Relationship between continuous EEG monitoring findings and prognostic factors in patients with status epilepticus.

BACKGROUND AND PURPOSE: Little information is available regarding the use of continuous electroencephalography (cEEG) monitoring findings to predict the prognosis of patients with status epilepticus, which could aid in prognostication. This study investigated the relationship between cEEG monitoring findings and various prognostic indicators in patients with status epilepticus. METHODS: We reviewed the clinical profiles and cEEG monitoring data of 28 patients with status epilepticus over a ten-year period. Patient demographics, etiology, EEG features, duration of hospital stay, number of antiseizure medications, and outcome measures were analyzed. Functional outcomes were assessed using the modified Rankin Scale (mRS), which evaluates the degree of daily living impairment and dependence on others resulting from neurological injury. RESULTS: Patients exhibiting electrographic status epilepticus (ESE) demonstrated significantly longer duration of status epilepticus (77.75 ± 58.25 vs. 39.86 ± 29.81 h, p = 0.024) and total length of hospital stay (13.00 ± 6.14 vs. 8.14 ± 5.66 days, p = 0.038) when compared to those with ictal-interictal continuum (IIC). Individuals who displayed any increase in modified Rankin Scale (mRS) score between their premorbid state and discharge also had significantly longer duration of status epilepticus (74.09 ± 34.94 vs. 51.56 ± 54.25 h, p = 0.041) and total length of hospital stay (15.89 ± 6.05 vs. 8.05 ± 4.80 days, p = 0.004) when compared to those who showed no difference. The most prevalent etiology of status epilepticus in our study was chronic structural brain lesions. CONCLUSIONS: This suggests that ESE may serve as a predictor of prolonged duration of status epilepticus and increased hospitalization among patients with status epilepticus.

Clinicopathological significance of hyaluronan and hyaluronidase 2 (HYAL2) in breast cancer.

Hyaluronan (HA), as a component of extracellular matrix, has pivotal roles in both physiological and pathological condition. In breast cancer, while high molecular weight HA is produced by hyaluronan synthase, it is degraded by hyaluronidases (hyaluronidase-1 (HYAL1) and hyaluronidase-2 (HYAL2)) into low molecular weight HA (LMW HA), which is considered to have pro-tumorigenic effects in human malignancies. However, HA and HYAL2, the rate-limiting enzyme of HA degradation, have not been comprehensively examined in breast cancer and clinicopathological significance of LMW HA remains to be elucidated in breast cancer. We therefore histochemically localized HA as well as HYAL2 in 116 breast cancer tissues. In addition, we examined size-dependent function of HA on breast cancer cell proliferation and migration using MCF-7 and MDA-MB-231 breast cancer cell lines. HA was localized in both the stroma and breast carcinoma cells, while HYAL2 was predominantly localized in breast carcinoma cells. HA was significantly correlated with cell proliferation and invasion ability as well as increased risk of recurrence especially in HYAL2 positive group. On the other hand, HYAL2 was correlated with breast cancer cell proliferation and increased risk of recurrence. In addition, in vitro analyses revealed that lower molecular weight HA increased sphere forming ability and migration in MCF-7 and MDA-MB-231, whereas higher molecular weight HA inhibited them. It was concluded that HA needs to be degraded by HYAL2 to exert pro-tumorigenic effects and comprehensive HA/HYAL2 status serves as a potent prognostic factor in breast cancer.

Phenotypic subgroup in serologically active clinically quiescent systemic lupus erythematosus: A cluster analysis based on CSTAR cohort.

BACKGROUND: Serologically active clinically quiescent (SACQ) is a state within systemic lupus erythematosus (SLE) characterized by elevated serologic markers without clinical activity. The heterogeneity in SACQ patients poses challenges in disease management. This multicenter prospective study aimed to identify distinct SACQ subgroups and assess their utility in predicting organ damage. METHODS: SACQ was defined as a sustained period of at least 6 months with persistent serologic activity, marked by positive anti-double-stranded DNA (dsDNA) antibodies and/or hypocomplementemia, and without clinical activity. Cluster analysis was employed, utilizing 16 independent components to delineate phenotypes. FINDINGS: Among the 4,107 patients with SLE, 990 (24.1%) achieved SACQ within 2.0 ± 2.3 years on average. Over a total follow-up of 7,105.1 patient years, 340 (34.3%) experienced flares, and 134 (13.5%) developed organ damage. Three distinct SACQ subgroups were identified. Cluster 1 (n = 219, 22.1%) consisted predominantly of elderly males with a history of major organ involvement at SLE diagnosis, showing the highest risk of severe flares (16.4%) and organ damage (27.9%). Cluster 2 (n = 279, 28.2%) was characterized by milder disease and a lower risk of damage accrual (5.7%). Notably, 86 patients (30.8%) in cluster 2 successfully discontinued low-dose glucocorticoids, with 49 of them doing so without experiencing flares. Cluster 3 (n = 492, 49.7%) featured the highest proportion of lupus nephritis and a moderate risk of organ damage (11.8%), with male patients showing significantly higher risk of damage (hazard ratio [HR] = 4.51, 95% confidence interval [CI], 1.82-11.79). CONCLUSION: This study identified three distinct SACQ clusters, each with specific prognostic implications. This classification could enhance personalized management for SACQ patients. FUNDING: This work was funded by the National Key R&D Program (2021YFC2501300), the Beijing Municipal Science & Technology Commission (Z201100005520023), the CAMS Innovation Fund (2021-I2M-1-005), and National High-Level Hospital Clinical Research Funding (2022-PUMCH-D-009).

The perceptions and knowledge of prognosis of physiotherapists in musculoskeletal practice: An exploratory qualitative study.

QUESTION(S): What are the perceptions and knowledge of physiotherapists who treat musculoskeletal disorders towards prognosis? DESIGN: Exploratory phenomenological study. PARTICIPANTS: 15 physiotherapists involved in the treatment of musculoskeletal disorders. DATA ANALYSIS: Data were collected through semi-structured interviews and analysed using inductive coding and thematic analysis. RESULTS: Four themes were identified. First, participants perception of prognosis was influenced by how they defined prognosis. Participants often perceived that prognosis was the timeline to recovery related to function, tissue health, or pain. Second, some participants could not recall foundational knowledge about prognosis being taught during their entry-level physiotherapy program. Others recalled it being taught in relation to the tissue healing model. Third, participants described learning about prognosis through experience, professional development, or from peers. Finally, participants identified that a potential learning opportunity is to conceptualise prognosis as separate outcomes associated with function, tissue health, and pain. Each can impact upon prognosis, have a prognosis of their own, and can occur simultaneously. CONCLUSION: How physiotherapists perceive and understand the concept of prognosis is influenced by their foundational knowledge. It appears for physiotherapists, prognosis may be conceptualised within the biomedical model of health. Indeed, physiotherapists may perceive that prognosis is the timeline for recovery determined by the tissue model of healing. Physiotherapists also rely on experiential knowledge gained from clinical practice, professional development, and their peers to enhance learning about prognosis. The understanding of prognosis may be enhanced if physiotherapists conceptualise prognosis in terms of the multifactorial outcomes associated with function, tissue health, and pain.

Levodopa-induced dyskinesia in Parkinson's disease: Insights from cross-cohort prognostic analysis using machine learning.

BACKGROUND: Prolonged levodopa treatment in Parkinson's disease (PD) often leads to motor complications, including levodopa-induced dyskinesia (LID). Despite continuous levodopa treatment, some patients do not develop LID symptoms, even in later stages of the disease. OBJECTIVE: This study explores machine learning (ML) methods using baseline clinical characteristics to predict the development of LID in PD patients over four years, across multiple cohorts. METHODS: Using interpretable ML approaches, we analyzed clinical data from three independent longitudinal PD cohorts (LuxPARK, n = 356; PPMI, n = 484; ICEBERG, n = 113) to develop cross-cohort prognostic models and identify potential predictors for the development of LID. We examined cohort-specific and shared predictive factors, assessing model performance and stability through cross-validation analyses. RESULTS: Consistent cross-validation results for single and multiple cohort analyses highlighted the effectiveness of the ML models and identified baseline clinical characteristics with significant predictive value for the LID prognosis in PD. Predictors positively correlated with LID include axial symptoms, freezing of gait, and rigidity in the lower extremities. Conversely, the risk of developing LID was inversely associated with the occurrence of resting tremors, higher body weight, later onset of PD, and visuospatial abilities. CONCLUSIONS: This study presents interpretable ML models for dyskinesia prognosis with significant predictive power in cross-cohort analyses. The models may pave the way for proactive interventions against dyskinesia in PD by optimizing levodopa dosing regimens and adjunct treatments with dopamine agonists or MAO-B inhibitors, and by employing non-pharmacological interventions such as dietary adjustments affecting levodopa absorption for high-risk LID patients.

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

OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Epigenetically associated IGF2BP3 upregulation promotes cell proliferation by regulating E2F1 expression in hepatocellular carcinoma.

RNA-binding proteins (RBPs) are a class of proteins that primarily function by interacting with different types of RNAs and play a critical role in regulating the transcription and translation of cancer-related genes. However, their role in the progression of hepatocellular carcinoma (HCC) remains unclear. In this study, we analyzed RNA sequencing data and the corresponding clinical information of patients with HCC to screen for prognostic RBPs. Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) was identified as an independent prognostic factor for liver cancer. It is upregulated in HCC and is associated with a poor prognosis. Elevated IGF2BP3 expression was validated via immunohistochemical analysis using a tissue microarray of patients with HCC. IGF2BP3 knockdown inhibited the proliferation of Hep3B and HepG2 cells, whereas IGF2BP3 overexpression promoted the expansion of HuH-7 and MHCC97H cells. Mechanistically, IGF2BP3 modulates cell proliferation by regulating E2F1 expression. DNA hypomethylation of the IGF2BP3 gene may increase the expression of IGF2BP3, thereby enhancing cell proliferation in HCC. Therefore, IGF2BP3 may act as a novel prognostic biomarker and a potential therapeutic target for HCC.

Development and validation of AI-derived segmentation of four-chamber cine cardiac magnetic resonance.

BACKGROUND: Cardiac magnetic resonance (CMR) in the four-chamber plane offers comprehensive insight into the volumetrics of the heart. We aimed to develop an artificial intelligence (AI) model of time-resolved segmentation using the four-chamber cine. METHODS: A fully automated deep learning algorithm was trained using retrospective multicentre and multivendor data of 814 subjects. Validation, reproducibility, and mortality prediction were evaluated on an independent cohort of 101 subjects. RESULTS: The mean age of the validation cohort was 54 years, and 66 (65%) were males. Left and right heart parameters demonstrated strong correlations between automated and manual analysis, with a ρ of 0.91-0.98 and 0.89-0.98, respectively, with minimal bias. All AI four-chamber volumetrics in repeatability analysis demonstrated high correlation (ρ = 0.99-1.00) and no bias. Automated four-chamber analysis underestimated both left ventricular (LV) and right ventricular (RV) volumes compared to ground-truth short-axis cine analysis. Two correction factors for LV and RV four-chamber analysis were proposed based on systematic bias. After applying the correction factors, a strong correlation and minimal bias for LV volumetrics were observed. During a mean follow-up period of 6.75 years, 16 patients died. On stepwise multivariable analysis, left atrial ejection fraction demonstrated an independent association with death in both manual (hazard ratio (HR) = 0.96, p = 0.003) and AI analyses (HR = 0.96, p < 0.001). CONCLUSION: Fully automated four-chamber CMR is feasible, reproducible, and has the same real-world prognostic value as manual analysis. LV volumes by four-chamber segmentation were comparable to short-axis volumetric assessment. TRIALS REGISTRATION: ClinicalTrials.gov: NCT05114785. RELEVANCE STATEMENT: Integrating fully automated AI in CMR promises to revolutionise clinical cardiac assessment, offering efficient, accurate, and prognostically valuable insights for improved patient care and outcomes. KEY POINTS: • Four-chamber cine sequences remain one of the most informative acquisitions in CMR examination. • This deep learning-based, time-resolved, fully automated four-chamber volumetric, functional, and deformation analysis solution. • LV and RV were underestimated by four-chamber analysis compared to ground truth short-axis segmentation. • Correction bias for both LV and RV volumes by four-chamber segmentation, minimises the systematic bias.

The expression and clinical significance of CFAP65 in colon cancer.

BACKGROUND: CFAP65 (cilia and flagella associated protein 65) is a fundamental protein in the development and formation of ciliated flagella, but few studies have focused on its role in cancer. This study aimed to investigate the prognostic significance of CFAP65 in colon cancer. METHODS: The functionally enriched genes related to CFAP65 were analyzed through the Gene Ontology (GO) database. Subsequently, CFAP65 expression levels in colon cancer were evaluated by reverse transcription and quantitative polymerase chain reaction (RT-qPCR) and immunoblotting in 20 pairs of frozen samples, including tumors and their matched paratumor tissue. Furthermore, protein expression of CFAP65 in 189 colon cancer patients were assessed via immunohistochemical staining. The correlations between CFAP65 expression and clinical features as well as long-term survival were statistically analyzed. RESULTS: CFAP65-related genes are significantly enriched on cellular processes of cell motility, ion channels, and GTPase-associated signaling. The expression of CFAP65 was significantly higher in colon cancer tissue compared to paratumor tissue. The proportion of high expression and low expression of CFAP65 in the clinical samples of colon cancer were 61.9% and 38.1%, respectively, and its expression level was not associated with the clinical parameters including gender, age, tumor location, histological differentiation, tumor stage, vascular invasion and mismatch repair deficiency. The five-year disease-free survival rate of the patients with CFAP65 low expression tumors was significantly lower than that those with high expression tumors (56.9% vs. 72.6%, P = 0.03), but the overall survival rate has no significant difference (69% vs. 78.6%, P = 0.171). The cox hazard regression analysis model showed that CFAP65 expression, tumor stage and tumor location were independent prognostic factors. CONCLUSIONS: In conclusion, we demonstrate CFAP65 is a potential predictive marker for tumor progression in colon cancer.

Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the USs. Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), 3 adenosarcomas, 2 carcinosarcomas, and 1 uterine tumor resembling an ovarian sex-cord tumor (UTROSCT). ESS (including high-grade ESS and low-grade ESS) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A - PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uDEGs were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named MMN-MIL showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion: USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Imaging Role in Diagnosis, Prognosis, and Treatment Response Prediction Associated with High-grade Glioma.

Background: Glioma is one of the most drug and radiation-resistant tumors. Gliomas suffer from inter- and intratumor heterogeneity which makes the outcome of similar treatment protocols vary from patient to patient. This article is aimed to overview the potential imaging markers for individual diagnosis, prognosis, and treatment response prediction in malignant glioma. Furthermore, the correlation between imaging findings and biological and clinical information of glioma patients is reviewed. Materials and Methods: The search strategy in this study is to select related studies from scientific websites such as PubMed, Scopus, Google Scholar, and Web of Science published until 2022. It comprised a combination of keywords such as Biomarkers, Diagnosis, Prognosis, Imaging techniques, and malignant glioma, according to Medical Subject Headings. Results: Some imaging parameters that are effective in glioma management include: ADC, FA, Ktrans, regional cerebral blood volume (rCBV), cerebral blood flow (CBF), ve, Cho/NAA and lactate/lipid ratios, intratumoral uptake of 18F-FET (for diagnostic application), RD, ADC, ve, vp, Ktrans, CBFT1, rCBV, tumor blood flow, Cho/NAA, lactate/lipid, MI/Cho, uptakes of 18F-FET, 11C-MET, and 18F-FLT (for prognostic and predictive application). Cerebral blood volume and Ktrans are related to molecular markers such as vascular endothelial growth factor (VEGF). Preoperative ADCmin value of GBM tumors is associated with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. 2-hydroxyglutarate metabolite and dynamic 18F-FDOPA positron emission tomography uptake are related to isocitrate dehydrogenase (IDH) mutations. Conclusion: Parameters including ADC, RD, FA, rCBV, Ktrans, vp, and uptake of 18F-FET are useful for diagnosis, prognosis, and treatment response prediction in glioma. A significant correlation between molecular markers such as VEGF, MGMT, and IDH mutations with some diffusion and perfusion imaging parameters has been identified.

CDKL3 is a promising biomarker for diagnosis and prognosis prediction in patients with hepatocellular carcinoma.

Cyclin-dependent kinase-like 3 (CDKL3) has been identified as an oncogene in certain types of tumors. Nonetheless, its function in hepatocellular carcinoma (HCC) is poorly understood. In this study, we conducted a comprehensive analysis of CDKL3 based on data from the HCC cohort of The Cancer Genome Atlas (TCGA). Our analysis included gene expression, diagnosis, prognosis, functional enrichment, tumor microenvironment and metabolic characteristics, tumor burden, mRNA expression-based stemness, alternative splicing, and prediction of therapy response. Additionally, we performed a cell counting kit-8 assay, TdT-mediated dUTP nick-end Labeling staining, migration assay, wound healing assay, colony formation assay, and nude mouse experiments to confirm the functional relevance of CDKL3 in HCC. Our findings showed that CDKL3 was significantly upregulated in HCC patients compared to controls. Various bioinformatic analyses suggested that CDKL3 could serve as a potential marker for HCC diagnosis and prognosis. Furthermore, CDKL3 was found to be involved in various mechanisms linked to the development of HCC, including copy number variation, tumor burden, genomic heterogeneity, cancer stemness, and alternative splicing of CDKL3. Notably, CDKL3 was also closely correlated with tumor immune cell infiltration and the expression of immune checkpoint markers. Additionally, CDKL3 was shown to independently function as a risk predictor for overall survival in HCC patients by multivariate Cox regression analysis. Furthermore, the knockdown of CDKL3 significantly inhibited cell proliferation in vitro and in vivo, indicating its role as an oncogene in HCC. Taken together, our findings suggest that CDKL3 shows promise as a biomarker for the detection and treatment outcome prediction of HCC patients.

Significance and Possible Biological Mechanism for CLDN8 Downregulation in Kidney Renal Clear Cell Carcinoma Tissues.

Background: The clinical role of claudin 8 (CLDN8) in kidney renal clear cell carcinoma (KIRC) remains unclarified. Herein, the expression level and potential molecular mechanisms of CLDN8 underlying KIRC were determined. Methods: High-throughput datasets of KIRC were collected from GEO, ArrayExpress, SRA, and TCGA databases to determine the mRNA expression level of the CLDN8. In-house tissue microarrays and immunochemistry were performed to examine CLDN8 protein expression. A summary receiver operating characteristic curve (SROC) and standardized mean difference (SMD) forest plot were generated using Stata v16.0. Single-cell analysis was conducted to further prove the expression level of CLDN8. A clustered regularly interspaced short palindromic repeats knockout screen analysis was executed to assess the growth impact of CLDN8. Functional enrichment analysis was conducted using the Metascape database. Additionally, single-sample gene set enrichment analysis was implied to explore immune cell infiltration in KIRC. Results: A total of 17 mRNA datasets comprising 1,060 KIRC samples and 452 non-cancerous control samples were included in this study. Additionally, 105 KIRC and 16 non-KIRC tissues were analyzed using in-house immunohistochemistry. The combined SMD was -5.25 (95% confidence interval (CI): -6.13 to -4.37), and CLDN8 downregulation yielded an SROC area under the curve (AUC) close to 1.00 (95% CI: 0.99 - 1.00). CLDN8 downregulation was also confirmed at the single-cell level. Knocking out CLDN8 stimulated KIRC cell proliferation. Lower CLDN8 expression was correlated with worse overall survival of KIRC patients (hazard ratio of CLDN8 downregulation = 1.69, 95% CI: 1.2 - 2.4). Functional pathways associated with CLDN8 co-expressed genes were centered on carbon metabolism obstruction, with key hub genes ACADM, ACO2, NDUFS1, PDHB, SDHD, SUCLA2, SUCLG1, and SUCLG2. Conclusions: CLDN8 is downregulated in KIRC and is considered a potential tumor suppressor. CLDN8 deficiency may promote the initiation and progression of KIRC, potentially in conjunction with metabolic dysfunction.

Clinical outcome predictors for metastatic renal cell carcinoma: a retrospective multicenter real-life case series.

Over the last decades, the therapeutic armamentarium of metastatic renal cell carcinoma (mRCC) has been revolutionized by the advent of tyrosin-kinase inhibitors (TKI), immune-checkpoint inhibitors (ICI), and immune-combinations. RCC is heterogeneous, and even the most used validated prognostic systems, fail to describe its evolution in real-life scenarios. Our aim is to identify potential easily-accessible clinical factors and design a disease course prediction system. Medical records of 453 patients with mRCC receiving sequential systemic therapy in two high-volume oncological centres were reviewed. The Kaplan-Meier method and Cox proportional hazard model were used to estimate and compare survival between groups. As first-line treatment 366 patients received TKI monotherapy and 64 patients received ICI, alone or in combination. The mean number of therapy lines was 2.5. A high Systemic Inflammation Index, a BMI under 25 Kg/m2, the presence of bone metastases before systemic therapy start, age over 65 years at the first diagnosis, non-clear-cell histology and sarcomatoid component were correlated with a worse OS. No significant OS difference was observed between patients receiving combination therapies and those receiving exclusively monotherapies in the treatment sequence. Our relapse prediction system based on pathological stage and histological grade was effective in predicting the time between nephrectomy and systemic treatment. Our multicentric retrospective analysis reveals additional potential prognostic factors for mRCC, not included in current validated prognostic systems, suggests a model for disease course prediction and describes the outcomes of the most common therapeutic strategies currently available.

Prognosis of Lung Transplantation in Patients with Acute Exacerbations of Interstitial Lung Disease: A Meta-Analysis Based on Cohort Studies.

PURPOSE: This meta-analysis aimed to examine the prognosis of patients with acute exacerbation of interstitial lung disease (AE-ILD) treated with lung transplantation compared to those with stable interstitial lung disease (ILD). METHODS: We conducted a detailed search in PubMed, Embase, Web of Science, and the Cochrane Library, with the primary outcomes being overall survival (OS), acute cellular rejection (ACR), primary graft dysfunction (PGD), and length of stay (LOS). RESULTS: Five cohort studies were included in this meta-analysis, with 183 patients enrolled in the AE-ILD group and 337 patients in the stable-ILD group. The results showed that in regard to perioperative outcomes, the AE-ILD group did not differ from the stable-ILD group in the incidence of ACR (relative risks [RR] = 0.34, p = 0.44) and the incidence of PGD Ⅲ (RR = 0.53, p = 0.43), but had a longer LOS (mean difference = 9.15, p = 0.02). Regarding prognosis, the two also did not differ in 90-day OS (RR = 0.97, p = 0.59), 1-year OS (RR = 1.05, p = 0.66), and 3-year OS (RR = 0.91, p = 0.76). CONCLUSION: Our study concluded that the efficacy of lung transplantation in patients with AE-ILD is not inferior to that of patients with stable ILD. Lung transplantation is one of the potential treatments for patients with AE-ILD.

Investigation of prognostic values of immune infiltration and LGMN expression in the microenvironment of osteosarcoma.

BACKGROUND: Osteosarcoma (OS), the most common primary malignant bone tumor, predominantly affects children and young adults and is characterized by high invasiveness and poor prognosis. Despite therapeutic advancements, the survival rate remains suboptimal, indicating an urgent need for novel biomarkers and therapeutic targets. This study aimed to investigate the prognostic significance of LGMN expression and immune cell infiltration in the tumor microenvironment of OS. METHODS: We performed an integrative bioinformatics analysis utilizing the GEO and TARGET-OS databases to identify differentially expressed genes (DEGs) associated with LGMN in OS. We conducted Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) to explore the biological pathways and functions. Additionally, we constructed protein-protein interaction (PPI) networks, a competing endogenous RNA (ceRNA) network, and applied the CIBERSORT algorithm to quantify immune cell infiltration. The diagnostic and prognostic values of LGMN were evaluated using the area under the receiver operating characteristic (ROC) curve and Cox regression analysis. Furthermore, we employed Consensus Clustering Analysis to explore the heterogeneity within OS samples based on LGMN expression. RESULTS: The analysis revealed significant upregulation of LGMN in OS tissues. DEGs were enriched in immune response and antigen processing pathways, suggesting LGMN's role in immune modulation within the TME. The PPI and ceRNA network analyses provided insights into the regulatory mechanisms involving LGMN. Immune cell infiltration analysis indicated a correlation between high LGMN expression and increased abundance of M2 macrophages, implicating an immunosuppressive role. The diagnostic AUC for LGMN was 0.799, demonstrating its potential as a diagnostic biomarker. High LGMN expression correlated with reduced overall survival (OS) and progression-free survival (PFS). Importantly, Consensus Clustering Analysis identified two distinct subtypes of OS, highlighting the heterogeneity and potential for personalized medicine approaches. CONCLUSIONS: Our study underscores the prognostic value of LGMN in osteosarcoma and its potential as a therapeutic target. The identification of LGMN-associated immune cell subsets and the discovery of distinct OS subtypes through Consensus Clustering Analysis provide new avenues for understanding the immunosuppressive TME of OS and may aid in the development of personalized treatment strategies. Further validation in larger cohorts is warranted to confirm these findings.

Analysis of tumor abnormal protein expression and epidermal growth factor receptor mutation status in non-small cell lung cancer.

BACKGROUND: The level of tumor abnormal protein (TAP) level has a significant impact on tumor growth, recurrence, and metastasis. Previous studies have highlighted the influence of the mutations in exons 19 and 21 of the epidermal growth factor receptor (EGFR), particularly the sensitivity displayed by tumor cells to epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) therapy. Our study is centered on exploring the clinical relevance of TAP and EGFR mutations in patients with non-small cell lung cancer (NSCLC). MATERIAL AND METHODS: In this study, tissue samples were collected from a total of 176 patients diagnosed with non-small cell lung cancer (NSCLC). Real-time PCR technology was utilized to detect mutations within exons 19 and 21 of the epidermal growth factor receptor (EGFR) gene in these samples. This approach enables precise identification of EGFR mutations associated with NSCLC. Furthermore, the study investigated the impact of various tumor markers, including tumor abnormal protein (TAP) and carcinoembryonic antigen (CEA), on EGFR mutation status. Established assays were employed to evaluate TAP and CEA levels, aiming to ascertain their potential correlation with EGFR mutation in NSCLC patients. RESULTS: EGFR exhibited mutation rates of 23.86% and 12.50% in exons 19 and 21, respectively. EGFR mutations were more prevalent in younger women (< 60 years old) and in cases with pleural invasion, vessel invasion, CEA > 6.5 ng/mL, and TAP > 228 µm2 for both genders. Increased TAP levels independently predicted EGFR mutations (P = 0.001 for males; P = 0.000 for females). An area under the curve (AUC) of 0.833 indecated EGFR mutation prediction with sensitivity and specificity of 79.7% and 87.0%, respectively. For females, the sensitivity increased to 89.7% and specificity increased to 93.8%. CONCLUSIONS: TAP effectively predicts EGFR mutations in NSCLC patients with moderate accuracy, particularly benefiting diagnosis in females with high sensitivity and specificity. Integrating TAP assessment into EGFR mutation testing can significantly enhance diagnostic precision, especially in female NSCLC cases.

Urine output is an early and strong predictor of acute kidney injury and associated mortality: a systematic literature review of 50 clinical studies.

BACKGROUND: Although the present diagnosis of acute kidney injury (AKI) involves measurement of acute increases in serum creatinine (SC) and reduced urine output (UO), measurement of UO is underutilized for diagnosis of AKI in clinical practice. The purpose of this investigation was to conduct a systematic literature review of published studies that evaluate both UO and SC in the detection of AKI to better understand incidence, healthcare resource use, and mortality in relation to these diagnostic measures and how these outcomes may vary by population subtype. METHODS: The systematic literature review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Data were extracted from comparative studies focused on the diagnostic accuracy of UO and SC, relevant clinical outcomes, and resource usage. Quality and validity were assessed using the National Institute for Health and Care Excellence (NICE) single technology appraisal quality checklist for randomized controlled trials and the Newcastle-Ottawa Quality Assessment Scale for observational studies. RESULTS: A total of 1729 publications were screened, with 50 studies eligible for inclusion. A majority of studies (76%) used the Kidney Disease: Improving Global Outcomes (KDIGO) criteria to classify AKI and focused on the comparison of UO alone versus SC alone, while few studies analyzed a diagnosis of AKI based on the presence of both UO and SC, or the presence of at least one of UO or SC indicators. Of the included studies, 33% analyzed patients treated for cardiovascular diseases and 30% analyzed patients treated in a general intensive care unit. The use of UO criteria was more often associated with increased incidence of AKI (36%), than was the application of SC criteria (21%), which was consistent across the subgroup analyses performed. Furthermore, the use of UO criteria was associated with an earlier diagnosis of AKI (2.4-46.0 h). Both diagnostic modalities accurately predicted risk of AKI-related mortality. CONCLUSIONS: Evidence suggests that the inclusion of UO criteria provides substantial diagnostic and prognostic value to the detection of AKI.

USP18 promotes colon adenocarcinoma progression via targeting the ERK-MNK signaling pathway.

BACKGROUND: Colorectal cancer is the third most common malignancy worldwide and is one of the leading causes of cancer-related mortality. Ubiquitin-specific peptidase 18 (USP18) protein has been reported to exert different tumor-related effects in distinct tumor types. Here, we initially investigated the expression and signaling pathways of USP18 in colon adenocarcinoma (COAD). METHODS: A quantitative real-time PCR was conducted to evaluate the mRNA level of USP18 in cultured cells. Immunohistochemical staining was used to explore the protein expression of USP18 in clinical COAD samples. Specific knockdown was achieved by transient transfection of small interfering RNAs into SW480 and HT29 cells using Lipo3000. Cell conting kit-8 assay, transwell assay and matrigel-transwell assays were conducted to evaluate proliferation, migration and invasion capacities, respectively. Western blotting was performed to analyze downstream signaling pathways. A chi-squared test and univariate and multivariate analyses were used to evaluate the clinical data. Xenografts from mice model were assessed to validate the in vitro findings. RESULTS: Higher USP18 level was identified in COAD tissues and was positively correlated with advanced tumor stage. High USP18 protein expression indicated poorer prognosis of COAD patients. Silencing USP18 suppressed COAD cell proliferation and invasion via destabilizing extracellular signal-regulated kinase (ERK) protein and suppressing ERK downstream pathways. Simultaneously silencing interferon-stimulated gene 15 (ISG15) with USP18 can partially rescue the tumor cell viability, indicating its involvement in USP18 signaling. The oncogenic effects of USP18 were also confirmed in mice models. CONCLUSIONS: USP18 plays oncogenic effects in colon adenocarcinoma via ISG15-ERK pathways. High USP18 expression indicates poor clinical outcomes for colon adenocarcinoma patients.

Platelet glycoprotein IIb/IIIa antagonists in ischemic stroke patients without endovascular therapy: A meta-analysis.

Platelet glycoprotein (GP) IIb/IIIa antagonists have been employed in selective patients after endovascular therapy (EVT) for acute ischemic stroke (AIS), yet application in patients without EVT is debated. This meta-analysis of randomized controlled studies on AIS patients without EVT assessed the effectiveness and safety of platelet GP IIb/IIIa antagonists compared with traditional antiplatelet or thrombolysis therapy. Articles were retrieved from databases, including PubMed, Web of Science, EMBASE, and Cochrane. The risk of bias and certainty level of evidence were assessed. Fifteen studies were included. GP IIb/IIIa antagonists increased the proportion of patients with modified Rankin Scale (mRS) 0-1 (odd ratio [OR] 1.37, 95% confidence interval [CI] 1.04-1.81, p = 0.03), mRS 0-2 (OR 1.27, 95% CI 1.12-1.46, p = 0.0004), and Barthel Index (BI) 95-100 (OR 1.25, p = 0.005); decreased the proportion of stroke progression within 5 days (OR 0.66, p = 0.006); and lowered the mean mRS score at 90 days (mean difference [MD] -0.43, p = 0.002) and the National Institute of Health stroke scale score at 7 days (MD -1.64, p < 0.00001) compared with conventional treatment. Proportions of stroke recurrence within 90 days (OR 1.20, p = 0.60), any intracranial hemorrhage (aICH) (OR 1.20, p = 0.12), symptomatic intracranial hemorrhage (sICH) (OR 0.91, p = 0.88), and death (OR 0.87, p = 0.25) had no statistical difference between both groups. This meta-analysis finds that compared with traditional antiplatelet or thrombolysis therapy, GP IIb/IIIa antagonists administered within 24-96 h of ischemic stroke onset significantly improve functional prognosis of patients with AIS not receiving EVT, as indicated by mRS and BI at 90 days, and do not increase the incidence of aICH, sICH, and death.