Background Cytomegalovirus (CMV) infection remains a significant problem in kidney transplantation despite advances in screening, monitoring, therapeutics, and management. Although universal prophylaxis with antiviral therapy has significantly reduced the risk of early CMV infection and disease, late-onset CMV is still common and can be difficult to clinically manage in high-risk patients. A recent systematic review showed that with antiviral prophylaxis, early CMV infection occurred in only 6% of kidney recipients, and late infection occurred in more than one in six patients. The two antiviral prophylaxis medications this study is comparing, valganciclovir (VGC) and maribavir, are highly effective at preventing CMV infection. In studies using valganciclovir, the reported occurrence of leukopenia is 20%-40%, and neutropenia is 10%-30%. In studies using maribavir, the reported occurrence of neutropenia was 4%-5% versus 15%-18% in valganciclovir patients. With appropriate dosing, maribavir appears to have similar efficacy to valganciclovir in treating current and preventing future CMV infection with a significantly reduced rate of neutropenia. Methods Maribavir IIR is a 12-month, single-center, open-label, randomized controlled trial enrolling 70 patients (35 in each arm) examining the difference in preventing CMV infection while specifically assessing the tolerability of the two antiviral prophylactic medications. The trial is currently in the follow-up phase, with the first patient enrolled in November 2023 and enrollment concluding in June 2024. Discussion The primary objective of this study is to assess the tolerability of maribavir versus valganciclovir (VGC) prophylaxis in adult kidney transplant recipients at high risk of CMV infection (D+/R- or thymo use if R+). This was done by assessing the incidence of leukopenia in the two arms, the occurrence of CMV infection despite prophylaxis, the impact of these medications on healthcare utilization and costs, and any outcome differences associated with race and sex. In this preliminary report, we describe the study design, methods, aims, and outcome measures that will be utilized in the ongoing Maribavir IIR clinical trial. Trial registration The trial is registered at ClinicalTrials.gov NCT06034925: https://www.clinicaltrials.gov/study/NCT06034925.

Aim Kidney transplant recipients (KTRs), due to their immunosuppressed status, are potentially more susceptible to both the severe effects of COVID-19 and complications in their transplanted organ. The aim of this study is to investigate whether COVID-19 infection increases the risk of rejection in kidney transplant recipients (KTRs). Methods This study involved a detailed literature review, conducted using PubMed, with the search being completed by September 7th, 2023. The search strategy incorporated a combination of relevant keywords: 'COVID', 'Renal', 'Kidney', 'Transplant', and 'Rejection'. The results from controlled and uncontrolled studies were separately collated and analyzed. Results A total of 11 studies were identified, encompassing 1,179 patients. Among these, two controlled studies reported the incidence of rejection in KTRs infected with COVID-19. Pooling data from these studies revealed no significant statistical correlation between COVID-19 infection and biopsy-proven rejection (p = 0.26). In addition, nine non-controlled studies were found, with rejection incidences ranging from 0% to 66.7%. The majority of these studies (eight out of nine) had small sample sizes, ranging from 3 to 75 KTRs, while the largest included 372 KTRs. The combined rejection rate across these studies was calculated to be 11.8%. Conclusion In conclusion, the limited number of published controlled studies revealed no statistically significant association between COVID-19 infection and biopsy-proven rejection among KTRs. However, the broader analysis of non-controlled studies showed a variable rejection incidence with a pooled rejection rate of 11.8%. There is insufficient high-quality data to explore the association of COVID-19 infection and rejection.

The high noise level of dynamic Positron Emission Tomography (PET) images degrades the quality of parametric images. In this study, we aim to improve the quality and quantitative accuracy of Ki images by utilizing deep learning techniques to reduce the noise in dynamic PET images. We propose a novel denoising technique, Population-based Deep Image Prior (PDIP), which integrates population-based prior information into the optimization process of Deep Image Prior (DIP). Specifically, the population-based prior image is generated from a supervised denoising model that is trained on a prompts-matched static PET dataset comprising 100 clinical studies. The 3D U-Net architecture is employed for both the supervised model and the following DIP optimization process. We evaluated the efficacy of PDIP for noise reduction in 25%-count and 100%-count dynamic PET images from 23 patients by comparing with two other baseline techniques: the Prompts-matched Supervised model (PS) and a conditional DIP (CDIP) model that employs the mean static PET image as the prior. Both the PS and CDIP models show effective noise reduction but result in smoothing and removal of small lesions. In addition, the utilization of a single static image as the prior in the CDIP model also introduces a similar tracer distribution to the denoised dynamic frames, leading to lower Ki in general as well as incorrect Ki in the descending aorta. By contrast, as the proposed PDIP model utilizes intrinsic image features from the dynamic dataset and a large clinical static dataset, it not only achieves comparable noise reduction as the supervised and CDIP models but also improves lesion Ki predictions.

Vaccination against Coronavirus disease-19 (COVID-19) was pivotal to limit spread, morbidity and mortality. Our aim is to find out whether vaccines against COVID-19 lead to an immunological response stimulating the production of de novo donor specific antibodies (DSAs) or increase in mean fluorescence intensity (MFI) of pre-existing DSAs in kidney transplant recipients (KTRs). This study involved a detailed literature search through December 2nd, 2023 using PubMed as the primary database. The search strategy incorporated a combination of relevant Medical Subject Headings terms and keywords: "COVID-19", "SARS-CoV-2 Vaccination", "Kidney, Renal Transplant", and "Donor specific antibodies". The results from related studies were collated and analyzed. A total of 6 studies were identified, encompassing 460 KTRs vaccinated against COVID-19. Immunological responses were detected in 8 KTRs of which 5 had increased MFIs, 1 had de novo DSA, and 2 were categorized as either having de novo DSA or increased MFI. There were 48 KTRs with pre-existing DSAs prior to vaccination, but one study (Massa et al ) did not report whether pre-existing DSAs were associated with post vaccination outcomes. Of the remaining 5 studies, 35 KTRs with pre-existing DSAs were identified of which 7 KTRs (20%) developed de novo DSAs or increased MFIs. Overall, no immunological response was detected in 452 (98.3%) KTRs. Our study affirms prior reports that COVID-19 vaccination is safe for KTRs, especially if there are no pre-existing DSAs. However, if KTRs have pre-existing DSAs, then an increased immunological risk may be present. These findings need to be taken cautiously as they are based on a limited number of patients so further studies are still needed for confirmation.

We present a sequential transfer learning framework for transformers on functional Magnetic Resonance Imaging (fMRI) data and demonstrate its significant benefits for decoding musical timbre. In the first of two phases, we pre-train our stacked-encoder transformer architecture on Next Thought Prediction, a self-supervised task of predicting whether or not one sequence of fMRI data follows another. This phase imparts a general understanding of the temporal and spatial dynamics of neural activity, and can be applied to any fMRI dataset. In the second phase, we fine-tune the pre-trained models and train additional fresh models on the supervised task of predicting whether or not two sequences of fMRI data were recorded while listening to the same musical timbre. The fine-tuned models achieve significantly higher accuracy with shorter training times than the fresh models, demonstrating the efficacy of our framework for facilitating transfer learning on fMRI data. Additionally, our fine-tuning task achieves a level of classification granularity beyond standard methods. This work contributes to the growing literature on transformer architectures for sequential transfer learning on fMRI data, and provides evidence that our framework is an improvement over current methods for decoding timbre.

The influence of converting to once daily, extended‐release LCP‐Tacrolimus (Tac) for those with high tacrolimus variability in kidney transplant recipients (KTRs) is not well‐studied.

The management of failing kidney allograft and transition of care to general nephrologists (GN) remain a complex process. The Kidney Pancreas Community of Practice (KPCOP) Failing Allograft Workgroup designed and distributed a survey to GN between May and September 2021. Participants were invited via mail and email invitations. There were 103 respondents with primarily adult nephrology practices, of whom 41% had an academic affiliation. More than 60% reported listing for a second kidney as the most important concern in caring for patients with a failing allograft, followed by immunosuppression management (46%) and risk of mortality (38%), while resistant anemia was considered less of a concern. For the initial approach to immunosuppression reduction, 60% stop antimetabolites first, and 26% defer to the transplant nephrologist. Communicating with transplant centers about immunosuppression cessation was reported to occur always by 60%, and sometimes by 29%, while 12% reported making the decision independently. Nephrologists with academic appointments communicate with transplant providers more than private nephrologists (74% vs. 49%, p = 0.015). There are heterogeneous approaches to the care of patients with a failing allograft. Efforts to strengthen transitions of care and to develop practical practice guidelines are needed to improve the outcomes of this vulnerable population.

BACKGROUND: African Americans (AAs) have reduced access to kidney transplant (KTX). Our center undertook a multilevel quality improvement endeavor to address KTX access barriers, focused on vulnerable populations. This program included dialysis center patient/staff education, embedding telehealth services across South Carolina, partnering with community providers to facilitate testing/procedures, and increased use of high-risk donors.STUDY DESIGN: This was a time series analysis from 2017 to 2021 using autoregression to assess trends in equitable access to KTX for AAs. Equity was measured using a modified version of the Kidney Transplant Equity Index (KTEI), defined as the proportion of AAs in South Carolina with end-stage kidney disease (ESKD) vs the proportion of AAs initiating evaluation, completing evaluation, waitlisting, and undergoing KTX. A KTEI of 1.00 is considered complete equity; a KTEI of < 1.00 is indicative of disparity.RESULTS: From January 2017 to September 2021, 11,487 ESKD patients (64.7% AA) were referred, 6,748 initiated an evaluation (62.8% AA), 4,109 completed evaluation (59.7% AA), 2,762 were wait listed (60.0% AA), and 1,229 underwent KTX (55.3% AA). The KTEI for KTX demonstrated significant improvements in equity. The KTEI for initiated evaluations was 0.89 in 2017, improving to 1.00 in 2021 (p = 0.0045). Completed evaluation KTEI improved from 0.85 to 0.95 (p = 0.0230), while waitlist addition KTEI improved from 0.83 to 0.96 (p = 0.0072). The KTEI for KTX also improved from 0.76 to 0.91, which did not reach statistical significance (p = 0.0657).CONCLUSIONS: A multilevel intervention focused on improving access to vulnerable populations was significantly associated with reduced disparities for AAs.

Stimulus decoding of functional Magnetic Resonance Imaging (fMRI) data with machine learning models has provided new insights about neural representational spaces and task-related dynamics. However, the scarcity of labelled (task-related) fMRI data is a persistent obstacle, resulting in model-underfitting and poor generalization. In this work, we mitigated data poverty by extending a recent pattern-encoding strategy from the visual memory domain to our own domain of auditory pitch tasks, which to our knowledge had not been done. Specifically, extracting preliminary information about participants' neural activation dynamics from the unlabelled fMRI data resulted in improved downstream classifier performance when decoding heard and imagined pitch. Our results demonstrate the benefits of leveraging unlabelled fMRI data against data poverty for decoding pitch based tasks, and yields novel significant evidence for both separate and overlapping pathways of heard and imagined pitch processing, deepening our understanding of auditory cognitive neuroscience.

Outcomes analyzing conversion from IR‐tacrolimus (IR) to LCP‐tacrolimus (LCP) in obesity are limited. This was a retrospective longitudinal cohort study of patients converted from IR to LCP from June 2019 to October 2020. Primary outcomes were conversion ratios for weight‐based dose at a steady‐state therapeutic level and identification of appropriate dosing weight. Other outcomes included tacrolimus coefficient of variation (CV), time in therapeutic range (TITR), adverse events, infections, donor specific antibodies (DSAs), and acute rejection. A total of 292 patients were included; 156 and 136 patients with a BMI < 30 and BMI ≥ 30 kg/m2, respectively. Baseline characteristics were similar, except for pancreas transplant, diabetes, and HLA mismatch. IR to LCP conversion ratio ranged from .73 to .79. Mean LCP dose was similar (.08 vs. .07 mg/kg/day for BMI < 30 and BMI ≥ 30 kg/m2, respectively); there was a significant difference in IR and LCP mg/kg dosing at steady state with TBW (.11 mg/kg vs.09 mg/kg and .08 mg/kg vs. .06 mg/kg, respectively). The most appropriate dosing weight was adjusted body weight (AdjBW), consistent across IR and LCP steady‐state doses, and might yield more accurate steady‐state dosing requirements. In multivariable modeling, BMI was a significant predictor of steady state mg/kg dosing at therapeutic goal for total body weight (TBW), but not ideal body weight (IBW) or AdjBW.

Breathing can cause blurring and artifacts in PET images, especially in the body trunk region. The blurring and artifacts can negatively impact cancer detection and response to therapy assessment. Many motion detection techniques, such as using external motion sensors or data driving methods, have been used to facilitate respiratory motion correction for PET. These methods require sophisticated gating or motion compensated image reconstruction, which are time consuming. In our work, we propose a deep learning framework based on U-Net to directly perform respiratory motion correction for whole-body PET in the image domain. Our framework was trained with the patches of the PET images without motion correction as input and the motion-corrected images using the data-driving gating (DDG) method as label. The framework also incorporated spatial information of voxels by adding additional layer of voxels’ vertical locations to the input. To evaluate our framework, we conducted 5-fold cross validations to generate the motion-corrected images for 30 subjects and compared them with the ground truth images corrected by the DDG methods. Our framework could correct the PET images in regions affected by respiratory motion. The incorporation of voxels’ spatial information could further improve the performance of motion correction. There is a great potential of our framework to perform direct respiratory motion correction in the image domain in a convenient manner.

A diagram is described which demonstrates important aspects of the exit velocity triangle of a radial compressor impeller with no inlet swirl. Although this diagram is based on work dating back to 1941, it is not widely known in the radial compressor community. It aids the selection of the exit velocity triangle for impellers and gives significant insight into impeller-diffuser matching. It can be used to analyze performance maps from both experimental and computational fluid dynamics (CFD) studies. Important aspects made clear in the diagram are as follows: The degree of reaction and the de Haller number of the impeller are both determined primarily by the work coefficient, and both decrease as the work coefficient increases; the degree of reaction is also affected by the exit flow coefficient, and for typical backswept impeller designs, it remains nearly constant at off-design flow conditions; the inlet and exit velocity triangles can be shown in the same diagram to visualize the deceleration of the relative velocity along the casing streamline and of the meridional velocity across an impeller, together with the acceleration of the relative flow on the hub streamline; the slope of the impeller gas path work coefficient versus exit flow coefficient at off-design conditions can be added to the diagram and this provides a new approach to estimate the mean slip factor from a measured or calculated compressor performance map; the diagram can be used as a useful template to compare different impeller design styles and to explain why different impellers are needed for use with vaned and vaneless diffusers; and the absolute velocity at the diffuser inlet of a backswept impeller increases with a decrease in flowrate along the operating line, which is an important aid to compressor stability.

ObjectivesLCP tac has a recommended starting dose of 0.14 mg/kg/day in kidney transplant. The goal of this study was to assess the influence of CYP3A5 on perioperative LCP tac dosing and monitoring. MethodsThis was a prospective observational cohort study of adult kidney recipients receiving de-novo LCP tac. CYP3A5 genotype was measured and 90-day pharmacokinetic and clinical were assessed. Patients were classified as CYP3A5 expressors (*1 homozygous or heterozygous) or nonexpressors (LOF *3/*6/*7 allele). ResultsIn this study, 120 were screened, 90 were contacted and 52 provided consent; 50 had genotype results, and 22 patients expressed CYP3A5*1. African Americans (AA) comprised 37.5% of nonexpressors versus 81.8% of expressors (P = 0.001). Initial LCP tac dose was similar between CYP3A5 groups (0.145 vs. 0.137 mg/kg/day; P = 0.161), whereas steady state dose was higher in expressors (0.150 vs. 0.117 mg/kg/day; P = 0.026). CYP3A5*1 expressors had significantly more tac trough concentrations of less than 6 ng/ml and significantly fewer tac trough concentrations of more than 14 ng/ml. Providers were significantly more likely to under-adjust LCP tac by 10 and 20% in CYP3A5 expressors versus nonexpressors (P < 0.03). In sequential modeling, CYP3A5 genotype status explained the LCP tac dosing requirements significantly more than AA race. ConclusionCYP3A5*1 expressors require higher doses of LCP tac to achieve therapeutic concentrations and are at higher risk of subtherapeutic trough concentrations, persisting for 30-day posttransplant. LCP tac dose changes in CYP3A5 expressors are more likely to be under-adjusted by providers.

Background: Static [18F]FDG-PET/CT is the imaging method of choice for the evaluation of indeterminate lung lesions and NSCLC staging; however, histological confirmation of PET-positive lesions is needed in most cases due to its limited specificity. Therefore, we aimed to evaluate the diagnostic performance of additional dynamic whole-body PET. Methods: A total of 34 consecutive patients with indeterminate pulmonary lesions were enrolled in this prospective trial. All patients underwent static (60 min p.i.) and dynamic (0–60 min p.i.) whole-body [18F]FDG-PET/CT (300 MBq) using the multi-bed-multi-timepoint technique (Siemens mCT FlowMotion). Histology and follow-up served as ground truth. Kinetic modeling factors were calculated using a two-compartment linear Patlak model (FDG influx rate constant = Ki, metabolic rate = MR-FDG, distribution volume = DV-FDG) and compared to SUV using ROC analysis. Results: MR-FDGmean provided the best discriminatory power between benign and malignant lung lesions with an AUC of 0.887. The AUC of DV-FDGmean (0.818) and SUVmean (0.827) was non-significantly lower. For LNM, the AUCs for MR-FDGmean (0.987) and SUVmean (0.993) were comparable. Moreover, the DV-FDGmean in liver metastases was three times higher than in bone or lung metastases. Conclusions: Metabolic rate quantification was shown to be a reliable method to detect malignant lung tumors, LNM, and distant metastases at least as accurately as the established SUV or dual-time-point PET scans.

In this work we introduce a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

This chapter will discuss the current knowledge about the use of music-based interventions (music therapy and music medicine) for adults and children with epilepsy. We review the epidemiology of epilepsy and discuss possible mechanisms for the effects of music on clinical seizures and electroencephalographic activity, including theories regarding the "Mozart effect". We discuss the specific effects of Mozart's music on interictal and ictal activity, then outline key future research directions to improve our understanding of how music can help individuals with epilepsy. The contents of this chapter reveal limitations to past research while encouraging the investigation of music-based neuromodulation as an adjunctive intervention for epilepsy.

Diabetes (DM) is a common comorbidity in transplant patients with known effects on gastrointestinal (GI) motility and absorption; however, DM's impact on immediate release (IR) tacrolimus to LCP-tacrolimus (LCP) conversion ratios has not been studied. This multivariable analysis of a retrospective longitudinal cohort study included kidney transplant recipients converted from IR to LCP between 2019 and 2020. The primary outcome was IR to LCP conversion ratio based on DM status. Other outcomes included tacrolimus variability, rejection, graft loss, and death. Of the 292 patients included, 172 patients had DM and 120 did not. The IR:LCP conversion ratio was significantly higher with DM (67.5% +/- 21.1% no DM vs. 79.8% +/- 28.7% in DM; P < .001). In multivariable modeling, DM was the only variable significantly and independently associated with IR:LCP conversion ratios. No difference was observed in rejection rates. Graft (97.5% no DM vs. 92.4% in DM; P = .062) and patient survival (100% no DM vs. 94.8% in DM; P = .011) were lower with DM. The presence of DM significantly increased the IR:LCP conversion ratio by 13%-14%, compared to patients without DM. On multivariable analysis, DM was the only significant predictor of conversion ratios, potentially related to GI motility or absorption differences.