonia, which may be a new direction for diagnosing severe pneumonia and guide early clinical intervention.

Purpose: To clarify the value of AGR2 for diagnosis and prognosis in epithelial ovarian cancer (EOC). Methods: Serum AGR2 from 203 subjects were detected by ELISA, while CA125 and HE4 were determined by enhanced chemiluminescence immunoassay. The diagnostic efficacy was assessed using receiver operating characteristic curves. Tissue microarray was employed to compare tissue AGR2. Results: Combined detection of AGR2, CA125 and HE4 improved the diagnostic specificity in the discrimination of EOC from healthy controls. Serum AGR2 was significantly higher, while CA125 and HE4 were significantly lower in EOC patients post-operatively. Low AGR2 expression may predict poorer prognosis. Conclusion: Incorporation of AGR2 improved the specificity of CA125 and HE4 in EOC diagnosis, and may act as a tumor suppressor whose low expression in EOC patients predicted poorer outcomes.

UNASSIGNED: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD). There are unmet needs for noninvasive diagnosis and prognosis prediction of DKD in clinical practice. This study examines the diagnostic and prognostic value of magnetic resonance (MR) markers of renal compartment volume and the apparent diffusion coefficient (ADC) for mild, moderate, and severe DKD.
UNASSIGNED: This study was registered at the Chinese Clinical Trial Registry Center (registration number: ChiCTR-RRC-17012687). Sixty-seven DKD patients were prospectively randomly enrolled and underwent clinical examination and diffusion-weighted magnetic resonance imaging (DW-MRI). Patients with comorbidities that affected renal volumes or components were excluded. Ultimately, 52 DKD patients were included in the cross-sectional analysis. The ADC in the renal cortex (ADCcortex), ADC in the renal medulla (ADCmedulla) and difference between ADCcortex and ADCmedulla (ΔADC) were measured using a twelve-layer concentric objects (TLCO) approach. Renal compartment volumes of the parenchyma and pelvis were derived from T2-weighted MRI. Due to lost contact or ESRD diagnosed before follow-up (n=14), only 38 DKD patients remained for follow-up (median period =8.25 years) to investigate the correlations between MR markers and renal outcomes. The primary outcomes were the composite of doubling of the primary serum creatinine concentration or ESRD.
UNASSIGNED: ADCcortex presented superior performance in discriminating DKD with normal and declined estimated glomerular filtration rate (eGFR) over ADCmedulla, ΔADC and renal compartment volumes with an AUC of 0.904 (sensitivity of 83% and specificity of 91%) and was moderately correlated with the clinical biomarkers eGFR and proteinuria (P<0.05). The Cox survival analysis demonstrated that ADCcortex rather than ΔADC is a predictor of renal outcomes with a hazard ratio of 3.4 (95% CI: 1.1-10.2, P<0.05) independent of baseline eGFR and proteinuria.
UNASSIGNED: ADCcortex is a valuable imaging marker for the diagnosis and prediction of renal function decline in DKD.

Acute kidney injury (AKI) in critically ill patients has poor renal outcome with high mortality. Changes in intra-renal microcirculation and tissue oxygenation are currently considered essential pathophysiological mechanisms to the development and progression of AKI. This study aims to investigate the characteristics of contrast-enhanced ultrasonography (CEUS) derived parameters in biopsy-proven AKI patients, and examine the predictive value of these markers for renal outcome.
This prospective observational study will enroll AKI patients who are diagnosed and staging following KDIGO (Kidney Disease: Improving Global Outcomes) criteria. All patients undergo a kidney biopsy and pathological tubulointerstitial nephropathy is confirmed. The CEUS examination will be performed at 0, 4 and 12 weeks after biopsy to monitor renal microcirculation. The percentage decrease of serum creatinine, 4-week and 12-week eGFR (estimated glomerular filtration rate) will also be reviewed as renal prognosis. The relationship of CEUS parameters with clinical and pathological markers will be analyzed. We perform a lassologit procedure to select potential affecting variables, including clinical, laboratory indexes and CEUS markers, to be included in the logistic regression model, and examine their predictive performance to AKI outcomes.
If we are able to show that CEUS derived parameters contribute to diagnosis and prognosis of AKI, the quality of life of patients will be improved while healthcare costs will be reduced.
This study is retrospectively registered on the Chinese Medical Research Registration information System( https://61.49.19.26/login ) on December 31, 2021: MR-11-22-003,503. This study has been approved by the Ethics and Scientific Research Department of Peking University First Hospital.

State-of-art non-invasive diagnosis processes for bladder cancer (BLCA) harbour shortcomings such as low sensitivity and specificity, unable to distinguish between high- (HG) and low-grade (LG) tumours, as well as inability to differentiate muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). This study investigates a comprehensive characterization of the entire DNA methylation (DNAm) landscape of BLCA to determine the relevant biomarkers for the non-invasive diagnosis of BLCA.
A total of 304 samples from 224 donors were enrolled in this multi-centre, prospective cohort study. BLCA-specific DNAm signature discovery was carried out with genome-wide bisulfite sequencing in 32 tumour tissues and 12 normal urine samples. A targeted sequencing assay for BLCA-specific DNAm signatures was developed to categorize tumour tissue against normal urine, or MIBC against NMIBC. Independent validation was performed with targeted sequencing of 259 urine samples in a double-blinded manner to determine the clinical diagnosis and prognosis value of DNAm-based classification models. Functions of genomic region harbouring BLCA-specific DNAm signature were validated with biological assays. Concordances of pathology to urine tumour DNA (circulating tumour DNA [ctDNA]) methylation, genomic mutations or other state-of-the-art diagnosis methods were measured.
Genome-wide DNAm profile could accurately classify LG tumour from HG tumour (LG NMIBC vs. HG NMIBC: p = .038; LG NMIBC vs. HG MIBC, p = .00032; HG NMIBC vs. HG MIBC: p = .82; Student\'s t-test). Overall, the DNAm profile distinguishes MIBC from NMIBC and normal urine. Targeted-sequencing-based DNAm signature classifiers accurately classify LG NMIBC tissues from HG MIBC and could detect tumours in urine at a limit of detection of less than .5%. In tumour tissues, DNAm accurately classifies pathology, thus outperforming genomic mutation or RNA expression profiles. In the independent validation cohort, pre-surgery urine ctDNA methylation outperforms fluorescence in situ hybridization (FISH) assay to detect HG BLCA (n = 54) with 100% sensitivity (95% CI: 82.5%-100%) and LG BLCA (n = 26) with 62% sensitivity (95% CI: 51.3%-72.7%), both at 100% specificity (non-BLCA: n = 72; 95% CI: 84.1%-100%). Pre-surgery urine ctDNA methylation signature correlates with pathology and predicts recurrence and metastasis. Post-surgery urine ctDNA methylation (n = 61) accurately predicts recurrence-free survival within 180 days, with 100% accuracy.
With the discovery of BLCA-specific DNAm signatures, targeted sequencing of ctDNA methylation outperforms FISH and DNA mutation to detect tumours, predict recurrence and make prognoses.

UNASSIGNED: Insulin-like growth factor binding protein-3 (IGFBP3) has been reported to be related to the risk of some cancers. Here we focussed on serum IGFBP3 as a possible biomarker of diagnosis and prognosis for oesophageal squamous carcinoma (ESCC).
UNASSIGNED: Enzyme-linked immunosorbent assay (ELISA) was used to measure the serum IGFBP3 level in the training cohort including 136 ESCC patients and 119 normal controls and the validation cohort with 55 ESCC patients and 42 normal controls. The receiver operating characteristics curve (ROC) was used to assess the diagnosis value. Cox proportional hazards model was applied to select factors for survival nomogram construction.
UNASSIGNED: Serum IGFBP3 levels were significantly lower in early-stage ESCC or ESCC patients than those in normal controls (p < .05). The specificity and sensitivity of serum IGFBP3 for the diagnosis of ESCC were 95.80% and 50.00%, respectively, with the area under the ROC curve (AUC) of 0.788 in the training cohort. Similar results were observed in the validation cohort (88.10%, 38.18%, and 0.710). Importantly, serum IGFBP3 could also differentiate early-stage ESCC from controls (95.80%, 52.54%, 0.777 and 88.10%, 36.36%, 0.695 in training and validation cohorts, respectively). Furthermore, Cox multivariate analysis revealed that serum IGFBP3 was an independent prognostic risk factor (HR = 2.599, p = .002). Lower serum IGFBP3 level was correlated with reduced overall survival (p < .05). Nomogram based on serum IGFBP3, TNM stage, and tumour size improved the prognostic prediction of ESCC with a concordance index of 0.715.
UNASSIGNED: We demonstrated that serum IGFBP3 was a potential biomarker of diagnosis and prognosis for ESCC. Meanwhile, the nomogram might help predict the prognosis of ESCC. Key MessageSerum IGFBP3 showed early diagnostic value in oesophageal squamous cell carcinoma with independent cohort validation. Moreover, serum IGFBP3 was identified as an independent prognostic risk factor, which was used to construct a nomogram with improved prognosis ability in oesophageal squamous cell carcinoma.