bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved oncologic outcomes for minimally invasive left pancreatectomy: Propensity‐score matched analysis of the National Cancer Database
Authors: Watson Michael D. , Baimas‐George Maria R. , Thompson Kyle J. , Iannitti David A. , Ocuin Lee M. , Baker Erin H. , Martinie John B. , Vrochides Dionisios 
Published: August 2020

AbstractBackground and objectivesMinimally invasive (MIS) left pancreatectomy (LP) is increasingly used to treat pancreatic adenocarcinoma (PDAC). Despite improved short‐term outcomes, no studies have demonstrated long‐term benefits over open resection.MethodsThe National Cancer Database was queried between 2010 and 2016 for patients with PDAC, grouped by surgical approach (MIS vs open). Demographics, comorbidities, clinical staging, and pathologic staging were used for propensity‐score matching. Perioperative, short‐term oncologic, and survival outcomes were compared.ResultsAfter matching, both cohorts included 805 patients. There were no differences in baseline characteristics, staging, or preoperative therapy between cohorts. The MIS cohort had a shorter length of stay (6.8 ± 5.5 vs 8.5 ± 7.3 days; P < .0001) with the trend toward improved time to chemotherapy (53.9 ± 26.1 vs 57.9 ± 29.9 days; P = .0511) and margin‐positive resection rate (15.3% vs 18.9%; P = .0605). Lymph node retrieval and receipt of chemotherapy were similar. The MIS cohort had higher median overall survival (28.0 vs 22.1 months; P = .0067). Subgroup analysis demonstrated the highest survival for robotic compared with laparoscopic and open LP (41.9 vs 26.6 vs 22.1 months; P < .0001).ConclusionsThis study demonstrates the safety of MIS LP and favorable long‐term oncologic outcomes. The improved survival after MIS LP warrants further study with prospective, randomized trials.
Surgical approach, management, and oncologic outcomes of primary leiomyosarcoma of the inferior vena cava: An institutional case series
Authors: Joung Hae Soo , Nooromid Michael J. , Eskandari Mark K. , Wayne Jeffrey D. 
Published: August 2020

AbstractBackgroundLeiomyosarcoma of the inferior vena cava (IVC) is a rare tumor arising from the smooth muscle of vessel walls. Surgery is the only potential curative treatment. Given its rarity, optimal surgical, and oncologic management is not well described. We review our institutional series of primary leiomyosarcomas treated with resection and IVC reconstruction over the last decade.MethodsRetrospective chart review of all patients who underwent surgical resection of primary leiomyosarcoma of the IVC from November 2009 to March 2020 at a single tertiary care center was performed.ResultsAmong the eight patients treated, the majority were female (87.5%) with a median age of 52 years (range, 44‐63). Tumor was located in the infrarenal IVC in five patients (62.5%). IVC was reconstructed using a ring‐enforced PTFE graft in six patients (75%). All but one patient had an intermediate (grade 2) or high grade (grade 3) tumor, and all resections achieved grossly negative margins. The 1‐ and 3‐year disease‐free survival was 85.7% and 64.3%, respectively. There were no disease‐specific deaths during a median follow‐up of 36 months (interquartile range, 10‐51 months).ConclusionsWith a well‐coordinated multidisciplinary approach, primary leiomyosarcoma of the IVC can be safely resected with good long‐term survival.
QT interval prolongation noted in one percent of 2553 Asian patients with schizophrenia: Findings from the REAP‐AP survey
Authors: Park Seon‐Cheol , Lee Bong Ju , Park Jae Hong , Kawasaki Hiroaki , Avasthi Ajit , Grover Sandeep , Tanra Andi J. , Lin Shih‐Ku , Javed Afzal , Tan Chay Hoon , Sartorius Norman , Shinfuku Naotaka , Park Yong Chon 
Published: August 2020

AbstractAlthough the association between antipsychotic use and corrected QT interval (QTc) prolongation has been repeatedly confirmed, the relationship has been rarely studied in a practical setting. Using data from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics (REAP‐AP) survey, our study aimed to investigate the prevalence and clinical correlates of QTc prolongation in 2553 Asian patients with schizophrenia. After adjusting for the potential effect of confounding factors, the baseline and clinical characteristics of the schizophrenia patients with and without QTc prolongation were compared using analyses of covariance and binary logistic analyses. In addition, a binary logistic analysis model with a forward selection method was used to identify the distinctive clinical correlates of QTc prolongation. QTc prolongation was noted in 1.1% of Asian patients with schizophrenia. Schizophrenia patients were characterized by lower proportions of disorganized speech and negative symptoms; higher use of amisulpride and clozapine; and higher proportions of rigidity, hypercholesterolemia, and sedation than those without QTc prolongation. Finally, a binary logistic mode showed that amisulpride, clozapine, rigidity, and hypercholesterolemia might be the distinctive clinical correlates of QTc prolongation in Asian patients with schizophrenia. These findings indicate the clinical implications that the uses of amisulpride and clozapine and the occurrences of rigidity and hypercholesterolemia may be potential risk factors for QTc prolongation of schizophrenia patients.
Estimating soil salinity with different fractional vegetation cover using remote sensing
Authors: Zhang Junrui , Zhang Zhitao , Chen Junying , Chen Haiying , Jin Jiming , Han Jia , Wang Xintao , Song Zhishuang , Wei Guangfei 
Published: August 2020

AbstractSoil salinization is a serious restrictive factor affecting sustainable agricultural development. In order to explore the effect of Fractional Vegetation Cover (FVC), we monitored soil salinization in sites different vegetation coverage in Jiefangzha Irrigation District in Inner Mongolia using satellite remote sensing. From May to August 2018, we carried out field sampling at different depths in each month, and calculated FVC and spectral covariates using GF‐1 satellite images in the corresponding sampling period. Based on the FVC division criteria for Inner Mongolia, we took the following steps: (a) setting up a control treatment A (the full data with undivided FVC, TA) and experimental treatments B (bare land, TB), C (mid‐low FVC, TC), D (mid FVC, TD) and E (high FVC, TE); (b) conducting the Best Subset Selection (BSS) for all spectral covariates at different depths of each treatment; and (c) constructing the Soil Salt Content (SSC) inversion models using partial least square regression (PLSR), Cubist, and Extreme Learning Machine (ELM). The results indicated that (a) classifying FVC could improve the stability and predictive ability of the models; (b) the performance of the three modeling methods were different (Cubist was the best, ELM next and PLSR the poorest); (c) the optimal inversion models for TB, TC and TE were constructed by Cubist at 0–20, 0–40 and 0–20 cm, and for TD was constructed by ELM at 0–60 cm, respectively. The results can provide references for soil salinization prevention and agricultural production in Jiefangzha Irrigation District and other areas with the similar vegetation cover.
Self‐contained deep learning‐based boosting of 4D cone‐beam CT reconstruction
Authors: Madesta Frederic , Sentker Thilo , Gauer Tobias , Werner René 
Published: August 2020

PurposeFour‐dimensional cone‐beam computed tomography (4D CBCT) imaging has been suggested as a solution to account for interfraction motion variability of moving targets like lung and liver during radiotherapy (RT) of moving targets. However, due to severe sparse view sampling artifacts, current 4D CBCT data lack sufficient image quality for accurate motion quantification. In the present paper, we introduce a deep learning‐based framework for boosting the image quality of 4D CBCT image data that can be combined with any CBCT reconstruction approach and clinical 4D CBCT workflow.MethodsBoosting is achieved by learning the relationship between so‐called sparse view pseudo‐time‐average CBCT images obtained by a projection selection scheme introduced to mimic phase image sparse view artifact characteristics and corresponding time‐average CBCT images obtained by full view reconstruction. The employed convolutional neural network architecture is the residual dense network (RDN). The underlying hypothesis is that the RDN learns the appearance of the streaking artifacts that is typical for 4D CBCT phase images — and removes them without influencing the anatomical image information. After training the RDN, it can be applied to the 4D CBCT phase images to enhance the image quality without affecting the contained temporal and motion information. Different to existing approaches, no patient‐specific prior knowledge about anatomy or motion characteristics is needed, that is, the proposed approach is self‐contained.ResultsApplication of the trained network to reconstructed phase images of an external (SPARE challenge) as well as in‐house 4D CBCT patient and motion phantom data set reduces the phase image streak artifacts consistently for all patients and state‐of‐the‐art reconstruction approaches. Using the SPARE data set, we show that the root mean squared error compared to ground truth data provided by the challenge is reduced by approximately 50% while normalized cross correlation of reconstruction and ground truth is improved up to 10%. Compared to direct deep learning‐based 4D CBCT to 4D CT mapping, our proposed method performs better because inappropriate prior knowledge about the patient anatomy and physiology is taken into account. Moreover, the image quality enhancement leads to more plausible motion fields estimated by deformable image registration (DIR) in the 4D CBCT image sequences.ConclusionsThe presented framework enables significantly boosting of 4D CBCT image quality as well as improved DIR and motion field consistency. Thus, the proposed method facilitates extraction of motion information from severely artifact‐affected images, which is one of the key challenges of integrating 4D CBCT imaging into RT workflows.
Feasibility study of patient‐specific dose verification in proton therapy utilizing positron emission tomography (PET) and generative adversarial network (GAN)
Authors: Ma Saiqun , Hu Zongsheng , Ye Kuangkuang , Zhang Xiaoke , Wang Yuenan , Peng Hao 
Published: August 2020

PurposeOnline dose verification based on proton‐induced positron emitters is a promising strategy for quality assurance in proton therapy. Because of the nonlinear correlation between dose and the activity distributions, a machine learning‐based approach was developed to establish their relationship.MethodsSimulations were carried out using a pencil beam scanning system and a computed tomography (CT) image‐based phantom. A DiscoGAN model was developed to perform dose verification for both central and off‐center lines. Besides the activity as input, HU information from CT images and stopping power (SP) prior were incorporated as auxiliary features for the model. The performance was quantitatively studied in terms of mean absolute error (MAE) and mean relative error (MRE), under different signal‐to‐noise ratios (SNRs). In addition to a dataset comprising monoenergetic beams, two additional datasets were generated to evaluate the model’s generalization capability: five reconstructed PET images based on an in‐beam PET system and a dataset comprising spread‐out Bragg peaks (SOBPs).ResultsThe feasibility of dose verification was successfully demonstrated for all three datasets. For the monoenergetic case (i.e., raw activity of positron emitters), the MRE is found to be <1% for the central lines and 5% for the off‐center lines, respectively. The range uncertainty is found to be less than 1 mm. The prediction based on five PET images, which take into account the detection of 511‐keV photons and image reconstruction, yields slightly inferior performance. For the SOBP case, the MRE of the center lines is found to be <3% and the range uncertainty is <1 mm. The inclusion of anatomical information (HU and SP) improves both accuracy and generalization of the DiscoGAN model.ConclusionThe combination of proton‐induced positron emitters, in‐beam PET, and machine learning may become a useful tool allowing for patient‐specific online dose verification in proton therapy.
Estimating Migratory Behavior and Age for Anadromous Coastal Cutthroat Trout in South Puget Sound: Evaluation of Approaches Based on Fish Scales versus Otoliths
Authors: Claiborne Andrew M. , Losee James P. , Miller Jessica A. 
Published: August 2020

Abstract
Important variability exists in life history attributes among localized populations of Coastal Cutthroat Trout Oncorhynchus clarkii clarkii in relation to geographic and environmental factors. Describing the life history of locally adapted populations is critical to successful fishery management and conservation. The number of annuli and distance between circuli in scales (i.e., scale analysis) are often used to describe migratory behavior and age of Coastal Cutthroat Trout, but the accuracy of these estimates is largely unknown. In this study, we compared estimates of age (based on analyses of scale and otolith structure) and migratory patterns (based on scale structure and otolith structure and chemistry) for anadromous Coastal Cutthroat Trout in South Puget Sound, Washington State. We compared 48 paired scale and otolith samples (age range = 1–5 years), and age estimates agreed 79% of the time (average percent error [APE] = 5%; CV = 6%), supporting historical age estimates that were generated using scales. However, the number of migrations between freshwater and marine environments estimated using scales and otoliths agreed 44% of the time (n = 50; APE = 25%; CV = 35%). Comparisons of scales and otoliths indicated that more individuals overwinter in marine waters than previously thought based on scale analysis. The majority of fish in this study (68%) were the progeny of females that matured in marine waters and may be vulnerable to fisheries in the marine environment. Current management actions that prohibit the harvest of Coastal Cutthroat Trout in marine waters may be important for the conservation of small localized populations in South Puget Sound.
In Utero Exposure to Maternal Overweight or Obesity is Associated with Altered Offspring Brain Function in Middle Childhood
Authors: Shapiro Allison L. B. , Moore Brianna F. , Sutton Brianne , Wilkening Greta , Stence Nicholas , Dabelea Dana , Tregellas Jason R. 
Published: August 2020

ObjectiveThe impact of in utero exposure to maternal overweight and obesity on offspring metabolic health is well documented. Neurodevelopmental outcomes among these children are, however, less well studied. To address this gap, the current study investigated brain function among 4‐ to 6‐year‐old children exposed to maternal overweight or obesity during gestation compared with that of children born to mothers with healthy BMI in pregnancy.MethodsResting‐state functional magnetic resonance imaging was used to study neuronal activity and connectivity during a passive viewing task (movie) among 101 typically developing children enrolled in the Healthy Start study, a longitudinal prebirth cohort in Colorado.ResultsForty‐nine children (48%) were exposed to maternal overweight or obesity in utero (mean age = 5 years, SD = 0.9). Children born to mothers with overweight or obesity demonstrated hyperactivity in the left posterior cingulate cortex and hypoactivity in the dorsal anterior cingulate and the supplementary motor area (P < 0.05 for all). Children born to mothers with overweight or obesity also showed ubiquitously weaker brain connectivity (P < 0.05 for all).ConclusionsThese novel results suggest altered brain function among children exposed to maternal overweight and obesity in utero.
Diversified exploitation of aerolysin nanopore in single‐molecule sensing and protein sequencing
Authors: Lu Si‐Min , Wu Xue‐Yuan , Li Meng‐Yin , Ying Yi‐Lun , Long Yi‐Tao 
Published: August 2020

AbstractNanopore electrochemistry has emerged as a promising technology to achieve the real‐time investigation of nanoscale processes at the single‐molecule level in a label‐free manner. To further extend the single‐molecule sensing versatility of nanopore single‐biomolecule interface, mutant aerolysin nanopore is developed followed by exploring the sensing mechanism. The exquisite design enables the site‐directed controlling of every amino acid along the aerolysin single‐biomolecule interface with the precision of chemical group. Owing to diversified pore‐analyte weak interactions between chemical groups (e.g., electrostatic interactions, hydrogen bond, van der Waals’ force) and steric confined effect, the mutant aerolysin displays extraordinarily high sensitivity and selectivity toward individual analytes in the stochastic sensing process. These well‐designed nanopores open more opportunities for biophysical, diagnostic applications, and even emerge as promising candidates for single‐molecule protein sequencing.
Tumor therapy based on self‐assembling peptides nanotechnology
Authors: Ma Xiaoyan , Xing Ruirui , Yuan Chengqian , Ogino Kenji , Yan Xuehai 
Published: August 2020

AbstractSelf‐assembling peptides display great potential in biological and medical applications, especially tumor therapy with noninvasive ways. The rapid expansion of self‐assembling peptides is almost on account of their favorable biocompatibility, tumor microenvironment responsiveness, multivalency, and structural versatility. With taking full advantage of self‐assembling peptide peculiarities, peptide‐based nanomaterials are applied for delivery carriers, chemotherapy, immunotherapy, and noninvasive tumor treatments including photothermal therapy (PTT), photodynamic therapy (PDT), and sonodynamic therapy (SDT). In addition, immunogenic cell death of tumor cells originating from PDT and SDT, and the necrosis of tumor cells due to PTT can elicit some degree of immune responses. Therefore, synergistic therapy has served as a more effective and powerful strategy for tumor therapy. Importantly, self‐assembling peptides are capable of subtly making combination of various treatments. This review outlines biomedical applications of nanomaterials based on self‐assembling peptides with emphasizing variegated treatment methods.
Distribution of intestinal parasites of baboons (Papio anubis) and warthogs (Phacochoerus aethiopicus) at the Mole National Park, Ghana
Authors: Larbi John A. , Akyeampong Stephen , Addo Seth Offei , Dakwa Kwaku Brako , Boampong Kwadwo , Opoku‐Nketiah Bright 
Published: August 2020

AbstractThe identification of intestinal parasite of baboons (Papio anubis) and warthogs (Phacochoerus aethiopicus) was undertaken at the Mole National Park, Ghana. The main objective of the study was to determine the types and prevalence of intestinal parasites in baboons and warthogs in the Mole National Park. A total of nineteen (19) and twenty‐three (23) samples were collected from the baboons and warthogs, respectively, and examined using the direct saline smear and formol‐ether concentration technique for the identification of cysts, eggs and larvae of parasites. The survey showed that 94.74% of the baboon samples examined was infected with at least one parasite, whereas that of the warthogs showed 95.65% prevalence. A total of seven (7) and eight (8) different parasites were identified in baboon and warthog faecal samples, respectively. Strongyloides sp. had the highest prevalence in baboons (84.21%) and warthogs (78.26%). The second prevalent parasite identified was Ascaris sp. in the baboons (31.58%) and warthogs (30.43%). The results showed a high level of multiparasitism in these wild animals and an increased risk of zoonotic transmission which may result from interaction with inhabitants of the park community.
Vertical greenery systems: from plants to trees with self-growing interconnections
Authors: Wang Xiuli , Gard Wolfgang , Borska Helena , Ursem Bob , van de Kuilen J. W. G. 
Published: August 2020

AbstractThe integration of buildings into vegetation has become a necessity in many metropolitan areas of the world today. It expands the potential of vertical and horizontal, exterior and interior, exposed and enclosed spaces in a building that can be used to accommodate plants. Green infrastructures have benefits both on urban and building scales. They can be categorized into green roofs and vertical greenery systems that can be divided further into green façade, green wall, green terraces, elevated forest and vertical forest. There are many design and planting considerations for architects, structural engineers and botanists when using living architectures to mimic natural systems, such as plant characteristics and environmental conditions. Plants used for vertical greenery are more likely to be hardwood species to adjust solar radiation during cooling and heating periods, as well as for aesthetic pleasure. Take Bosco Verticale, which is located in Milan, as an example to look into engineering methods when trees grow on balconies of high-rise buildings. It can be concluded that planting restraint safety systems and regular maintenance are necessary for the tree growth in the sky. However, the change in growing conditions causes various problems such as stability and irregular growth of trees. Instead of using steel cables and cages to prevent trees from falling off in the sky, the concept of self-growing connections is proposed to act as natural bracings and provide the stability for vertical forests. This paper is meant to generate awareness of the possibilities of the vertical integration of trees into buildings, show application considerations, and inspire future developments.
Motivic Tambara functors
Authors: Bachmann Tom 
Published: August 2020

AbstractLet k be a field and denote by $$\mathcal {SH}(k)$$

SH
(
k
)

the motivic stable homotopy category. Recall its full subcategory $$\mathcal {SH}(k)^{{\text {eff}}\heartsuit }$$

SH

(
k
)

eff
♡

(Bachmann in J Topol 10(4):1124–1144. arXiv:1610.01346, 2017). Write $$\mathrm {NAlg}(\mathcal {SH}(k))$$

NAlg
(
SH
(
k
)
)

for the category of $${\mathrm {S}\mathrm {m}}$$

S
m

-normed spectra (Bachmann-Hoyois in arXiv:1711.03061, 2017); recall that there is a forgetful functor $$U: \mathrm {NAlg}(\mathcal {SH}(k)) \rightarrow \mathcal {SH}(k)$$

U
:
NAlg
(
SH
(
k
)
)
→
SH
(
k
)

. Let $$\mathrm {NAlg}(\mathcal {SH}(k)^{{\text {eff}}\heartsuit }) \subset \mathrm {NAlg}(\mathcal {SH}(k))$$

NAlg

(
SH

(
k
)

eff
♡

)

⊂
NAlg

(
SH

(
k
)

)

denote the full subcategory on normed spectra E such that $$UE \in \mathcal {SH}(k)^{{\text {eff}}\heartsuit }$$

U
E
∈
SH

(
k
)

eff
♡

. In this article we provide an explicit description of $$\mathrm {NAlg}(\mathcal {SH}(k)^{{\text {eff}}\heartsuit })$$

NAlg
(
SH

(
k
)

eff
♡

)

as the category of effective homotopy modules with étale norms, at least if $$char(k) = 0$$

c
h
a
r
(
k
)
=
0

. A weaker statement is available if k is perfect of characteristic $$> 2$$

>
2

.