bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neoadjuvant Therapy for Pancreatic Cancer: Increased Use and Improved Optimal Outcomes
Authors: Davis Catherine H , Beane Joal D , Gazivoda Victor P , Grandhi Miral S , Greenbaum Alissa A , Kennedy Timothy J , Langan Russell C , August David A , Alexander H Richard , Pitt Henry A 
Published: April 2022

BACKGROUND:
The introduction of more effective chemotherapy a decade ago has led to increased use of neoadjuvant therapy (NAT) in patients with pancreatic ductal adenocarcinoma (PDAC). The aim of this study was to assess the evolving use of NAT in individuals with PDAC undergoing pancreatoduodenectomy (PD) and to compare their outcomes with patients undergoing upfront operation.

STUDY DESIGN:
The American College of Surgeons NSQIP Procedure Targeted Pancreatectomy database was queried from 2014 to 2019. Patients undergoing pancreatoduodenectomy were evaluated based on the use of NAT versus upfront operation. Multivariable analysis was performed to determine the effect of NAT on postoperative outcomes, including the composite measure optimal pancreatic surgery (OPS). Mann-Kendall trend tests were performed to assess the use of NAT and associated outcomes over time.

RESULTS:
A total of 13,257 patients were identified who underwent PD for PDAC between 2014 and 2019. Overall, 33.6% of patients received NAT. The use of NAT increased steadily from 24.2% in 2014 to 42.7% in 2019 (p < 0.0001). On multivariable analysis, NAT was associated with reduced serious morbidity (odds ratio [OR] 0.83, p < 0.001), clinically relevant pancreatic fistulas (OR 0.52, p < 0.001), organ space infections (OR 0.74, p < 0.001), percutaneous drainage (OR 0.73, p < 0.001), reoperation (OR 0.76, p = 0.005), and prolonged length of stay (OR 0.63, p < 0.001). OPS was achieved more frequently in patients undergoing NAT (OR 1.433, p < 0.001) and improved over time in patients receiving NAT (50.7% to 56.6%, p < 0.001).

CONCLUSION:
NAT before pancreatoduodenectomy increased more than 3-fold over the past decade and was associated with improved optimal operative outcomes.
Using Process Flow Disruption Analysis to Guide Quality Improvement
Authors: Slakey Douglas P , Sargut Gökçe , Glowacki Nicole E , Katoozian Parisa Y , Baylis William J , Anderson Edwin J 
Published: April 2022

BACKGROUND:
Process flow describes the efficiency and consistency with which a process functions. Disruptions in surgical flow have been shown to be associated with an increase in error. Despite this, little experience exists in using surgical flow analysis to guide quality improvement (QI).

STUDY DESIGN:
In a 900-bed teaching hospital with an annual surgical volume of 24,000 cases, a 4-month observational study of process flow was done by experts in complex system evaluation. Identified flow disruptions were used to guide QI. Statistical analysis included descriptive and bivariate techniques.

RESULTS:
More than 200 unique process data points were evaluated. There was a high degree of variability in completion of 79 individual intraoperative data elements. Lack of completion of all elements of the time out was associated with number of times the operating room door opened during case (19, 11–27; p = 0.01). Flow disruptions were used to direct surgical QI. One example was a disruption affecting the use of Sugammadex. Resolving this flow disruption resulted in a 59% reduction in the incidence of postoperative respiratory failure (p < 0.01) and a direct and variable cost savings of $447,200 and $313,160, respectively, in the first 12 months.

CONCLUSIONS:
The use of process flow analysis to direct surgical quality initiatives is a novel approach that emphasizes system-level strategy. Resolving flow disruptions can lead to effective QI that embraces reliability by focusing attention on common processes rather than adverse events that may be unique and therefore difficult to apply broadly.
Machine Learning Refinement of the NSQIP Risk Calculator: Who Survives the “Hail Mary” Case?
Authors: Rogers Michael P , Janjua Haroon , DeSantis Anthony J , Grimsley Emily , Pietrobon Ricardo , Kuo Paul C 
Published: April 2022

BACKGROUND:
The American College of Surgeons (ACS) NSQIP risk calculator helps guide operative decision making. In patients with significant surgical risk, it may be unclear whether to proceed with “Hail Mary”–type interventions. To refine predictions, a local interpretable model-agnostic explanations machine (LIME) learning algorithm was explored to determine weighted patient-specific factors’ contribution to mortality.

STUDY DESIGN:
The ACS-NSQIP database was queried for all surgical patients with mortality probability greater than 50% between 2012 and 2019. Preoperative factors (n = 38) were evaluated using stepwise logistic regression; 26 significant factors were used in gradient boosted machine (GBM) modeling. Data were divided into training and testing sets, and model performance was substantiated with 10-fold cross validation. LIME provided individual subject mortality. The GBM-trained model was interpolated to LIME, and predictions were made using the test dataset.

RESULTS:
There were 6,483 deaths (53%) among 12,248 admissions. GBM modeling displayed good performance (area under the curve = 0.65, 95% CI 0.636–0.671). The top 5 factors (% contribution) to mortality included: septic shock (27%), elevated International Normalized Ratio (22%), ventilator-dependence (14%), thrombocytopenia (14%), and elevated serum creatinine (5%). LIME modeling subset personalized patients by factors and weights on survival. In the entire cohort, mortality positive predictive value with 2 factor combinations was 53.5% (specificity 0.713), 3 combinations 64.2% (specificity 0.835), 4 combinations 72.1% (specificity 0.943), and all 5 combinations 77.9% (specificity 0.993). Conversely, mortality positive predictive value fell to 34% in the absence of 4 factors.

CONCLUSIONS:
Through the application of machine learning algorithms (GBM and LIME), our model individualized predicted mortality and contributing factors with substantial ACS-NSQIP predicted mortality. USE of machine learning techniques may better inform operative decisions and family conversations in cases of significant surgical risk.
Disparity in Clinical Trial Participation Among Patients with Gastrointestinal Cancer
Authors: Abbas Alizeh , Diaz Adrian , Obeng-Gyasi Samilia , Cloyd Jordan M , Ejaz Aslam , Stewart John H , Pawlik Timothy M 
Published: April 2022

BACKGROUND:
Clinical trial participation among cancer patients remains low. We sought to examine the impact of patient- and system-level factors on clinical trial participation among gastrointestinal (GI) surgical patients.

STUDY DESIGN:
Adult patients with a GI cancer who underwent oncologic surgery who were enrolled in National Cancer Institute (NCI)–funded clinical trials from 2000 through 2019 were compared with trial-eligible adult patients in the National Cancer Database (NCDB) between 2004 and 2017. Multivariable logistic regression was used to identify factors associated with clinical trial participation.

RESULTS:
Participants from 36 NCI-funded clinical trials (n = 10,518) were compared with 2,255,730 trial-eligible nonparticipants from the NCDB. Patients aged 65 years or younger (odds ratio [OR] = 0.5, 95% CI 0.47–0.53), Medicare (OR = 0.46, 95% CI 0.43–0.49) or Medicaid (OR = 0.51, 95% CI 0.46–0.58) insurance, as well as lower levels of education (OR = 0.82, 95% CI 0.75–0.89) were associated with a lower likelihood of clinical trial enrollment. Black (OR = 0.72, 95% CI 0.67–0.78) and Asian/Pacific Islander (OR = 0.96, 95% CI 0.85–1.08) patients were less likely to participate in trials vs White patients. There were interactions between race/ethnicity and income; high-income (OR = 0.67, 95% CI 0.55–0.81) and low-income Black (OR = 0.75, 95% CI 0.66–0.87) patients were less likely, respectively, to participate than high- or low-income White individuals (p < 0.001).

CONCLUSIONS:
Clinical trial participation is low among adult GI cancer patients who undergo surgery in the US. Programs aimed at improving trial participation among vulnerable populations are needed to improve trial participation.
Are Current National Review Board Downstaging Protocols for Hepatocellular Carcinoma Too Restrictive?
Authors: Ahmed Ola , Vachharajani Neeta , Croome Kris P , Tabrizian Parissa , Agopian Vatche , Halazun Karim , Hong Johnny C , Dageforde Leigh Anne , Chapman William C , Doyle MB Majella ,   for the Primary Liver Tumor Study Group
Published: April 2022

BACKGROUND:
Liver transplantation (LT) is an effective strategy for patients with unresectable hepatocellular carcinoma (HCC). To qualify for standardized LT model for end-stage liver disease exception points, the United Network for Organ Sharing National Liver Review Board (NLRB) requires that the presenting and final HCC tumor burden be within the University of California San Francisco criteria, which were recently expanded (within expanded UCSF [W-eUCSF]). Current NLRB criteria may be too restrictive because it has been shown previously that the initial burden does not predict LT failure when tumors downstage to UCSF. This study aims to assess LT outcomes for HCC initially presenting beyond expanded UCSF (B-eUCSF) criteria in a large multicenter collaboration.

STUDY DESIGN:
Comparisons of B-eUCSF and W-eUCSF candidates undergoing LT at seven academic institutions between 2001 and 2017 were made from a multi-institutional database. Survival outcomes were compared by Kaplan-Meier and Cox regression analyses.

RESULTS:
Of 1,846 LT recipients with HCC, 86 (5%) met B-eUCSF criteria at initial presentation, with the remainder meeting W-eUCSF criteria. Despite differences in tumor burden, B-eUCSF candidates achieved comparable 1-, 5- and 10-year overall (89%, 70%, and 55% vs 91%, 74%, and 60%, respectively; p = 0.2) and disease-free (82%, 60%, and 53% vs 89%, 71%, and 59%, respectively; p = 0.07) survival to patients meeting W-eUCSF criteria after LT. Despite increased tumor recurrence in B-eUCSF vs W-eUCSF patients (24% vs 10%, p = 0.0002), post-recurrence survival was similar in both groups (p = 0.69).

CONCLUSION:
Transplantation for patients initially presenting with HCC B-eUSCF criteria offers a survival advantage similar to those with tumors meeting W-eUCSF criteria at presentation. The current NLRB policy is too stringent, and considerations to expand criteria should be discussed.
Haemolysis detection in microRNA-seq from clinical plasma samples
Authors: Smith Melanie D. , Leemaqz Shalem Y. , Jankovic-Karasoulos Tanja , McAninch Dale , McCullough Dylan , Breen James , Roberts Claire T. , Pillman Katherine A. 
Published: April 2022

AbstractThe abundance of cell-free microRNA (miRNA) has been measured in many body fluids, including blood plasma, which has been proposed as a source with novel, minimally invasive biomarker potential for several diseases. Despite improvements in quantification methods for plasma miRNAs, there is no consensus on optimal reference miRNAs or to what extent haemolysis may affect plasma miRNA content. Here we propose a new method for the detection of haemolysis in miRNA high-throughput sequencing (HTS) data from libraries prepared using human plasma. To establish a miRNA haemolysis signature in plasma we first identified differentially expressed miRNAs between samples with known haemolysis status and selected miRNA with statistically significant higher abundance in our haemolysed group. Given there may be both technical and biological reasons for differential abundance of signature miRNA, and to ensure the method developed here was relevant outside of our specific context, that is women of reproductive age, we tested for significant differences between pregnant and non-pregnant groups. Here we report a novel 20 miRNA signature (miR-106b-3p, miR-140-3p, miR-142-5p, miR-532-5p, miR-17-5p, miR-19b-3p, miR-30c-5p, miR-324-5p, miR-192-5p, miR-660-5p, miR-186-5p, miR-425-5p, miR-25-3p, miR-363-3p, miR-183-5p, miR-451a, miR-182-5p, miR-191-5p, miR-194-5p, miR-20b-5p) that can be used to identify the presence of haemolysis, in silico, in high throughput miRNA sequencing data. Given the potential for haemolysis contamination, we recommend that assay for haemolysis detection become standard pre-analytical practice and provide here a simple method for haemolysis detection.
Frequent Cocaine Use is Associated with Larger HIV Latent Reservoir Size
Authors: Aouizerat Bradley E. , Garcia Josephine N. , Domingues Carlos V. , Xu Ke , Quach Bryan C. , Page Grier P. , Konkle-Parker Deborah , Bolivar Hector H. , Lahiri Cecile D. , Golub Elizabeth T. , Cohen Mardge H. , Kassaye Seble G. , DeHovitz Jack , Kuniholm Mark H. , Archin Nancie M. , Tien Phyllis C. , Hancock Dana B. , Johnson Eric Otto 
Published: April 2022

AbstractBackgroundWith the success of combination antiretroviral therapy, HIV is now treated as a chronic disease, including among drug users. Cocaine—one of the most frequently abused illicit drugs among persons living with HIV (PLWH)— slows the decline of viral production after ART, and is associated with higher HIV viral load, more rapid HIV progression, and increased mortality. We examined the impact of cocaine use on the CD4+ T-cell HIV Latent Reservoir (HLR) in virally suppressed PLWH.MethodsCD4+ T-cell genomic DNA was isolated from peripheral blood mononuclear cells collected from 434 women of diverse ancestry (i.e., 75% Black, 14% Hispanic, 12% White) who self-reported cocaine use (i.e., 160 cocaine users, 59 prior users, 215 non-users). Participants had to have an undetectable HIV RNA viral load measured by commercial assay for at least 6 months. The Intact Proviral HIV DNA Assay (IPDA) provided estimates of intact provirus per 106 CD4+ T-cells.ResultsThe HLR size differed by cocaine use (i.e., median [interquartile range]: 72 [14, 193] for never users, for prior users 165 [63, 387], 184 [28, 502] for current users), which was statistically significantly larger in both prior (p=0.023) and current (p=0.001) cocaine users compared with never users.ConclusionOur study is the first to provide evidence that cocaine use may contribute to a larger replication competent HLR in CD4* T-cells among virologically suppressed women living with HIV. Our findings are important, because women are under-represented in HIV reservoir studies and in studies of the impact of cocaine use on outcomes among PLWH.
Framework for prioritizing variants of unknown significance from clinical genetic testing in kidney disease – utility of multidisciplinary approach to gather evidence of pathogenicity for Hepatocyte Nuclear Factor-1β (HNF1B) p.Arg303His
Authors: Mirshahi Uyenlinh L. , Bhan Ahana , Tholen Lotte E. , Fang Brian , Chen Guoli , Moore Bryn , Cook Adam , Mohan Prince , Patel Kashyap , Igarashi Peter , de Baaij Jeroen H.F. , Ferrè Silvia , Hoenderop Joost G.J. , Carey David J. , Chang Alexander R. 
Published: April 2022

AbstractMonogenic causes in over 300 kidney-associated genes account for roughly 12% of end stage kidney disease (ESKD) cases. Advances in next generation sequencing, and large customized panels enable the diagnosis of monogenic kidney disease noninvasively at relatively low cost, allowing for more precise management for patients and their families. A major challenge is interpreting rare variants, many of which are classified as variants of unknown significance (VUS). We present a framework in which we thoroughly evaluated and provided evidence of pathogenicity for HNF1B-p.Arg303His, a VUS returned from clinical genetic testing for a kidney transplant candidate. This blueprint, designed by a multi-disciplinary team of clinicians, molecular biologists, and diagnostic geneticists, includes using a health system-based cohort with genetic and clinical information to perform deep phenotyping of VUS carriers, examination of existing genetic databases, as well as functional testing. With our approach, we demonstrate evidence for pathogenicity for HNF1B-p.Arg303His by showing similar burden of kidney manifestations in this variant to known HNF1B pathogenic variants, and greater burden compared to non-carriers. Determination of a molecular diagnosis for the example family allows for proper surveillance and management of HNF1B-related manifestations such as kidney disease, diabetes, and hypomagnesemia with important implications for safe living-related kidney donation. The candidate gene-variant pair also allows for clinical biomarker testing for aberrations of linked pathways. This working model may be applicable other diseases of genetic etiology.
Linking hubness, embryonic neurogenesis, transcriptomics and diseases in human brain networks
Authors: Diez Ibai , Garcia-Moreno Fernando , Carral-Sainz Nayara , Stramaglia Sebastiano , Nieto-Reyes Alicia , D’Amato Mauro , Cortes Jesús Maria , Bonifazi Paolo 
Published: April 2022

SUMMARYUnderstanding the architectural principles that shape human brain networks is a major challenge for systems neuroscience. We hypothesize that the centrality of the different brain circuits in the human connectome is a product of their embryogenic age, such that early-born nodes should become stronger hubs than those born later. Using a human brain segmentation based on embryogenic age, we observed that nodes’ structural centrality correlated with their embryogenic age, fully confirming our hypothesis. Distinct trends were found at different resolutions on a functional level. The difference in embryonic age between nodes inversely correlated with the probability of existence of links and their weights. Brain transcriptomic analysis revealed strong associations between embryonic age, structure-function centrality, and the expression of genes related to nervous system development, synapse regulation and human neurological diseases. Our results highlight two key principles regarding the wiring of the human brain, “preferential age attachment” and “the older gets richer”.
Climate and competition combine to set elevational distributions of tropical rainforestDrosophila
Authors: Chen Jinlin , Lewis Owen T. 
Published: April 2022

AbstractSpecies turnover with elevation is a widespread phenomenon and provides valuable information on why and how ecological communities might reorganize as the climate warms. Tropical mountains typically have pronounced thermal gradients and intense species interactions, providing a testing ground for investigating the relationship between thermal tolerances and biotic interactions as the proximate factors influencing species’ distributions. We investigated temperature and interspecific competition as causes of species turnover and abundance changes of the nine most abundant species ofDrosophilaalong elevational gradients in the Australian Wet Tropics. Thermal performance curves revealed that species’ distributions were better explained by their performance at extreme temperatures, rather than their thermal optima. Upper thermal limits varied less among species than lower thermal limits. Nonetheless, these small differences were associated with differences in centred elevation of distribution, consistent with environmental sorting as a driver of community composition at low-elevation sites. In contrast, community composition at cool, high elevations was driven by temperature-dependent interspecific competition rather than tolerance to low temperatures. These results run counter to common assumptions about the role of abiotic and biotic factors in structuring communities along thermal gradients, and indicate that tropical insects may be highly vulnerable to future warming. Our study illustrates the importance of experimental, quantitative tests across biological levels (i.e., individuals to populations) and temporal scales (i.e., within-generation to multi-generation) for characterizing effects of climate on a guild of closely-interacting species.
LENS: Landscape of Effective Neoantigens Software
Authors: Vensko Steven P. , Olsen Kelly , Bortone Dante , Smith Christof C. , Chai Shengjie , Beckabir Wolfgang , Fini Misha , Jadi Othmane , Rubinsteyn Alex , Vincent Benjamin G. 
Published: April 2022

AbstractMotivationElimination of cancer cells by T cells is a critical mechanism of anti-tumor immunity and cancer immunotherapy response. T cells recognize cancer cells by engagement of T cell receptors with peptide epitopes presented by major histocompatibility complex (MHC) molecules on the cancer cell surface. Peptide epitopes can be derived from antigen proteins coded for by multiple genomic sources. Bioinformatics tools used to identify tumor-specific epitopes via analysis of DNA and RNA sequencing data have largely focused on epitopes derived from somatic variants, though a smaller number have evaluated potential antigens from other genomic sources.ResultsWe report here an open-source workflow utilizing the Nextflow DSL2 workflow manager, Landscape of Effective Neoantigen Software (LENS), which predicts tumor-specific and tumor-associated antigens from single nucleotide variants, insertions and deletions, fusion events, splice variants, cancer testis antigens, overexpressed self-antigens, viruses, and endogenous retroviruses. The primary advantage of LENS is that it expands the breadth of genomic sources of discoverable tumor antigens using genomics data. Other advantages include modularity, extensibility, ease of use, and harmonization of relative expression level and immunogenicity prediction across multiple genomic sources. We present an analysis of 115 acute myeloid leukemia (AML) samples to demonstrate the utility of LENS. We expect LENS will be a valuable platform and resource for T cell epitope discovery bioinformatics, especially in cancers with few somatic variants where tumor-specific epitopes from alternative genomic sources are an elevated priority.AvailabilityMore information about LENS, including workflow documentation and instructions, can be found athttps://gitlab.com/landscape-of-effective-neoantigens-softwareContactsteven_vensko@med.unc.edu,benjamin_vincent@med.unc.eduSupplementary informationSupplementary data are available atBioinformaticsonline.
Speed-dependent biomechanical changes vary across individual gait metrics post-stroke relative to neurotypical adults
Authors: Kettlety Sarah A. , Finley James M. , Reisman Darcy S. , Schweighofer Nicolas , Leech Kristan A 
Published: April 2022

ABSTRACTBackgroundGait training at fast speeds is recommended to reduce walking activity limitations post-stroke. Fast walking may also reduce gait kinematic impairments post-stroke. However, the magnitude of speed-dependent kinematic impairment reduction in people post-stroke relative to neurotypical adult walking patterns is unknown.ObjectiveTo determine the effect of faster walking speeds on gait kinematics post-stroke relative to neurotypical adults walking at similar speeds.MethodsWe performed a secondary analysis with data from 28 people post-stroke and 50 neurotypical adults treadmill walking at multiple speeds. We evaluated the effects of speed and group on individual spatiotemporal and kinematic metrics and performed k-means clustering with all metrics at self-selected and fast speedsResultsPeople post-stroke decreased step length asymmetry and trailing limb angle impairment, reducing between-group differences at fast speeds. Speed-dependent changes in peak swing knee flexion, hip hiking, and temporal asymmetries exaggerated between-group differences. Our clustering analyses revealed two clusters. One represented neurotypical gait behavior, composed of neurotypical and post-stroke participants. The other characterized stroke gait behavior, comprised entirely of participants post-stroke. Cluster composition was largely consistent at both speeds, and the distance between clusters increased at fast speedsConclusionsThe biomechanical effect of fast walking post-stroke varied across individual gait metrics. For participants within the stroke gait behavior cluster, speed-dependent changes did not lead to an overall gait pattern more similar to neurotypical adults. This suggests that combining fast walking with an approach to strategically target gait metrics with smaller speed-dependent changes may potentiate the biomechanical benefits of fast walking.