Joint shape/texture representation learning for cardiovascular disease diagnosis from magnetic resonance imaging.

Aims: Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide. Cardiac image and mesh are two primary modalities to present the shape and structure of the heart and have been demonstrated to be efficient in CVD prediction and diagnosis. However, previous research has been generally focussed on a single modality (image or mesh), and few of them have tried to jointly consider the image and mesh representations of heart. To obtain efficient and explainable biomarkers for CVD prediction and diagnosis, it is needed to jointly consider both representations. Methods and results: We design a novel multi-channel variational auto-encoder, mesh-image variational auto-encoder, to learn joint representation of paired mesh and image. After training, the shape-aware image representation (SAIR) can be learned directly from the raw images and applied for further CVD prediction and diagnosis. We demonstrate our method on data from UK Biobank study and two other datasets via extensive experiments. In acute myocardial infarction prediction, SAIR achieves 81.43% accuracy, significantly higher than traditional biomarkers like metadata and clinical indices (left ventricle and right ventricle clinical indices of cardiac function like chamber volume, mass, and ejection fraction). Conclusion: Our mesh-image variational auto-encoder provides a novel approach for 3D cardiac mesh reconstruction from images. The extraction of SAIR is fast and without need of segmentation masks, and its focussing can be visualized in the corresponding cardiac meshes. SAIR archives better performance than traditional biomarkers and can be applied as an efficient supplement to them, which is of significant potential in CVD analysis.

Is SWEEPS better than PUI in reducing intracanal bacteria and inflammation in cases of apical periodontitis?

To evaluate the efficacy of SWEEPS mode of the Er: YAG laser(SL) and passive ultrasonic irrigation(PUI) in the eradication of microorganisms and in the inflammation detection by IL-1ß. Thirty patients with chronic apical periodontitis(AP) were allocated into two groups: Group SL-SWEEPS laser activated irrigation(n = 15) and Group PUI-passive ultrasonic irrigation(n = 15). Bacteriological samples were taken before(S1) and after chemomechanical preparation(S2), and then after final irrigation activation(S3). The levels of total bacteria and Streptococci were measured by means of PCR. Blood samples were collected before and 3rd day after treatment. Enzyme-linked immunosorbent assay was used to measure the levels of IL-1ß. The bacterial reduction showed no differences between groups after chemo-mechanical treatment and after irrigant activation(p = 0.590). Post-treatment IL-1ß levels were lower than pretreatment levels in both groups(p < 0.001). SL or PUI application in addition to chemomechanical preparation has similar effects on total bacterial level and inflammation detected by IL-1ß in patients with AP.

Identification of organs of origin of macrophages that produce presepsin via neutrophil extracellular trap phagocytosis.

Presepsin (P-SEP) is a specific biomarker for sepsis. Monocytes produce P-SEP by phagocytosing neutrophil extracellular traps (NETs). Herein, we investigated whether M1 macrophages (M1 MΦs) are the primary producers of P-SEP after NET phagocytosis. We co-cultured M1 MΦs and NETs from healthy participants, measured P-SEP levels in the culture medium supernatant, and detected P-SEP using western blotting. When NETs were co-cultured with M1 MΦs, the P-SEP level of the culture supernatant was high. Notably, we demonstrated, for the first time, the intracellular kinetics of P-SEP production by M1 MΦs via NET phagocytosis: M1 MΦs produced P-SEP intracellularly 15 min after NET phagocytosis and then released it extracellularly. In a sepsis mouse model, the blood NET ratio and P-SEP levels, detected using ELISA, were significantly increased (p < 0.0001). Intracellular P-SEP analysis via flow cytometry demonstrated that lung, liver, and kidney MΦs produced large amounts of P-SEP. Therefore, we identified these organs as the origin of M1 MΦs that produce P-SEP during sepsis. Our data indicate that the P-SEP level reflects the trend of NETs, suggesting that monitoring P-SEP can be used to both assess NET-induced organ damage in the lungs, liver, and kidneys during sepsis and determine treatment efficacy.

Monocyte distribution width as a promising biomarker for differential diagnosis of chronic hepatitis, cirrhosis, and hepatocellular carcinoma.

Objective: We aimed to investigate the association and diagnostic value of monocyte distribution width (MDW) for chronic hepatitis B (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC). Methods: MDW levels were measured in 483 individuals (103 CHB, 77 LC, 153 HCC, and 150 controls). MDW was detected using UniCel Dx900 for specific cell volume parameters and the distribution of cell volumes. Results: Our findings revealed a dynamic upward change in MDW levels across different stages of chronic liver disease, from CHB to LC and HCC. In CHB, MDW levels were highest among HBeAg-positive CHB patients and exhibited a negative correlation with HBV markers while positively correlating with ALT levels. In LC, MDW showed a positive association with the pathological progression of LC, demonstrating consistency with CP scores. MDW proved to be equally effective as traditional detection for diagnosing LC. In HCC, MDW was positively correlated with HCC occurrence and development, with higher levels observed in the high MDW group, which also exhibited elevated AFP levels, MELD scores, and 90-day mortality rates. MDW surpassed predictive models in its effectiveness for diagnosing HCC, as well as CHB and LC, with respective areas under the curve of 0.882, 0.978, and 0.973. Furthermore, MDW emerged as an independent predictor of HCC. Conclusion: MDW holds significant diagnostic efficacy in identifying CHB, LC, and HCC. These findings suggest that MDW could serve as a promising biomarker for predicting the severity of liver diseases and aid in rational clinical treatment strategies.

A Bibliometric Analysis of Clinical Trials on Salivary Biomarkers for Mental Health (2003-2024).

Mental health conditions, such as depression, anxiety, and stress-related disorders, are often difficult to diagnose and monitor using traditional methods. Salivary biomarkers offer a promising alternative due to their non-invasive nature, ease of collection, and the potential to reflect real-time physiological changes associated with mental health. This bibliometric analysis examines 95 clinical trials on stress biomarkers for mental health, published between 2003 and 2024. The field is characterized by extensive collaboration and global participation, involving 593 authors and publications across 73 journals. Despite a consistent annual publication rate, notable increases in 2011, 2014, and 2018 indicate growing research interest. The United States leads in research output, followed by Australia, Germany, and Japan, with Psychoneuroendocrinology being the most prominent journal. Co-occurrence analysis identified nine research clusters, suggesting diverse directions such as the impact of stress-related hormones, circadian rhythms, mindfulness, various therapies, aging, psychological adaptation mechanisms, exercise therapy, anxiety disorders, and the autonomic nervous system on salivary biomarkers. Key terms such as "biomarkers/metabolism," AND "hydrocortisone/metabolism," AND "saliva/metabolism" were central, with significant activity from 2012 to 2018. This analysis highlights a growing focus on the metabolic processes and therapeutic applications of salivary biomarkers in mental health. This bibliometric analysis calls attention to the promising potential of salivary biomarkers to revolutionize mental health diagnostics and treatment through non-invasive methods, fostering interdisciplinary research, technological advancements, and global health improvements.

Progress in the study of pentraxin-3(PTX-3) as a biomarker for sepsis.

Sepsis is a intricate pathological process characterized by life-threatening organ dysfunction resulting from a dysregulated host response to infection. It stands as a prominent cause of mortality among critically ill patients globally. The pivotal focus in sepsis management lies in the early identification and prompt administration of antimicrobial agents. Owing to the constraints of current diagnostic methodologies, marked by insufficient sensitivity and delayed outcomes, extensive research has been undertaken to ascertain novel biomarkers for sepsis. In this review, we provide an overview discussing the latest advancements in the study of PTX-3 as a biomarker for sepsis. We acknowledge pivotal discoveries from preceding research and engage in discourse regarding the challenges and limitations confronted by PTX-3 as a sepsis biomarker.

Early fetal sex determination using a fluorescent DNA nanosensing platform capable of simultaneous detection of SRY and DYS14 sequences in cell-free fetal DNA.

Early fetal sex determination is of crucial importance in the management of prenatal diagnosis of X-linked genetic abnormalities and congenital adrenal hyperplasia. The development of an efficient and simple method for high-sensitivity, affordable, and rapid screening of cell-free fetal DNA (cffDNA) is crucial for fetal sex determination in early pregnancy. In this study, single- and dual-fluorophore DNA biosensors based on multi-walled carbon nanotubes (MWCNT) were fabricated for the individual and simultaneous detection of the SRY gene and DYS14 marker in cffDNA obtained from maternal plasma samples. This nanosensing platform is based on the immobilization of single-stranded DNA (ssDNA) probes, labeled with ROX or FAM fluorophores, on MWCNT, resulting in the quenching of fluorescence emission in the absence of the targets. Upon the addition of the complementary target DNA (ctDNA) to the hybridization reaction, the fluorescence emission of fluorophore-labeled probes was significantly recovered to 79.5 % for ROX-labeled probes (i.e. SRY-specific probes), 81.5 % for FAM-labeled probes (i.e. DYS14-specific probes), and 65.9 % for dual-fluorophore biosensor compared to the quenching mode. The limit of detection (LOD) for ROX, and FAM was determined to be 4.5 nM, and 7.6 nM, respectively. For dual-color probes, LOD was found to be 5.4 (ROX) and 9.2 nM (FAM). Finally, the clinical applicability of the proposed method was confirmed through the detection of both biomarkers in maternal plasma samples, suggesting that the proposed nanosensing platform may be useful for the early detection of fetal sex using cffDNA.

NfL concentration in CSF is a quantitative marker of the rate of neurodegeneration in aging and Huntington's disease: a semi-mechanistic model-based analysis.

The concentrations of neurofilament light chain (NfL) in cerebrospinal fluid (CSF) and plasma have become key biomarkers of many neurodegenerative diseases, including Huntington's Disease (HD). However, the relationship between the dynamics of NfL concentrations in CSF and the time-course of neurodegeneration (whole brain atrophy) has not yet been described in a quantitative and mechanistic manner. Here, we present a novel semi-mechanistic model, which postulates that the amount of NfL entering the CSF corresponds to the amount of NfL released from damaged neurons, whose degeneration results in a decrease in brain volume. In mathematical terms, the model expresses the NfL concentration in CSF in terms of the NfL concentration in brain tissue, the rate of change of whole brain volume and the CSF flow rate. To test our model, we used a non-linear mixed effects approach to analyze NfL and brain volume data from the HD-CSF study, a 24-month prospective study of individuals with premanifest HD, manifest HD and healthy controls. The time-course of whole brain volume, obtained from MRI, was represented empirically by a 2nd order polynomial, from which its rate of change was computed. CSF flow rates in healthy and HD populations were taken from recent literature data. By estimating the NfL concentration in brain tissue, the model successfully described the time-course of the NfL concentration in CSF in both HD subjects and healthy controls. Furthermore, the model-derived estimate of NfL concentration in brain agreed well with recent direct experimental measurements. The consistency of our model with the NfL and brain volume data suggests that the NfL concentration in CSF reflects the rate, rather than the extent, of neurodegeneration and that the increase in NfL concentration over time is a measure of the accelerating rate of neurodegeneration associated with aging and HD. For HD subjects, the degree of acceleration was found to increase markedly with the number of CAG repeats on their HTT gene. The application of our semi-mechanistic NfL model to other neurodegenerative diseases is discussed.

PDCD2 as a prognostic biomarker in glioma correlates with malignant phenotype.

Programmed cell death 2 (PDCD2) is related to cancer progression and chemotherapy sensitivity. The role of PDCD2 in solid cancers (excluding hematopoietic malignancies) and their diagnosis and prognosis remains unclear. The TCGA, CGGA, GEPIA, cBioPortal, and GTEx databases were analyzed for expression, prognostic value, and genetic modifications of PDCD2 in cancer patients. Functional enrichment analysis, CCK8, colony formation assay, transwell assay, and xenograft tumor model were undertaken to study the PDCD2's biological function in glioma (GBMLGG). The PDCD2 gene was associated with solid cancer progression. In the functional enrichment analysis results, PDCD2 was shown to participate in several important GBMLGG biological processes. GBMLGG cells may be inhibited in their proliferation, migration, invasion, and xenograft tumor growth by knocking down PDCD2. Our research can provide new insights into solid cancer prognostic biomarkers of PDCD2.

Multiparametric quantitative magnetic resonance imaging of uterine fibroids for prediction of growth rate-a pilot study.

Background: Uterine fibroid (UF) growth rate and future morbidity cannot be predicted. This can lead to sub-optimal clinical management, with women being lost to follow-up and later presenting with severe disease that may require hospitalization, transfusions, and urgent surgical interventions. Multi-parametric quantitative magnetic resonance imaging (MRI) could provide a biomarker to predict growth rate facilitating better-informed disease management and better clinical outcomes. We assessed the ability of putative quantitative and qualitative MRI predictive factors to predict UF growth rate. Methods: Twenty women with UFs were recruited and completed baseline and follow-up MRI exams, 1-2.5 years apart. The subjects filled out symptom severity and health-related quality of life questionnaires at each visit. A standard clinical pelvic MRI non-contrast exam was performed at each visit, followed by a contrast-enhanced multi-parametric quantitative MRI (mp-qMRI) exam with T2, T2*, and apparent diffusion coefficient (ADC) mapping and dynamic contrast-enhanced MRI. Up to 3 largest fibroids were identified and outlined on the T2-weighted sequence. Fibroid morphology and enhancement patterns were qualitatively assessed on dynamic contrast-enhanced MRI. The UFs' volumes and average T2, T2*, and ADC values were calculated. Pearson correlation coefficients were calculated between UF growth rate and T2, T2*, ADC, and baseline volume. Multiple logistic regression and receiver operating characteristic (ROC) analysis were performed to predict fast-growing UFs using combinations of up to 2 significant predictors. A significance level of alpha =0.05 was used. Results: Forty-four fibroids in 20 women had growth rate measurement available, and 36 fibroids in 16 women had follow-up quantitative MRI available. The distribution of fibroid growth rate was skewed, with approximately 20% of the fibroids exhibiting fast growth (>10 cc/year). However, there were no significant changes in median baseline and follow-up values of symptom severity and health-related quality of life scores. There was no change in average T2, T2*, and ADC at follow-up exams and there was a moderate to strong correlation to the fibroid growth rate in baseline volume and average T2 and ADC in slow-growing fibroids (<10 cc/year). A multiple logistic regression to identify fast growing UFs (>10 cc/year) achieved an area under the curve (AUC) of 0.80 with specificity of 69% at 100% sensitivity. Conclusions: The mp-qMRI parameters T2, ADC, and UF volume obtained at the time of initial fibroid diagnosis may be able to predict UF growth rate. Mp-qMRI could be integrated into the management of UFs, for individualized care and improved clinical outcomes.

Expression of the plasma membrane citrate carrier (pmCiC) in human cancerous tissues-correlation with tumour aggressiveness.

We have recently shown that cancer cells of various origins take up extracellular citrate through the plasma membrane citrate carrier (pmCiC), a specific plasma membrane citrate transporter. Extracellular citrate is required to support cancer cell metabolism, in particular fatty acid synthesis, mitochondrial activity, protein synthesis and histone acetylation. In addition, cancer cells tend to acquire a metastatic phenotype in the presence of extracellular citrate. Our recent study also showed that cancer-associated stromal cells synthesise and release citrate and that this process is controlled by cancer cells. In the present study, we evaluated the expression of pmCiC, fibroblast activation protein-α (FAP) and the angiogenesis marker cluster of differentiation 31 (CD31) in human cancer tissues of different origins. In the cohort studied, we found no correlation between disease stage and the expression of FAP or CD31. However, we have identified a clear correlation between pmCiC expression in cancer cells and cancer-associated stroma with tumour stage. It can be concluded that pmCiC is increased in cancer cells and in cancer-supporting cells in the tumour microenvironment at the later stages of cancer development, particularly at the metastatic sites. Therefore, pmCiC expression has the potential to serve as a prognostic marker, although further studies are needed.

Behavioral biomarkers in fishes: A non-lethal approach to assess the effects of chemical pollution on freshwater ecosystems.

The expansion of the human population and the escalating use of chemical products pose a considerable threat to aquatic biodiversity. Consequently, there is an imperative need for the implementation of non-lethal, cost-effective, and easily deployable biomonitoring tools. In this context, fish and their behavior as biomarkers have gained prominence in monitoring of freshwater ecosystems. The aim of this study was to assess the state of art in the use of behavioral biomarkers in ecotoxicology, emphasizing their role as informative tools for global environmental monitoring. Through a systematic literature search, ninety-two articles focusing on the evaluation of behavioral changes in freshwater fish in response to pollution were identified. The most prevalent keywords were "behavior" (7%) and "zebrafish" (6%). Experiments were conducted in countries with expansive territories, such as the United States (18%) and Brazil (17%). Exotic species were primarily employed (58%), with Danio rerio (26%) being the most frequently studied species. Among pollutants, pesticides (32%) and medicines (25%) were the most frequently studied, while locomotion (38%) and social behaviors (18%) were the most frequently evaluated behaviors. Across these studies, authors consistently reported significant changes in the behavior of fish exposed to contaminants, including decreased swimming speed and compromised feeding efficiency. The review findings affirm that evaluating behavioral biomarkers in freshwater fish offers an informative, non-lethal, cost-effective, and easily implementable approach to understanding pollution impacts on freshwater ecosystems. Although few studies on behavioral biomarkers were available to date, the number has rapidly increased in recent years. Furthermore, a variety of novel approaches and study models are being included. Research into behavioral biomarkers is crucial for understanding and managing environmental risks in freshwater ecosystems. Nevertheless, further studies are needed to enhance our understanding of behavioral toxicity indicators, considering factors such as life stage, sex, and breeding season in the tested species.

Serum metabolomic profile of myasthenia gravis and potential values as biomarkers in disease monitoring.

OBJECTIVE: Serum metabolites from 19 myasthenia gravis (MG) patients and 15 normal controls were analyzed via untargeted metabolomics, including 6 pre/post-treatment paired MG patients, to assess the value of serum metabolites as biomarkers in monitoring MG. METHOD: Differential metabolites between MG patients and normal controls were identified through liquid and gas chromatography-mass spectrometry simultaneously. Principal component analysis and orthogonal partial least squares-discriminant analysis were conducted to identify the differential metabolites. Candidate metabolites and pathways associated with MG were selected through a random forest machine learning model. RESULT: A total of 310 differential metabolites were identified with a threshold of variable projected importance > 1 and P value < 0.05. Among these, 158 metabolites were upregulated and 152 were downregulated. The random forest machine learning model selected 5 metabolites as potential biomarkers associated with MG: lignoceric acid (AUC=0.944), uridine diphosphate-N-acetylglucosamine (AUC=0.951), arachidonic acid (AUC=0.951), beta-glycerophosphoric acid (AUC=0.933), and L-Asparagine (AUC=0.877). Further analysis using 6 paired MG patients pre- and post-immunosuppression treatment revealed 25 upregulated and 6 downregulated metabolites in post-treatment serum, which might be relevant to disease intervention. The significance remains elusive due to the limited number of patients. CONCLUSION: A subset of differential metabolites was identified in the serum of MG patients, some of which changed with immunosuppressive therapy. Small molecule metabolites may serve as valuable biomarkers for disease monitoring in MG.

PSA, an outdated biomarker for prostate cancer: In search of a more specific biomarker, citrate takes the spotlight.

The prevailing biomarker employed for prostate cancer (PCa) screening and diagnosis is the prostate-specific antigen (PSA). Despite excellent sensitivity, PSA lacks specificity, leading to false positives, unnecessary biopsies and overdiagnosis. Consequently, PSA is increasingly less used by clinicians, thus underscoring the imperative for the identification of new biomarkers. An emerging biomarker in this context is citrate, a molecule secreted by the normal prostate, which has been shown to be inversely correlated with PCa. Here, we discuss about PSA and its usage for PCa diagnosis, its lack of specificity, and the various conditions that can affect its levels. We then provide our vision about what we think would be a valuable addition to our PCa diagnosis toolkit, citrate. We describe the unique citrate metabolic program in the prostate and how this profile is reprogrammed during carcinogenesis. Finally, we summarize the evidence that supports the usage of citrate as a biomarker for PCa diagnosis, as it can be measured in various patient samples and be analyzed by several methods. The unique relationship between citrate and PCa, combined with the stability of citrate levels in other prostate-related conditions and the simplicity of its detection, further accentuates its potential as a biomarker.

Long noncoding RNA KCNMA1-AS2 regulates the function of colorectal cancer cells and sponges miR-1227-5p.

BACKGROUND: Many long noncoding RNAs (lncRNAs) with altered expression significantly influence colorectal cancer (CRC) progression and behavior. The functions of many lncRNAs in CRC are not clear yet. This study aimed to discover novel lncRNA entities and comprehensively examine and validate their roles and underlying molecular mechanisms in CRC. METHODS: Tissue samples, both tumourous and non-tumourous, from three CRC patients were submitted for sequencing. Following expression validation in samples from ten patients and four CRC cell lines. The lncRNA KCNMA1-AS2 was synthesized by In-vitro transcription RNA synthesis and the lncRNA was directly transfected into CRC cell lines to overexpress. Functional assays including MTT proliferation assay, Annexin-V/propidium iodide apoptosis assay, wound healing migration assay and cell cycle assays were performed to evaluate the effect of overexpression of KCNMA1-AS2. Furthermore, the binding of KCNMA1-AS2 to miR-1227-5p was confirmed using dual luciferase reporter assays and qPCR analyses. Subsequent bioinformatics analyses identified 58 potential downstream targets of miR-1227-5p across three databases. RESULTS: In this study, we identified the lncRNA KCNMA1-AS2, the expression of which was down-regulated consistently in cancer tissues and CRC cell lines compared to non-cancerous tissues. The overexpression of lncRNA KCNMA1-AS2 led to significant reduction in CRC cell proliferation and migration, increase in cell apoptosis, and more cells arrested in S phase. Additionally, the interaction between KCNMA1-AS2 and miR-1227-5p was confirmed through dual luciferase reporter assay and qPCR analysis. It is also putatively predicted that MTHFR and ST8SIA2 may be linked to CRC based on bioinformatics analyses. CONCLUSIONS: LncRNA KCNMA1-AS2 exhibited distinct gene expression patterns in both CRC tissue and cell lines, impacting various cellular functions while also acting as a sponge for miR-1227-5p.The findings spotlight lncRNA KCNMA1-AS2 as a potential marker for diagnosis and treatment of CRC.

[Research Progress on Predictive Biomarkers of Immunotherapy Efficacy
in Non-small Cell Lung Cancer].

Lung cancer is one of the most common malignant tumors in the world, of which non-small cell lung cancer (NSCLC) is the majority. The emergence of immune checkpoint inhibitors (ICIs) has greatly changed the treatment strategy of NSCLC and improved the prognosis of patients. However, in reality, only a small number of patients can achieve long-term benefit. Therefore, the identification of reliable predictive biomarkers is essential for the selection of treatment modalities. With the development of molecular biology and genome sequencing technology in recent years, as well as the in-depth understanding of tumor and its host immune microenvironment, research on biomarkers has emerged in an endless stream. This review focuses on the predictive biomarkers of immunotherapy efficacy in NSCLC, in order to provide some guidance for precision immunotherapy.
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Biomarkers associated with survival in patients with platinum-refractory urothelial carcinoma treated with paclitaxel.

BACKGROUND: Taxane- based chemotherapy is widely used in patients with platinum- and immunotherapy refractory, metastatic urothelial carcinoma (mUC). Outcomes are poor and biomarkers associated with outcome are lacking. We aim to identify cancer hallmarks associated with survival in patients receiving paclitaxel. METHODS: Whole-transcriptome profiles were generated for a subset of patients enrolled in a randomised phase II study investigating paclitaxel and pazopanib in platinum refractory mUC (PLUTO, EudraCT 2011-001841-34). Estimates of gene expression were calculated and input into the Almac proprietary analysis pipeline and signature scores were calculated using ClaraT V3.0.0. Ten key gene signatures were assessed: Immuno-Oncology, Epithelial to Mesenchymal Transition, Angiogenesis, Proliferation, Cell Death, Genome Instability, Energetics, Inflammation, Immortality and Evading Growth. Hazard ratios were calculated using Cox regression model and Kaplan-Meier methods were used to estimate progression free survival (PFS) and overall survival (OS). RESULTS: 38 and 45 patients treated with paclitaxel or pazopanib were included. Patients with high genome instability expression treated with paclitaxel had significantly improved survival with a HR of 0.29 (95% CI: 0.14-0.61, p=0.001) and HR 0.34 (95% CI: 0.17-0.69, p=0.003) for PFS and OS, respectively. Similarly, patients with high evading growth suppressor expression treated with paclitaxel had improved PFS and OS with a HR of 0.35 (95% CI: 0.19-0.77, p=0.007) and HR 0.46 (95% CI: 0.23-0.91, p=0.026), respectively. No other gene signatures had significant impact on outcome. In both paclitaxel and pazopanib cohorts, angiogenesis activation was associated with worse PFS and OS, and VEGF targeted therapy did not improve outcomes. CONCLUSION: High Genome-instability and Evading-growth suppressor biologies are associated with improved survival in patients with platinum refractory mUC receiving paclitaxel. These may refine mUC risk stratification and guide treatment decision in the future.

Serum autotaxin level: a promising diagnostic biomarker in differentiating Graves' disease and thyroiditis.

BACKGROUND: Recent studies have suggested that serum autotaxin (ATX) may be a promising diagnostic biomarker in differentiating between Graves' disease (GD) and thyroiditis, as well as serving as a monitoring biomarker for GD. This study will evaluate the use of serum ATX as a diagnostic biomarker in these conditions. METHODS: In this prospective interventional study, blood samples were collected from the patients who met both inclusion and exclusion criteria, and serum ATX levels were measured by using the MyBioSource human Autotaxin ELISA kit. RESULTS: A total of 32 patients were enrolled, of which 18.8% were newly diagnosed with GD, 21.9% were thyroiditis, and 59.3% were on treatment for GD. Serum autotaxin antigen was significantly higher in GD patients than in thyroiditis (603.3217 ± 444.24 v/s 214.74 ± 55.91, P = <.005). Serum ATX measurement successfully discriminated GD patients from thyroiditis (AUC = 0.952, 95%CI: 0.00-1.00) with an optimal cutoff value of ≥257.20 ng/L (sensitivity = 100 and specificity = 81.71). Monitoring the efficacy of serum ATX was analyzed and showed a significant difference. CONCLUSION: The serum ATX was higher in subjects with GD as compared to thyroiditis, and ATX levels were found to be decreased during the treatment period. In conclusion, serum ATX can be used as a diagnostic and monitoring biomarker in GD.

Role of miRNA­122 in cancer (Review).

MicroRNAs (miRNAs) are small non­coding RNAs that serve key roles in cell proliferation, migration, invasion and apoptosis by regulating gene expression. In malignant tumors, miRNA­122 serves either as a tumor suppressor or oncogene, influencing tumor progression via downstream gene targeting. However, the precise role of miRNA­122 in cancer remains unclear. miRNA­122 is a potential biomarker and modulator of radiotherapy and chemotherapy. The present review aimed to summarize the roles of miRNA­122 in cancer, its potential as a biomarker for diagnosis and prognosis and its implications in cancer therapy, including radiotherapy and chemotherapy, alongside strategies for systemic delivery.

Development and preliminary evaluation toward a new tuberculosis treatment monitoring tool: the PATHFAST TB LAM Ag assay.

The PATHFAST TB LAM Ag assay is based on a chemiluminescent enzyme immunoassay to quantify lipoarabinomannan (LAM) in sputum within 1 h, and was developed as an alternative to conventional culture methods for monitoring tuberculosis (TB) treatment. This study aimed to evaluate the analytical performance and initial clinical feasibility of using five Mycobacterium tuberculosis variants, 178 non-tuberculous mycobacteria (NTM), 34 upper respiratory and oral cavity microorganisms, 100 sputum specimens from untreated patients, and potential interfering substances, including 27 drugs. The results reveled a single-site repeatability coefficient of variation (CV) of 5.2%-7.0%, and a multi-site reproducibility CV of 7.1%-8.4%. The limit of blank, limit of detection, and limit of quantification were 3.03 pg/mL, 6.67 pg/mL, and 7.44 pg/mL, respectively. Linearity was observed over the analytical measurement range (10.0 pg/mL-50,000 pg/mL), and no hook effect was observed. The assay tended to cross-react with slow-growing NTMs, but not with common upper respiratory and oral cavity microorganisms, except Nocardia asteroides, Nocardia farcinica, and Tsukamurella paurometabola. No interference was observed in the presence of mucin, blood, or major anti-TB, anti-HIV, and anti-pneumonia drugs. Regarding clinical performance, the assay had a sensitivity of 88.8% (95% CI: 80.0%-94.0%) and specificity of 100.0% (95% CI: 83.9%-100.0%) using mycobacterial culture as the reference standard, and a correlation (Spearman's r = -0.770) was observed between LAM concentration and time to detection of culture. These findings show, for the first time, that the PATHFAST TB LAM Ag assay has potential value for monitoring TB treatment.