bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metabolic rewiring induced by ranolazine improves melanoma responses to targeted therapy and immunotherapy
Authors: Redondo-Muñoz Marta , Rodriguez-Baena Francisco Javier , Aldaz Paula , Caballé-Mestres Adriá , Moncho-Amor Verónica , Otaegi-Ugartemendia Maddalen , Carrasco-Garcia Estefania , Olias-Arjona Ana , Lasheras-Otero Irene , Santamaria Eva , Bocanegra Ana , Chocarro Luisa , Grier Abby , Dzieciatkowska M Monika , Bigas Claudia , Martin Josefina , Urdiroz-Urricelqui Uxue , Marzo Florencio , Santamaria Enrique , Kochan Grazyna , Escors David , Larrayoz Ignacio Marcos , Heyn Holger , D’Alessandro Angelo , Attolini Camille Stephan-Otto , Matheu Ander , Wellbrock Claudia , Benitah Salvador Aznar , Sanchez-Laorden Berta , Arozarena Imanol 
Published: August 2023

AbstractResistance of melanoma to targeted therapy and immunotherapy is linked to metabolic rewiring. Here, we show that increased fatty acid oxidation (FAO) during prolonged BRAF inhibitor (BRAFi) treatment contributes to acquired therapy resistance in mice. Targeting FAO using the US Food and Drug Administration-approved and European Medicines Agency-approved anti-anginal drug ranolazine (RANO) delays tumour recurrence with acquired BRAFi resistance. Single-cell RNA-sequencing analysis reveals that RANO diminishes the abundance of the therapy-resistant NGFRhi neural crest stem cell subpopulation. Moreover, by rewiring the methionine salvage pathway, RANO enhances melanoma immunogenicity through increased antigen presentation and interferon signalling. Combination of RANO with anti-PD-L1 antibodies strongly improves survival by increasing antitumour immune responses. Altogether, we show that RANO increases the efficacy of targeted melanoma therapy through its effects on FAO and the methionine salvage pathway. Importantly, our study suggests that RANO could sensitize BRAFi-resistant tumours to immunotherapy. Since RANO has very mild side-effects, it might constitute a therapeutic option to improve the two main strategies currently used to treat metastatic melanoma.
Uncertainty in land-use adaptation persists despite crop model projections showing lower impacts under high warming
Authors: Molina Bacca Edna J. , Stevanović Miodrag , Bodirsky Benjamin Leon , Karstens Kristine , Chen David Meng-Chuen , Leip Debbora , Müller Christoph , Minoli Sara , Heinke Jens , Jägermeyr Jonas , Folberth Christian , Iizumi Toshichika , Jain Atul K. , Liu Wenfeng , Okada Masashi , Smerald Andrew , Zabel Florian , Lotze-Campen Hermann , Popp Alexander 
Published: August 2023

AbstractClimate change is expected to impact crop yields and alter resource availability. However, the understanding of the potential of agricultural land-use adaptation and its costs under climate warming is limited. Here, we use a global land system model to assess land-use-based adaptation and its cost under a set of crop model projections, including CO2 fertilization, based on climate model outputs. In our simulations of a low-emissions scenario, the land system responds through slight changes in cropland area in 2100, with costs close to zero. For a high emissions scenario and impacts uncertainty, the response tends toward cropland area changes and investments in technology, with average adaptation costs between −1.5 and +19 US$05 per ton of dry matter per year. Land-use adaptation can reduce adverse climate effects and use favorable changes, like local gains in crop yields. However, variance among high-emissions impact projections creates challenges for effective adaptation planning.
Novel pharmacological approaches in abdominal aortic aneurysm
Authors: Puertas-Umbert Lídia , Almendra-Pegueros Rafael , Jiménez-Altayó Francesc , Sirvent Marc , Galán María , Martínez-González José , Rodríguez Cristina 
Published: August 2023

Abstract
Abdominal aortic aneurysm (AAA) is a severe vascular disease and a major public health issue with an unmet medical need for therapy. This disease is featured by a progressive dilation of the abdominal aorta, boosted by atherosclerosis, ageing, and smoking as major risk factors. Aneurysm growth increases the risk of aortic rupture, a life-threatening emergency with high mortality rates. Despite the increasing progress in our knowledge about the etiopathology of AAA, an effective pharmacological treatment against this disorder remains elusive and surgical repair is still the unique available therapeutic approach for high-risk patients. Meanwhile, there is no medical alternative for patients with small aneurysms but close surveillance. Clinical trials assessing the efficacy of antihypertensive agents, statins, doxycycline, or anti-platelet drugs, among others, failed to demonstrate a clear benefit limiting AAA growth, while data from ongoing clinical trials addressing the benefit of metformin on aneurysm progression are eagerly awaited. Recent preclinical studies have postulated new therapeutic targets and pharmacological strategies paving the way for the implementation of future clinical studies exploring these novel therapeutic strategies. This review summarises some of the most relevant clinical and preclinical studies in search of new therapeutic approaches for AAA.
Laboratory bistatic synthetic aperture radar coherent change detection investigation
Authors: Hagelberg Alexander , Andre Daniel , Finnis Mark 
Published: August 2023

AbstractSynthetic Aperture Radar (SAR) Coherent Change Detection (CCD) allows for the detection of very small scene changes. This is particularly useful for reconnaissance and surveillance as small changes such as vehicle tracks can be identified. In some situations, it is desirable to rapidly collect repeat pass SAR images for use in change detection, and multistatic geometries may facilitate this. Such repeat passes may however have significant baselines, particularly for satellite‐based platforms, though CCD products are reliant on high coherence for good interpretability. This work investigates the sources and levels of incoherence associated with bistatic SAR imagery with increasing baselines using simulations and measured laboratory data.
An active learning method based on result quality evaluation for printed circuit board computed tomography image segmentation
Authors: Song Baojie , Qiao Kai , Yang Jie , Shi Shuhao , Chen Jian , Yan Bin 
Published: August 2023

AbstractElement detection is a key step in non‐destructive testing of printed circuit board (PCB) based on computed tomography (CT). In recent years, some image segmentation methods based on deep learning have shown great potential in the element segmentation task of PCB CT images, and greatly improved the efficiency and accuracy. However, since image segmentation is based on pixel‐level classification, the annotation of training data is difficult and costly. Aiming at this problem, the authors proposed a new active learning method based on the integration of relevant information about segmentation tasks and data variance. In this method, the Result Quality Evaluation Module (RQEM) proposed by us is used to generate task‐related information, and an adversarial network is used to generate the difference information between samples and the initial labelled data. Finally, the two parts of information are fused and used as the standard of data selecting. In the PCB CT image element segmentation task, the authors only need to select 12.7% of the whole training set with their proposed method to make Mean Intersection Over Union (MIOU) reach 79.7, which has reached 95% of the optimal performance of 83.7. The in‐depth analysis also verifies the effectiveness and stability of the authors’ method.
DMAGNet: Dual‐path multi‐scale attention guided network for medical image segmentation
Authors: Ji Qiulang , Wang Jihong , Ding Caifu , Wang Yuhang , Zhou Wen , Liu Zijie , Yang Chen 
Published: August 2023

AbstractIn recent years, convolutional neural networks (CNN)‐based automatic segmentation of medical images has become one of the hot topics in clinical disease diagnosis. It is still a challenging task to improve the segmentation accuracy of the network model with the large variation of pathological regions in different patients and the fuzzy boundary of pathological regions. A Dual‐path Multi‐scale Attention Guided network (DMAGNet) for medical image segmentation is proposed in this paper. First, the Dual‐path Multi‐scale Attention Fusion Module (DMAF) is proposed as a novel skip connection strategy, which is applied to encode semantic dependencies between high‐level and low‐level channels. Second, the Multi‐scale Normalized Channel Attention Module (MNCA) based on the atrous convolution, normalization channel attention mechanism, and the Depthwise Separable Convolutions (DSConv) is developed to strengthen dependencies between channels. Finally, the encoder–decoder backbone employs the DSConv, as well as the pretrained Resnet34 block is combined in the encoder part to further improve the backbone network performance. Comprehensive experiments on brain, lung, and liver segmentation tasks show that the proposed DMAGNet outperforms the original U‐Net method and other advanced methods.
Passing‐yielding intention estimation during lane change conflict: A semantic‐based Bayesian inference method
Authors: Cui Mingyang , Liu Jinxin , Zheng Haotian , Xu Qing , Wang Jiangqiang , Geng Lu , Sekiguchi Takaaki 
Published: August 2023

AbstractIntention estimation has been widely studied in lane change scenarios, which explains a vehicle's behaviour and implies its future motion. However, in dense traffic, lane‐changing is more tactical and interactive. Due to the conflict between merging vehicles and adjacent vehicles, driving intentions become interdependent which fuses passing and yielding. In addition, lane change occurs without a fixed location. Drivers should be aware of each other's intentions along conflict process, and take instant responses. To address these challenges, this paper proposes semantic‐based interactive intention estimation (SIIE), to understand driving intentions during lane change conflict. The problem is addressed by combining driving semantics with probability inference model based on dynamic Bayesian network (DBN). Firstly, the DBN is modelled for the interaction process with Condition‐Intention‐Behaviour relationships. Secondly, the semantics are extracted from the lane change conflict and are inferred with observation methods. Thirdly, SIIE is trained and verified with real‐world driving data. The intention estimation results are demonstrated, and then utilized for multi‐modal motion identification and trajectory prediction. Lane change in dense traffic requires interactive cognition of driving intentions, the findings of this research shall inspire future studies into related scenarios, and promote interactive driving technologies.
Optimal load demand forecasting in air conditioning using deep belief networks optimized by an improved version of snake optimization algorithm
Authors: Jiang Haichang , Li Minghai , Fathi Gholamreza 
Published: August 2023

AbstractAir conditioning systems play a vital role in maintaining comfortable indoor environments, particularly in hot and humid climates. However, these systems consume a significant amount of energy, making load demand forecasting an important aspect of energy management. In this study, the authors propose a novel approach for load demand forecasting in air conditioning systems using a hybrid deep belief network (HDBN) and an improved snake optimization algorithm (ISOA). The HDBN is a machine learning technique that combines deep learning and probabilistic graphical models to capture complex patterns in the input data. The ISOA is a nature‐inspired optimization algorithm that mimics the movement of a snake to search for optimal solutions. The proposed approach is evaluated using real‐world data from a commercial building in a hot and humid region. The results show that the proposed HDBN/ISOA approach outperforms other commonly used techniques in terms of accuracy. The proposed approach can be used to optimize energy consumption and reduce costs in air conditioning systems.
XRBcats: Galactic High Mass X-ray Binary Catalogue
Authors: Neumann M. , Avakyan A. , Doroshenko V. , Santangelo A. 
Published: August 2023

Context. We present a new catalogue of high mass X-ray binaries (HMXBs) in the Galaxy that we call the Galactic High Mass X-ray Binary Catalogue (XRBcats), which improves upon the most recent of such catalogues. We include new HMXBs discovered since previous publications and revise the classification for several objects previously considered HMXBs or HMXB candidates. The catalogue includes basic information (e.g. source names, coordinates, types), other data (e.g. distance and X-ray flux estimates, binary system parameters), and other characteristic properties of the 169 HMXBs catalogued. We also present finding charts in several bands from the infrared to hard X-rays for each object.
Aims. The aim of this catalogue is to provide a list of all currently known Galactic HMXBs, including basic information on both compact objects and non-degenerate counterpart properties (where available). We also include objects tentatively classified as HXMBs in the literature and give a brief motivation for the classification in each case.
Methods. The catalogue is compiled based on a search of known HMXBs and candidates in all publicly available databases and literature published before May 2023. The relevant properties in various wavelength bands were collected for all objects, either from the literature or using data provided by large-scale surveys. For the latter case, the counterparts in each individual survey were found by cross-correlating positions of identified HMXBs with relevant databases.
Results. An up-to-date catalogue of Galactic HMXBs is presented to facilitate research in this field. Our goal was to collect a larger set of relevant HMXB properties in a more uniform way compared to previously published works.
Sektorenübergreifende Versorgungsverläufe von
Patient*innen mit kolorektalem Karzinom in
Sachsen-Anhalt
Authors: Beutner Katrin , Medenwald Daniel , Meyer Gabriele 
Published: August 2023

Zusammenfassung
Einleitung Die kleinräumige Gesundheitsversorgung Sachsen-Anhalts
wird als disparat beschrieben, da sich Regionen mit guter Versorgungsstruktur
und zunehmend unterversorgte Regionen gegenüberstehen. Defizite beim
sektorenübergreifenden Therapiemanagement gefährden die
poststationäre Versorgung in ländlichen Gebieten. Ziel der
Arbeit war es, anhand von GKV-Routinedaten beispielhaft für
Patient*innen mit kolorektalem Karzinom sektorenübergreifend die
Versorgungssituation in Sachsen-Anhalt über den Zeitraum von
Diagnosestellung bis zu einem Jahr poststationär zu analysieren und zu
prüfen, ob Versorgungsunterschiede zwischen Versicherten aus
städtischen und ländlichen Regionen auszumachen sind.
Methoden Die Studienpopulation umfasst 13.218 Versicherte der AOK
Sachsen-Anhalt mit kolorektalem Karzinom der Jahre 2010–2014. Die
abgerechneten Versorgungsleistungen von Krankenhäusern und ambulanten
Ärzt*innen wurden in Bezug auf den Wohnort (Stadt oder Land) der
betroffenen Patient*innen betrachtet. Die Ermittlung der
Überlebenszeiten erfolgte nach Kaplan & Meier und die Analyse
erklärender Variablen auf das Überleben mittels
Regressionsanalyse nach dem Cox-Proportional-Hazards-Model.
Ergebnisse Unterschiede zwischen städtischen und
ländlichen Regionen wurden bei den involvierten Facharztgruppen im
ambulanten Bereich sowie bei der Versorgung in Darmkrebszentren deutlich. Der
Anteil der Versicherten mit onkologischen Zusatztherapien war sehr gering,
sodass nur in Ansätzen von leitliniengerechter Therapie ausgegangen
wird. Die Analyse offenbarte einen signifikanten Überlebensvorteil
für Versicherte aus der Großstadt im Vergleich zu Versicherten
aus ländlichen Regionen, wofür v. a. eine frühere
Diagnosestellung, ein jüngeres Alter, weniger Komorbiditäten und
eine adäquatere Krebstherapie ursächlich sind.
Schlussfolgerung Es bedarf einer Optimierung der Versorgungsstrukturen und
-prozesse, die eine frühe Diagnosestellung und barrierefreie
Inanspruchnahme adäquater Therapien ermöglicht.
Aus der Krise zur Empathie: Martin Gumperts Vermächtnis für die Medizin des 21. Jahrhunderts
Authors: Keim Ulrike , Schröder Hartmut , Mildenberger Florian G. 
Published: August 2023

ZusammenfassungDie 1920er Jahre gelten in der medizinhistorischen Überlieferung als das klassische Krisenjahrzehnt im 20. Jahrhundert, von dem aus der Weg der deutschen Medizin mehr oder weniger direkt in den nationalsozialistischen Untergang geführt habe. Doch die „Krisis der Medizin“ führte mitnichten zwangsläufig in den Strudel aus Eugenik und Rassenhass, sondern begünstigte auch eine Rückbesinnung auf ethische Traditionen und zeitlose Werte. Dies zeigt sich in besonderem Maße am Beispiel des Arztes Martin Gumpert (1897–1955). Gumpert agierte als politisch denkender und handelnder Arzt, der als Pionier der Entstellungschirurgie, der Gerontologie und Prävention gilt und ein großes Vermächtnis als Dermatologe, Sozialmediziner sowie als Forscher und Journalist hinterlassen hat, dass es heute mehr denn je zu würdigen gilt.
Einsatz von erweiterten Realitäten (XR) in der Thoraxchirurgie
Authors: Feodorovici Philipp , Arensmeyer Jan , Schnorr Philipp , Schmidt Joachim 
Published: August 2023

ZusammenfassungErweiterte Realitäten (XR) mit den Unterbegriffen Virtual Reality (VR), Augmented Reality (AR) und Mixed Reality (MR) beschreiben interaktive und immersive Technologien, welche die reelle
Welt durch digitale Elemente ersetzen oder diese um solche nahtlos erweitern. Die XR bieten somit ein sehr breites mögliches Anwendungsspektrum in der Medizin. In der Chirurgie und
insbesondere in der Thoraxchirurgie lassen sich XR-Technologien für Anwendungen der Behandlungsplanung, Navigation, Ausbildung und Patienteninformationen nutzbar machen. Solche
Anwendungsfälle befinden sich zunehmend in der Erprobung und müssen hinsichtlich ihrer Wertigkeit evaluiert werden. Wir geben einen Überblick über den Status quo der technischen Entwicklung,
aktuelle chirurgische Einsatzgebiete der XR und blicken in die Zukunft der medizinischen XR-Landschaft mit Integration von künstlicher Intelligenz (KI).
Recycling von chirurgischen Einweginstrumenten – lohnt sich das?
Authors: Dohmen Jonas , Lessau Meike , Schmitz Michael , Kalff Jörg C. 
Published: August 2023

ZusammenfassungDer deutsche Gesundheitssektor ist für 5,2% der landesweiten Treibhausgasemissionen verantwortlich. Mitverantwortlich hierfür ist die erhebliche Menge an tagtäglich in deutschen
Krankenhäusern erzeugtem Abfall, der die Kliniken zum fünftgrößten Müllproduzenten Deutschlands macht. Die gesetzlichen Regelungen sehen vor, dass ein wesentlicher Anteil der
Krankenhausabfälle, trotz potenzieller Recyclingfähigkeit, energetisch verwertet, also verbrannt, wird. Hierdurch werden einerseits hohe CO2-Emissionen erzeugt und andererseits
wertvolle Rohstoffe dem Kreislauf entzogen. Ziel dieses Projekts war es, anhand von chirurgischen Einweginstrumenten die Machbarkeit des Recyclings von komplexen, kontaminierten
Medizingeräten nachzuweisen.Inkludiert wurden häufig eingesetzte chirurgische Einweginstrumente, die potenziell als Elektroschrott recycelt werden konnten. Diese Instrumente wurden wischdesinfiziert und anschließend
krankenhausintern sterilisiert. Nach der Sterilisation konnten die Geräte in Rücksprache mit der Umweltbehörde als Elektroschrott klassifiziert und durch ein Entsorgungsunternehmen extern
maschinell recycelt werden. Durch Schredder- und Sortiermaschinen wurden die Instrumente in die einzelnen Fraktionen Kabel, Kunststoffe, verschiedene Metalle und Platinen aufgeteilt und zu
Sekundärrohstoffen weiterverarbeitet.In den ersten 6 Monaten (09/2022–03/2023) wurden 239 kg Material recycelt anstatt verbrannt. Dies entspricht einer Einsparung von 545 kg CO2e. Der Metallanteil lag bei ca. 50%
des Gesamtgewichts. Hinzu kamen 30% recycelbare Kunststoffe, sodass eine Recyclingquote von 80% erreicht wurde. Die laufenden Kosten für das Recycling lagen nach Abzug der Einnahmen bei
1,90 €/kg. Damit ist Recycling in diesem Modell 3,9-mal so teuer wie die Verbrennung. Eine Umfrage unter dem beteiligten OP-Personal ergab eine hohe Zufriedenheit mit dem Recyclingprojekt
und einen geringen Mehraufwand von < 5 min.Wir konnten zeigen, dass das Recycling kontaminierter Einweginstrumente in Absprache mit den staatlichen Behörden möglich ist und hierdurch Abfallverbrennung vermieden und
CO2-Äquivalente eingespart werden können. Einschränkend auf die Umsetzbarkeit solcher Projekte wirken derzeit noch die deutlich höheren Kosten des Recyclings und die
Verpflichtung der krankenhausinternen Dekontamination. Um dies zu ändern, ist der Gesetzgeber gefragt, die derzeitigen Vorschriften zu überdenken und die Hersteller an den Recyclingkosten
zu beteiligen, um das riesige Recyclingpotenzial vollständig auszunutzen.
Adrenal Crisis – Definition, Prevention and Treatment:
Results from a Delphi Survey
Authors: Kienitz Tina , Bechmann Nicole , Deutschbein Timo , Hahner Stefanie , Honegger Jürgen , Kroiss Matthias , Quinkler Marcus , Rayes Nada , Reisch Nicole , Willenberg Holger Sven , Meyer Gesine 
Published: August 2023

AbstractBased on recent data, a total number of about 29 000 patients with adrenal
insufficiency can be calculated for Germany, and about 1500 fatalities due to
adrenal crises have to be expected within the next decade. Management of adrenal
crises is still unsatisfactory. The objectives of this study were to establish
consensus for diagnostic criteria, prevention strategies, and treatment
recommendations for adrenal crises. The study was conducted from January 2022 to
April 2023, using Delphi technique. Four rounds of questionnaires were sent to
45 experts, selected by a coordinating group on behalf of the adrenal section of
the German Society of Endocrinology. The survey was implemented online using the
REDCap web application. Responses were captured anonymously. During the Delphi
process the expert panel developed diagnostic criteria to identify patients
likely to have an adrenal crisis. Education about adrenal insufficiency among
patients as well as non-endocrine medical personnel were regarded as highly
important. It was suggested that recommendations for the management of adrenal
insufficiency have to be simplified and made widely available. This study
provides pragmatic strategies to identify and treat patients prone to adrenal
crisis, thereby highlighting the need for an improved management of patients
with adrenal insufficiency.
Prevalence of sonographic signs in women with uterine sarcoma: a systematic review and meta-analysis
Authors: Raffone Antonio , Raimondo Diego , Neola Daniele , Travaglino Antonio , Doglioli Marisol , Ambrosio Marco , Raimondo Ivano , De Meis Lucia , Turco Luigi Carlo , Cosentino Francesco , Seracchioli Renato , Casadio Paolo , Mollo Antonio 
Published: August 2023

Abstract
Objective To assess the prevalence of sonographic signs in women with uterine sarcoma.
Materials and Methods A systematic review and meta-analysis were performed. Five electronic databases were searched from inception to June 2022 for all studies allowing calculation of the prevalence of sonographic signs in women with uterine sarcoma. Pooled prevalence with 95% confidence intervals was calculated for each sonographic sign and was a priori defined as “very high” when it was ≥ 80%, “high” when it ranged from 80% to 70%, and less relevant when it was ≤ 70%.
Results 6 studies with 317 sarcoma patients were included. The pooled prevalence was:
Conclusion Solid component, irregular walls of cystic areas, and singular lesions are signs with very high prevalence, while inhomogeneous echogenicity of solid component, anechoic cystic areas, and absence of calcifications are signs with high prevalence. The remaining signs were less relevant.