Approach to Kidney Allograft Dysfunction: A Brief Review.

It is important for providers caring for kidney transplant recipients to be familiar with the common causes of allograft dysfunction. Early detection of allograft dysfunction leads to timely management, with the goal of preventing or delaying progression to allograft failure. Although transplant rejection is always a concern, the differential diagnoses for allograft dysfunction are broad and include perioperative complications, infections, recurrent disease, and calcineurin nephrotoxicity. In this review, we will go over early and late causes of allograft dysfunction and discuss the basic workup and principles of management for each condition.

Reproductive Health in Kidney Transplant Recipients.

Increasing number of women with kidney transplants are of reproductive age and desire successful pregnancies. Successful outcomes of pregnancy can be achieved with preconception counseling, education about contraception use, the timing of pregnancy (delaying by first year post-transplant), and the choice of immunosuppression medication. Ensuring stable renal function including optimized creatinine, proteinuria, and blood pressure increases successful outcomes. Pregnancy with kidney transplant has an increased risk of preeclampsia, gestational diabetes militeus, cesarean section, and preterm delivery. Multidisciplinary cooperation with high-risk obstetrics and transplant nephrologists is vital.

Insertion and Anchoring of HIV-1 Fusion Peptide into Complex Membrane Mimicking Human T-cell.

A fundamental understanding of how HIV-1 envelope (Env) protein facilitates fusion is still lacking. The HIV-1 fusion peptide, consisting of 15 to 22 residues, is the N-terminus of the gp41 subunit of the Env protein. Further, this peptide, a promising vaccine candidate, initiates viral entry into target cells by inserting and anchoring into human immune cells. The influence of membrane lipid reorganization and the conformational changes of the fusion peptide during the membrane insertion and anchoring processes, which can significantly affect HIV-1 cell entry, remains largely unexplored due to the limitations of experimental measurements. In this work, we investigate the insertion of the fusion peptide into an immune cell membrane mimic through multiscale molecular dynamics simulations. We mimic the native T-cell by constructing a 9-lipid asymmetric membrane, along with geometrical restraints accounting for insertion in the context of gp41. To account for the slow timescale of lipid mixing while enabling conformational changes, we implement a protocol to go back and forth between atomistic and coarse-grained simulations. Our study provides a molecular understanding of the interactions between the HIV-1 fusion peptide and the T-cell membrane, highlighting the importance of conformational flexibility of fusion peptides and local lipid reorganization in stabilizing the anchoring of gp41 into the targeted host membrane during the early events of HIV-1 cell entry. Importantly, we identify a motif within the fusion peptide critical for fusion that can be further manipulated in future immunological studies.

Psychosocial Evaluation of Living Kidney Donors: A Survey of Current Practices in the United States.

BACKGROUND: Best practices in psychosocial evaluation and care of living donor candidates and donors are not well established. METHODS: We surveyed 195 living kidney donor (LKD) transplant centers in United States from October 2021 to April 2022 querying (1) composition of psychosocial teams, (2) evaluation processes including clinical tools and domains assessed, (3) selection criteria, and (4) psychosocial follow-up post-donation. RESULTS: We received 161 responses from 104 programs, representing 53% of active LKD programs and 67% of LKD transplant volume in 2019. Most respondents (63%) were social workers/independent living donor advocates. Over 90% of respondents indicated donor candidates with known mental health or substance use disorders were initially evaluated by the psychosocial team. Validated psychometric or transplant-specific tools were rarely utilized but domains assessed were consistent. Active suicidality, self-harm, and psychosis were considered absolute contraindications in >90% of programs. Active depression was absolute contraindication in 50% of programs; active anxiety disorder was excluded 27%. Conditions not contraindicated to donation include those in remission: anxiety (56%), depression (53%), and posttraumatic stress disorder (41%). There was acceptance of donor candidates using alcohol, tobacco, or cannabis recreationally, but not if pattern met criteria for active use disorder. Seventy-one percent of programs conducted post-donation psychosocial assessment and use local resources to support donors. CONCLUSIONS: There was variation in acceptance of donor candidates with mental health or substance use disorders. Although most programs conducted psychosocial screening post-donation, support is not standardized and unclear if adequate. Future studies are needed for consensus building among transplant centers to form guidelines for donor evaluation, acceptance, and support.

Interfacial Interactions between Nanoplastics and Biological Systems: toward an Atomic and Molecular Understanding of Plastics-Driven Biological Dyshomeostasis.

Micro- and nano-plastics (NPs) are found in human milk, blood, tissues, and organs and associate with aberrant health outcomes including inflammation, genotoxicity, developmental disorders, onset of chronic diseases, and autoimmune disorders. Yet, interfacial interactions between plastics and biomolecular systems remain underexplored. Here, we have examined experimentally, in vitro, in vivo, and by computation, the impact of polystyrene (PS) NPs on a host of biomolecular systems and assemblies. Our results reveal that PS NPs essentially abolished the helix-content of the milk protein ß-lactoglobulin (BLG) in a dose-dependent manner. Helix loss is corelated with the near stoichiometric formation of ß-sheet elements in the protein. Structural alterations in BLG are also likely responsible for the nanoparticle-dependent attrition in binding affinity and weaker on-rate constant of retinol, its physiological ligand (compromising its nutritional role). PS NP-driven helix-to-sheet conversion was also observed in the amyloid-forming trajectory of hen egg-white lysozyme (accelerated fibril formation and reduced helical content in fibrils). Caenorhabditis elegans exposed to PS NPs exhibited a decrease in the fluorescence of green fluorescent protein-tagged dopaminergic neurons and locomotory deficits (akin to the neurotoxin paraquat exposure). Finally, in silico analyses revealed that the most favorable PS/BLG docking score and binding energies corresponded to a pose near the hydrophobic ligand binding pocket (calyx) of the protein where the NP fragment was found to make nonpolar contacts with side-chain residues via the hydrophobic effect and van der Waals forces, compromising side chain/retinol contacts. Binding energetics indicate that PS/BLG interactions destabilize the binding of retinol to the protein and can potentially displace retinol from the calyx region of BLG, thereby impairing its biological function. Collectively, the experimental and high-resolution in silico data provide new insights into the mechanism(s) by which PS NPs corrupt the bimolecular structure and function, induce amyloidosis and onset neuronal injury, and drive aberrant physiological and behavioral outcomes.

Expanding the access to kidney transplantation: Strategies for kidney transplant programs.

Kidney transplantation is the most successful kidney replacement therapy available, resulting in improved recipient survival and societal cost savings. Yet, nearly 70 years after the first successful kidney transplant, there are still numerous barriers and untapped opportunities that constrain the access to transplant. The literature describing these barriers is extensive, but the practices and processes to solve them are less clear. Solutions must be multidisciplinary and be the product of strong partnerships among patients, their networks, health care providers, and transplant programs. Transparency in the referral, evaluation, and listing process as well as organ selection are paramount to build such partnerships. Providing early culturally congruent and patient-centered education as well as maximizing the use of local resources to facilitate the transplant work up should be prioritized. Every opportunity to facilitate pre-emptive kidney transplantation and living donation must be taken. Promoting the use of telemedicine and kidney paired donation as standards of care can positively impact the work up completion and maximize the chances of a living donor kidney transplant.

An Atomic and Molecular Insight into How PFOA Reduces α-Helicity, Compromises Substrate Binding, and Creates Binding Pockets in a Model Globular Protein.

Per- and polyfluoroalkyl substances (PFAS) pose significant health risks due to their widespread presence in various environmental and biological matrices. However, the molecular-level mechanisms underlying the interactions between PFAS and biological constituents, including proteins, carbohydrates, lipids, and DNA, remain poorly understood. Here, we investigate the interactions between a legacy PFAS, viz. perfluorooctanoic acid (PFOA), and the milk protein ß-lactoglobulin (BLG) obtained using a combination of experimental and computational techniques. Circular dichroism studies reveal that PFOA perturbs the secondary structure of BLG, by driving a dose-dependent loss of α-helicity and alterations in its ß-sheet content. Furthermore, exposure of the protein to PFOA attenuates the on-rate constant for the binding of the hydrophobic probe 8-anilino-1-naphthalene sulfonic acid (ANS), suggesting potential functional impairment of BLG by PFOA. Steered molecular dynamics and umbrella sampling calculations reveal that PFOA binding leads to the formation of an energetically favorable novel binding pocket within the protein, when residues 129-142 are steered to unfold from their initial α-helical structure, wherein a host of intermolecular interactions between PFOA and BLG's residues serve to insert the PFOA into the region between the unfolded helix and beta-sheets. Together, the data provide a novel understanding of the atomic and molecular mechanism(s) by which PFAS modulates structure and function in a globular protein, leading to a beginning of our understanding of altered biological outcomes.

Psychosocial evaluation of living liver donors-State of current practices in the United States.

We surveyed living donor liver transplant programs in the United States to describe practices in the psychosocial evaluation of living donors focused on (1) composition of psychosocial team; (2) domains, workflow, and tools of the psychosocial assessment; (3) absolute and relative mental health-related contraindications to donation; and (4) postdonation psychosocial follow-up. We received 52 unique responses, representing 33 of 50 (66%) of active living donor liver transplant programs. Thirty-one (93.9%) provider teams included social workers, 22 (66.7%) psychiatrists, and 14 (42.4%) psychologists. Validated tools were rarely used, but domains assessed were consistent. Respondents rated active alcohol (93.8%), cocaine (96.8%), and opioid (96.8%) use disorder, as absolute contraindications to donation. Active suicidality (97%), self-injurious behavior (90.9%), eating disorders (87.9%), psychosis (84.8%), nonadherence (71.9%), and inability to cooperate with the evaluation team (78.1%) were absolute contraindications to donation. There were no statistically significant differences in absolute psychosocial contraindications to liver donation between geographical areas or between large and small programs. Programs conduct postdonation psychosocial follow-up (57.6%) or screening (39.4%), but routine follow-up of declined donors is rarely conducted (15.8%). Psychosocial evaluation of donor candidates is a multidisciplinary process. The structure of the psychosocial evaluation of donors is not uniform among programs though the domains assessed are consistent. Psychosocial contraindications to living liver donation vary among the transplant programs. Mental health follow-up of donor candidates is not standardized.

Triepoxide formation by a flavin-dependent monooxygenase in monensin biosynthesis.

Monensin A is a prototypical natural polyether polyketide antibiotic. It acts by binding a metal cation and facilitating its transport across the cell membrane. Biosynthesis of monensin A involves construction of a polyene polyketide backbone, subsequent epoxidation of the alkenes, and, lastly, formation of cyclic ethers via epoxide-opening cyclization. MonCI, a flavin-dependent monooxygenase, is thought to transform all three alkenes in the intermediate polyketide premonensin A into epoxides. Our crystallographic study has revealed that MonCI's exquisite stereocontrol is due to the preorganization of the active site residues which allows only one specific face of the alkene to approach the reactive C(4a)-hydroperoxyflavin moiety. Furthermore, MonCI has an unusually large substrate-binding cavity that can accommodate premonensin A in an extended or folded conformation which allows any of the three alkenes to be placed next to C(4a)-hydroperoxyflavin. MonCI, with its ability to perform multiple epoxidations on the same substrate in a stereospecific manner, demonstrates the extraordinary versatility of the flavin-dependent monooxygenase family of enzymes.

Characterizing the Interactions of Cell-Membrane-Disrupting Peptides with Lipid-Functionalized Single-Walled Carbon Nanotubes.

Lipid-functionalized single-walled carbon nanotubes (SWNTs) have garnered significant interest for their potential use in a wide range of biomedical applications. In this work, we used molecular dynamics simulations to study the equilibrium properties of SWNTs surrounded by the phosphatidylcholine (POPC) corona phase and their interactions with three cell membrane disruptor peptides: colistin, TAT peptide, and crotamine-derived peptide. Our results show that SWNTs favor asymmetrical positioning within the POPC corona, so that one side of the SWNT, covered by the thinnest part of the corona, comes in contact with charged and polar functional groups of POPC and water. We also observed that colistin and TAT insert deeply into the POPC corona, while crotamine-derived peptide only adsorbs to the corona surface. In separate simulations, we show that three examined peptides exhibit similar insertion and adsorption behaviors when interacting with POPC bilayers, confirming that peptide-induced perturbations to POPC in conjugates and bilayers are similar in nature and magnitude. Furthermore, we observed correlations between the peptide-induced structural perturbations and the near-infrared emission of the lipid-functionalized SWNTs, which suggest that the optical signal of the conjugates transduces the morphological changes in the lipid corona. Overall, our findings indicate that lipid-functionalized SWNTs could serve as simplified cell membrane model systems for prescreening of new antimicrobial compounds that disrupt cell membranes.

Characterizing the Interactions of Cell Membrane-Disrupting Peptides with Lipid-Functionalized Single-Walled Carbon Nanotube Systems for Antimicrobial Screening.

Lipid-functionalized single-walled carbon nanotubes (SWNTs) have garnered significant interest for their potential use in a wide range of biomedical applications. In this work, we used molecular dynamics simulations to study the equilibrium properties of SWNTs surrounded by the phosphatidylcholine (POPC) corona phase, and their interactions with three cell membrane disruptor peptides: colistin, TAT peptide, and crotamine-derived peptide. Our results show that SWNTs favor asymmetrical positioning within the POPC corona, so that one side of the SWNT, covered by the thinnest part of the corona, comes in contact with charged and polar functional groups of POPC and water. We also observed that colistin and TAT insert deeply into POPC corona, while crotamine-derived peptide only adsorbs to the corona surface. Compared to crotamine-derived peptide, colistin and TAT also induce larger perturbations in the thinnest region of the corona, by allowing more water molecules to directly contact the SWNT surface. In separate simulations, we show that three examined peptides exhibit similar insertion and adsorption behaviors when interacting with POPC bilayers, confirming that peptide-induced perturbations to POPC in conjugates and bilayers are similar in nature and magnitude. Furthermore, we observed correlations between the peptide-induced structural perturbations and the near-infrared emission of the lipid-functionalized SWNTs, which suggest that the optical signal of the conjugates transduces the morphological changes in the lipid corona. Overall, our findings indicate that lipid-functionalized SWNTs could serve as simplified cell membrane model systems for pre-screening of new antimicrobial compounds that disrupt cell membranes.

BRMCF: Binary Relevance and MLSMOTE Based Computational Framework to Predict Drug Functions From Chemical and Biological Properties of Drugs.

In silico machine learning based prediction of drug functions considering the drug properties would substantially enhance the speed and reduce the cost of identifying promising drug leads. The drug function prediction capability of different drug properties happens to be different. So assessing these is advantageous in drug discovery. The task of drug function prediction is multi-label in nature reason being, in case of several drugs, multiple functions are associated with a drug. A number of existing works have ignored this inherent multi-label nature of the problem in context of addressing the issue of class imbalance. In the present work, a computational framework named as BRMCF has been proposed for analysing the prediction capability of chemical and biological properties of drugs toward drug functions in view of multi-label nature of problem. It employs Binary Relevance (BR) approach along with five base classifiers for handling the multi-label prediction task and MLSMOTE for addressing the issue of class imbalance. The proposed framework has been validated and compared with BR, Classifier Chains (CC) and Deep Neural Network (DNN) method on four drug properties datasets: SMILES Strings (SS) dataset, 17 Molecular Descriptors (17MD) dataset, Protein Sequences (PS) dataset and drug perturbed Gene EXpression Profiles (GEX) dataset. The analysis of results shows that the proposed framework BRMCF has outperformed BR, CC and DNN method in terms of exact match ratio, precision, recall, F1-score, ROC-AUC which signifies the effectiveness of MLSMOTE. Further, assessment of prediction capability of different drug properties is done and they are ranked as SS GEX PS 17MD. Additionally, the visualization and analysis of drug function co-occurrences signify the appropriateness of the proposed framework for drug function co-occurrence detection and in signaling the new possible drug leads where the detection rate varies from 94.34% to 99.61%.

Telemedicine services for living kidney donation: A US survey of multidisciplinary providers.

Individuals considering living kidney donation face geographic, financial, and logistical challenges. Telemedicine can facilitate healthcare access/care coordination. Yet difficulties exist in telemedicine implementation and sustainability. We sought to examine centers' practices and providers' attitudes toward telemedicine to improve services for donors. We surveyed multidisciplinary providers from 194 active adult US living donor kidney transplant centers; 293 providers from 128 unique centers responded to the survey (center representation rate = 66.0%), reflecting 83.9% of practice by donor volume and 91.5% of US states/territories. Most centers (70.3%) plan to continue using telemedicine beyond the pandemic for donor evaluation/follow-up. Video was mostly used by nephrologists, surgeons, and psychiatrists/psychologists. Telephone and video were mostly used by social workers, while video or telephone was equally used by coordinators. Half of respondent nephrologists and surgeons were willing to accept a remote completion of physical exam; 68.3% of respondent psychiatrists/psychologists and social workers were willing to accept a remote completion of mental status exam. Providers strongly agreed that telemedicine was convenient for donors and would improve the likelihood of completing donor evaluation. However, providers (65.5%) perceived out-of-state licensing as a key policy/regulatory barrier. These findings help inform practice and underscore the instigation of policies to remove barriers using telemedicine to increase living kidney donation.

Acute kidney injury during pregnancy in kidney transplant recipients.

Pregnancy-related acute kidney injury (AKI) is a public health problem and remains an important cause of maternal and fetal morbidity and mortality. The incidence of pregnancy-related AKI has increased in developed countries due to increase in maternal age and higher detection rates. Pregnancy in women with kidney transplants is associated with higher adverse outcomes like preeclampsia, preterm births, and allograft dysfunction, but limited data exists on causes and outcomes of pregnancy-related AKI in the kidney transplant population. Diagnosis of AKI during pregnancy remains challenging in kidney transplant recipients due to lack of diagnostic criteria. Management of pregnancy-related AKI in the kidney transplant population requires a multidisciplinary team consisting of transplant nephrologists, high-risk obstetricians, and neonatologists. In this review, we discuss pregnancy-related AKI in women with kidney transplants, etiologies, pregnancy outcomes, and management strategies.

Performance Analysis of Deep Learning Models for Binary Classification of Cancer Gene Expression Data.

The classification of patients as cancer and normal patients by applying the computational methods on their gene expression profiles is an extremely important task. Recently, deep learning models, mainly multilayer perceptron and convolutional neural networks, have gained popularity for being applied on this type of datasets. This paper aims to analyze the performance of deep learning models on different types of cancer gene expression datasets as no such consolidated work is available. For this purpose, three deep learning models along with two feature selection method and four cancer gene expression datasets have been considered. It has resulted in a total of 24 different combinations to be analyzed. Out of four datasets, two are imbalanced and two are balanced in terms of number of normal and cancer samples. Experimental results show that the deep learning models have performed well in terms of true positive rate, precision, F1-score, and accuracy.

FVC-NET: An Automated Diagnosis of Pulmonary Fibrosis Progression Prediction Using Honeycombing and Deep Learning.

Pulmonary fibrosis is a severe chronic lung disease that causes irreversible scarring in the tissues of the lungs, which results in the loss of lung capacity. The Forced Vital Capacity (FVC) of the patient is an interesting measure to investigate this disease to have the prognosis of the disease. This paper proposes a deep learning-based FVC-Net architecture to predict the progression of the disease from the patient's computed tomography (CT) scan and the patient's metadata. The input to the model combines the image score generated based on the degree of honeycombing for a patient identified based on segmented lung images and the metadata. This input is then fed to a 3-layer net to obtain the final output. The performance of the proposed FVC-Net model is compared with various contemporary state-of-the-art deep learning-based models, which are available on a cohort from the pulmonary fibrosis progression dataset. The model showcased significant improvement in the performance over other models for modified Laplace Log-Likelihood (-6.64). Finally, the paper concludes with some prospects to be explored in the proposed study.

BID-Net: An Automated System for Bone Invasion Detection Occurring at Stage T4 in Oral Squamous Carcinoma Using Deep Learning.

Detection of the presence and absence of bone invasion by the tumor in oral squamous cell carcinoma (OSCC) patients is very significant for their treatment planning and surgical resection. For bone invasion detection, CT scan imaging is the preferred choice of radiologists because of its high sensitivity and specificity. In the present work, deep learning algorithm based model, BID-Net, has been proposed for the automation of bone invasion detection. BID-Net performs the binary classification of CT scan images as the images with bone invasion and images without bone invasion. The proposed BID-Net model has achieved an outstanding accuracy of 93.62%. The model is also compared with six Transfer Learning models like VGG16, VGG19, ResNet-50, MobileNetV2, DenseNet-121, ResNet-101 and BID-Net outperformed over the other models. As there exists no previous studies on bone invasion detection using Deep Learning models, so the results of the proposed model have been validated from the experts of practitioner radiologists, S.M.S. hospital, Jaipur, India.