Revolutionizing DNA repair research and cancer therapy with CRISPR-Cas screens.

All organisms possess molecular mechanisms that govern DNA repair and associated DNA damage response (DDR) processes. Owing to their relevance to human disease, most notably cancer, these mechanisms have been studied extensively, yet new DNA repair and/or DDR factors and functional interactions between them are still being uncovered. The emergence of CRISPR technologies and CRISPR-based genetic screens has enabled genome-scale analyses of gene-gene and gene-drug interactions, thereby providing new insights into cellular processes in distinct DDR-deficiency genetic backgrounds and conditions. In this Review, we discuss the mechanistic basis of CRISPR-Cas genetic screening approaches and describe how they have contributed to our understanding of DNA repair and DDR pathways. We discuss how DNA repair pathways are regulated, and identify and characterize crosstalk between them. We also highlight the impacts of CRISPR-based studies in identifying novel strategies for cancer therapy, and in understanding, overcoming and even exploiting cancer-drug resistance, for example in the contexts of PARP inhibition, homologous recombination deficiencies and/or replication stress. Lastly, we present the DDR CRISPR screen (DDRcs) portal , in which we have collected and reanalysed data from CRISPR screen studies and provide a tool for systematically exploring them.

Unrepaired base excision repair intermediates in template DNA strands trigger replication fork collapse and PARP inhibitor sensitivity.

DNA single-strand breaks (SSBs) disrupt DNA replication and induce chromosome breakage. However, whether SSBs induce chromosome breakage when present behind replication forks or ahead of replication forks is unclear. To address this question, we exploited an exquisite sensitivity of SSB repair-defective human cells lacking PARP activity or XRCC1 to the thymidine analogue 5-chloro-2'-deoxyuridine (CldU). We show that incubation with CldU in these cells results in chromosome breakage, sister chromatid exchange, and cytotoxicity by a mechanism that depends on the S phase activity of uracil DNA glycosylase (UNG). Importantly, we show that CldU incorporation in one cell cycle is cytotoxic only during the following cell cycle, when it is present in template DNA. In agreement with this, while UNG induces SSBs both in nascent strands behind replication forks and in template strands ahead of replication forks, only the latter trigger fork collapse and chromosome breakage. Finally, we show that BRCA-defective cells are hypersensitive to CldU, either alone and/or in combination with PARP inhibitor, suggesting that CldU may have clinical utility.

SOX9 maintains human foetal lung tip progenitor state by enhancing WNT and RTK signalling.

The balance between self-renewal and differentiation in human foetal lung epithelial progenitors controls the size and function of the adult organ. Moreover, progenitor cell gene regulation networks are employed by both regenerating and malignant lung cells, where modulators of their effects could potentially be of therapeutic value. Details of the molecular networks controlling human lung progenitor self-renewal remain unknown. We performed the first CRISPRi screen in primary human lung organoids to identify transcription factors controlling progenitor self-renewal. We show that SOX9 promotes proliferation of lung progenitors and inhibits precocious airway differentiation. Moreover, by identifying direct transcriptional targets using Targeted DamID, we place SOX9 at the centre of a transcriptional network, which amplifies WNT and RTK signalling to stabilise the progenitor cell state. In addition, the proof-of-principle CRISPRi screen and Targeted DamID tools establish a new workflow for using primary human organoids to elucidate detailed functional mechanisms underlying normal development and disease.

A hormone-dependent module regulating energy balance.

Under fasting conditions, metazoans maintain energy balance by shifting from glucose to fat burning. In the fasted state, SIRT1 promotes catabolic gene expression by deacetylating the forkhead factor FOXO in response to stress and nutrient deprivation. The mechanisms by which hormonal signals regulate FOXO deacetylation remain unclear, however. We identified a hormone-dependent module, consisting of the Ser/Thr kinase SIK3 and the class IIa deacetylase HDAC4, which regulates FOXO activity in Drosophila. During feeding, HDAC4 is phosphorylated and sequestered in the cytoplasm by SIK3, whose activity is upregulated in response to insulin. SIK3 is inactivated during fasting, leading to the dephosphorylation and nuclear translocation of HDAC4 and to FOXO deacetylation. SIK3 mutant flies are starvation sensitive, reflecting FOXO-dependent increases in lipolysis that deplete triglyceride stores; reducing HDAC4 expression restored lipid accumulation. Our results reveal a hormone-regulated pathway that functions in parallel with the nutrient-sensing SIRT1 pathway to maintain energy balance.

Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows.

Quantifying the flow of cerebrospinal fluid (CSF) is crucial for understanding brain waste clearance and nutrient delivery, as well as edema in pathological conditions such as stroke. However, existing in vivo techniques are limited to sparse velocity measurements in pial perivascular spaces (PVSs) or low-resolution measurements from brain-wide imaging. Additionally, volume flow rate, pressure, and shear stress variation in PVSs are essentially impossible to measure in vivo. Here, we show that artificial intelligence velocimetry (AIV) can integrate sparse velocity measurements with physics-informed neural networks to quantify CSF flow in PVSs. With AIV, we infer three-dimensional (3D), high-resolution velocity, pressure, and shear stress. Validation comes from training with 70% of PTV measurements and demonstrating close agreement with the remaining 30%. A sensitivity analysis on the AIV inputs shows that the uncertainty in AIV inferred quantities due to uncertainties in the PVS boundary locations inherent to in vivo imaging is less than 30%, and the uncertainty from the neural net initialization is less than 1%. In PVSs of N = 4 wild-type mice we find mean flow speed 16.33 ± 11.09 µm/s, volume flow rate 2.22 ± 1.983 × 103 µm3/s, axial pressure gradient ( - 2.75 ± 2.01)×10-4 Pa/µm (-2.07 ± 1.51 mmHg/m), and wall shear stress (3.00 ± 1.45)×10-3 Pa (all mean ± SE). Pressure gradients, flow rates, and resistances agree with prior predictions. AIV infers in vivo PVS flows in remarkable detail, which will improve fluid dynamic models and potentially clarify how CSF flow changes with aging, Alzheimer's disease, and small vessel disease.

Phosphoproteomic identification of ULK substrates reveals VPS15-dependent ULK/VPS34 interplay in the regulation of autophagy.

Autophagy is a process through which intracellular cargoes are catabolised inside lysosomes. It involves the formation of autophagosomes initiated by the serine/threonine kinase ULK and class III PI3 kinase VPS34 complexes. Here, unbiased phosphoproteomics screens in mouse embryonic fibroblasts deleted for Ulk1/2 reveal that ULK loss significantly alters the phosphoproteome, with novel high confidence substrates identified including VPS34 complex member VPS15 and AMPK complex subunit PRKAG2. We identify six ULK-dependent phosphorylation sites on VPS15, mutation of which reduces autophagosome formation in cells and VPS34 activity in vitro. Mutation of serine 861, the major VPS15 phosphosite, decreases both autophagy initiation and autophagic flux. Analysis of VPS15 knockout cells reveals two novel ULK-dependent phenotypes downstream of VPS15 removal that can be partially recapitulated by chronic VPS34 inhibition, starvation-independent accumulation of ULK substrates and kinase activity-regulated recruitment of autophagy proteins to ubiquitin-positive structures.

Spike ripples localize the epileptogenic zone best: an international intracranial study.

We evaluated whether spike ripples, the combination of epileptiform spikes and ripples, provide a reliable and improved biomarker for the epileptogenic zone compared with other leading interictal biomarkers in a multicentre, international study. We first validated an automated spike ripple detector on intracranial EEG recordings. We then applied this detector to subjects from four centres who subsequently underwent surgical resection with known 1-year outcomes. We evaluated the spike ripple rate in subjects cured after resection [International League Against Epilepsy Class 1 outcome (ILAE 1)] and those with persistent seizures (ILAE 2-6) across sites and recording types. We also evaluated available interictal biomarkers: spike, spike-gamma, wideband high frequency oscillation (HFO, 80-500 Hz), ripple (80-250 Hz) and fast ripple (250-500 Hz) rates using previously validated automated detectors. The proportion of resected events was computed and compared across subject outcomes and biomarkers. Overall, 109 subjects were included. Most spike ripples were removed in subjects with ILAE 1 outcome (P < 0.001), and this was qualitatively observed across all sites and for depth and subdural electrodes (P < 0.001 and P < 0.001, respectively). Among ILAE 1 subjects, the mean spike ripple rate was higher in the resected volume (0.66/min) than in the non-removed tissue (0.08/min, P < 0.001). A higher proportion of spike ripples were removed in subjects with ILAE 1 outcomes compared with ILAE 2-6 outcomes (P = 0.06). Among ILAE 1 subjects, the proportion of spike ripples removed was higher than the proportion of spikes (P < 0.001), spike-gamma (P < 0.001), wideband HFOs (P < 0.001), ripples (P = 0.009) and fast ripples (P = 0.009) removed. At the individual level, more subjects with ILAE 1 outcomes had the majority of spike ripples removed (79%, 38/48) than spikes (69%, P = 0.12), spike-gamma (69%, P = 0.12), wideband HFOs (63%, P = 0.03), ripples (45%, P = 0.01) or fast ripples (36%, P < 0.001) removed. Thus, in this large, multicentre cohort, when surgical resection was successful, the majority of spike ripples were removed. Furthermore, automatically detected spike ripples localize the epileptogenic tissue better than spikes, spike-gamma, wideband HFOs, ripples and fast ripples.

The Differing Effects of Sleep on Ictal and Interictal Network Dynamics in Drug-Resistant Epilepsy.

OBJECTIVE: Sleep has important influences on focal interictal epileptiform discharges (IEDs), and the rates and spatial extent of IEDs are increased in non-rapid eye movement (NREM) sleep. In contrast, the influence of sleep on seizures is less clear, and its effects on seizure topography are poorly documented. We evaluated the influences of NREM sleep on ictal spatiotemporal dynamics and contrasted these with interictal network dynamics. METHODS: We included patients with drug-resistant focal epilepsy who underwent continuous intracranial electroencephalography (iEEG) with depth electrodes. Patients were selected if they had 1 to 3 seizures from each vigilance state, wakefulness and NREM sleep, within a 48-hour window, and under the same antiseizure medication. A 10-minute epoch of the interictal iEEG was selected per state, and IEDs were detected automatically. A total of 25 patients (13 women; aged 32.5 ± 7.1 years) were included. RESULTS: The seizure onset pattern, duration, spatiotemporal propagation, and latency of ictal high-frequency activity did not differ significantly between wakefulness and NREM sleep (all p > 0.05). In contrast, IED rates and spatial distribution were increased in NREM compared with wakefulness (p < 0.001, Cliff's d = 0.48 and 0.49). The spatial overlap between vigilance states was higher for seizures (57.1 ± 40.1%) than IEDs (41.7 ± 46.2%; p = 0.001, Cliff's d = 0.51). INTERPRETATION: In contrast to its effects on IEDs, NREM sleep does not affect ictal spatiotemporal dynamics. This suggests that once the brain surpasses the seizure threshold, it will follow the underlying epileptic network irrespective of the vigilance state. These findings offer valuable insights into neural network dynamics in epilepsy and have important clinical implications for localizing seizure foci. ANN NEUROL 2023.

A Subpopulation of Spikes Predicts Successful Epilepsy Surgery Outcome.

OBJECTIVE: Epileptic spikes are the traditional interictal electroencephalographic (EEG) biomarker for epilepsy. Given their low specificity for identifying the epileptogenic zone (EZ), they are given only moderate attention in presurgical evaluation. This study aims to demonstrate that it is possible to identify specific spike features in intracranial EEG that optimally define the EZ and predict surgical outcome. METHODS: We analyzed spike features on stereo-EEG segments from 83 operated patients from 2 epilepsy centers (37 Engel IA) in wakefulness, non-rapid eye movement sleep, and rapid eye movement sleep. After automated spike detection, we investigated 135 spike features based on rate, morphology, propagation, and energy to determine the best feature or feature combination to discriminate the EZ in seizure-free and non-seizure-free patients by applying 4-fold cross-validation. RESULTS: The rate of spikes with preceding gamma activity in wakefulness performed better for surgical outcome classification (4-fold area under receiver operating characteristics curve [AUC] = 0.755 ± 0.07) than the seizure onset zone, the current gold standard (AUC = 0.563 ± 0.05, p = 0.015) and the ripple rate, an emerging seizure-independent biomarker (AUC = 0.537 ± 0.07, p = 0.006). Channels with a spike-gamma rate exceeding 1.9/min had an 80% probability of being in the EZ. Combining features did not improve the results. INTERPRETATION: Resection of brain regions with high spike-gamma rates in wakefulness is associated with a high probability of achieving seizure freedom. This rate could be applied to determine the minimal number of spiking channels requiring resection. In addition to quantitative analysis, this feature is easily accessible to visual analysis, which could aid clinicians during presurgical evaluation. ANN NEUROL 2023;93:522-535.

Computational fluid dynamics based digital twins of fixed bed bioreactors validate scaling principles for recombinant adeno-associated virus gene therapy manufacturing.

Gene therapy using recombinant adeno-associated virus (rAAV) as delivery vehicles has garnered much interest in recent years. There are still significant gaps in our fundamental understanding of the manufacturing processes to deliver sufficient products. Manufacturing efforts of rAAV using HEK293 cells have commonly relied on fixed bed falling film bioreactors like the iCELLis®. We used computational fluid dynamics (CFD) to validate the operating conditions required for a predictive iCELLis® 500 scale-down model. The small-scale and at-scale systems have different flow paths causing validation of the corresponding agitation rates required to achieve the same linear flow through the fixed bed across scales to be non-trivial. Therefore, we used CFD to predict the theoretical scaling relationship. In addition, CFD could predict kLa differences between the two systems and the operating conditions required to match kLa between scales. We also confirmed that the location of DO control must be the same in both systems to achieve proper scaling. Experimental runs confirming the validity of the novel scale-down model showed that based on the modifications to the iCELLis® Nano system, we achieved similar DO, key metabolite, pH, and GC titer trends in both systems.

CFD-based bioreactor model with proportional-integral-derivative controller functionality for dissolved oxygen and pH.

A physics-based model for predicting cell culture fluid properties inside a stirred tank bioreactor with embedded PID controller logic is presented. The model evokes a time-accurate solution to the fluid velocity field and overall volumetric mass transfer coefficient, as well as the ongoing effects of interfacial mass transfer, species mixing, and aqueous chemical reactions. The modeled system also includes a direct coupling between process variables and system control variables via embedded controller logic. Satisfactory agreement is realized between the model prediction and measured bioreactor data in terms of the steady-state operating conditions and the response to setpoint changes. Simulation runtimes are suitable for industrial research and design timescales.

Natural language processing pipeline to extract prostate cancer-related information from clinical notes.

OBJECTIVES: To develop an automated pipeline for extracting prostate cancer-related information from clinical notes. MATERIALS AND METHODS: This retrospective study included 23,225 patients who underwent prostate MRI between 2017 and 2022. Cancer risk factors (family history of cancer and digital rectal exam findings), pre-MRI prostate pathology, and treatment history of prostate cancer were extracted from free-text clinical notes in English as binary or multi-class classification tasks. Any sentence containing pre-defined keywords was extracted from clinical notes within one year before the MRI. After manually creating sentence-level datasets with ground truth, Bidirectional Encoder Representations from Transformers (BERT)-based sentence-level models were fine-tuned using the extracted sentence as input and the category as output. The patient-level output was determined by compilation of multiple sentence-level outputs using tree-based models. Sentence-level classification performance was evaluated using the area under the receiver operating characteristic curve (AUC) on 15% of the sentence-level dataset (sentence-level test set). The patient-level classification performance was evaluated on the patient-level test set created by radiologists by reviewing the clinical notes of 603 patients. Accuracy and sensitivity were compared between the pipeline and radiologists. RESULTS: Sentence-level AUCs were ≥ 0.94. The pipeline showed higher patient-level sensitivity for extracting cancer risk factors (e.g., family history of prostate cancer, 96.5% vs. 77.9%, p < 0.001), but lower accuracy in classifying pre-MRI prostate pathology (92.5% vs. 95.9%, p = 0.002) and treatment history of prostate cancer (95.5% vs. 97.7%, p = 0.03) than radiologists, respectively. CONCLUSION: The proposed pipeline showed promising performance, especially for extracting cancer risk factors from patient's clinical notes. CLINICAL RELEVANCE STATEMENT: The natural language processing pipeline showed a higher sensitivity for extracting prostate cancer risk factors than radiologists and may help efficiently gather relevant text information when interpreting prostate MRI. KEY POINTS: When interpreting prostate MRI, it is necessary to extract prostate cancer-related information from clinical notes. This pipeline extracted the presence of prostate cancer risk factors with higher sensitivity than radiologists. Natural language processing may help radiologists efficiently gather relevant prostate cancer-related text information.

The autism spectrum among transgender youth: default mode functional connectivity.

The common intersection of autism and transgender identities has been described in clinical and community contexts. This study investigates autism-related neurophenotypes among transgender youth. Forty-five transgender youth, evenly balanced across non-autistic, slightly subclinically autistic, and full-criteria autistic subgroupings, completed resting-state functional magnetic resonance imaging to examine functional connectivity. Results confirmed hypothesized default mode network (DMN) hub hyperconnectivity with visual and motor networks in autism, partially replicating previous studies comparing cisgender autistic and non-autistic adolescents. The slightly subclinically autistic group differed from both non-autistic and full-criteria autistic groups in DMN hub connectivity to ventral attention and sensorimotor networks, falling between non-autistic and full-criteria autistic groups. Autism traits showed a similar pattern to autism-related group analytics, and also related to hyperconnectivity between DMN hub and dorsal attention network. Internalizing, gender dysphoria, and gender minority-related stigma did not show connectivity differences. Connectivity differences within DMN followed previously reported patterns by designated sex at birth (i.e. female birth designation showing greater within-DMN connectivity). Overall, findings suggest behavioral diagnostics and autism traits in transgender youth correspond to observable differences in DMN hub connectivity. Further, this study reveals novel neurophenotypic characteristics associated with slightly subthreshold autism, highlighting the importance of research attention to this group.

Analysis of Top 100 Articles Cited in Top Pain Journals: A Comprehensive Two Decade Bibliometric Analysis.

PURPOSE OF REVIEW: A bibliometric analysis was performed to analyze and compare the top 100 articles from the most well-known five pain journals: Pain, Pain Physician, Pain Medicine, Regional Anesthesia & Pain Medicine, and Journal of Pain. A query of the Scopus database was performed to filter the top 200 most cited articles from each journal. CY score was calculated for the top 200 articles from each journal by dividing the total number of citations by the number of years the article has been published. RECENT FINDINGS: All articles had a collective analysis of the top CY scores, the top 100 of which were further analyzed. The pain subtype, type of publication, country of origin, and senior author were extrapolated from these top 100 articles. Frequency tables were organized, revealing Pain Journal as the highest publishing journal out of the top 100 articles. Chronic pain was the most studied subtype of pain and narrative reviews were the most common type of evidence. Studies were also organized in five-year epochs to analyze the frequency of publications in these intervals. Results show that 2010-2014 had the highest frequency of articles published overall. Journal Impact Factor (JIF) is also an objective indicator of the average number of citations per published article from each journal. The journal with the highest JIF was Pain with an impact factor of 7.926. (6).

Are children with food allergies more likely to have lower urinary tract symptoms? A case-control study.

INTRODUCTION: There are multiple historic reports linking lower urinary tract symptoms (LUTS) in children with food allergies (FA), but contemporary studies are sparse. The objective of this study was to evaluate a potential link between FA and LUTS in the pediatric population. We hypothesized that children with FAs are more likely to have LUTS. MATERIALS AND METHODS: After local IRB approval, pediatric patients (6-17 years [y]) with FAs proven by positive skin prick and/or serum IgE testing were invited to participate. A control group of pediatric patients without FAs was also recruited. All families/legal guardians signed informed consent, and all children signed written assent. Each participant filled out the Vancouver Symptom Score (VSS), a validated questionnaire for dysfunctional elimination syndrome, and the Pediatric Incontinence Questionnaire (PinQ), a validated quality of life assessment for children with bladder dysfunction. Demographic and clinical information were obtained retrospectively. RESULTS: From 2019-2020, 26 children with FAs and 57 without agreed to participate. Mean age was 9.3 y (IQR 7.9 y-13.5 y). There were no differences in gender, age, or race between the two cohorts. There were no significant differences between the two groups in mean VSS score or mean PinQ score. Four children with FAs (15%) and 15 children without (26%) had VSS score ≥ 11 (p = 0.339), indicating dysfunctional elimination. The median PinQ score was 0 (IQR 0-2) in both cohorts. CONCLUSIONS: This study did not identify an association between FAs and LUTS in a population of pediatric patients with laboratory proven FAs.

Crtc modulates fasting programs associated with 1-C metabolism and inhibition of insulin signaling.

Fasting in mammals promotes increases in circulating glucagon and decreases in circulating insulin that stimulate catabolic programs and facilitate a transition from glucose to lipid burning. The second messenger cAMP mediates effects of glucagon on fasting metabolism, in part by promoting the phosphorylation of CREB and the dephosphorylation of the cAMP-regulated transcriptional coactivators (CRTCs) in hepatocytes. In Drosophila, fasting also triggers activation of the single Crtc homolog in neurons, via the PKA-mediated phosphorylation and inhibition of salt-inducible kinases. Crtc mutant flies are more sensitive to starvation and oxidative stress, although the underlying mechanism remains unclear. Here we use RNA sequencing to identify Crtc target genes that are up-regulated in response to starvation. We found that Crtc stimulates a subset of fasting-inducible genes that have conserved CREB binding sites. In keeping with its role in the starvation response, Crtc was found to induce the expression of genes that inhibit insulin secretion (Lst) and insulin signaling (Impl2). In parallel, Crtc also promoted the expression of genes involved in one-carbon (1-C) metabolism. Within the 1-C pathway, Crtc stimulated the expression of enzymes that encode modulators of S-adenosyl-methionine metabolism (Gnmt and Sardh) and purine synthesis (ade2 and AdSl) Collectively, our results point to an important role for the CREB/CRTC pathway in promoting energy balance in the context of nutrient stress.

Hippocrates, the first aphorism, and decorum: A personal view of caution and guidance regarding Generation Z students.

Generation Z students can be challenging. The Internet, the Covid-19 epidemic, its political aftermath, and the substantial online educational content they have been required to endure, has left them with a perspective towards a work-life balance to which we older, more experienced faculty are not accustomed. Here, I give caution and guidance to my colleagues regarding their interactions with this cohort through my reading of the Hippocratic corpus.

Near-Field Coupling with a Nanoimprinted Probe for Dark Exciton Nanoimaging in Monolayer WSe2.

Tip-enhanced photoluminescence (TRPL) is a powerful technique for spatially and spectrally probing local optical properties of 2-dimensional (2D) materials that are modulated by the local heterogeneities, revealing inaccessible dark states due to bright state overlap in conventional far-field microscopy at room temperature. While scattering-type near-field probes have shown the potential to selectively enhance and reveal dark exciton emission, their technical complexity and sensitivity can pose challenges under certain experimental conditions. Here, we present a highly reproducible and easy-to-fabricate near-field probe based on nanoimprint lithography and fiber-optic excitation and collection. The novel near-field measurement configuration provides an ∼3 orders of magnitude out-of-plane Purcell enhancement, diffraction-limited excitation spot, and subdiffraction hyperspectral imaging resolution (below 50 nm) of dark exciton emission. The effectiveness of this high spatial XD mapping technique was then demonstrated through reproducible hyperspectral mapping of oxidized sites and bubble areas.

Direct Visualization of the Charge Transfer in a Graphene/α-RuCl3 Heterostructure via Angle-Resolved Photoemission Spectroscopy.

We investigate the electronic properties of a graphene and α-ruthenium trichloride (α-RuCl3) heterostructure using a combination of experimental techniques. α-RuCl3 is a Mott insulator and a Kitaev material. Its combination with graphene has gained increasing attention due to its potential applicability in novel optoelectronic devices. By using a combination of spatially resolved photoemission spectroscopy and low-energy electron microscopy, we are able to provide a direct visualization of the massive charge transfer from graphene to α-RuCl3, which can modify the electronic properties of both materials, leading to novel electronic phenomena at their interface. A measurement of the spatially resolved work function allows for a direct estimate of the interface dipole between graphene and α-RuCl3. Their strong coupling could lead to new ways of manipulating electronic properties of a two-dimensional heterojunction. Understanding the electronic properties of this structure is pivotal for designing next generation low-power optoelectronics devices.

Reduction of Environmental Pollutants and Travel Burden Through an Academic Medical Center-based Electronic Consultation Program.

Background: We evaluated the impact of electronic consultation (eConsult) in reducing the environmental pollutants associated with health care delivery. Methods: A retrospective analysis of the eConsult data between July 2018 and December 2022 was extracted from the electronic health record (Epic). Travel time and mileage from the patient home to the academic medical center (AMC) were calculated along with fuel expenditure and greenhouses gas savings. Projected savings through the end of the decade were forecast using a random walk model. Results: A total of 15,499 eConsults were submitted to AMC specialist providers from community primary care providers. Completed eConsults (n = 11,590) eliminated the need for a face-to-face visit with a specialist provider, eliminating mileage, fuel, time, and pollutants associated with face to face visits. In-state travel distance saved was 310,858 miles, travel time saved was 5,491 h, with an associated fuel reduction of 13,575 gallons and $56,893 savings. This reduced greenhouse gas emissions by 128 metric tons of carbon dioxide, 0.022 tons of nitrogen oxide, 0.005 tons of methane, and 0.001 tons of nitrous oxide. Out of state travel distance saved was 188,346 miles with 2,842 h reduced travel time, and associated fuel reduction of 8,225 gallons and of $34,118. Reduced greenhouse gas emissions were equivalent to 77 metric tons of carbon dioxide, 0.0132 tons of nitrogen oxide, 0.0033 tons of methane, and 0.0007 tons of nitrous oxide. Conclusion: This study indicates that medical care provided through telehealth modalities reduces the environmental impact of pollutants associated with face to face visits.