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Characterization, Enrichment, and Computational Modeling of Cross-Linked Actin Networks in Transformed Trabecular Meshwork Cells
No full textPurpose: Cross-linked actin networks (CLANs) are prevalent in the glaucomatous trabecular meshwork (TM). We previously developed the GTM3L cell line, which spontaneously forms fluorescently labeled CLANs, by transducing GTM3, a transformed glaucomatous TM cell line, with a lentivirus expressing the LifeAct-GFP fusion protein. Here, we determined if LifeAct-GFP viral copy numbers are associated with CLANs, developed approaches to increase CLAN incidence, and computationally studied the biomechanical properties of CLAN-containing GTM3L cells.
Methods: GTM3L cells were fluorescently sorted for viral copy number analysis to determine whether increased CLAN incidence was associated with copy number. CLAN incidence was increased by combining (1) differential adhesion sorting, (2) cell deswelling, and (3) cell stiffness selection. GTM3L cells were cultured on glass or soft hydrogels for stiffness measurement by atomic force microscopy. Computational models studied the biomechanical properties of CLANs.
Results: GTM3L cells had one LifeAct-GFP viral copy/cell on average, and viral copy number or LifeAct-GFP expression level did not associate with CLAN incidence rate. However, CLAN rate was increased from -0.28% to -50% by combining the three enrichment methods noted above. Further, GTM3L cells formed more CLANs on a stiff versus a soft substrate. Computational modeling predicted that CLANs contribute to higher cell stiffness, including increased resistance of the nucleus to tensile stress when CLANs are physically linked to the nucleus.
Conclusions: It is possible to greatly enhance CLAN incidence in GTM3L cells. CLANs are mechanosensitive structures that affect cell biomechanical properties. Further research is needed to determine the biomechanics, mechanobiology, and etiology of CLANs in the TM
Conservative Kidney Management in the Middle East and North Africa: Attitudes, Practices, and Implementation Barriers
No full textIntroduction: Conservative kidney management (CKM) is poorly developed and not easily accessible globally, especially in middle- and low-income countries. This study aimed to understand the perspectives of nephrologists on CKM and the barriers to its implementation in the Middle East and North Africa (MENA) region.
Methods: We conducted an online survey. Nephrologists were contacted through their local nephrology societies. Responses were divided into the following 3 groups as per the country's income classification by the World Bank: high-, middle-, and low-income.
Results: A total of 336 surveys were analyzed (response rate: 34.28%). The mean age of participants was 43.3 ± 9.8 years; 50% were male, 91% practiced in urban settings, and 18% were affiliated with academic centers. Of the participants, 76% were from middle-income countries. Nearly 80% of the participants were aware of CKM, and 65% accepted CKM as a treatment modality for kidney failure. However, only 20% consistently offered CKM to their patients and only 16% had a formal CKM program at their institution. Among these, 12% had a multidisciplinary team and only 6% had formal CKM training. The major perceived barriers to CKM implementation were financial and resource constraints (37.7% and 32.7%, respectively). Cultural and religious barriers constituted 18.3% and 8.6%, respectively, and were similar among the 3 income groups.
Conclusion: Despite the significant awareness of CKM in the MENA region, its implementation remains poor. Key barriers include financial limitations, resource shortages, and a lack of training. Regional and national research is required to address these challenges and guide policies to improve CKM accessibility and implementation
Campylobacter jejuni Periplasmic Nitrate Reductase NapA as a Medium for Elucidating Molybdenum Cofactor Reactivity
No full textIUIPeriplasmic nitrate reductase NapA is found within many gram-negative bacteria and catalyzes oxygen atom transfer reactions. NapA utilizes nitrate as a terminal electron acceptor in place of oxygen in low-air conditions, such as in the human gastrointestinal tract. Within the scope of this thesis, NapA from Campylobacter jejuni is primarily focused due to its reputation in poultry husbandry and antibiotic resistance. Although nitrate reduction aids in pathogen survival, it is also a geochemically essential process. Many enzymes closely related to NapA are involved in geochemical cycling and contain the same active site ligand structure. The ligand within these enzymes is called molybdenum cofactor, or Moco. The structure of the enzyme is influential on reactivity of the molybdenum cofactor. The rate of catalysis, electron and proton transfer, and substrate preference can be affected by the amino acids surrounding Moco. Elucidating details of Moco reactivity aids in understanding bacteria in relation to human health and geochemical cycles. The primary tools throughout this research were site-directed mutagenesis and steady-state kinetics
University students’ self-assessment of data literacy: A validation study
No full textAs data literacy has emerged as a critical skill for professionals across industries, educators in higher education have incorporated it into their curricula and instruction. Understanding and evaluating the factors that shape an individual's data literacy is important for benchmarking proficiency and tailoring curricula, yet the underlying components and structure of data literacy for students in four-year institutions are unknown. This study validated the Data Literacy Self-Efficacy Scale (DLSES) with 1,816 students enrolled in two four-year institutions. Exploratory and confirmatory factor analyses were conducted to determine the construct of the scale, and the item analysis was used to address the validity of the items on the scale. The exploratory factor analysis identified eight distinct factors comprising 29 items. The results of confirmatory factor analysis showed a good model fit, CFI = 0.994, TLI = 0.994, RMSEA = 0.053, SRMR = 0.044. This study demonstrated the 29-item refined version of the DLSES to be a reliable and valid tool for measuring individuals' self-efficacy levels for data literacy. Furthermore, the scale could form the basis for curriculum development and help educators design targeted interventions that address specific learning needs
Natural language processing to evaluate texting conversations between patients and healthcare providers during COVID-19 Home-Based Care in Rwanda at scale
No full textCommunity isolation of patients with communicable infectious diseases limits spread of pathogens but our understanding of isolated patients' needs and challenges is incomplete. Rwanda deployed a digital health service nationally to assist public health clinicians to remotely monitor and support SARS-CoV-2 cases via their mobile phones using daily interactive short message service (SMS) check-ins. We aimed to assess the texting patterns and communicated topics to better understand patient experiences. We extracted data on all COVID-19 cases and exposed contacts who were enrolled in the WelTel text messaging program between March 18, 2020, and March 31, 2022, and linked demographic and clinical data from the national COVID-19 registry. A sample of the text conversation corpus was English-translated and labeled with topics of interest defined by medical experts. Multiple natural language processing (NLP) topic classification models were trained and compared using F1 scores. Best performing models were applied to classify unlabeled conversations. Total 33,081 isolated patients (mean age 33·9, range 0-100), 44% female, including 30,398 cases and 2,683 contacts) were registered in WelTel. Registered patients generated 12,119 interactive text conversations in Kinyarwanda (n = 8,183, 67%), English (n = 3,069, 25%) and other languages. Sufficiently trained large language models (LLMs) were unavailable for Kinyarwanda. Traditional machine learning (ML) models outperformed fine-tuned transformer architecture language models on the native untranslated language corpus, however, the reverse was observed of models trained on English-only data. The most frequently identified topics discussed included symptoms (69%), diagnostics (38%), social issues (19%), prevention (18%), healthcare logistics (16%), and treatment (8·5%). Education, advice, and triage on these topics were provided to patients. Interactive text messaging can be used to remotely support isolated patients in pandemics at scale. NLP can help evaluate the medical and social factors that affect isolated patients which could ultimately inform precision public health responses to future pandemics
Aging x Environment x genetic risk for late onset Alzheimer’s disease results in alterations in cognitive function in mice independent of amyloid and tau pathology
No full textBackground:
Alzheimer’s disease (AD) research has been historically dominated with studies in mouse models expressing familial AD mutations; however, the majority of AD patients have the sporadic, late‐onset form of AD (LOAD). To address this gap, the IU/JAX/PITT MODEL‐AD Consortium has focused on development of mouse models that recapitulate LOAD by combining genetic risk variants with environmental risk factors and aging to enable more precise models to evaluate potential therapeutics. The present studies were undertaken to characterize cognitive and neurophysiological phenotypes in LOAD mice.
Method:
Two genetic risk factors, APOE4 and Trem2*R47H, were incorporated into C57BL/6J mice with humanized amyloid‐beta to produce the LOAD2 model (JAX# 030670). Male and female LOAD2 and WT mice were exposed to ad libitum 45% high‐fat diet from 2‐months of age (LOAD2+HFD or WT+HFD, respectively) throughout their lifespan and compared to LOAD2 and WT mice on control diet (+CD). Cognitive training began at 14‐months of age using a touchscreen testing battery, similar to previously described methods (Oomen et al 2013). At the conclusion of touchscreen testing, subjects were implanted with wireless telemetry devices (DSI) for evaluation of electroencephalography (EEG) signatures.
Result:
All subjects met the touch‐reward association criteria. During task acquisition LOAD2+CD mice demonstrated impaired acquisition relative to WT+CD, while both LOAD2+HFD and WT+HFD failed to learn the task as indicated by accuracy less than chance (<50%); which was confirmed in a separate cohort. LOAD2+HFD mice demonstrated increased spikewave events as measured by EEG, relative to LOAD2+CD. At 18‐months of age +CD mice that met acquisition criteria were evaluated in a location discrimination task with LOAD2+CD mice demonstrating modest impairments in pattern separation relative to age‐matched WT+CD.
Conclusion:
These data are the first reports of cognitive deficits and neurophysiological alterations in mice with environmental x genetic risk for LOAD, independent of amyloid and tau pathology. Importantly, the present findings demonstrate the sensitivity of the translational touchscreen testing battery for detecting mild cognitive impairment in LOAD mice with corresponding neurophysiologic alterations, and extend previous characterization data for the LOAD2 model and its utility for the study of the biology of LOAD
Precision Medicine for Pulmonary Vascular Disease: The Future Is Now (2023 Grover Conference Series)
No full textPulmonary vascular disease is not a single condition; rather it can accompany a variety of pathologies that impact the pulmonary vasculature. Applying precision medicine strategies to better phenotype, diagnose, monitor, and treat pulmonary vascular disease is increasingly possible with the growing accessibility of powerful clinical and research tools. Nevertheless, challenges exist in implementing these tools to optimal effect. The 2023 Grover Conference Series reviewed the research landscape to summarize the current state of the art and provide a better understanding of the application of precision medicine to managing pulmonary vascular disease. In particular, the following aspects were discussed: (1) Clinical phenotypes, (2) genetics, (3) epigenetics, (4) biomarker discovery, (5) application of precision biology to clinical trials, (6) the right ventricle (RV), and (7) integrating precision medicine to clinical care. The present review summarizes the content of these discussions and the prospects for the future
Utility of Candidate Genes From an Algorithm Designed to Predict Genetic Risk for Opioid Use Disorder
No full textImportance: Recently, the US Food and Drug Administration gave premarketing approval to an algorithm based on its purported ability to identify individuals at genetic risk for opioid use disorder (OUD). However, the clinical utility of the candidate genetic variants included in the algorithm has not been independently demonstrated.
Objective: To assess the utility of 15 genetic variants from an algorithm intended to predict OUD risk.
Design, setting, and participants: This case-control study examined the association of 15 candidate genetic variants with risk of OUD using electronic health record data from December 20, 1992, to September 30, 2022. Electronic health record data, including pharmacy records, were accrued from participants in the Million Veteran Program across the US with opioid exposure (n = 452 664). Cases with OUD were identified using International Classification of Diseases, Ninth Revision, or International Classification of Diseases, Tenth Revision, diagnostic codes, and controls were individuals with no OUD diagnosis.
Exposures: Number of risk alleles present across 15 candidate genetic variants.
Main outcome and measures: Performance of 15 genetic variants for identifying OUD risk assessed via logistic regression and machine learning models.
Results: A total of 452 664 individuals with opioid exposure (including 33 669 with OUD) had a mean (SD) age of 61.15 (13.37) years, and 90.46% were male; the sample was ancestrally diverse (with individuals of genetically inferred European, African, and admixed American ancestries). Using Nagelkerke R2, collectively, the 15 candidate genes accounted for 0.40% of variation in OUD risk. In comparison, age and sex alone accounted for 3.27% of the variation. The ensemble machine learning. The ensemble machine learning model using the 15 variants as predictive factors correctly classified 52.83% (95% CI, 52.07%-53.59%) of individuals in an independent testing sample.
Conclusions and relevance: Results of this study suggest that the candidate genetic variants included in the approved algorithm do not meet reasonable standards of efficacy in identifying OUD risk. Given the algorithm's limited predictive accuracy, its use in clinical care would lead to high rates of both false-positive and false-negative findings. More clinically useful models are needed to identify individuals at risk of developing OUD
Identification of Chemical Tool Compounds to Investigate the Role of Lyn Kinase in TREM2‐Mediated Microglia Activation and Phagocytosis
No full textBackground:
Lyn kinase, a member of the Src family of tyrosine kinases, predominantly phosphorylates ITIM and ITAM motifs linked to immune receptors and adaptor proteins, and is emerging as a target for Alzheimer’s disease (AD). The role of Lyn in TREM2‐mediated microglial activation and phagocytosis, a critical pathway for clearing Aβ plaques, remains unclear and potent, selective, and brain penetrant Lyn inhibitors are unavailable. In this study, we report the characterization of Lyn kinase inhibitors from the literature as well as the establishment of an advanced virtual screening platform at the IUSM‐Purdue‐TREAT‐AD center to identify new type II Lyn inhibitors suitable as molecular probes.
Method:
We first performed a thorough literature survey and found 14 reported Lyn kinase inhibitors. We then validated their Lyn inhibitor activities and Lyn selectivities using the HotSpot kinase assay. We tested these compounds for microglia activation in a high‐content imaging assay using HMC3 (human) and BV2 (mouse) microglia‐like cell lines. We also performed kinome profiling in these cells to evaluate cellular target engagement and selectivity. Finally, we screened a million‐compounds using a computational pipeline that combined molecular docking, shape‐based screening, and MD simulations to identify novel and potent type II Lyn kinase inhibitors.
Result:
Our findings revealed that Type I inhibitors, particularly Saracatinib and Bosutinib, potently inhibit Lyn within the picomolar (pM) range. On the other hand, Type II inhibitors, such as Masitinib and Imatinib, displayed pronounced >20‐fold selectivity for Lyn over Hck with low nM Lyn inhibitor activities. Saracatinib and Bosutinib significantly induced phagocytosis in HMC3 cells, whereas Type II inhibitors demonstrated moderate activity in both HMC3 and BV2 cells. Our virtual screening platform identified a new type II Lyn inhibitor with picomolar activity and good Lyn/Hck selectivity.
Conclusion:
We have successfully evaluated previously reported inhibitors and introduced a novel type II Lyn kinase inhibitor with picomolar (pM) activities suitable for use as chemical probes to investigate the role of Lyn in TREM2‐mediated microglial activation
Characterization and molecular targeting of CFIm25 (NUDT21/CPSF5) mRNA using miRNAs
No full textChanges in protein levels of the mammalian cleavage factor, CFIm25, play a role in regulating pathological processes including neural dysfunction, fibrosis, and tumorigenesis. However, despite these effects, little is known about how CFIm25 (NUDT21) expression is regulated at the RNA level. A potential regulator of NUDT21 mRNA are small non-coding microRNAs (miRNAs). In general, miRNAs bind to the 3'untranslated regions (3'UTRs) and can target the bound mRNA for degradation or inhibit translation thus affecting the levels of protein in cells. Interestingly, a mechanism known as alternative polyadenylation (APA) enables mRNAs to escape miRNA regulation by generating mRNAs with 3'UTRs of different sizes. As many miRNA target sites are located within the 3'UTR, shortening the 3'UTR allows mRNAs to evade miRNAs targeting this region. The differences in the lengths and the sequence composition of the 3'UTRs may also impact the mRNA's translatability and subcellular localization. APA has been reported to regulate over 70% of protein coding genes, thus increasing the transcript repertoire. Several proteins, including mammalian cleavage factor, CFIm25 (NUDT21), have been shown to regulate APA. In this study we wanted to determine whether CFIm25 (NUDT21), itself a regulator of APA, undergoes APA to evade miRNA regulation. We used the blood cancer mantle cell lymphoma (MCL) cells as a model and showed that in these cells, NUDT21 is relatively stable with a long half-life. In addition, the NUDT21 pre-mRNA undergoes alternative APA within the same terminal exon. The three different sized NUDT21 mRNAs have different 3'UTR lengths and they each use a different canonical polyadenylation signal, AAUAAA, for 3'end cleavage and polyadenylation. Use of miRNA mimics and inhibitors showed that miR-23a, miR-222, and miR-323a play a significant role in regulating NUDT21 expression. Hence, these results suggest that NUDT21 mRNA is stable and the different 3'UTRs generated through APA of NUDT21 play an important role in evading miRNA regulation and offers insights into how levels of CFIm25 (NUDT21) may be fine-tuned as needed under different physiological and pathological conditions