bluuebunny/crossref_metadata_2025_split huggingface dataset:
Best imaging signs identified by radiomics could outperform the model: application to differentiating lung carcinoid tumors from atypical hamartomas
Authors: Habert Paul , Decoux Antoine , Chermati Lilia , Gibault Laure , Thomas Pascal , Varoquaux Arthur , Le Pimpec-Barthes Françoise , Arnoux Armelle , Juquel Loïc , Chaumoitre Kathia , Garcia Stéphane , Gaubert Jean-Yves , Duron Loïc , Fournier Laure 
Published: September 2023

Abstract
Objectives
Lung carcinoids and atypical hamartomas may be difficult to differentiate but require different treatment. The aim was to differentiate these tumors using contrast-enhanced CT semantic and radiomics criteria.

Methods
Between November 2009 and June 2020, consecutives patient operated for hamartomas or carcinoids with contrast-enhanced chest-CT were retrospectively reviewed. Semantic criteria were recorded and radiomics features were extracted from 3D segmentations using Pyradiomics. Reproducible and non-redundant radiomics features were used to training a random forest algorithm with cross-validation. A validation-set from another institution was used to evaluate of the radiomics signature, the 3D ‘median’ attenuation feature (3D-median) alone and the mean value from 2D-ROIs.

Results
Seventy-three patients (median 58 years [43‒70]) were analyzed (16 hamartomas; 57 carcinoids). The radiomics signature predicted hamartomas vs carcinoids on the external dataset (22 hamartomas; 32 carcinoids) with an AUC = 0.76. The 3D-median was the most important in the model. Density thresholds < 10 HU to predict hamartoma and > 60 HU to predict carcinoids were chosen for their high specificity > 0.90. On the external dataset, sensitivity and specificity of the 3D-median and 2D-ROIs were, respectively, 0.23, 1.00 and 0.13, 1.00 < 10 HU; 0.63, 0.95 and 0.69, 0.91 > 60 HU. The 3D-median was more reproducible than 2D-ROIs (ICC = 0.97 95% CI [0.95‒0.99]; bias: 3 ± 7 HU limits of agreement (LoA) [− 10‒16] vs. ICC = 0.90 95% CI [0.85‒0.94]; bias: − 0.7 ± 21 HU LoA [− 4‒40], respectively).

Conclusions
A radiomics signature can distinguish hamartomas from carcinoids with an AUC = 0.76. Median density < 10 HU and > 60 HU on 3D or 2D-ROIs may be useful in clinical practice to diagnose these tumors with confidence, but 3D is more reproducible.

Critical relevance statement
Radiomic features help to identify the most discriminating imaging signs using random forest. ‘Median’ attenuation value (Hounsfield units), extracted from 3D-segmentations on contrast-enhanced chest-CTs, could distinguish carcinoids from atypical hamartomas (AUC = 0.85), was reproducible (ICC = 0.97), and generalized to an external dataset.

Key points
• 3D-‘Median’ was the best feature to differentiate carcinoids from atypical hamartomas (AUC = 0.85).
• 3D-‘Median’ feature is reproducible (ICC = 0.97) and was generalized to an external dataset.
• Radiomics signature from 3D-segmentations differentiated carcinoids from atypical hamartomas with an AUC = 0.76.
• 2D-ROI value reached similar performance to 3D-‘median’ but was less reproducible (ICC = 0.90).

Graphical Abstract
The diagnostic performance and clinical value of deep learning-based nodule detection system concerning influence of location of pulmonary nodule
Authors: You Seulgi , Park Ji Hyun , Park Bumhee , Shin Han-Bit , Ha Taeyang , Yun Jae Sung , Park Kyoung Joo , Jung Yongjun , Kim You Na , Kim Minji , Sun Joo Sung 
Published: September 2023

Abstract
Background
The deep learning-based nodule detection (DLD) system improves nodule detection performance of observers on chest radiographs (CXRs). However, its performance in different pulmonary nodule (PN) locations remains unknown.

Methods
We divided the CXR intrathoracic region into non-danger zone (NDZ) and danger zone (DZ). The DZ included the lung apices, paramediastinal areas, and retrodiaphragmatic areas, where nodules could be missed. We used a dataset of 300 CXRs (100 normal and 200 abnormal images with 216 PNs [107 NDZ and 109 DZ nodules]). Eight observers (two thoracic radiologists [TRs], two non-thoracic radiologists [NTRs], and four radiology residents [RRs]) interpreted each radiograph with and without the DLD system. The metric of lesion localization fraction (LLF; the number of correctly localized lesions divided by the total number of true lesions) was used to evaluate the diagnostic performance according to the nodule location.

Results
The DLD system demonstrated a lower LLF for the detection of DZ nodules (64.2) than that of NDZ nodules (83.2, p = 0.008). For DZ nodule detection, the LLF of the DLD system (64.2) was lower than that of TRs (81.7, p < 0.001), which was comparable to that of NTRs (56.4, p = 0.531) and RRs (56.7, p = 0.459). Nonetheless, the LLF of RRs significantly improved from 56.7 to 65.6 using the DLD system (p = 0.021) for DZ nodule detection.

Conclusion
The performance of the DLD system was lower in the detection of DZ nodules compared to that of NDZ nodules. Nonetheless, RR performance in detecting DZ nodules improved upon using the DLD system.

Critical relevance statement
Despite the deep learning-based nodule detection system’s limitations in detecting danger zone nodules, it proves beneficial for less-experienced observers by providing valuable assistance in identifying these nodules, thereby advancing nodule detection in clinical practice.

Key points
• The deep learning-based nodule detection (DLD) system can improve the diagnostic performance of observers in nodule detection.
• The DLD system shows poor diagnostic performance in detecting danger zone nodules.
• For less-experienced observers, the DLD system is helpful in detecting danger zone nodules.

Graphical Abstract
Umbilical cord mesenchymal stem cell-derived apoptotic extracellular vesicles ameliorate cutaneous wound healing in type 2 diabetic mice via macrophage pyroptosis inhibition
Authors: Wang Yiming , Jing Lin , Lei Xiao , Ma Zhen , Li Bei , Shi Yuanyuan , Zhang Wuyang , Li Yuan , Zhou Hongzhi , Hu Kaijin , Xue Yang , Jin Yan 
Published: September 2023

Abstract
Background
Delayed healing of diabetic cutaneous wounds is one of the most common complications of type 2 diabetes mellitus (T2DM), which can bring great distress to patients. In diabetic patients, macrophages accumulate around skin wounds and produce NLRP3 (NOD-, LRR-, and pyrin domain-containing protein 3) inflammasomes, which in turn undergo pyroptosis and produce inflammatory factors such as interleukin-1β that affect wound healing. Although our previous study revealed that apoptotic extracellular vesicles (ApoEVs) produced from mesenchymal stem cells (MSCs) improve cutaneous wound healing in normal C57BL/6 mice, whether ApoEVs can also improve diabetic wound healing remains unclear.

Methods
Umbilical cord mesenchymal stem cells (UCMSCs) were cultured in vitro and apoptosis was induced. ApoEVs were extracted and identified and used in a T2DM mouse cutaneous wound model to evaluate the efficacy. The inhibitory effect of ApoEVs on macrophage pyroptosis was verified in vivo and in vitro, and the level of oxidative stress in macrophages was assessed to explore the mechanism by which ApoEVs play a role.

Results
UCMSC-derived ApoEVs improved skin defect healing in T2DM mice. Moreover, UCMSC-derived ApoEVs inhibited macrophage pyroptosis in T2DM mice in vivo as well as in vitro under high-glucose culture conditions. In addition, we demonstrated that ApoEVs reduce oxidative stress levels, which is a possible mechanism by which they inhibit macrophage pyroptosis.

Conclusions
Our study confirmed that local application of UCMSC-derived ApoEVs improved cutaneous wound healing in T2DM mice. ApoEVs, as products of MSC apoptosis, can inhibit macrophage pyroptosis and regulate the death process by decreasing the level of oxidative stress.
Extended study on atomic featurization in graph neural networks for molecular property prediction
Authors: Wojtuch Agnieszka , Danel Tomasz , Podlewska Sabina , Maziarka Łukasz 
Published: September 2023

AbstractGraph neural networks have recently become a standard method for analyzing chemical compounds. In the field of molecular property prediction, the emphasis is now on designing new model architectures, and the importance of atom featurization is oftentimes belittled. When contrasting two graph neural networks, the use of different representations possibly leads to incorrect attribution of the results solely to the network architecture. To better understand this issue, we compare multiple atom representations by evaluating them on the prediction of free energy, solubility, and metabolic stability using graph convolutional networks. We discover that the choice of atom representation has a significant impact on model performance and that the optimal subset of features is task-specific. Additional experiments involving more sophisticated architectures, including graph transformers, support these findings. Moreover, we demonstrate that some commonly used atom features, such as the number of neighbors or the number of hydrogens, can be easily predicted using only information about bonds and atom type, yet their explicit inclusion in the representation has a positive impact on model performance. Finally, we explain the predictions of the best-performing models to better understand how they utilize the available atomic features.
Association of antimicrobial perioperative prophylaxis with cefuroxime plus metronidazole or amoxicillin/clavulanic acid and surgical site infections in colorectal surgery
Authors: Stavropoulou Elisavet , Atkinson Andrew , Eisenring Marie-Christine , Fux Christoph A. , Marschall Jonas , Senn Laurence , Troillet Nicolas 
Published: September 2023

Abstract
Objective
To compare intravenous (IV) amoxicillin/clavulanic acid (A/CA) to IV cefuroxime plus metronidazole (C + M) for preventing surgical site infections (SSI) in colorectal surgery.

Background
Given their spectra that include most Enterobacterales and anaerobes, C + M is commonly recommended as prophylaxis of SSI in colorectal surgery. A/CA offers good coverage of Enterobacterales and anaerobes as well, but, in contrast to C + M, it also includes Enterococcus faecalis which is also isolated from patients with SSI and could trigger anastomotic leakage.

Methods
Data from a Swiss SSI surveillance program were used to compare SSI rates after class II (clean contaminated) colorectal surgery between patients who received C + M and those who received A/CA. We employed multivariable logistic regression to adjust for potential confounders, along with propensity score matching to adjust for group imbalance.

Results
From 2009 to 2018, 27,922 patients from 127 hospitals were included. SSI was diagnosed in 3132 (11.2%): 278/1835 (15.1%) in those who received A/CA and 2854/26,087 (10.9%) in those who received C + M (p < 0.001). The crude OR for SSI in the A/CA group as compared to C + M was 1.45 [CI 95% 1.21–1.75]. The adjusted OR was 1.49 [1.24–1.78]. This finding persisted in a 1:1 propensity score matched cohort of 1835 patients pairs with an OR of 1.60 [1.28–2.00]. Other factors independently associated with SSI were an ASA score > 2, a longer duration of operation, and a reoperation for a non-infectious complication. Protective factors were female sex, older age, antibiotic prophylaxis received 60 to 30 min before surgery, elective operation, and endoscopic approach.

Conclusions
Despite its activity against enterococci, A/CA was less effective than C + M for preventing SSI, suggesting that it should not be a first choice antibiotic prophylaxis for colorectal surgery.
Space weather impacts on the ionosphere over the southern African mid-latitude region
Authors: Matamba Tshimangadzo Merline , Danskin Donald W. , Nndanganeni Rendani R. , Tshisaphungo Mpho 
Published: September 2023

AbstractThe ionosphere suffers major perturbations during severe space weather events such as Coronal Mass Ejections (CMEs), solar flares, high-speed streams, and Corotating Interaction Regions (CIRs). The ionosphere can experience depletions or enhancements in Total Electron Content (TEC) during severe space weather conditions. The South African National Space Agency (SANSA) near-real-time (NRT) TEC maps were used to show the ionospheric variability during the geomagnetic storm of 3–8 Nov 2021 over the southern Africa mid-latitude region. The ionosonde TEC, NRT TEC, and the quiet-time AfriTEC model were compared during the 6-day period. A negative ionospheric response was observed during the main and recovery phases of the geomagnetic storm (4–5 Nov 2021). The changes to neutral composition O/N2 was one of the physical processes attributed to the decrease in TEC over the mid-latitude region. The GPS TEC maps showed a very good agreement with ionosonde measurements and the AfriTEC model. A strong east–west TEC gradient was observed occurring between two ionosonde stations.
Graphical Abstract
In vitro inhibition mechanism of Trichoderma asperellum isolates from corn against Rhizoctonia solani causing banded leaf and sheath blight disease and its role in improving the growth of corn seedlings
Authors: Mirsam Hishar , Suriani  , Kurniawati Sri , Purwanto Oky Dwi , Muis Amran , Pakki Syahrir , Tenrirawe A. , Nonci Nurnina , Herawati  , Muslimin  , Azrai Muhammad 
Published: September 2023

Abstract
Background
One of the primary corn diseases, banded leaf and sheath blight, is carried on by the pathogenic fungus Rhizoctonia solani. Efforts to control R. solani are more directed at environmentally friendly control using a biological control agent, such as Trichoderma spp. as antagonistic agents and plant growth promoter. This study aimed to identify T. asperellum isolates based on molecular characteristics and to determine the in vitro inhibition mechanism against R. solani and its role in enhancing the growth of corn seedlings.

Results
The HMRP7, HMRF7A, HMEDF1B, HMEDF6A, and CHM01 isolates were identified as T. asperellum with a genetic distance coefficient value of 0.000 and a very high similarity of 100%. Meanwhile, the RsHM isolate was identified as R. solani with a homology level of > 90% and genetic distance coefficient values ranging from 0.000 to 0.032. The antagonistic ability showed that the five T. asperellum isolates were able to inhibit the growth of R. solani in vitro on PDA medium with an inhibition percentage of ≥ 50%, so they were categorized as antagonist agents. T. asperellum showed the antagonistic mechanism in inhibiting the R. solani growth through the action of parasitism. The five T. asperellum isolates tested on corn seedlings showed a significantly high difference from the control treatment on the observational variables of maximum growth potential (MGP), growth rate (GtR), growth simultaneity (GS), vigor index (VI), germination rate (GR), and median germination time (T50).

Conclusion
CHM01 isolate showed better potential than other isolates in inhibiting the growth of R. solani in vitro on PDA medium with a parasitism mechanism and enhancing the growth of corn seedlings.
RETRACTED ARTICLE: FireXnet: an explainable AI-based tailored deep learning model for wildfire detection on resource-constrained devices
Authors: Ahmad Khubab , Khan Muhammad Shahbaz , Ahmed Fawad , Driss Maha , Boulila Wadii , Alazeb Abdulwahab , Alsulami Mohammad , Alshehri Mohammed S. , Ghadi Yazeed Yasin , Ahmad Jawad 
Published: September 2023

Abstract
Background
Forests cover nearly one-third of the Earth’s land and are some of our most biodiverse ecosystems. Due to climate change, these essential habitats are endangered by increasing wildfires. Wildfires are not just a risk to the environment, but they also pose public health risks. Given these issues, there is an indispensable need for efficient and early detection methods. Conventional detection approaches fall short due to spatial limitations and manual feature engineering, which calls for the exploration and development of data-driven deep learning solutions. This paper, in this regard, proposes 'FireXnet', a tailored deep learning model designed for improved efficiency and accuracy in wildfire detection. FireXnet is tailored to have a lightweight architecture that exhibits high accuracy with significantly less training and testing time. It contains considerably reduced trainable and non-trainable parameters, which makes it suitable for resource-constrained devices. To make the FireXnet model visually explainable and trustable, a powerful explainable artificial intelligence (AI) tool, SHAP (SHapley Additive exPlanations) has been incorporated. It interprets FireXnet’s decisions by computing the contribution of each feature to the prediction. Furthermore, the performance of FireXnet is compared against five pre-trained models — VGG16, InceptionResNetV2, InceptionV3, DenseNet201, and MobileNetV2 — to benchmark its efficiency. For a fair comparison, transfer learning and fine-tuning have been applied to the aforementioned models to retrain the models on our dataset.

Results
The test accuracy of the proposed FireXnet model is 98.42%, which is greater than all other models used for comparison. Furthermore, results of reliability parameters confirm the model’s reliability, i.e., a confidence interval of [0.97, 1.00] validates the certainty of the proposed model’s estimates and a Cohen’s kappa coefficient of 0.98 proves that decisions of FireXnet are in considerable accordance with the given data.

Conclusion
The integration of the robust feature extraction of FireXnet with the transparency of explainable AI using SHAP enhances the model’s interpretability and allows for the identification of key characteristics triggering wildfire detections. Extensive experimentation reveals that in addition to being accurate, FireXnet has reduced computational complexity due to considerably fewer training and non-training parameters and has significantly fewer training and testing times.
The main controlling factors of tensile strength in sight of shale reservoir under horizontal bedding: Example of the Lower Paleozoic Niutitang Formation shale from Micangshan, China
Authors: Li Delu , Li Haibin , He Qianyang , Gao Jianwen , Tao Wenxing , Wang Shimiao 
Published: September 2023

Understanding the mechanical characteristics of marine shale during fracturing is essential for shale gas development, and its core scientific problem is what factors in shale control its mechanical properties. The 12 shale samples from the Lower Paleozoic Niutitang Formation in Micangshan are tested for tensile strength and examined using X-ray diffraction, low-field nuclear magnetic resonance (NMR), EA2000 elemental analyzer, and scanning electron microscopy to explore the main controlling factors of shale tensile strength under horizontal bedding conditions. The findings are as follows. (1) The tensile strength of the shale is relatively high, ranging from 10.05 MPa to 20.34 MPa. Quartz is the largest proportion of the shale minerals, accounting for 53.2 wt%–59.0 wt%, followed by anorthose and clay minerals. Total organic carbon (TOC) concentration ranges from 1.7 wt% to 4.1 wt%. (2) NMR results indicate that the pore structure of shale is mainly mesoporous, accounting for 75.76%–88.03%, followed by macropores (12.57%–21.24%) and micropores (0.68%–4.91%). Low-pressure nitrogen adsorption and desorption results indicate that the average pore diameter of shale is 12.58–16.02 nm, which is basically consistent with NMR results. The negative correlation between fractal dimension D2 and tensile strength indicates that the higher the tensile strength of the shale, the lower the complexity of its seepage pores. (3) Micropores occur mainly in clay minerals, whereas quartz indicates positively correlation with mesoporous content. The higher the proportion of mesopores, the lower the tensile strength. This indicates that the mesopores are the main factor controlling the tensile strength, and the quartz content in minerals is a secondary factor restricting the tensile strength. TOC has little controlling action on the tensile strength. This contribution provides a theoretical basis for shale fracturing.
Which Patients With Rhabdomyosarcoma Need Radiotherapy? Analysis of the Radiotherapy Strategies of the CWS-96 and CWS-2002P Studies and SoTiSaR Registry
Authors: Koscielniak Ewa , Timmermann Beate , Münter Marc , Weclawek-Tompol Jadwiga , Ladenstein Ruth , Niggli Felix , Ljungman Gustaf , Brecht Ines B. , Blank Bernd , Hallmen Erika , Scheer Monika , Fuchs Joerg , Seitz Guido , Blattmann Claudia , Sparber-Sauer Monika , Klingebiel Thomas 
Published: September 2023

PURPOSE To analyze and compare the indications, doses, and application methods of radiotherapy (RT) and their influence on prognosis of patients with localized rhabdomyosarcoma (RMS). METHODS One thousand four hundred seventy patients with localized RMS 21 years and younger entered on CWS-96, CWS-2002P, and SoTiSaR were eligible for the analysis. The median follow-up was 6.5 years (IQR, 3.3-9.5). RESULTS The 5-year event-free survival (EFS) and local control survival (LCS) for 910 (62%) irradiated versus nonirradiated patients were 71% versus 69% and 78% versus 73% ( P = .03), respectively. Ninety-five percent of patients in IRS I (90% embryonal RMS [eRMS]) were nonirradiated (EFS, 87%). Irradiated patients with IRS II had improved LCS (91% v 80%; P = .01) and EFS (not significant). In IRS III, EFS and LCS were significantly better for RT patients: 71% versus 56% ( P = 3.1e-06) and 76% versus 61% ( P = 4.1e-07). Patients with tumors in the head and neck region (orbita, parameningeal, and nonparameningeal) and in other sites had significantly better EFS and LCS and in parameningeal also overall survival (OS). The efficacy of low RT doses of 32 Gy (hyperfractionated, accelerated RT [HART]) and 36 and 41.4 Gy (conventional fractionated RT [CFRT]) in the favorable groups and higher doses of 44.8 Gy (HART) and 50.4 and 55.4 Gy (CFRT) in the unfavorable groups was comparable. Proton RT was used predominantly in head/neck—parameningeal (HN—PM) tumors, with similar EFS and LCS to photon RT. CONCLUSION RT can be omitted in patients with IRS I eRMS. RT improves LCS and EFS in IRS II and III. RT improves OS in patients with HN-PM, with proton RT comparable with photon RT. Doses of 32 Gy (HART) or 36 and 41.4 Gy (CFRT) had comparable efficacy in patients with favorable risk profiles and 44.8 Gy (HART) or 50.4 and 55.8 Gy (CFRT) in the unfavorable groups.