Dynamic Nuclear Polarization Enhanced Multiple-Quantum Spin Counting of Molecular Assemblies in Vitrified Solutions.

Crystallization pathways are essential to various industrial, geological, and biological processes. In nonclassical nucleation theory, prenucleation clusters (PNCs) form, aggregate, and crystallize to produce higher order assemblies. Microscopy and X-ray techniques have limited utility for PNC analysis due to the small size (0.5-3 nm) and time stability constraints. We present a new approach for analyzing PNC formation based on 31P nuclear magnetic resonance (NMR) spin counting of vitrified molecular assemblies. The use of glassing agents ensures that vitrification generates amorphous aqueous samples and offers conditions for performing dynamic nuclear polarization (DNP)-amplified NMR spectroscopy. We demonstrate that molecular adenosine triphosphate along with crystalline, amorphous, and clustered calcium phosphate materials formed via a nonclassical growth pathway can be differentiated from one another by the number of dipolar coupled 31P spins. We also present an innovative approach for examining spin counting data, demonstrating that a knowledge-based fitting of integer multiples of cosine wave functions, instead of the traditional Fourier transform, provides a more physically meaningful retrieval of the existing frequencies. This is the first report of multiquantum spin counting of assemblies formed in solution as captured under vitrified DNP conditions, which can be useful for future analysis of PNCs and other aqueous molecular clusters.

Integrating Mobile and Fixed-Site Black Carbon Measurements to Bridge Spatiotemporal Gaps in Urban Air Quality.

Urban air pollution can vary sharply in space and time. However, few monitoring strategies can concurrently resolve spatial and temporal variation at fine scales. Here, we present a new measurement-driven spatiotemporal modeling approach that transcends the individual limitations of two complementary sampling paradigms: mobile monitoring and fixed-site sensor networks. We develop, validate, and apply this model to predict black carbon (BC) using data from an intensive, 100-day field study in West Oakland, CA. Our spatiotemporal model exploits coherent spatial patterns derived from a multipollutant mobile monitoring campaign to fill spatial gaps in time-complete BC data from a low-cost sensor network. Our model performs well in reconstructing patterns at fine spatial and temporal resolution (30 m, 15 min), demonstrating strong out-of-sample correlations for both mobile (Pearson's R ∼ 0.77) and fixed-site measurements (R ∼ 0.95) while revealing features that are not effectively captured by a single monitoring approach in isolation. The model reveals sharp concentration gradients near major emission sources while capturing their temporal variability, offering valuable insights into pollution sources and dynamics.

Evaluating a novel model of hepatitis B care, Hep B PAST, in the Northern Territory of Australia: results from a prospective, population-based study.

Background: The Northern Territory (NT) has the highest prevalence of chronic hepatitis B (CHB) in Australia. The Hep B PAST program aims to improve health outcomes for people living with CHB. Methods: This mixed methods study involves First Nations peoples living in the NT. We used participatory action research principles across three steps: 1. Foundation step: establishing hepatitis B virus (HBV) status and linkage to care; 2. Capacity building: training the health workforce; 3. Supported transition to primary healthcare: implementation of the "Hub and Spoke" model and in-language resources. Analysis occurred at three time points: 1. Pre-Hep B PAST (2018); 2. Foundation step (2020); and 3. Completion of Hep B PAST (2023). Evaluation focuses on four key indicators, the number of people: 1) with documented HBV status; 2) diagnosed with CHB; 3) receiving care; and 4) receiving treatment. Findings: Hep B PAST (2018-23) reached 40,555 people. HBV status was documented in 11% (1192/10,853), 79.2% (26,075/32,915) and 90.8% (28,675/31,588) of people at pre-Hep B PAST, foundation step, and completion respectively. An estimated 99.9% (821/822) of people were diagnosed, 86.3% (709/822) engaged in care, and 24.1% (198/822) on antiviral treatment at completion. CHB prevalence in the study population is 2.6%, decreasing from 6.1% to 0.4% in the pre- and post-vaccination cohorts. Interpretation: Hep B PAST is an effective model of care. Partner health services are exceeding elimination targets. This model could enable other countries to enhance the cascade of care and work towards eliminating HBV. Funding: National Health and Medical Research Council.

Evaluation of 3D T1-weighted spoiled gradient echo MR image quality using artificial intelligence image reconstruction techniques in the pediatric brain.

PURPOSE: To assess image quality and diagnostic confidence of 3D T1-weighted spoiled gradient echo (SPGR) MRI using artificial intelligence (AI) reconstruction. MATERIALS AND METHODS: This prospective, IRB-approved study enrolled 50 pediatric patients (mean age = 11.8 ± 3.1 years) undergoing clinical brain MRI. In addition to standard of care (SOC) compressed SENSE (CS = 2.5), 3D T1-weighted SPGR images were obtained with higher CS acceleration factors (5 and 8) to evaluate the ability of AI reconstruction to improve image quality and reduce scan time. Images were reviewed independently on dedicated research PACS workstations by two neuroradiologists. Quantitative analysis of signal intensities to calculate apparent grey and white matter signal to noise (aSNR) and grey-white matter apparent contrast to noise ratios (aCNR) was performed. RESULTS: AI improved overall image quality compared to standard CS reconstruction in 35% (35/100) of evaluations in CS = 2.5 (average scan time = 221 ± 6.9 s), 100% (46/46) of CS = 5 (average scan time = 113.3 ± 4.6 s) and 94% (47/50) of CS = 8 (average scan time = 74.1 ± 0.01 s). Quantitative analysis revealed significantly higher grey matter aSNR, white matter aSNR and grey-white matter aCNR with AI reconstruction compared to standard reconstruction for CS 5 and 8 (all p-values < 0.001), however not for CS 2.5. CONCLUSIONS: AI reconstruction improved overall image quality and gray-white matter qualitative and quantitative aSNR and aCNR in highly accelerated (CS = 5 and 8) 3D T1W SPGR images in the majority of pediatric patients.

Phase transfer catalysts shift the pathway to transmetalation in biphasic Suzuki-Miyaura cross-couplings.

The Suzuki-Miyaura coupling is a widely used C-C bond forming reaction. Numerous mechanistic studies have enabled the use of low catalyst loadings and broad functional group tolerance. However, the dominant mode of transmetalation remains controversial and likely depends on the conditions employed. Herein we detail a mechanistic study of the palladium-catalyzed Suzuki-Miyaura coupling under biphasic conditions. The use of phase transfer catalysts results in a remarkable 12-fold rate enhancement in the targeted system. A shift from an oxo-palladium based transmetalation to a boronate-based pathway lies at the root of this activity. Furthermore, a study of the impact of different water loadings reveals reducing the proportion of the aqueous phase increases the reaction rate, contrary to reaction conditions typically employed in the literature. The importance of these findings is highlighted by achieving an exceptionally broad substrate scope with benzylic electrophiles using a 10-fold reduction in catalyst loading relative to literature precedent.

Adapting Surgical Coaching: Feasibility and Perceptions of Intraoperative Resident Peer Coaching.

INTRODUCTION: Surgical coaching is utilized to enhance technical, nontechnical, and teaching skills. This study aims to evaluate the feasibility and benefit of a resident peer coaching program. METHODS: Chief residents (postgraduate year 5) acted as coaches for junior residents (postgraduate year 1-3, "coachees"). All participants completed the Harvard Surgical Coaching for Operative Performance Enhancement curriculum. The coaching structure included 1) preoperative goal setting, 2) unscrubbed intraoperative observation, and 3) postoperative debrief. Upon completion, residents were surveyed to assess their experience. Descriptive and thematic analyses were performed. RESULTS: There were 22 participants (6 coaches, 16 coachees). Five (83.3%) coaches and 14 (87.5%) coachees reported the program was useful, citing dedicated reflection outside the operating room, in-depth feedback, and structured self-assessment with increased accountability. Thirteen (81.3%) coachees reported perceived improvement in technical skills and 12 (75%) within nontechnical skills. All coaches felt they benefited and improved their ability to provide feedback. When asked how coaching compared to usual methods of operative feedback, 14 (87.5%) coachees and 5 (83.3%) coaches reported it was better, with only 1 coachee reporting it was worse. Benefits over typical operating room teaching included more feedback provided, more specific feedback, and the benefit of peer relationships. Twelve (54.5%) residents cited difficulty with coordinating sessions, but 21 (95.5%) reported that they would participate again. CONCLUSIONS: Implementation of a resident peer surgical coaching program is feasible. Both coaches and coachees perceive significant benefit with improvement in technical, nontechnical, and feedback delivery skills. Given preference over other methods of operative feedback, expansion of peer coaching programs is warranted.

Contemporary Evaluation of Work-Life Integration and Wellbeing in US Surgical Residents: A National Mixed-Methods Study.

BACKGROUND: The demands of surgical training present challenges for work-life integration (WLI). We sought to identify factors associated with work-life conflicts and to understand how programs support WLI. STUDY DESIGN: A cross-sectional national survey conducted after the 2020 American Board of Surgery In-Training Examination queried 4 WLI items. Multivariable regression models evaluated factors associated with (1) work-life conflicts and (2) well-being (career dissatisfaction, burnout, thoughts of attrition, suicidality). Semi-structured interviews conducted with faculty and residents from 15 general surgery programs were analyzed to identify strategies for supporting WLI. RESULTS: Of 7,233 residents (85.5% response rate) 5,133 had data available on work-life conflicts. 44.3% reported completing non-educational task-work at home, 37.6% were dissatisfied with time for personal life (e.g., hobbies), 51.6% with maintaining healthy habits (e.g., exercise), and 48.0% with performing routine health maintenance (e.g., dentist). In multivariable analysis, parents and female residents were more likely to report work-life conflicts (all p<0.05). After adjusting for other risk factors (e.g., duty-hour violations, and mistreatment), residents with work-life conflicts remained at increased risk for career dissatisfaction, burnout, thoughts of attrition, and suicidality (all p<0.05). Qualitative analysis revealed interventions for supporting WLI including (1) protecting time for health maintenance (e.g., therapy); (2) explicitly supporting life outside of work (e.g., prioritizing time with family); and (3) allowing meaningful autonomy in scheduling (e.g., planning for major life events). CONCLUSIONS: Work-life conflicts are common among surgical residents and are associated with poor resident well-being. Well-designed program-level interventions have the potential to support WLI in surgical residency.

Predictors of Incident Stroke and Subsequent Mortality Among a Sample of Veterans with Experience of Housing Instability.

Homelessness is associated with poor health outcomes and early development of cardiovascular disease. This study investigated the correlates of incident stroke and its association with mortality among Veterans experiencing housing instability. Using a national sample of Veterans (n=565,608) with incident housing instability between 2014-2018, we compared characteristics of Veterans who did and did not experience incident stroke and conducted logistic regressions to assess two outcomes: incident stroke and mortality. Almost four percent experienced a first stroke and were more frequently male, older than 55 years, Black, and non-Hispanic. A higher rate of mortality was observed among those with a first stroke compared with those with no stroke (17.6% vs. 10.8%), although the difference was not statistically significant. Incident stroke was associated with triple the odds of death among unstably-housed Veterans compared with those who did not have an incident stroke. Implications include the need to screen and monitor for stroke risk among Veterans with experience of housing instability, particularly for those who are older.

Pharmacologically inducing anoikis offers novel therapeutic opportunities in hepatocellular carcinoma.

Tumor metastasis occurs in hepatocellular carcinoma (HCC), leading to tumor progression and therapeutic failure. Anoikis is a matrix detachment-induced apoptosis, also known as detachment-induced cell death, and mechanistically prevents tumor cells from escaping their native extracellular matrix to metastasize to new organs. Deciphering the regulators and mechanisms of anoikis in cancer metastasis is urgently needed to treat HCC. Several natural and synthetic products induce anoikis in HCC cells and in vivo models. Here, we first briefly summarize the current understanding of the molecular mechanisms of anoikis regulation and relevant regulators involved in HCC metastasis. Then we discuss the therapeutic potential of pharmacological induction of anoikis as a potential treatment against HCC. Finally, we discuss the key limitations of this therapeutic paradigm and propose possible strategies to overcome them. Cumulatively this review suggests that the pharmacological induction of anoikis can be used a promising therapeutic modality against HCC.

Multi-parametric atlas of the pre-metastatic liver for prediction of metastatic outcome in early-stage pancreatic cancer.

Metastasis occurs frequently after resection of pancreatic cancer (PaC). In this study, we hypothesized that multi-parametric analysis of pre-metastatic liver biopsies would classify patients according to their metastatic risk, timing and organ site. Liver biopsies obtained during pancreatectomy from 49 patients with localized PaC and 19 control patients with non-cancerous pancreatic lesions were analyzed, combining metabolomic, tissue and single-cell transcriptomics and multiplex imaging approaches. Patients were followed prospectively (median 3 years) and classified into four recurrence groups; early (<6 months after resection) or late (>6 months after resection) liver metastasis (LiM); extrahepatic metastasis (EHM); and disease-free survivors (no evidence of disease (NED)). Overall, PaC livers exhibited signs of augmented inflammation compared to controls. Enrichment of neutrophil extracellular traps (NETs), Ki-67 upregulation and decreased liver creatine significantly distinguished those with future metastasis from NED. Patients with future LiM were characterized by scant T cell lobular infiltration, less steatosis and higher levels of citrullinated H3 compared to patients who developed EHM, who had overexpression of interferon target genes (MX1 and NR1D1) and an increase of CD11B+ natural killer (NK) cells. Upregulation of sortilin-1 and prominent NETs, together with the lack of T cells and a reduction in CD11B+ NK cells, differentiated patients with early-onset LiM from those with late-onset LiM. Liver profiles of NED closely resembled those of controls. Using the above parameters, a machine-learning-based model was developed that successfully predicted the metastatic outcome at the time of surgery with 78% accuracy. Therefore, multi-parametric profiling of liver biopsies at the time of PaC diagnosis may determine metastatic risk and organotropism and guide clinical stratification for optimal treatment selection.

New insights into the mechanism of resistance to lenvatinib and strategies for lenvatinib sensitization in hepatocellular carcinoma.

Lenvatinib is a multikinase inhibitor that suppresses vascular endothelial growth factor receptor (VEGFR), fibroblast growth factor receptor (FGFR), platelet-derived growth factor receptor α (PDGFRα), as well as the proto-oncogenes RET and KIT. Lenvatinib has been approved by the US Food and Drug Administration (FDA) for the first-line treatment of hepatocellular carcinoma (HCC) due to its superior efficacy when compared to sorafenib. Unfortunately, the development of drug resistance to lenvatinib is becoming increasingly common. Thus, there is an urgent need to identify the factors that lead to drug resistance and ways to mitigate it. We summarize the molecular mechanisms that lead to lenvatinib resistance (LR) in HCC, which involve programmed cell death (PCD), translocation processes, and changes in the tumor microenvironment (TME), and provide strategies to reverse resistance.

Genomic investigation and clinical correlates of the in vitro ß-lactam: NaHCO3 responsiveness phenotype among methicillin-resistant Staphylococcus aureus isolates from a randomized clinical trial.

NaHCO3 responsiveness is a novel phenotype where some methicillin-resistant Staphylococcus aureus (MRSA) isolates exhibit significantly lower minimal inhibitory concentrations (MIC) to oxacillin and/or cefazolin in the presence of NaHCO3. NaHCO3 responsiveness correlated with treatment response to ß-lactams in an endocarditis animal model. We investigated whether treatment of NaHCO3-responsive strains with ß-lactams was associated with faster clearance of bacteremia. The CAMERA2 trial (Combination Antibiotics for Methicillin-Resistant Staphylococcus aureus) randomly assigned participants with MRSA bloodstream infections to standard therapy, or to standard therapy plus an anti-staphylococcal ß-lactam (combination therapy). For 117 CAMERA2 MRSA isolates, we determined by broth microdilution the MIC of cefazolin and oxacillin, with and without 44 mM of NaHCO3. Isolates exhibiting ≥4-fold decrease in the MIC to cefazolin or oxacillin in the presence of NaHCO3 were considered "NaHCO3-responsive" to that agent. We compared the rate of persistent bacteremia among participants who had infections caused by NaHCO3-responsive and non-responsive strains, and that were assigned to combination treatment with a ß-lactam. Thirty-one percent (36/117) and 25% (21/85) of MRSA isolates were NaHCO3-responsive to cefazolin and oxacillin, respectively. The NaHCO3-responsive phenotype was significantly associated with sequence type 93, SCCmec type IVa, and mecA alleles with substitutions in positions -7 and -38 in the regulatory region. Among participants treated with a ß-lactam, there was no association between the NaHCO3-responsive phenotype and persistent bacteremia (cefazolin, P = 0.82; oxacillin, P = 0.81). In patients from a randomized clinical trial with MRSA bloodstream infection, isolates with an in vitro ß-lactam-NaHCO3-responsive phenotype were associated with distinctive genetic signatures, but not with a shorter duration of bacteremia among those treated with a ß-lactam.

Deep learning restores speech intelligibility in multi-talker interference for cochlear implant users.

Cochlear implants (CIs) do not offer the same level of effectiveness in noisy environments as in quiet settings. Current single-microphone noise reduction algorithms in hearing aids and CIs only remove predictable, stationary noise, and are ineffective against realistic, non-stationary noise such as multi-talker interference. Recent developments in deep neural network (DNN) algorithms have achieved noteworthy performance in speech enhancement and separation, especially in removing speech noise. However, more work is needed to investigate the potential of DNN algorithms in removing speech noise when tested with listeners fitted with CIs. Here, we implemented two DNN algorithms that are well suited for applications in speech audio processing: (1) recurrent neural network (RNN) and (2) SepFormer. The algorithms were trained with a customized dataset ( ∼ 30 h), and then tested with thirteen CI listeners. Both RNN and SepFormer algorithms significantly improved CI listener's speech intelligibility in noise without compromising the perceived quality of speech overall. These algorithms not only increased the intelligibility in stationary non-speech noise, but also introduced a substantial improvement in non-stationary noise, where conventional signal processing strategies fall short with little benefits. These results show the promise of using DNN algorithms as a solution for listening challenges in multi-talker noise interference.

Arteriovenous malformations in the cerebellopontine angle: assessment of the "backdoor resection" technique and microsurgical results in 38 patients.

OBJECTIVE: Posterior fossa arteriovenous malformations (AVMs) represent 7% to 15% of all intracranial AVMs and are associated with an increased risk of hemorrhage, morbidity, and mortality compared with supratentorial AVMs, thus prompting urgent and definitive treatment. Cerebellopontine angle (CPA) AVMs are a unique group of posterior fossa AVMs incorporating characteristics of brainstem and cerebellar lesions, which are particularly amenable to microsurgical resection. This study reports the clinical, radiological, operative, and outcome features of patients with CPA AVMs in a large cohort. METHODS: The authors conducted a single-surgeon, 2-institution retrospective cohort study of all consecutive patients with CPA AVMs treated with microsurgical resection during a 25-year period. RESULTS: CPA AVMs represented 22% (38 of 176) of all infratentorial AVMs resected by the senior author. Overall, 38 patients (22 [58%] male and 16 [42%] female) met the study inclusion criteria and were analyzed. Most patients presented with hemorrhage (n = 29, 76%). The median age at surgery was 56 (range 6-82) years. Subtypes included 22 (58%) petrosal cerebellar AVMs, 11 (29%) lateral pontine AVMs, and 5 (13%) AVMs involving both the brainstem and cerebellum. Most AVM niduses were small (< 3 cm; n = 35, 92%) and compact (n = 31, 82%). Fourteen (37%) patients harbored flow-related aneurysms. Twenty (53%) patients underwent preoperative embolization. Complete angiographic obliteration was achieved with microsurgery in 35 (92%) patients. Five (13%) patients with poor neurological conditions at presentation died before hospital discharge. Of the 7 (18%) patients with new postoperative neurological deficits, 5 had transient deficits. The median (interquartile range) follow-up was 1.7 (0.5-3.2) years; 32 (84%) patients were alive at last follow-up, and 30 (79%) had achieved a favorable neurological outcome (modified Rankin Scale [mRS] score 0-2). The only independent predictor of unfavorable postoperative outcome (mRS score 3-6) was the preoperative mRS score (p = 0.002). CONCLUSIONS: CPA AVMs are unique posterior fossa lesions, including petrosal cerebellar and lateral pontine AVMs. The "backdoor resection" technique provides a safe and efficient strategy with high obliteration rates and a low risk of treatment-related morbidity. Microsurgical resection should be considered the frontline treatment for most CPA AVMs, except for those with a significant diffuse brainstem component.

Targeting anoikis resistance as a strategy for cancer therapy.

Anoikis, known as matrix detachment-induced apoptosis or detachment-induced cell death, is crucial for tissue development and homeostasis. Cancer cells develop means to evade anoikis, e.g. anoikis resistance, thereby allowing for cells to survive under anchorage-independent conditions. Uncovering the mechanisms of anoikis resistance will provide details about cancer metastasis, and potential strategies against cancer cell dissemination and metastasis. Here, we summarize the principal elements and core molecular mechanisms of anoikis and anoikis resistance. We discuss the latest progress of how anoikis and anoikis resistance are regulated in cancers. Furthermore, we summarize emerging data on selective compounds and nanomedicines, explaining how inhibiting anoikis resistance can serve as a meaningful treatment modality against cancers. Finally, we discuss the key limitations of this therapeutic paradigm and possible strategies to overcome them. In this review, we suggest that pharmacological modulation of anoikis and anoikis resistance by bioactive compounds could surmount anoikis resistance, highlighting a promising therapeutic regimen that could be used to overcome anoikis resistance in cancers.

FEV1 Variability Predicts Lung Transplant or Mortality in Cystic Fibrosis Patients in the US.

RATIONALE: Declines in percent predicted Forced Expiratory Volume in 1 Second (ppFEV1) are an important marker of clinical progression of Cystic Fibrosis (CF). OBJECTIVES: We examined ppFEV1 variability on a combined outcome of lung transplant or death. METHODS: We estimated the association between ppFEV1 variability and the combined outcome of lung transplant or death. We included children ages 8 years and above with CF and two prior years of ppFEV1 data before baseline between 2005 and 2021. We defined ppFEV1 increased variability as any relative increase or decrease of at least 10% in ppFEV1 from a two-year averaged baseline. A marginal structural Cox proportional hazards model was used. We examined a cumulative measure of ppFEV1 variability, defined as the cumulative proportion of visits with ppFEV1 variability at each visit. Kaplan-Meier survival curves were generated based upon quartiles of the cumulative distribution of ppFEV1 variability. MEASUREMENTS AND MAIN RESULTS: We included 9,706 CF patients in our cohort. Median age at cohort entry was 8.3 (IQR 8.2 - 8.4) years, 50% of patients were female, 94% white, and median baseline ppFEV1 was 94.4 (IQR 81.6 - 106.1). The unadjusted HR for increased ppFEV1 variability on lung transplant/mortality was 4.13 (95% CI 3.48 - 4.90) and the weighted HR was 1.49 (95% CI 1.19 - 1.86). Survival curves stratified by quartile of cumulative variability demonstrated an increased hazard of lung transplant/mortality as the proportion of cumulative ppFEV1 variability increased. CONCLUSIONS: We found a strong association between ppFEV1 variability and lung transplant or mortality in a cohort of people with CF in the US.

Meaningfully Characterizing Cannabis Use for Research and Clinical Settings: A Comprehensive Review of Existing Measures and Proposed Future Directions.

Cannabis use is increasingly common. There is a need for validated tools to meaningfully assess recreational, medical, and disordered cannabis use in both research and clinical contexts. Cannabis assessments were considered against pre-determined inclusion criteria within a comprehensive review. Measures were categorized as either (i) evaluating use frequency or quantity, (ii) measuring symptoms of disordered use and withdrawal, or (iii) assessing use motives, effects, and perceptions. The applications and validations for each assessment are summarized. Finally, recommendations for refining of existing measures or development of new measures are presented. The literature review resulted in 289 publications that were reviewed in detail, yielding 21 assessments that met inclusion criteria. The applications of these assessments are described here, in addition to the information about the validation studies of each assessment. Based on the complication of these tools, 5 areas of potential development are highlighted to guide future research, including (i) sensitivity to the mode of cannabis administration as well as sensitivity to (ii) potency of cannabis products alongside frequency and quantity, (iii) unit equivalence, (iv) aligning clinical measures consistently with cannabis use disorder (CUD) diagnostic criteria, and (v) creating measures specific to medical users, their motives for use, and their perceptions of therapeutic benefits or side effects. Clinicians and researchers can pragmatically benefit from this summary of validated measures of cannabis use, and future work could improve the study of and clinical care for cannabis use and CUD by pursuing one or more key areas of development described here.

Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment.

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole-genome sequencing (WGS). Here we now introduce MRD-EDGE, a machine-learning-guided WGS ctDNA single-nucleotide variant (SNV) and copy-number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by ~300× compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, vastly expanding its applicability within solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in TF in response to neoadjuvant immunotherapy in lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables plasma-only (non-tumor-informed) disease monitoring in advanced melanoma and lung cancer, yielding clinically informative TF monitoring for patients on immune-checkpoint inhibition.

Predicting responses to climate change using a joint species, spatially dependent physiologically guided abundance model.

Predicting the effects of warming temperatures on the abundance and distribution of organisms under future climate scenarios often requires extrapolating species-environment correlations to climatic conditions not currently experienced by a species, which can result in unrealistic predictions. For poikilotherms, incorporating species' thermal physiology to inform extrapolations under novel thermal conditions can result in more realistic predictions. Furthermore, models that incorporate species and spatial dependencies may improve predictions by capturing correlations present in ecological data that are not accounted for by predictor variables. Here, we present a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming. The jsPGA model uses a basis function approach to capture both species and spatial dependencies. We apply the jsPGA model to predict the response of eight fish species to projected climate warming in thousands of lakes in Minnesota, USA. By the end of the century, the cold-adapted species was predicted to have high probabilities of extirpation across its current range-with 10% of lakes currently inhabited by this species having an extirpation probability >0.90. The remaining species had varying levels of predicted changes in abundance, reflecting differences in their thermal physiology. Though the model did not identify many strong species dependencies, the variation in estimated spatial dependence across species suggested that accounting for both dependencies was important for predicting the abundance of these fishes. The jsPGA model provides a new tool for predicting changes in the abundance, distribution, and extirpation probability of poikilotherms under novel thermal conditions.

Shifting From Best Practice to Standard Practice: Implementing Measurement-Based Care in Health Systems.

There is a high prevalence of untreated depression in adults and youth observed at the population level in the United States, and many who would benefit from treatment do not receive it. One proposed effort to increase access to care is the use of measurement-based care (MBC; repeated use of symptom measures for screening and treatment guidance) by primary care physicians to treat non-complex cases of depression. MBC has been shown to improve patient outcomes compared to care as usual, but there are barriers that need to be addressed at the health system level for effective implementation to occur. Herein we provide an overview of MBC and detail benefits and barriers of MBC implementation. Relevant considerations and guidance for implementing MBC are presented, and a case example of a health system implementing MBC is included. Though issues of reimbursement, limited human and technological resources, and resistance to systemic change are barriers to implementing MBC, effective strategies exist to overcome these barriers. In addition to helping health systems align with changes to value-based care models, effective implementation of MBC can likely improve patient outcomes and result in net financial benefits.