Category: Nevin Manimala

Funct Integr Genomics. 2023 Apr 15;23(2):125. doi: 10.1007/s10142-023-01055-7.

ABSTRACT

Although many genes may serve as reference genes, they may cause different expression patterns by selecting different reference genes because no single gene is expressed consistently in all tested tissues of an organism under all environmental and developmental conditions. Thus, it is becoming increasingly important and necessary to identify suitable reference genes before performing gene expression analysis. Currently, there are several computational tools available for evaluating the stability of candidate reference genes. These tools are based on different statistical algorithms and may produce different rankings in stability within the same reference gene study. To date, the RefFinder is the only web-based tool available for comparing and evaluating housekeeping genes as candidates to be reference genes. In this tool, we integrated the four currently available computational programs (geNorm, NormFinder, BestKeeper, and the comparative ΔCt method) into a web-based tool for evaluating the stability and reliability of reference genes. According to the gene stability rankings derived from the four programs, we assigned an appropriate weight to each gene and calculated the geometric mean of weights for the final rankings. Aside from the overall ranking, a single program or combination of the four programs can be selected for evaluating the ranking of candidate reference genes. This tool has been widely used and validated by many research laboratories around the world. You may use this tool at http://www.heartcure.com.au/reffinder/ or https://blooge.cn/RefFinder/ . You can also download this algorithm program from https://github.com/fulxie/RefFinder and setup on your own computer. RefFinder is developed by PHP. Users can deploy it to a Php-based server (Apache + PHP) and run it.

PMID:37060478 | DOI:10.1007/s10142-023-01055-7

J Cancer Res Clin Oncol. 2023 Apr 15. doi: 10.1007/s00432-023-04751-w. Online ahead of print.

ABSTRACT

BACKGROUND: Acute myeloid leukaemia carries the risk of complications associated with dysfunctions in haemostasis system. The purpose of this study was to investigate the factors associated with the risk of bleeding in patients with newly diagnosed acute myeloid leukaemia (AML).

METHODS: This study involved the methods of immunoenzymatic analysis and classical coagulation studies. The number of biochemical parameters important for establishing coagulative dysfunction in acute myeloid leukaemia was determined, the main ones being the level of von Willebrand factor, the Ristocetin-cofactor activity of von Willebrand factor and factor VIII activity, prothrombin time, platelet count, and fibrinogen concentration.

RESULTS: According to the results of the present study, the reduced activity of von Willebrand factor in patients with AML was associated with severe bleeding. The authors observed an increase in the number of platelets count in patients with AML who experienced haemorrhages compared to patients with no bleeding signs. The study also established an increase in the concentration of fibrinogen in cancer patients, compared to the control sample. Symptoms and quantitative indicators for diagnosing the severity of haemorrhagic syndrome were grouped. The authors considered the advantages and disadvantages of many therapeutic preparations and focussed on specific markers of activated haemorrhage-predicting platelets.

CONCLUSION: Further studies concern the search for effective markers and therapeutic approaches to minimize haemorrhagic syndrome. The results were statistically processed using the functions ANOVA, t test, CORREL, determination of the value of reliability, and mean square deviation.

PMID:37060474 | DOI:10.1007/s00432-023-04751-w

Eur Radiol. 2023 Apr 15. doi: 10.1007/s00330-023-09625-w. Online ahead of print.

ABSTRACT

OBJECTIVES: The prognostic value of subventricular zone distance (SVD) is unclear because of different definitions and lack of evaluation of clinical survival models. The aim of this study was to define SVD and evaluate its prognostic value in a survival nomogram for glioblastoma.

METHODS: This retrospective study included 158 (SVD biomarker) from historical glioblastoma patients and 187 (survival modeling) with IDH-wild type glioblastoma from a prospective registry (NCT02619890). SVD was assessed by two radiologists: definition 1, the distance between the tumor edge to subventricular zone (SVZ); definition 2, the distance between the tumor centroid to SVZ; definition 3, enhancement at the ventricular wall. The associations between SVD and overall survival (OS) were evaluated using multivariable Cox proportional hazards regression analysis. Performance of an updated SVD survival model was compared with that of the Radiation Therapy Oncology Group (RTOG) 0525 nomogram.

RESULTS: SVD according to both definition 1 (hazard ratio [HR]: 0.97, 95% CI: 0.94-0.99; p = .011) and definition 2 (HR: 0.96, 0.94-0.98, p < .001) was adversely associated with OS. Definition 1 was adversely associated with PFS (HR: 0.96, 0.94-0.99, p = .008) and showed the highest reproducibility (intraclass correlation coefficient, 0.90). The SVD-updated model showed similar to better performance than the RTOG model for predicting OS of up to 3 years (AUC: 0.735-0.738 vs. 0.687-0.708), with higher time-dependent specificity for 1-year (89.9% vs. 70.6%) and 3-year OS (93.3% vs. 80.0%).

CONCLUSION: SVZ distance is an independent adverse prognostic factor in patients with IDH-wild type glioblastoma. Updating the survival model with SVZ provides better time-dependent specificity and reproducibility.

KEY POINTS: • Subventricular zone distance (SVD) measurement from tumor edge showed high reproducibility. • Longer SVD was independently associated with longer overall survival. • Adding SVD improved time-dependent specificity for survival model in a prospective registry.

PMID:37060448 | DOI:10.1007/s00330-023-09625-w

Eur Radiol. 2023 Apr 15. doi: 10.1007/s00330-023-09573-5. Online ahead of print.

ABSTRACT

OBJECTIVE: To develop and validate a deep learning (DL) model based on CT for differentiating bone islands and osteoblastic bone metastases.

MATERIALS AND METHODS: The patients with sclerosing bone lesions (SBLs) were retrospectively included in three hospitals. The images from site 1 were randomly assigned to the training (70%) and intrinsic verification (10%) datasets for developing the two-dimensional (2D) DL model (single-slice input) and “2.5-dimensional” (2.5D) DL model (three-slice input) and to the internal validation dataset (20%) for evaluating the performance of both models. The diagnostic performance was evaluated using the internal validation set from site 1 and additional external validation datasets from site 2 and site 3. And statistically analyze the performance of 2D and 2.5D DL models.

RESULTS: In total, 1918 SBLs in 728 patients in site 1, 122 SBLs in 71 patients in site 2, and 71 SBLs in 47 patients in site 3 were used to develop and test the 2D and 2.5D DL models. The best performance was obtained using the 2.5D DL model, which achieved an AUC of 0.996 (95% confidence interval [CI], 0.995-0.996), 0.958 (95% CI, 0.958-0.960), and 0.952 (95% CI, 0.951-0.953) and accuracies of 0.950, 0.902, and 0.863 for the internal validation set, the external validation set from site 2 and site 3, respectively.

CONCLUSION: A DL model based on a three-slice CT image input (2.5D DL model) can improve the prediction of osteoblastic bone metastases, which can facilitate clinical decision-making.

KEY POINTS: • This study investigated the value of deep learning models in identifying bone islands and osteoblastic bone metastases. • Three-slice CT image input (2.5D DL model) outweighed the 2D model in the classification of sclerosing bone lesions. • The 2.5D deep learning model showed excellent performance using the internal (AUC, 0.996) and two external (AUC, 0.958; AUC, 0.952) validation sets.

PMID:37060446 | DOI:10.1007/s00330-023-09573-5

Eur Radiol. 2023 Apr 15. doi: 10.1007/s00330-023-09641-w. Online ahead of print.

ABSTRACT

OBJECTIVES: To evaluate the prognostic value of TLR from PET/CT in patients with resection margin-negative stage IB and IIA non-small cell lung cancer (NSCLC) and compare high-risk factors necessitating adjuvant treatment (AT).

METHODS: Consecutive FDG PET/CT scans performed for the initial staging of NSCLC stage IB and IIA were retrospectively reviewed. The maximum standardized uptake value (SUVmax) of the primary tumor and mean SUV of the liver were acquired. The tumor-to-liver SUV ratio (TLR) was also calculated. Charts were reviewed for basic patient characteristics and high-risk factors for considering AT (poor differentiation, visceral pleura invasion, vascular invasion, tumors > 4 cm, and wedge resection). Statistical analysis was performed using Cox regression analysis and the Kaplan-Meier method.

RESULTS: Of the 112 patients included, 15 (13.4%) died, with a median overall survival (OS) of 43.8 months. Twenty-two patients (19.6%) exhibited recurrence, with median disease-free survival (DFS) of 36.0 months. In univariable analysis, pathology, poor differentiation, and TLR were associated with shorter DFS and OS. In multivariable analysis, TLR (hazard ratio [HR] = 1.263, p = 0.008) and differentiation (HR = 3.087, p = 0.012) were associated with shorter DFS. Also, TLR (HR = 1.422, p < 0.001) was associated with shorter OS.

CONCLUSION: TLR from FDG PET/CT was an independent prognostic factor for recurrence and survival. PET parameters constitute risk factors for consideration in the decision-making for AT in margin-negative stage IB and IIA NSCLC.

CLINICAL RELEVANCE STATEMENT: In this study, TLR from FDG PET/CT was an independent prognostic factor in stage IB-IIA non-small cell cancer patients. Although additional validation studies are warranted, TLR has the potential to be used to determine the need for adjuvant therapy.

KEY POINTS: • High TLR is an independent poor prognostic factor in stage IB-IIA NSCLC. • Adjuvant treatment should be considered in patients with high TLR following complete tumor resection.

PMID:37060445 | DOI:10.1007/s00330-023-09641-w

Target Oncol. 2023 Apr 15. doi: 10.1007/s11523-023-00961-x. Online ahead of print.

ABSTRACT

BACKGROUND: This study investigated whether schedule modification of bi-weekly nanoparticle albumin-bound paclitaxel (nab-PTX) plus ramucirumab (RAM) is efficacious against gastric cancer (GC) or gastroesophageal junction cancer (GJC).

PATIENTS AND METHODS: Patients with unresectable GC or GJC who were previously treated with fluoropyrimidine-containing regimens received nab-PTX (100 mg/m²) on days 1, 8, and 15 and RAM (8 mg/kg) on days 1 and 15 of a 28-day cycle. Based on the incidence of severe adverse events (AEs) during the first cycle, patients were modified to bi-weekly therapy from the second cycle. The primary endpoint was progression-free survival (PFS) in the bi-weekly therapy population. Based on the hypothesis that bi-weekly nab-PTX plus RAM would improve PFS from 4.5 to 7.0 months, 40 patients were required for power of 0.8 with a one-sided α of 0.05.

RESULTS: Of the 81 patients enrolled, 47 patients (58%) were assigned to bi-weekly therapy. Patient characteristics were Eastern Cooperative Oncology Group performance status of 1 (19%) and diffuse type (45%). Median PFS was 4.7 months (95% confidence interval [CI] 3.7-5.6 months) and overall response rate was 25% (95% CI 11-39%). Severe AEs of grade 3 or worse were mainly neutropenia (83%) and hypertension (23%). EQ-5D scores were maintained during the treatment. In patients who continued standard-schedule therapy, median PFS was 2.7 months (95% CI 1.8-4.0 months).

CONCLUSIONS: The primary endpoint for PFS was statistically not met, but modification of nab-PTX plus RAM to a bi-weekly schedule might be a feasible treatment option as second-line treatment for advanced GC/GJC patients, especially elderly patients, with severe AEs during the first cycle.

PMID:37060430 | DOI:10.1007/s11523-023-00961-x

Environ Sci Pollut Res Int. 2023 Apr 15. doi: 10.1007/s11356-023-26911-8. Online ahead of print.

ABSTRACT

The coordination of urbanization with the ecological environment has become a significant sustainable urban development problem given the current acceleration in China’s urbanization. The existing research lacks in-depth discussion on the coordination relationship between urbanization and energy eco-environment from the perspective of urban agglomeration. This paper takes the Yangtze River Delta Urban Agglomeration as its research area. The combination of CRITIC and entropy weight methods is used to measure the comprehensive urbanization level (CUL) from the four dimensions of population, economy, land, and society, and the SBM-Undesirable model is used to measure the energy eco-efficiency (EE). The spatiotemporal pattern and dynamic evolution law of the coupling coordination degree (CCD) between CUL and EE are analyzed using the coupling coordination model and the spatial Markov chain. The research results reveal that (1) from the comprehensive development level standpoint, both CUL and EE are on the rise from 2010 to 2021; however, a problem of unbalanced development is observed. (2) The overall CCD displays an upward trend and evinces significant spatial differentiation characteristics from the coordinated development level viewpoint. (3) The CCD transition state is not isolated to certain geographic spaces: adjacent cities will impact changes in the coupling coordination types of an urban center. Therefore, we propose strategies to improve the CCD between CUL and EE to offer theoretical and policy inferences for the formulation of sustainable urban development strategies.

PMID:37060412 | DOI:10.1007/s11356-023-26911-8

High Blood Press Cardiovasc Prev. 2023 Apr 15. doi: 10.1007/s40292-023-00574-5. Online ahead of print.

ABSTRACT

INTRODUCTION: Arterial Hypertension (HT) has been described as a common comorbidity and independent risk factor of short-term outcome in COVID-19 patients. However, data regarding the risk of new-onset HT during the post-acute phase of COVID-19 are scant.

AIM: We assess the risk of new-onset HT in COVID-19 survivors within one year from the index infection by a systematic review and meta-analysis of the available data.

METHODS: Data were obtained searching MEDLINE and Scopus for all studies published at any time up to February 11, 2023, and reporting the long-term risk of new-onset HT in COVID-19 survivors. Risk data were pooled using the Mantel-Haenszel random effects models with Hazard ratio (HR) as the effect measure with 95% confidence interval (CI). Heterogeneity among studies was assessed using I² statistic.

RESULTS: Overall, 19,293,346 patients (mean age 54.6 years, 54.6% males) were included in this analysis. Of them, 758,698 survived to COVID-19 infection. Over a mean follow-up of 6.8 months, new-onset HT occurred to 12.7 [95% CI 11.4-13.5] out of 1000 patients survived to COVID-19 infection compared to 8.17 [95% CI 7.34-8.53] out of 1000 control subjects. Pooled analysis revealed that recovered COVID-19 patients presented an increased risk of new-onset HT (HR 1.70, 95% CI 1.46-1.97, p < 0.0001, I² = 78.9%) within seven months. This risk was directly influenced by age (p = 0.001), female sex (p = 0.03) and cancer (p < 0.0001) while an indirect association was observed using the follow-up length as moderator (p < 0.0001).

CONCLUSIONS: Our findings suggest that new-onset HT represents an important post-acute COVID-19 sequelae.

PMID:37060396 | DOI:10.1007/s40292-023-00574-5

J Neurol. 2023 Apr 15. doi: 10.1007/s00415-023-11715-0. Online ahead of print.

ABSTRACT

BACKGROUND: Specific antiviral treatment is only available for a small subset of viral encephalitis (VE). Adjunctive steroids are used, but there is scant evidence evaluating its utility. We present a systematic review and meta-analysis on the outcome of steroid use in VE.

METHODS: We conducted a systematic literature review and reported it according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. Two observational studies from unpublished or partially published data were added. For the meta-analysis, we employed the metaphor package of the statistical software R-4.3.1.

RESULTS: We screened 378 studies and included 50. 155 patients were added from the Houston and Linz cohorts. Individual data were available for 281 persons, 120 (43%) of whom received steroids. The most common pathogens were herpes simplex virus 1, West Nile virus, and measles. Study designs and patient outcomes were heterogeneous. Only three of the trials report an advantage of steroid therapy. Steroid-induced side effects were scarce. Ten cohorts were included into the meta-analysis. For the pooled data, the null hypothesis could not be rejected (p = 0.245) using a random effects model, i.e., a benefit of steroid treatment on survival in VE could not be shown.

CONCLUSIONS: Steroids as potent anti-inflammatory agents may act through a reduction of secondary inflammation-mediated damage. Our data do not support the use of steroids in VE. However, multiple shortcomings apply. Standardized controlled trials are needed to investigate optimal dosing and timing of steroid administration and to explore potential subgroups that could benefit.

PMID:37060361 | DOI:10.1007/s00415-023-11715-0

Angiology. 2023 Apr 15:33197231170979. doi: 10.1177/00033197231170979. Online ahead of print.

ABSTRACT

This study compared the predictive power of the systemic immune-inflammation index (SII) and Naples prognostic score (NPS) in determining the severity of coronary artery disease (CAD). The study included 1138 patients who underwent coronary computed tomographic angiography (CCTA). The primary outcome was the evaluation of CAD severity, determined by the Coronary Artery Disease-Reporting and Data System (CAD-RADS) obtained from the CCTA scans. A basic statistical model including age, gender, chest pain, diabetes mellitus, hypertension, hyperlipidemia, and smoking was built, and categorical variables, NPS (Naples 3,4 vs 0,1,2) and SII, were added to the basic statistical model. The net benefits of the predictive parameters were determined by a decision curve analysis, and the association between CAD-RADS and NPS, SII was quantified by odds ratios (OR) and 95% confidence intervals (CI). The decision curve analysis showed that adding SII to the statistical model had a better full range of probability of clinical net benefit compared with the baseline model (OR: 5.77, 95% CI 4.15-8.02, P < .001). However, adding the NPS (P = .11) to the model did not outperform the basic statistical model. In conclusion, the SII may have a net predictive effect on top of traditional risk factors.

PMID:37060352 | DOI:10.1177/00033197231170979