Frequency- and state-dependent dynamics of EEG microstates during propofol anesthesia by Yun Zhang, Haidong Wang, Fei Yan, Dawei Song, Qiang Wang, Yubo Wang, Liyu Huang

“…In the EEG-without-delta band, GEV, Cov, and Occ significantly increased for MS1 and MS3 (p < 0.01) and decreased for MS2 and MS4 (p < 0.05) during unconsciousness. …”
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Cooking Skills and Mediterranean Diet Adherence: Societal Insights from the iMC SALT Trial by Carla Gonçalves, Patrícia Padrão, Olívia Pinho, Tânia Silva-Santos, Pedro Moreira

“…Food and beverage processing levels were categorized using the NOVA classification, and the sodium/potassium intake was measured via 24 h urinary excretion. …”
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Clouds Detection in Polar Icy Terrains: A Deformable Attention-Based Deep Neural Network for Multispectral Polar Scene Parsing by Shaojin Dong, Cailan Gong, Yong Hu, Long Cheng, Yang Wang, Fuqiang Zheng

“…Within the dataset, our proposed model achieves an impressive overall classification accuracy of 95.97% and a mean intersection over union of 90.98%. …”
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The Results of Management of Distal End Radius Fractures by Various Modalities by Mansi J Patel, Dhyey Baldha, Aaksh Nareshbhai Koladiya, Lalit Bambhaniya, Utkarsh Panchal, Tejas Jogi, Ishani Patel, Neel Bhavsar

“…Material and method:40 patients were treated and followed up for a period from 3 to 14 months. Each patient underwent detailed clinical and radiological examinations of the affected wrist, using AO Classification. …”
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Hydroclimatic and Land Use Drivers of Wildfire Risk in the Colombian Caribbean by Yiniva Camargo Caicedo, Sindy Bolaño-Diaz, Geraldine M. Pomares-Meza, Manuel Pérez-Pérez, Tionhonkélé Drissa Soro, Tomás R. Bolaño-Ortiz, Andrés M. Vélez-Pereira

“…Fire-prone zones in the Magdalena Department covered ~744.35 km² (3.21%), with a weak but significant (τ = 0.20, <i>p</i> < 0.01) degree of coincidence between classification based on fire density, as pre-fire variable, and burned area, as a post-fire variable. …”
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TRIM6 ablation reverses ICB resistance in MSS gastric cancer by unleashing cGAS-STING-dependent antitumor immunity by Yinan Niu, Chen Ding, Quansheng Wang, Jingyi Yin, Lingmeng Li, Wenshuai Liu, Xuefei Wang, Liyu Huang

“…Methods Through weighted gene co-expression network analysis (WGCNA), we identified the E3 ubiquitin ligase TRIM6 as inversely associated with MSI-H status. …”
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Development and cross-validation of predictive equations for fat-free mass estimation by bioelectrical impedance analysis in Brazilian subjects with overweight and obesity by Kalina Veruska Da Silva Bezerra Masset, Analiza M. Silva, Analiza M. Silva, Gerson Ferrari, Gerson Ferrari, Breno Guilherme De Araújo Tinoco Cabral, Paulo Moreira Silva Dantas, Roberto Fernandes Da Costa

“…Paired t-test, multiple regression, concordance correlation coefficient, and Bland–Altman analysis were used.ResultsMost existing equations were not valid and new equations were derived: (1) for individuals with overweight or obesity: CCC = 0.982; r2 = 0.95; standard error of estimate (SEE) = 2.50 kg; limits of agreement (LOA) = -5.0 to 4.8; and (2) specific for individuals with obesity: CCC = 0.968; r2 = 0.94; SEE = 2.53 kg; LOA = -5.3 to 5.2. No FFM differences were observed between the new models and the reference method (p &gt; 0.05).ConclusionThe new proposed models provide valid options to estimate FFM in an adult population with overweight/obesity.…”
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A deep learning model to predict Ki-67 positivity in oral squamous cell carcinoma by Francesco Martino, Gennaro Ilardi, Silvia Varricchio, Daniela Russo, Rosa Maria Di Crescenzo, Stefania Staibano, Francesco Merolla

“…We next used QuPath to quantify IHC positivity, achieving remarkable levels of agreement between genuine and synthetic IHC.Furthermore, a categorical analysis employing 3 Ki-67 positivity cut-offs (5%, 10%, and 15%) revealed high positive-predictive values. …”
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An improved height sampling approach used for global urban building height mapping by Tingting He, Yihua Hu, Fashuai Li, Yuwei Chen, Maoxin Zhang, Qiming Zheng, Baiyu Dong, He Ren

“…This study proposed an improved approach for building height sampling that combines the ALOS AW3D30 and Global Ecosystem Dynamics Investigation (GEDI) data. …”
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Mapping the Cerrado–Amazon Transition Using PlanetScope–Sentinel Data Fusion and a U-Net Deep Learning Framework by Chuanze Li, Angela Harris, Beatriz Schwantes Marimon, Ben Hur Marimon Junior, Matthew Dennis, Polyanna da Conceição Bispo

“…According to the best-performing model, 50.3% of the study area remains covered by natural vegetation. …”
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The association between Helicobacter pylori infection and anthropometric, clinical, and laboratory parameters in children and adults with celiac disease: A cross-sectional study by Ramin Niknam, Mitra Soltani, Naser Honar, Ebrahim Fallahzadeh Abarghooei, Seyed Mohammad Mazloomi, Siavash Babajafari, Sahar Foshati, Mohammad Reza Fattahi, Laleh Mahmoudi

“…Endoscopic results were assessed to categorize CD histological damage according to the Marsh classification and differentiate people with or without H. pylori infection. …”
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One-Hot Multi-Level Leaky Integrate-and-Fire Spiking Neural Networks for Enhanced Accuracy-Latency Tradeoff by Pierre Abillama, Changwoo Lee, Andrea Bejarano-Carbo, Qirui Zhang, Dennis Sylvester, David Blaauw, Hun-Seok Kim

“…For dynamic vision datasets, we demonstrate the ability of M-LIF SNNs to reduce latency by <inline-formula> <tex-math notation="LaTeX">$3\times $ </tex-math></inline-formula> compared to conventional LIF SNNs while limiting accuracy degradation (&#x003C;1%).…”
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Architecture and implementation of ulrb algorithm in R by Francisco Pascoal, Rodrigo Costa, Luís Torgo, Catarina Magalhães, Paula Branco

“…Specifically, we include four groups of functions: 1) process data of the user into the correct format for the ulrb algorithm; 2) cluster taxa into abundance classifications; 3) helper functions to evaluate detailed statistics of the clustering steps; and 4) visualization functions, focused on rank abundance curves and Silhouette scores, for assessment of clustering quality. …”
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Protocol for detection and monitoring of post-stroke cognitive impairment through AI-powered speech analysis: a mixed methods pilot study by Ravi Shankar, Effie Chew, Effie Chew, Effie Chew, Anjali Bundele, Anjali Bundele, Amartya Mukhopadhyay, Amartya Mukhopadhyay

“…Statistical analysis will include correlation analysis between speech features and MoCA scores, as well as machine learning classification and regression models to predict cognitive impairment. …”
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The Impact of Resection Margins in Primary Resection of High-Grade Soft Tissue Sarcomas: How Far Is Far Enough? by Julian Miles Steffens, Tymoteusz Budny, Georg Gosheger, Marieke De Vaal, Anna Maria Rachbauer, Andrea Laufer, Nina Myline Engel, Niklas Deventer

“…<b>Background/Objectives</b>: The World Health Organization’s (WHO) classification of tumors contains around 80 entities of soft tissue sarcomas (STSs). …”
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Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur, Gurjit S. Randhawa, Farhat Abbas, Mumtaz Ali, Travis J. Esau, Aitazaz A. Farooque, Rajandeep Singh

“…The most widely used algorithms incorporate Support Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network (CNN), and MobileNet with accuracy rates between 64.3 and 100%. The importance of accurate disease detection and eradication has been reported for food security, financial stability, and sustainable farming practices. …”
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Effect of dietary approaches to stop hypertension and curcumin co-administration on glycemic parameters in polycystic ovary syndrome: An RCT by Tayebeh Zohrabi, Azadeh Nadjarzadeh, Sara Jambarsang, Mohammad Hasan Sheikhha, Abbas Aflatoonian, Hassan Mozaffari-Khosravi

“…They remained significant even after adjusting for confounding variables in adjusted models (body mass index classification, energy difference, age, and physical activity levels at the baseline) ( β = -45.3, 95% CI [-73.23, -17.46], p = 0.002). …”
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Multi-sequence MRI based radiomics nomogram for prediction expression of programmed death ligand 1 in thymic epithelial tumor by Jie Shen, Lantian Zhang, Shuke Li, Xiaofei Mu, Tongfu Yu, Wei Zhang, Yue Yu, Jing He, Wen Gao

“…The combined radiomics nomogram, which incorporates the peri-cardial invasion sign, ADC value, WHO classification, and radiomics signature, showed excellent performance (training cohort: area under the curve [AUC] = 0.903; validation cohorts: AUC = 0.894). …”
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Complications of radical and partial nephrectomy for renal cell carcinoma up to 7 cm by Marić Predrag, Jovanović Mirko, Milović Novak, Stamenković Dušica, Košević Branko, Aleksić Predrag, Cerović Snežana, Spasić Aleksandar, Simić Dejan, Rašković Jelena

“…These complications were mostly grade I and II. Complications grade III and IV were only present in the group of patients treated by PN. …”
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Comparative analysis of oncologic outcomes in surgically treated patients with renal cell carcinoma and renal vein thrombosis by pathologic subtypes by Dongrul Shin, Bumjin Lim, Cheryn Song, Dalsan You, In Gab Jeong, Jun Hyuk Hong, Hanjong Ahn, Bumsik Hong, Chang Wook Jeong, Jang Hee Han, Jungyo Suh

“…In nccRCC, 44 (44.0%) were papillary, 17 (17.0%) were chromophobe, and 39 (39.0%) were rare subtypes, most commonly TFE3 rearranged RCC, followed by the RCC not otherwise specified subtype (according to the 2022 World Health Organization Classification of RCC). …”
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