Citations

Abstract Background and Aims The iBox is a validated prognostication system predicting long-term kidney allograft failure. Recently, it received regulatory endorsement by EMA, for surrogate endpoint for clinical trials. As the iBox system was primarily built using a deep phenotyped cohort, there is a need for proof of validity in extended clinical scenarios, geographic distinct medico-economic cohorts and transplant allocation systems. Method 10,851 transplant recipients were included from 17 academic medical centers from France, Belgium, Spain, Germany, Finland, United States, Brazil and Argentina. We applied to these cohorts the iBox algorithm that integrates eight independent prognostic factors including the time from transplantation to risk evaluation, functional parameters (eGFR, proteinuria), allograft histological lesions (IFTA, g+ptc, i+t, cg Banff scores), and circulating anti-HLA DSA. We stratified the performances of the iBox according to several real-life scenarios, including: 1) iBox + different eGFR formulas (MDRD186, MDRD175, CKD-Epi); 2) iBox + urinary dipstick; 3) iBox Functional + Structural (absence of DSA measurements); 4) iBox functional + Immunological (absence of histology); 5) iBox in response to treatment in T-cell mediated rejection (TCMR); 6) iBox for in response to treatment antibody mediated rejection (ABMR) clinical trials. The performances of the iBox system were assessed with the discrimination (C-index) and calibration. Results The derivation cohort included 4,000 recipients from France, and the international external validation cohort included 6,851 recipients from Europe (France, Belgium, Spain, Germany, Finland n = 4,643), the United States (n = 1,537) and South America (Brazil, Argentina n = 671). The mean recipient age was 50.26 years (14.05) with a median follow-up after evaluations of 5.41 years [IQR: 3.26 to 7]. 1336 patients (12.31%) lost their graft during the study follow-up. The performances of the iBox were confirmed in the different real-life setting with the following C-Index: 1) iBox + different eGFR formulas (MDRD186, MDRD175, CKD-Epi) 0.81; 2) iBox + urinary dipstick 0.80; 3) iBox Functional + Structural (histology) 0.80 (derivation) and 0.84 (validation); 4) iBox functional + Immunological 0.80 (derivation) and 0.83 (validation); 5) iBox in response to treatment in T-cell mediated rejection 0.81; 6) iBox for in response to treatment antibody mediated rejection trials 0.81. The score showed an accurate calibration in every scenario. Conclusion The iBoxEXTENDED trial confirms in various medico-economic settings the performances transportability and surrogacy of the iBox system, further reinforcing its use as a surrogate end point for clinical trials including TCMR and ABMR.

Abstract Background and Aims Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic kidney disease and is characterized by genetic complexity and phenotypic variability. The age of reaching kidney failure (KF) is variable and covers the complete age-spectrum. There is an unmet need for early biomarkers to differentiate between rapid and slow progressors. The PROPKD score identified hypertension before the age of 35 years as a risk factor for rapid kidney function decline. We aim to identify earlier risk factors for rapid disease progression by studying a population of ADPKD patients who reached kidney failure (KF) before the age of 40y. Method This multicentric retrospective study focusses on a unique population (n = 200) of ADPKD patients who reached KF before 40y. Kidney failure (KF) was defined as CKD5 or start of Kidney Replacement Therapy (KRT), whichever came first. Longitudinal data on childhood history, comorbidities and kidney function were collected. Life table and Proportional Hazards analysis were used to assess associations between clinical parameters and time to KF. Results Median age of ADPKD diagnosis was 22.3 (16.5 – 28.6) and median age of KF onset was 36.2 years (32.9-38.7 years). Fourty-seven patients were genotyped (23.5%) of which 38 patients (81.0%) were PKD1T and 8 (17.0%) were PKD1NTand only 1 patient (2.1%) was PKD2. Median age at first urological event was 27.0 (20.7 – 32.0) years. 71 patients (35.5%) had history of UTI's, 67 patients (33.5%) had hemorrhagic cysts on abdominal imaging, 66 patients (33.0%) presented with gross hematuria and 40 patients (25.0%) presented with kidney stones. There was a high prevalence of hypertension (N = 128, 64.0%). Four patients (N = 4/128, 3.1%) had a very early diagnosis of hypertension before the age of 10 years. Hypertension-onset before the age of 18 years correlated with a significantly faster progression (UV HR: 2.07 (1.32 – 3.25)). Conclusion This study describes a unique cohort of ADPKD patients with rapid disease progression. Hypertension at young age (<18) correlated with rapid disease progression, suggesting that ambulatory blood pressure in children might be useful to identify patients at risk for rapidly progressive ADPKD.

Glioblastoma is a highly aggressive disease with poor patient outcomes despite current treatment options, which consist of surgery, radiation, and chemotherapy. However, these strategies present challenges such as resistance development, damage to healthy tissue, and complications due to the blood–brain barrier. There is therefore a critical need for new treatment modalities that can selectively target tumor cells, minimize resistance development, and improve patient survival. Temozolomide is the current standard chemotherapeutic agent for glioblastoma, yet its use is hindered by drug resistance and severe side effects. Combination therapy using multiple drugs acting synergistically to kill cancer cells and with multiple targets can provide increased efficacy at lower drug concentrations and reduce side effects. In our previous work, we designed a therapeutic peptide (Bac-ELP1-H1) targeting the c-myc oncogene and demonstrated its ability to reduce tumor size, delay neurological deficits, and improve survival in a rat glioblastoma model. In this study, we expanded our research to the U87 glioblastoma cell line and investigated the efficacy of Bac-ELP1-H1/hyperthermia treatment, as well as the combination treatment of temozolomide and Bac-ELP1-H1, in suppressing tumor growth and extending survival in athymic mice. Our experiments revealed that the combination treatment of Bac-ELP1-H1 and temozolomide acted synergistically to enhance survival in mice and was more effective in reducing tumor progression than the single components. Additionally, our study demonstrated the effectiveness of hyperthermia in facilitating the accumulation of the Bac-ELP1-H1 protein at the tumor site. Our findings suggest that the combination of targeted c-myc inhibitory biopolymer with systemic temozolomide therapy may represent a promising alternative treatment option for glioblastoma patients.

An accurate estimate of glomerular filtration rate (eGFR) is essential for proper clinical management, especially in patients with kidney dysfunction. This prospective observational study evaluated the real-world performance of the nuclear magnetic resonance (NMR)-based GFRNMR equation, which combines creatinine, cystatin C, valine, and myo-inositol with age and sex. We compared GFRNMR performance to that of the 2021 CKD-EPI creatinine and creatinine-cystatin C equations (CKD-EPI2021Cr and CKD-EPI2021CrCys), using 115 fresh routine samples of patients scheduled for urinary iothalamate clearance measurement (mGFR). Median bias to mGFR of the three eGFR equations was comparably low, ranging from 0.4 to 2.0 mL/min/1.73 m2. GFRNMR outperformed the 2021 CKD-EPI equations in terms of precision (interquartile range to mGFR of 10.5 vs. 17.9 mL/min/1.73 m2 for GFRNMR vs. CKD-EPI2021CrCys; p = 0.01) and accuracy (P15, P20, and P30 of 66.1% vs. 48.7% [p = 0.007], 80.0% vs. 60.0% [p < 0.001] and 95.7% vs. 86.1% [p = 0.006], respectively, for GFRNMR vs. CKD-EPI2021CrCys). Clinical parameters such as etiology, comorbidities, or medications did not significantly alter the performance of the three eGFR equations. Altogether, this study confirmed the utility of GFRNMR for accurate GFR estimation, and its potential value in routine clinical practice for improved medical care.

Objective People with disabilities (PWDs) are at greater risk of COVID-19 infection, complications, and death, and experience more difficulty accessing care. We analyzed Twitter tweets to identify important topics and investigate health policies’ effects on PWDs. Methods Twitter's application programming interface was used to access its public COVID-19 stream. English-language tweets from January 2020 to January 2022 containing a combination of keywords related to COVID-19, disability, discrimination, and inequity were collected and refined to exclude duplicates, replies, and retweets. The remaining tweets were analyzed for user demographics, content, and long-term availability. Results The collection yielded 94,814 tweets from 43,296 accounts. During the observation period, 1068 (2.5%) accounts were suspended and 1088 (2.5%) accounts were deleted. Account suspension and deletion among verified users tweeting about COVID-19 and disability were 0.13% and 0.3%, respectively. Emotions were similar among active, suspended, and deleted users, with general negative and positive emotions most common followed by sadness, trust, anticipation, and anger. The overall average sentiment for the tweets was negative. Ten of the 12 topics identified (96.8%) related to pandemic effects on PWDs; “politics that rejects and leaves the disabled, elderly, and children behind” (48.3%) and “efforts to support PWDs in the COVID crisis” (31.8%) were most common. The sample of tweets by organizations (43.9%) was higher for this topic than for other COVID-19-related topics the authors have investigated. Conclusions The primary discussion addressed how pandemic politics and policies disadvantage PWDs, older adults, and children, and secondarily expressed support for these populations. The increased level of Twitter use by organizations suggests a higher level of organization and advocacy within the disability community than in other groups. Twitter may facilitate recognition of increased harm to or discrimination against specific populations such as people living with disability during national health events.

AbstractHuman lifespan continues to extend as an unprecedented number of people reach their seventh and eighth decades of life, unveiling chronic conditions that affect the older adult. Age-related skin conditions include senile purpura, seborrheic keratoses, pemphigus vulgaris, bullous pemphigoid, diabetic foot wounds and skin cancer. Current methods of drug testing prior to clinical trials require the use of pre-clinical animal models, which are often unable to adequately replicate human skin response. Therefore, a reliable model for aged human skin is needed. The current challenges in developing an aged human skin model include the intrinsic variability in skin architecture from person to person. An ideal skin model would incorporate innate functionality such as sensation, vascularization and regeneration. The advent of 3D bioprinting allows us to create human skin equivalent for use as clinical-grade surgical graft, for drug testing and other needs. In this review, we describe the process of human skin aging and outline the steps to create an aged skin model with 3D bioprinting using skin cells (i.e. keratinocytes, fibroblasts and melanocytes). We also provide an overview of current bioprinted skin models, associated limitations and direction for future research.