Cell-Free DNA for the detection of kidney allograft rejection.

Donor-derived cell-free DNA (dd-cfDNA) is an emerging non-invasive biomarker that has the potential to detect allograft injury. The capacity of donor-derived cell-free DNA to detect kidney allograft rejection and its added clinical value beyond standard of care patient monitoring is unclear. We enrolled 2,882 kidney allograft recipients from 14 transplantation centers in Europe and the US in an observational population-based study. The primary analysis included 1,134 patients. Donor-derived cell-free DNA levels strongly correlated with allograft rejection including antibody-mediated rejection (p < 0.0001), T-Cell mediated rejection (p < 0.0001) and mixed rejection (p < 0.0001). In multivariable analysis, circulating dd-cfDNA was significantly associated with allograft rejection (OR: 2.275; CI:1.902-2.739; p < 0.0001) independently of standard of care patient monitoring parameters. The inclusion of dd-cfDNA to a standard of care prediction model showed improved discrimination (0.777 [95% CI: 0.741-0.811] to 0.821 [95% CI: 0.784-0.852]; p = 0.0011) and calibration. These results were confirmed in the external validation cohorts (n = 1,748) including a cohort of African American patients (n = 439). Finally, dd-cfDNA showed high predictive value to detect subclinical rejection in stable patients. Our study provides insights on the potential value of assessing dd-cfDNA, in addition to standard of care monitoring, to improve the detection of allograft rejection. ClinicalTrials.gov registration: NCT05995379.

Assessment of prevalence and need for screening of diabetic retinopathy using non-mydriatic fundus camera in rural and tribal diabetic populations in Maharashtra.

PURPOSE: To assess the prevalence of DR and the need for screening and management of DR with medical management of diabetes in rural and tribal population in Maharashtra. METHODS: The known diabetics of rural area and tribal area were screened at corresponding primary health centers, subcenters, and village level with the help of local healthcare workers using a portable non-mydriatic fundus camera. The prevalence of blindness among known diabetics in rural area was 1.29%, and 0.84% in tribal area. RESULTS: In the rural area, the prevalence of diabetic retinopathy (DR) was 5.67% (n = 776), out of those 18.18% had sight threatening diabetic retinopathy (STDR). The prevalence of DR was 7.73% (n = 711) in tribal areas, out of those, 30.90% had STDR. CONCLUSIONS: The significant risk factors were identified to be the duration of diabetes and poor glycemic control. Implementation of targeted interventions for screening and management are required to reduce the risk of blindness among known diabetics in rural and tribal areas.

Comprehensive Review of Hypertensive Disorders Related to Pregnancy.

Hypertensive disorder of pregnancy is a common complication during pregnancy that affects approximately 10% of pregnancies and is responsible for nearly 14% of maternal deaths worldwide. It affects the mother and the fetus simultaneously, sometimes putting the health of the mother and the fetus at odds with each other. It may present with only hypertension and proteinuria or with life-threatening complications in the mother such as eclampsia; stroke; acute pulmonary edema; acute renal failure; disseminated intravascular coagulation; placental abruption; hemolysis, elevated liver enzymes, and low platelet syndrome; pregnancy loss; and fetal growth restriction and prematurity resulting from the frequent need of delivering preterm in the fetus. In this review, we aimed to describe hypertensive disorders of pregnancy, mainly preeclampsia and chronic hypertension in pregnancy, by discussing the pathophysiology, the central role of abnormal placentation, the release of antiangiogenic factors in the circulation and immunological factors, the clinical outcome in the mother and the fetus, and the diagnostic criteria and principles of management of both the conditions. We also discuss possible screening methods and prevention of preeclampsia using low-dose aspirin and eclampsia prophylaxis.

Impact of Covid-19 on Medical Students around the Globe.

The Coronavirus (COVID-19) pandemic has caused an unexpected disturbance in healthcare systems as well as medical education worldwide. This article aims to provide an overview of the circumstances experienced by medical students during the COVID-19 pandemic. As this disease can cause life-threatening conditions, it has presented challenges to medical educators and students as they must adapt to changes in their medical education to ensure lectures are given safely as well as effectively. Many medical students feel the sudden change in their education system impacted their training negatively; 74% of students surveyed by members of McGill University reported a decrease in the quality of their education since the start of COVID-19. As well as a negative impact on medical education, this pandemic has caused unprecedented psychological stress on numerous people around the world, especially individuals in the medical field. 48% of medical students at a Canadian university reported feeling more depressed since the onset of COVID-19. The sudden changes, isolation, and worries about health have impacted students' mental health drastically. On the other hand, some students have reported that this pandemic has made a positive impact on their mental health as they had more time to focus on their mental well-being and they felt an overall reduction in pressure and stress. As COVID-19 remains to impact individuals worldwide, effective strategies towards improving mental health and quality of education should be provided to medical students affected by the challenges of this pandemic.

A concerning trend in geriatric pharmacy that merits evidence-based intervention.

The effects of polypharmacy on geriatric populations are an emerging concern that merits more exploration. The primary goal of this review was to evaluate the current body of knowledge on polypharmacy and explore the preventive and corrective measures to avoid negative outcomes. Even if a medication has an appropriate indication, polypharmacy in the geriatric population is associated with an increased risk of drug-drug or drug-condition interactions. Recent efforts to prevent polypharmacy include the development of interprofessional teams in clinics dedicated to medication review and reconciliation, deprescription plans aimed to safely discontinue potentially inappropriate medications, and inpatient screening tools that provide prescribing recommendations. In conclusion, polypharmacy affects a high percentage of the geriatric population. Current efforts to address and prevent polypharmacy are ongoing but have not been widely adopted.

Peroperative Intra-Articular Infiltration of Tranexamic Acid and Ropivacaine Cocktail in Patients Undergoing Total Knee Arthroplasty: A Randomized Controlled Trial.

Background Total knee arthroplasty (TKA) is a procedure that has improved the quality of life of patients with knee arthritis. Postoperative pain and blood loss are the two major drawbacks of TKA which affect patient satisfaction and delay recovery and rehabilitation. Local infiltration analgesia has shown better results in controlling immediate postoperative pain, thus enabling early rehabilitation and mobilization, while local infiltration of antifibrinolytic agents has shown impressive results in controlling blood loss. In this study, we evaluate the effect of a combination of intra-articular infiltration of ropivacaine cocktail along with intra-articular instillation of tranexamic acid in reducing patient-reported postoperative pain and the level of blood loss control after TKA. Methodology Patients presenting with high-grade osteoarthritis and undergoing TKA were included and randomly allocated to two groups: one receiving the intra-articular infiltration (group A), and the other not receiving any infiltration (group B). Postoperative pain was measured through the Visual Analog Scale (VAS) every three hours for the first 24 hours, and then at 48 hours and 72 hours postoperatively. The need for additional analgesia, in the form of a slow epidural infusion, in patients experiencing severe postoperative pain was evaluated in both groups. Postoperative blood loss was assessed by measuring total drain output (in mL) and by comparing preoperative and postoperative (at 24 hours) hemoglobin, hematocrit drift, and blood transfusion rates. The duration of the postoperative hospital stay and the time taken to start postoperative knee mobilization exercises and weight-bearing were noted to assess the recovery and rehabilitation of the patients in the two groups. Results The study included 42 patients (group A, 22 patients; group B, 20 patients) with 28 knees in each group. Patients with intra-articular infiltration using ropivacaine cocktail with tranexamic acid showed excellent pain control compared to the non-infiltrated patients in the early 48 hours postoperatively. There was a significant drop in postoperative hemoglobin and hematocrit values in the non-infiltrated patients compared to the other group. Further, the intra-articular infiltration-instillation significantly reduced blood loss through the drain, the requirement of postoperative blood transfusions, and the duration of hospital stay. Conclusions It can be safely concluded that ropivacaine cocktail and tranexamic acid instillation postoperatively in knee arthroplasty patients is a very useful and effective technique to reduce postoperative pain and blood loss.

Lerna: transformer architectures for configuring error correction tools for short- and long-read genome sequencing.

BACKGROUND: Sequencing technologies are prone to errors, making error correction (EC) necessary for downstream applications. EC tools need to be manually configured for optimal performance. We find that the optimal parameters (e.g., k-mer size) are both tool- and dataset-dependent. Moreover, evaluating the performance (i.e., Alignment-rate or Gain) of a given tool usually relies on a reference genome, but quality reference genomes are not always available. We introduce Lerna for the automated configuration of k-mer-based EC tools. Lerna first creates a language model (LM) of the uncorrected genomic reads, and then, based on this LM, calculates a metric called the perplexity metric to evaluate the corrected reads for different parameter choices. Next, it finds the one that produces the highest alignment rate without using a reference genome. The fundamental intuition of our approach is that the perplexity metric is inversely correlated with the quality of the assembly after error correction. Therefore, Lerna leverages the perplexity metric for automated tuning of k-mer sizes without needing a reference genome. RESULTS: First, we show that the best k-mer value can vary for different datasets, even for the same EC tool. This motivates our design that automates k-mer size selection without using a reference genome. Second, we show the gains of our LM using its component attention-based transformers. We show the model's estimation of the perplexity metric before and after error correction. The lower the perplexity after correction, the better the k-mer size. We also show that the alignment rate and assembly quality computed for the corrected reads are strongly negatively correlated with the perplexity, enabling the automated selection of k-mer values for better error correction, and hence, improved assembly quality. We validate our approach on both short and long reads. Additionally, we show that our attention-based models have significant runtime improvement for the entire pipeline-18[Formula: see text] faster than previous works, due to parallelizing the attention mechanism and the use of JIT compilation for GPU inferencing. CONCLUSION: Lerna improves de novo genome assembly by optimizing EC tools. Our code is made available in a public repository at: https://github.com/icanforce/lerna-genomics .

Clinical outcomes from the Assessing Donor-derived cell-free DNA Monitoring Insights of kidney Allografts with Longitudinal surveillance (ADMIRAL) study.

The use of routine monitoring of donor-derived cell-free DNA (dd-cfDNA) after kidney transplant may allow clinicians to identify subclinical allograft injury and intervene prior to development of clinically evident graft injury. To evaluate this, data from 1092 kidney transplant recipients monitored for dd-cfDNA over a three-year period was analyzed to assess the association of dd-cfDNA with histologic evidence of allograft rejection. Elevation of dd-cfDNA (0.5% or more) was significantly correlated with clinical and subclinical allograft rejection. dd-cfDNA values of 0.5% or more were associated with a nearly three-fold increase in risk development of de novo donor-specific antibodies (hazard ratio 2.71) and were determined to be elevated a median of 91 days (interquartile range of 30-125 days) ahead of donor specific antibody identification. Persistently elevated dd-cfDNA (more than one result above the 0.5% threshold) predicted over a 25% decline in the estimated glomerular filtration rate over three years (hazard ratio 1.97). Therefore, routine monitoring of dd-cfDNA allowed early identification of clinically important graft injury. Biomarker monitoring complemented histology and traditional laboratory surveillance strategies as a prognostic marker and risk-stratification tool post-transplant. Thus, persistently low dd-cfDNA levels may accurately identify allograft quiescence or absence of injury, paving the way for personalization of immunosuppression trials.

Assessing safety critical driving patterns of heavy passenger vehicle drivers using instrumented vehicle data - An unsupervised approach.

Assessing the individual's driving profile and identifying the at-fault behaviors contributes to road safety, riding comfort, and driver assistance systems. This study proposes a framework to identify aggressive driving patterns in longitudinal control using real-time driving profiles of heavy passenger vehicle (HPV) drivers. The main objective is to detect and quantify the instantaneous driving decisions and classify the identified maneuvers (acceleration, braking) using unsupervised machine learning techniques without any prior-ground truth. To this end, total 8295 acceleration events, and 7151 braking events, were extracted from 142 driving profiles collected using high-resolution (10 Hz) GPS instrumentation. The principal component analysis was conducted on a multi-dimensional feature set, followed by a two-stage k-means clustering on the reduced feature subspace. The results showed that 86.5% of accelerations and 65.3% of braking maneuvers were characterized as non-aggressive, indicating safe or base-line driving behavior. However, 13.5% of accelerations and 34.7% of braking maneuvers were featured to be aggressive, indicative of the actual risky behaviors. Further analysis demonstrated the heterogeneity in drivers' trip-level frequency of aggressive maneuvers and highlighted the need for a continuous driving assessment. The study also revealed that the thresholds derived from the obtained clusters featuring the aggressive accelerations (+0.3 to +0.48 g) and aggressive braking (-0.42 to -0.27 g) maneuvers were beyond the acceptable limits of passenger safety and comfort. The insights from the study aids in developing driver assistance systems for personalized feedback provision and improve driver behavior.

Simultaneous learning of individual microRNA-gene interactions and regulatory comodules.

BACKGROUND: MicroRNAs (miRNAs) function in post-transcriptional regulation of gene expression by binding to target messenger RNAs (mRNAs). Because of the key part that miRNAs play, understanding the correct regulatory role of miRNAs in diverse patho-physiological conditions is of great interest. Although it is known that miRNAs act combinatorially to regulate genes, precise identification of miRNA-gene interactions and their specific functional roles in regulatory comodules remains a challenge. We developed THEIA, an effective method for simultaneously predicting miRNA-gene interactions and regulatory comodules, which group functionally related miRNAs and genes via non-negative matrix factorization (NMF). RESULTS: We apply THEIA to RNA sequencing data from breast invasive carcinoma samples and demonstrate its effectiveness in discovering biologically significant regulatory comodules that are significantly enriched in spatial miRNA clusters, biological pathways, and various cancers. CONCLUSIONS: THEIA is a theoretically rigorous optimization algorithm that simultaneously predicts the strength and direction (i.e., up-regulation or down-regulation) of the effect of modules of miRNAs on a gene. We posit that if THEIA is capable of recovering known clusters of genes and miRNA, then the clusters found by our method not previously identified by literature are also likely to have biological significance. We believe that these novel regulatory comodules found by our method will be a springboard for further research into the specific functional roles of these new functional ensembles of miRNAs and genes,especially those related to diseases like breast cancer.