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Context. Oxidative products take part in various physiological processes and overproduction of oxidative products is involved in the etiology of many diseases. Objectives. We aimed to evaluate thiol-disulfide homeostasis (TDH); one of the oxidative stress parameters, in girls with premature thelarche (PT) and precocious puberty (PP). Design. This case-control study was conducted between January 2022 and July 2022. Subjects and Methods. TDH parameters, involving native thiol (NT), disulfide, and total thiol (TT), were evaluated in 39 girls with PT, 41 girls with PP and 46 healthy prepubertal girls. The correlations of luteinizing hormone (LH), follicle-stimulating hormone (FSH), estradiol (E2) levels with the TDH parameters were determined and ROC curve analysis was performed. Results. NT, TT and NT/TT ratio were higher in the PT and PP groups compared to the control group (p<0.01). Disulfide/NT ratio and disulfide/TT ratio were lower in the PT and PP groups compared to the control group (p<0.05). All the TDH values did not statistically differ between the PP and PT group (p>0.05). There was a positive correlation between LH level, FSH level, and NT level, TT level, NT/TT ratio. The best parameter to discriminate PT or PT and control groups were NT and TT (p<0.01). Conclusion. TDH is altered in girls with PT and PP. NT and TT levels can be useful to discriminate prepubertal girls with lipomastia and girls with PP and PT in clinical practice. Further studies on larger cohorts of patients are required to clarify our results. [ABSTRACT FROM AUTHOR]

An overview of recent history of Nigerian higher education chronicles periods of phenomenal expansion, economic downturn and retrenchment, monitoring of efficiency and academic standards, continued uncontrolled expansion in the absence of basic facilities, recently improved fiscal management, revival of student aid, and proposals for the opening of private universities. (Author/MSE)

Millennium development goal target on infant mortality (MDG4) by 2015 would not be realised in some low-resource countries. This was in part due to unsustainable high-tech ideas that have been poorly executed. Prudent but high impact techniques could have been synthesised in these countries. A collaborative outreach was initiated to devise frugal measures that could reduce neonatal deaths in Nigeria. Prevailing issues of concern that could militate against neonatal survival within care centres were identified and remedies were proffered. These included application of (i) recycled incubator technology (RIT) as a measure of providing affordable incubator sufficiency, (ii) facility-based research groups, (iii) elective training courses for clinicians/nurses, (iv) independent local artisans on spare parts production, (v) power-banking and apnoea-monitoring schemes, and (v) 1/2 yearly failure-preventive maintenance and auditing system. Through a retrospective data analyses 4 outreach centres and one “control” were assessed. Average neonatal mortality of centres reduced from 254/1000 to 114/1000 whilst control remained at 250/1000. There was higher relative influx of incubator-dependent-neonates at outreach centres. It was found that 43% of mortality occurred within 48 hours of presentation (d48) and up to 92% of d48 were of very-low birth parameters. The RIT and associated concerns remedies have demonstrated the vital signs of efficiency that would have guaranteed MDG4 neonatal component in Nigeria.

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Purpose: Rectal spacers have gained popularity as a dose-sparing material for prostate cancer radiation therapy (RT). However, the procedure can be associated with unintended rectal wall infiltration (RWI) of the spacer gel. We therefore classified RWI severity as a function of depth and explored its association with rectal toxicity using a data set from prostate cancer patients treated with RT on a prospective randomized clinical trial (RCT)., Methods and Materials: Postimplant T2-weighted magnetic resonance images of 149 subjects randomized to the hydrogel spacer arm of a published multicenter RCT were assessed for the presence and depth of RWI. All implants were assigned a score of 0 (no rectal wall signal changes), 1 (rectal wall edema/signal change), 2 (partial RWI), or 3 (full-thickness RWI); RWI was defined as a score of 2 or 3. Correlations were made between RWI score and physician-reported procedure, acute, and late rectal toxicity., Results: Although 62.4% of implants had no rectal wall signal abnormalities, 24% [scores of 2 (20.1%) and 3 (4.0%)] of procedures exhibited radiographic evidence of RWI. Full-thickness RWI was associated with both a longer length (22.8 ± 7.0 mm, P = .008) and a larger circumferential percentage (35.8% ± 9.2%, P = .045) of rectal infiltration. Although 7 subjects (5%) experienced transient procedure-related rectal toxicities (most commonly perineal/rectal pain), only one had RWI (score of 2, National Cancer Institute's Common Terminology Criteria for Adverse Events grade 1). Consequently, no correlation was observed between procedural rectal toxicity and the presence/extent of RWI ( P = .64). Similarly, no difference in acute ( P = .64) or late ( P = .85) rectal toxicity incidence or grade was detected between RWI categories; none of the 6 men with a RWI score of 3 developed late rectal toxicity by 15 months., Conclusions: Based on data from an RCT, RWI did not contribute to increased rectal toxicity prior and up to 15 months after conventional prostate cancer RT., (© 2024 The Authors.)

Introduction: Most studies on body composition in kidney cancer have been conducted among patients with metastatic disease. Given that aggressive tumours can adversely impact body composition and even non-metastatic tumours can be aggressive, we evaluated associations between pre-surgical body composition features and tumour pathological features in patients with non-metastatic clear cell renal cell cancer (ccRCC)., Methods: The Resolve Cohort consists of 1239 patients with non-metastatic ccRCC who underwent nephrectomy at Memorial Sloan Kettering Cancer Center between 2000 and 2020. The cross-sectional areas and radiodensities of skeletal muscle, visceral adipose, and subcutaneous adipose tissues were determined from pre-surgical computed tomography (CT) scans at the third lumbar vertebrae using Automatica software. Pearson's correlation coefficients describe inter-relationships among BMI and body composition variables, while odds ratios (OR) and 95% confidence intervals (CI) estimate associations between continuous body composition features (per 1-standard deviation) and advanced stage (Stage III vs. Stages I-II) and high Fuhrman grade (Grades 3-4 vs. 1-2) from multivariable logistic regression models that considered the potential impact of biological sex, contrast enhanced CTs, and early age at onset of ccRCC., Results: The cohort was predominantly male (69%), white (89%), and had a median age of 58. The proportion of patients presenting with advanced stage and high-grade disease were 31% and 51%, respectively. In models that adjusted for demographics and all body composition variables simultaneously, decreasing skeletal muscle radiodensity (i.e., more fat infiltration) but increasing visceral adipose tissue radiodensity (i.e., more lipid depletion) were associated with advanced tumour features. Per 8.4 HU decrease in skeletal muscle radiodensity, the odds of presenting with advanced stage was 1.61 (95% CI: 1.34-1.93). Per 7.22 HU increase in visceral adipose tissue radiodensity, the odds of presenting with advanced stage was 1.45 (95% CI: 1.22-1.74). Skeletal muscle index (i.e., sarcopenia) was not associated with either tumour feature. Similar associations were observed for Fuhrman grade, a more direct marker of tumour aggressiveness. Associations did not differ by sex, contrast use, or age at onset of ccRCC., Conclusions: Lipid infiltrated skeletal muscle, but lipid depleted visceral adipose tissue were independently associated with advanced tumour features in non-metastatic ccRCC. Findings highlight the importance of evaluating the full range of body composition features simultaneously in multivariable models. Interpreting pre-surgical CTs for body composition for patients may be a novel and non-invasive way to identify patients with aggressive renal tumours, which is clinically relevant as renal biopsies are not routinely performed., (© 2024 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by Wiley Periodicals LLC.)

Context: Oxidative products take part in various physiological processes and overproduction of oxidative products is involved in the etiology of many diseases., Objectives: We aimed to evaluate thiol-disulfide homeostasis (TDH); one of the oxidative stress parameters, in girls with premature thelarche (PT) and precocious puberty (PP)., Design: This case-control study was conducted between January 2022 and July 2022., Subjects and Methods: TDH parameters, involving native thiol (NT), disulfide, and total thiol (TT), were evaluated in 39 girls with PT, 41 girls with PP and 46 healthy prepubertal girls. The correlations of luteinizing hormone (LH), follicle-stimulating hormone (FSH), estradiol (E2) levels with the TDH parameters were determined and ROC curve analysis was performed., Results: NT, TT and NT/TT ratio were higher in the PT and PP groups compared to the control group (p<0.01). Disulfide/NT ratio and disulfide/TT ratio were lower in the PT and PP groups compared to the control group (p<0.05). All the TDH values did not statistically differ between the PP and PT group (p>0.05). There was a positive correlation between LH level, FSH level, and NT level, TT level, NT/TT ratio. The best parameter to discriminate PT or PT and control groups were NT and TT (p<0.01)., Conclusion: TDH is altered in girls with PT and PP. NT and TT levels can be useful to discriminate prepubertal girls with lipomastia and girls with PP and PT in clinical practice. Further studies on larger cohorts of patients are required to clarify our results., Competing Interests: The authors declare that they have no conflict of interest., (©2024 Acta Endocrinologica (Buc).)

This review focuses on the principles, applications, and performance of mpMRI for bladder imaging. Quantitative imaging biomarkers (QIBs) derived from mpMRI are increasingly used in oncological applications, including tumor staging, prognosis, and assessment of treatment response. To standardize mpMRI acquisition and interpretation, an expert panel developed the Vesical Imaging-Reporting and Data System (VI-RADS). Many studies confirm the standardization and high degree of inter-reader agreement to discriminate muscle invasiveness in bladder cancer, supporting VI-RADS implementation in routine clinical practice. The standard MRI sequences for VI-RADS scoring are anatomical imaging, including T 2 w images, and physiological imaging with diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI). Physiological QIBs derived from analysis of DW- and DCE-MRI data and radiomic image features extracted from mpMRI images play an important role in bladder cancer. The current development of AI tools for analyzing mpMRI data and their potential impact on bladder imaging are surveyed. AI architectures are often implemented based on convolutional neural networks (CNNs), focusing on narrow/specific tasks. The application of AI can substantially impact bladder imaging clinical workflows; for example, manual tumor segmentation, which demands high time commitment and has inter-reader variability, can be replaced by an autosegmentation tool. The use of mpMRI and AI is projected to drive the field toward the personalized management of bladder cancer patients.

There is a need to develop user-friendly imaging tools estimating robust quantitative biomarkers (QIBs) from multiparametric (mp)MRI for clinical applications in oncology. Quantitative metrics derived from (mp)MRI can monitor and predict early responses to treatment, often prior to anatomical changes. We have developed a vendor-agnostic, flexible, and user-friendly MATLAB-based toolkit, MRI-Quantitative Analysis and Multiparametric Evaluation Routines ("MRI-QAMPER", current release v3.0), for the estimation of quantitative metrics from dynamic contrast-enhanced (DCE) and multi-b value diffusion-weighted (DW) MR and MR relaxometry. MRI-QAMPER's functionality includes generating numerical parametric maps from these methods reflecting tumor permeability, cellularity, and tissue morphology. MRI-QAMPER routines were validated using digital reference objects (DROs) for DCE and DW MRI, serving as initial approval stages in the National Cancer Institute Quantitative Imaging Network (NCI/QIN) software benchmark. MRI-QAMPER has participated in DCE and DW MRI Collaborative Challenge Projects (CCPs), which are key technical stages in the NCI/QIN benchmark. In a DCE CCP, QAMPER presented the best repeatability coefficient (RC = 0.56) across test-retest brain metastasis data, out of ten participating DCE software packages. In a DW CCP, QAMPER ranked among the top five (out of fourteen) tools with the highest area under the curve (AUC) for prostate cancer detection. This platform can seamlessly process mpMRI data from brain, head and neck, thyroid, prostate, pancreas, and bladder cancer. MRI-QAMPER prospectively analyzes dose de-escalation trial data for oropharyngeal cancer, which has earned it advanced NCI/QIN approval for expanded usage and applications in wider clinical trials.

Cancer care increasingly relies on imaging for patient management. The two most common cross-sectional imaging modalities in oncology are computed tomography (CT) and magnetic resonance imaging (MRI), which provide high-resolution anatomic and physiological imaging. Herewith is a summary of recent applications of rapidly advancing artificial intelligence (AI) in CT and MRI oncological imaging that addresses the benefits and challenges of the resultant opportunities with examples. Major challenges remain, such as how best to integrate AI developments into clinical radiology practice, the vigorous assessment of quantitative CT and MR imaging data accuracy, and reliability for clinical utility and research integrity in oncology. Such challenges necessitate an evaluation of the robustness of imaging biomarkers to be included in AI developments, a culture of data sharing, and the cooperation of knowledgeable academics with vendor scientists and companies operating in radiology and oncology fields. Herein, we will illustrate a few challenges and solutions of these efforts using novel methods for synthesizing different contrast modality images, auto-segmentation, and image reconstruction with examples from lung CT as well as abdome, pelvis, and head and neck MRI. The imaging community must embrace the need for quantitative CT and MRI metrics beyond lesion size measurement. AI methods for the extraction and longitudinal tracking of imaging metrics from registered lesions and understanding the tumor environment will be invaluable for interpreting disease status and treatment efficacy. This is an exciting time to work together to move the imaging field forward with narrow AI-specific tasks. New AI developments using CT and MRI datasets will be used to improve the personalized management of cancer patients.

Early intervention in kidney cancer helps to improve survival rates. Abdominal computed tomography (CT) is often used to diagnose renal masses. In clinical practice, the manual segmentation and quantification of organs and tumors are expensive and time-consuming. Artificial intelligence (AI) has shown a significant advantage in assisting cancer diagnosis. To reduce the workload of manual segmentation and avoid unnecessary biopsies or surgeries, in this paper, we propose a novel end-to-end AI-driven automatic kidney and renal mass diagnosis framework to identify the abnormal areas of the kidney and diagnose the histological subtypes of renal cell carcinoma (RCC). The proposed framework first segments the kidney and renal mass regions by a 3D deep learning architecture (Res-UNet), followed by a dual-path classification network utilizing local and global features for the subtype prediction of the most common RCCs: clear cell, chromophobe, oncocytoma, papillary, and other RCC subtypes. To improve the robustness of the proposed framework on the dataset collected from various institutions, a weakly supervised learning schema is proposed to leverage the domain gap between various vendors via very few CT slice annotations. Our proposed diagnosis system can accurately segment the kidney and renal mass regions and predict tumor subtypes, outperforming existing methods on the KiTs19 dataset. Furthermore, cross-dataset validation results demonstrate the robustness of datasets collected from different institutions trained via the weakly supervised learning schema.

Background: Although there are studies evaluating the psychological adjustment of healthy children when their siblings have type 1 diabetes mellitus (T1DM), no study evaluating their nutritional status exists. Thus, this study aimed to determine the nutritional status of children with T1DM and their healthy siblings., Material and Methods: Data from a control group, healthy siblings, and patients who were followed and treated for T1D in the Paediatric Gastroenterology and Paediatric Endocrinology outpatient clinics of the Health Sciences University Gülhane Medical Faculty between November 2019 and November 2020 were analysed and compared. The groups were compared in terms of nutritional characteristics, daily macro and micronutrient intakes and classified according to their body mass index (BMI) Z-scores., Results: The study population consisted of 29 children with T1DM (51.7% female, 48.3% male; age: 11.00 ±3.66 years), 36 healthy siblings of children with T1D (50% female, 50% male; age: 9.61 ±4.84 years), and a control group of 58 healthy children (51.7% female, 48.3% male; age: 10.68 ±3.01years).The BMI Z-score of 28.6%of healthy siblings and 25% of children with T1D was > 1 SD or overweight. All of the control group children were of normal weight. None of the children were obese; however, the overweight rate was significantly higher in the healthy siblings and diabetes groups compared to the control group (p = 0.012). Daily energy intake (%) was significantly higher in the control group than in the healthy siblings (p < 0.001)., Conclusions: A quarter of the children with T1D over five years of age were overweight. In addition, healthy siblings were found to have higher BMI Z-scores than controls. This is the first study to evaluate the nutritional status of siblings of patients with T1D and will hopefully lead to more comprehensive studies that will also assess their daily exercise and physical activity.

Medical imaging data annotation is expensive and time-consuming. Supervised deep learning approaches may encounter overfitting if trained with limited medical data, and further affect the robustness of computer-aided diagnosis (CAD) on CT scans collected by various scanner vendors. Additionally, the high false-positive rate in automatic lung nodule detection methods prevents their applications in daily clinical routine diagnosis. To tackle these issues, we first introduce a novel self-learning schema to train a pre-trained model by learning rich feature representatives from large-scale unlabeled data without extra annotation, which guarantees a consistent detection performance over novel datasets. Then, a 3D feature pyramid network ( 3DFPN ) is proposed for high-sensitivity nodule detection by extracting multi-scale features, where the weights of the backbone network are initialized by the pre-trained model and then fine-tuned in a supervised manner. Further, a High Sensitivity and Specificity ( HS 2 ) network is proposed to reduce false positives by tracking the appearance changes among continuous CT slices on Location History Images (LHI) for the detected nodule candidates. The proposed method's performance and robustness are evaluated on several publicly available datasets, including LUNA16, SPIE-AAPM, LungTIME, and HMS. Our proposed detector achieves the state-of-the-art result of 90.6 % sensitivity at 1 / 8 false positive per scan on the LUNA16 dataset. The proposed framework's generalizability has been evaluated on three additional datasets (i.e., SPIE-AAPM, LungTIME, and HMS) captured by different types of CT scanners., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2022 Liu, Cao, Akin and Tian.)

Purpose: High body mass index (BMI) may lead to improved immune-checkpoint blockade (ICB) outcomes in metastatic clear cell renal cell carcinoma (mccRCC). However, BMI is a crude body size measure. We investigated BMI and radiographically assessed body composition (BC) parameters association with mccRCC ICB outcomes., Experimental Design: Retrospective study of ICB-treated patients with mccRCC. BMI and BC variables [skeletal muscle index (SMI) and multiple adiposity indexes] were determined using pretreatment CT scans. We examined the associations between BMI and BC variables with ICB outcomes. Therapeutic responses per RECIST v1.1 were determined. We compared whole-transcriptomic patterns with BC variables in a separate cohort of 62 primary tumor samples., Results: 205 patients with mccRCC were included in the cohort (74% were male, 71% were overweight/obese, and 53% were classified as low SMI). High-BMI patients experienced longer overall survival (OS) than normal-weight patients [unadjusted HR, 0.66; 95% confidence interval (CI), 0.45-0.97; P = 0.035]. The only BC variable associated with OS was SMI [unadjusted HR comparing low vs. high SMI 1.65 (95% CI: 1.13-2.43); P = 0.009]. However, this OS association became nonsignificant after adjusting for International Metastatic Renal Cell Carcinoma Database Consortium score and line of therapy. No OS association was seen for adiposity and no BC variable was associated with progression-free survival or radiological responses. Tumors from patients with low SMI displayed increased angiogenic, inflammatory, and myeloid signals., Conclusions: Our findings highlight the relevance of skeletal muscle in the BMI paradox. Future studies should investigate if addressing low skeletal muscle in metastatic patients treated with ICB can improve survival., (©2022 American Association for Cancer Research.)