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Erica Spiculifolia Salisb. (Balkan Heath): a Focus on Metabolic Profiling and Antioxidant and Enzyme Inhibitory Properties
No full textErica spiculifolia Salisb. (formerly Bruckenthalia spiculifolia Benth.) (Balkan heath) is renowned for its traditional usage as a diuretic, anti-inflammatory and antioxidant agent. For the first time, acylquinic acids, flavonoids and numerous proanthocyanidin oligomers were annotated/dereplicated by liquid chromatography-high-resolution mass spectrometry in methanol-aqueous extracts from E. spiculifolia aerial parts harvested at the early and full flowering stage. Chlorogenic acid and proanthocyanidin tetra- and trimer A, B-type together with quercitrin and (+) catechin were the predominant compounds in the semi-quantitative analysis. Neutral triterpenoids, triterpenoid acids and phytosterols were determined in apolar extracts by gas chromatography-mass spectrometry. Triterpenoid acids accounted for 80% of the total triterpenoid content, dominated by ursolic and oleanolic acid, reaching up to 32.2 and 6.1 mg/g dw, respectively. Ursa/olean-2,12-dien-28-oic acids and 3-keto-derivatives together with alpha-amyrin acetate as a chemotaxonomic marker, alpha-amyrenone, alpha- and beta-amyrin were evaluated. Total phenolic and flavonoid contents were 83.85 +/- 0.89 mg gallic acid equivalents/g and 78.91 +/- 0.41 mg rutin equivalents/g, respectively. The extract actively scavenged DPPH and ABTS radicals (540.01 and 639.11 mg Trolox equivalents (TE)/g), possessed high potential to reduce copper and iron ions (660.32 and 869.22 mg TE/g, respectively), and demonstrated high metal chelating capacity (15.57 Ethylenediaminetetraacetic acid equivalents/g). It exhibited prominent anti-lipase (18.32 mg orlistat equivalents/g) and anti-tyrosinase (71.90 mg kojic acid equivalents/g) activity. The extract inhibited alpha-glucoside (1.35 mmol acarbose equivalents/g) and acetylcholinesterase (2.56 mg galanthamin equivalents/g), and had moderate effects on alpha-amylase, elastase, collagenase and hyaluronidase. Balkan heath could be recommended for raw material production with antioxidant and enzyme inhibitory properties.Agence Universitaire de la Francophonie; [AUF ECO 2024 DRECO-8591]This research was funded by Agence Universitaire de la Francophonie, grant number AUF ECO 2024 DRECO-8591.Science Citation Index Expande
The Effect of Topiramate on the Cerebellum of the Obese Female Rats: a Stereological, Histochemical and Bioinformatical Study by Investigation of Tnf-Α Interaction
No full textThe rising incidence of obesity underscores the necessity for alternative obesity treatments. Patients commonly prefer medication aiding in weight reduction. Topiramate, an antiepileptic drug, is gaining popularity among obese patients for its weight loss benefits. This study aims to explore Topiramate's impact on the cerebella of obese female rats. In the experiment, 24 female rats (200-250 g) were divided into four groups: non-obese control (NOC), obese control (OC), non-obese topiramate (NOT) and obese topiramate (OT). The non-obese rats were given a standard diet, while the obese rats received a high-fat diet (40% fat). After 9 weeks, topiramate was administered intraperitoneally daily for 6 weeks. Following this, the rats were euthanised, and their cerebella were removed. The volume of the cerebellum and mean numerical density of the molecular neurons, granular neurons and Purkinje cells were estimated using stereological methods, and the link between obesity-caused cerebellum damage and TNF-alpha was assessed through immunohistochemical and bioinformatic techniques. Additionally, histopathological evaluations of the tissues were conducted. The cerebellar volume in the OC group was decreased compared to the NOC group. The topiramate groups exhibited a decrease in molecular or/and granular neuron numbers in the NOT and OT groups. Notably, neurons with dark cytoplasm were observed in the topiramate-treated groups, alongside neuronal degeneration was seen in the obese groups. The connection between TNF-alpha and obesity or obesity-caused cerebellum damage was confirmed through both immunohistochemical and bioinformatics analyses. These findings suggest that topiramate might have a degenerative effect on the cerebellum, especially following obesity.Science Citation Index Expande
Seçim Kampanya Ürünlerinde Grafik Tasarımın Dijitalleşme Süreci
No full textBu araştırmada, 1990-2020 yılları arasında Türkiye’de gerçekleşen seçim kampanyalarındaki grafik tasarım ürünlerinin dijitalleşme süreçleri incelenmektedir. Araştırmanın amacı, dijital devrimin seçim kampanyalarında kullanılan grafik tasarım ürünleri üzerindeki etkilerini ve dijital ürünlerin geleneksel ürünlerle olan etkileşimini analiz etmektir. 2000'li yıllarla birlikte hız kazanan dijitalleşme süreci, seçim kampanyalarında yeni medya araçlarının kullanımını yaygınlaştırmaktadır. Geleneksel ürünlerin afiş, broşür gibi türleri dijital ortamlarda paylaşım görselleri, bilgi grafikleri ve tematik video içeriklerine dönüşmektedir. Bu dönüşüm, etkileşimli bir grafik tasarım dili oluştururken, aynı zamanda görsel sadelik ve etkiyi artırmıştır. Araştırmada tarama yöntemi kullanılarak, 1990-2020 yılları arasındaki seçim kampanyalarında üretilmiş grafik tasarım ürünleri üç dönem halinde incelenmektedir. Birinci dönem (1990-2000), ikinci dönem (2000-2010) ve üçüncü dönem (2010-2020) olarak ele alınan bu süreçlerde, her dönemdeki geleneksel ve dijital ürünlerin özellikleri analiz edilmektedir. Bulgular, geleneksel ürünlerin kampanyaların önemli bir parçası olmaya devam ettiğini; dijital ürünlerin ise özellikle yapılan son seçimlere doğru daha etkili kullanıldığını göstermektedir. Dijitalleşmenin etkisiyle, grafik tasarımlar görsel sadelik ve güç kazanarak dijital mecralarda daha fazla yer bulmaktadır
Respiratory Parameter Estimation Using Pharyngeal Phonetics and Machine Learning: Breaking Free from Spirometry
No full textThe capacity to screen for respiratory diseases is vital for clinical diagnostics. Forced Expiratory Volume in 1 relevant second and Forced Vital Capacity are the two most common parameters or measures of respiratory health. Although respiratory health may be assessed using spirometry or other traditional forms of diagnostics, spirometry has variances in device availability, patient compliance during testing, and complexity of the testing procedure. This study found a novel, non-invasive means of estimating pulmonary function based on the voiced pharyngeal sound of "He" using analysis of the voiced sound. The study explored a model for estimating Forced Expiratory Volume in 1 s and Forced Vital Capacity values based on the outputs from traditional spirometry and features extracted from voice signals. There were a total of 21 features that were extracted from the voiced segments of the pharyngeal sound. All machine learning models of Forced Expiratory Volume in 1 s and Forced Vital Capacity used three machine learning algorithms. Data was collected from 18 male participants, aged 33-49 years old, from June 2022 to August 2022, which resulted in 56 recordings. Among the models that were evaluated in comparison to the linear, neural network, and quadratic models, the quadratic model performed the worst, while the neural network performed the best. The neural network model that used three features estimated Forced Expiratory Volume in 1 s with a mean error of 0.24 % while the two-feature neural network model estimated Forced Vital Capacity with a mean error of 0.58 %.Jiangxi University of Science and Technology [341000]; Ganzhou, P.R. China [2021205200100563]; Jiangxi University of Science and Technology Ethics Committee [2024JXUST729]This work was supported by Jiangxi University of Science and Technology, 341000, Ganzhou, P.R. China, under funding number: 2021205200100563. The authors wish to acknowledge the Jiangxi University of Science and Technology Ethics Committee, with the number 2024JXUST729, for their oversight and approval of the ethical protocols employed in this study.Science Citation Index Expande
Search for Dark Matter Production in Association with a Single Top Quark in Proton-Proton Collisions at √s=13 TeV
No full textFigueiredo, Diego/0000-0003-2514-6930; Lee, Jason/0000-0002-2153-1519; Mondal, Spandan/0000-0003-0153-7590; , Mohammad Mobassir Ameen/0000-0002-1909-9843; Uslan, Ebru/0000-0002-2472-0526; Soha, Aron/0000-0002-5968-1192; Chernyavskaya, Nadezda/0000-0002-2264-2229; Chatterjee, Suman/0000-0003-2660-0349; Leonardo, Nuno/0000-0002-9746-4594; Kunnawalkam Elayavalli, Raghav/0000-0002-9202-1516; Cumalat, John/0000-0002-6032-5857; Gershtein, Yuri/0000-0002-4871-5449; Cavallari, Francesca/0000-0002-1061-3877; Simone, Federica Maria/0000-0002-1924-983X; Menezes De Oliveira, Thales/0009-0009-4729-8354; Moureaux, Louis/0000-0002-2310-9266; Faccioli, Pietro/0000-0003-1849-6692; Tok, Ufuk Guney/0000-0002-3039-021X; Lee, Jason/0000-0002-2153-1519; Goldstein, Joel/0000-0003-1591-6014; Lintuluoto, Adelina/0000-0002-0726-1452; Lu, Meng/0000-0002-6999-3931; Agicevic, Marko/0000-0003-1967-6783; Ahmad, Ashfaq/0000-0002-4770-1897; Cavallari, Francesca/0000-0002-1061-3877; Piccinelli, Anea/0000-0003-0386-0527; Pásztor, Gabriella/0000-0003-0707-9762; Novaes, Sergio/0000-0003-0471-8549; Goldouzian, Reza/0000-0002-0295-249X; D'Amante, Valeria/0000-0002-7342-2592; Yagil, Avi/0000-0002-6108-4004; Poncet, Océane/0000-0002-5346-2968; Konstantinou, Sotiroulla/0000-0003-0408-7636; Christoforou, Konstantinos/0000-0003-2205-1100; Kole, Gouranga/0000-0002-3285-1497; Han, Yixiao/0000-0002-3510-6505; Mantilla, Cristina/0000-0002-0177-5903; Mousa, Jehad/0000-0002-2978-2718; Saha, Nihar Ranjan/0000-0002-7954-7898; Meuser, Danilo/0000-0002-2722-7526; Kanuganti, Ankush Reddy/0000-0002-0789-1200; Vischia, Pietro/0000-0002-7088-8557; Pfeffer, Emanuel/0009-0009-1748-974X; Novak, Anzej/0000-0002-0389-5896; Sehrawat, Ashish/0000-0002-6816-7814; Zucchetta, Alberto/0000-0003-0380-1172; Dogra, Sunil Manohar/0000-0002-0812-0758; Dozen, Candan/0000-0002-4301-634X; De Souza Lemos, Dener/0000-0003-1982-8978; Melo Da Costa, Eliza/0000-0002-5016-6434; Pásztor, Gabriella/0000-0003-0707-9762; Castilla-Valdez, Heriberto/0009-0005-9590-9958; Tiwari, Praveen Chana/0000-0002-3667-3843; Tok, Ufuk Guney/0000-0002-3039-021X; Fischer, Yannick/0000-0002-3184-1457; Sharma, Ram Krishna/0000-0003-1181-1426; Duarte, Javier Mauricio/0000-0002-5076-7096; Navarrete Ramos, Efren/0000-0002-5180-4020; Salvatico, Riccardo/0000-0002-2751-0567; Aarrestad, Thea/0000-0002-7671-243X; Klanner, Robert/0000-0002-7004-9227; Hinzmann, Aneas/0000-0002-2633-4696; Garutti, Erika/0000-0003-0634-5539; Tytgat, Michael/0000-0002-3990-2074; Escalante Del Valle, Alberto/0000-0002-9702-6359; Sekhar, Sanjana/0000-0002-8307-7518; Alcaraz Maestre, Juan/0000-0003-0914-7474; Rieger, Marcel/0000-0003-0797-2606; Malik, Sudhir/0000-0002-6356-2655; Seidel, Markus/0000-0003-3550-6151; Brooke, James/0000-0003-2529-0684; Jabusch, Henrik Ronald/0000-0003-2444-1014; Chou, Pin-Chun/0000-0002-5842-8566; Vazquez-Escobar, Julia/0000-0002-7533-2283; Fehérkuti, Anna/0000-0002-5043-2958; Matorras-Cuevas, Pablo/0000-0001-7481-7273; Ruabhatla, Sahithi/0000-0002-7366-4225; Grummer, Aidan/0000-0003-2752-1183; Meridiani, Paolo/0000-0002-8480-2259; Ruiz, Jose/0000-0002-3306-0363; Erice Cid, Carlos Francisco/0000-0002-6469-3200; Osite, Dace/0000-0002-2912-319X; Ha, Seungkyu/0000-0003-2538-1551; Forthomme, Laurent/0000-0002-3302-336X; Dozen, Candan/0000-0002-4301-634X; Migliore, Ernesto/0000-0002-2271-5192; Ligabue, Franco/0000-0002-1549-7107; Fontanesi, Elisa/0000-0002-0662-5904; Selvaggi, Michele/0000-0002-5144-9655; Dansana, Soumya/0000-0002-7752-7471; Novaes, Sergio/0000-0003-0471-8549; Fiorina, Davide/0000-0002-7104-257X; Ehatäht, Karl/0000-0002-2387-4777; Pérez Prada, Maximilian/0000-0002-2831-463X; Chahal, Gurpreet Singh/0000-0003-0320-4407; Lee, Lawrence/0000-0002-5590-335X; Calligaris, Luigi/0000-0002-9951-9448; Ecklund, Karl/0000-0002-6976-4637; Kirpichnikov, Dmitry/0000-0002-7177-077X; Vannerom, David/0000-0002-2747-5095; Cavallari, Francesca/0000-0002-1061-3877; Golf, Frank/0000-0003-3567-9351; Gadallah, Mahmoud Moussa Abdelkhalek/0000-0002-8305-6661; Govoni, Pietro/0000-0002-0227-1301; Khvedelidze, Arsen/0000-0002-5953-0140; Hinzmann, Aneas/0000-0002-2633-4696; Kyriacou, Savvas/0000-0002-9254-4368; D'Enterria, David/0000-0002-5754-4303; Fernandez Perez Tomei, Thiago Rafael/0000-0002-1809-5226; Grab, Christophorus/0000-0002-6182-3380; Ptochos, Fotios/0000-0002-3432-3452; Neri Huerta, Fernando Enrique/0000-0002-2298-2215; Klyukhin, Vyacheslav/0000-0002-8577-6531; Gomez Espinosa, Tirso Alejano/0000-0002-9443-7769; Mudholkar, Tanmay/0000-0002-9352-8140; Dallavalle, Gaetano Marco/0000-0002-8614-0420; Ajmal, Sehar/0000-0002-2726-2858; D'Anzi, Brunella/0000-0002-9361-3142; Kim, Youngwan/0000-0002-4856-5989; Lucchini, Marco Toliman/0000-0002-7497-7450; Long, Kenneth/0000-0003-0664-1653; Heikkilä, Jaana/0000-0002-0538-1469; Yagil, Avi/0000-0002-6108-4004; Pigazzini, Simone/0000-0002-8046-4344; Lange, Clemens/0000-0002-3632-3157; Sahasransu, Abanti Ranadhir/0000-0003-1505-1743; Vai, Ilaria/0000-0003-0037-5032; Duarte, Javier Mauricio/0000-0002-5076-7096; Saha, Gourab/0000-0002-6125-1941; D'Amante, Valeria/0000-0002-7342-2592; Dharmaratna, Welathantri/0000-0002-6366-837X; Saha, Gourab/0000-0002-6125-1941; Ruales, Anderson/0000-0003-0826-0803; Kalbhor, Pritam/0000-0002-5892-3743; Watson, Ian James/0000-0003-2141-3413; Pesaresi, Mark/0000-0002-9759-1083; Bury, Florian/0000-0002-3077-2090; Martin Perez, Cristina/0000-0003-1581-6152; Tok, Ufuk Guney/0000-0002-3039-021X; Cetorelli, Flavia/0000-0002-3061-1553; Malik, Sudhir/0000-0002-6356-2655; Hatakeyama, Kenichi/0000-0002-6012-2451; Cavallari, Francesca/0000-0002-1061-3877; Petrucciani, Giovanni/0000-0003-0889-4726; Röwert, Nicolas/0000-0002-4745-5470; Escalante Del Valle, Alberto/0000-0002-9702-6359; Cattafesta, Filippo/0009-0006-6923-4544; Knight, Charlotte Rose/0009-0008-1167-4816; Arneodo, Michele/0000-0002-7790-7132; Reimers, Arne Christoph/0000-0002-9438-2059; Qin, Xuelong/0009-0007-5089-3694; Missiroli, Marino/0000-0002-1780-1344; Mantilla, Cristina/0000-0002-0177-5903; Lu, Meng/0000-0002-6999-3931; Robertshaw, Liam/0009-0006-5304-2492; Dominguez, Aaron/0000-0002-7420-5493; Pauls, Alexander/0000-0002-8117-5376; Zucchetta, Alberto/0000-0003-0380-1172; Lawhorn, Jay/0000-0002-8597-9259; Chou, Pin-Chun/0000-0002-5842-8566; Van Onsem, Gerrit/0000-0002-1664-2337; Kramer, Tobias Robert Jakob/0000-0002-7004-0214; Mastrapasqua, Paola/0000-0002-2043-2367; Naskar, Kousik/0000-0003-0638-4378; Golf, Frank/0000-0003-3567-9351; Simone, Federica Maria/0000-0002-1924-983X; Dozen, Candan/0000-0002-4301-634X; Watson, Ian James/0000-0003-2141-3413; Krintiras, Georgios Konstantinos/0000-0002-0380-7577; Dharmaratna, Welathantri/0000-0002-6366-837X; Zorbakir, Ibrahim Soner/0000-0002-5962-2221; Chatterjee, Suman/0000-0003-2660-0349; Niedziela, Jeremi/0000-0002-9514-0799; Grunewald, Martin/0000-0002-5754-0388; Alves, Gilvan/0000-0002-8369-1446; Kasemann, Matthias/0000-0002-0429-2448; Rieger, Marcel/0000-0003-0797-2606; Duarte, Javier Mauricio/0000-0002-5076-7096; Riti, Federica/0000-0002-1466-9077; Gomez-Ceballos, Guillelmo/0000-0003-1683-9460; Wittich, Peter/0000-0002-7401-2181; Mendizabal, Mikel/0000-0002-6506-5177; Bärtschi, Pascal/0000-0002-8842-6027; Jabeen, Shabnam/0000-0002-0155-7383; Frankenthal, Ane/0000-0002-2583-5982; Sculac, Toni/0000-0002-9578-4105; Stäger, Fabian/0009-0003-0724-7727; Chitroda, Bhakti/0000-0002-0220-8441; Lu, Meng/0000-0002-6999-3931; Nanda, Shirsendu/0000-0003-0550-4083; Meng, Fanqiang/0000-0003-0443-5071; Dozen, Candan/0000-0002-4301-634X; Guzzi, Luca/0000-0002-3086-8260; Leon Holgado, Jaime/0000-0002-4156-6460; Dubinin, Mikhail/0000-0002-7766-7175; Waltenberger, Wolfgang/0000-0002-6215-7228; Blumenfeld, Barry/0000-0003-1150-1735; Russell, Lucas/0000-0002-6502-2185; Grohsjean, Alexander/0000-0003-0748-8494; Tapper, Alexander/0000-0003-4543-864X; Novaes, Sergio/0000-0003-0471-8549; Alexakhin, Vadim/0000-0002-4886-1569; Torres Da Silva De Araujo, Felipe/0000-0002-4785-3057; Lorkowski, Florian/0000-0003-2677-3805; González Caballero, Isio/0000-0002-8087-3199; Mondal, Spandan/0000-0003-0153-7590; Luongo, Fabio/0000-0003-2743-4119; Manzoni, Riccardo Anea/0000-0002-7584-5038; Martin Perez, Cristina/0000-0003-1581-6152; Diotalevi, Tommaso/0000-0003-0780-8785; Pizzati, Giorgio/0000-0003-1692-6206; Colaleo, Anna/0000-0002-0711-6319; Lee, Jason/0000-0002-2153-1519; Kim, Suho/0000-0003-2381-5117; Piccinelli, Anea/0000-0003-0386-0527; Rinkevicius, Aurelijus/0000-0002-7510-255X; Sharma, Vivek/0000-0003-1736-8795; Petković, Ano/0009-0005-9565-6399; Assiouras, Panagiotis/0000-0002-5152-9006; Zorbakir, Ibrahim Soner/0000-0002-5962-2221; Bodek, Arie/0000-0003-0409-0341; Horzela, Maximilian/0000-0002-3190-7962; Escalante Del Valle, Alberto/0000-0002-9702-6359; Lange, Clemens/0000-0002-3632-3157; Sharma, Vivek/0000-0003-1736-8795;A search for the production of a single top quark in association with invisible particles is performed using proton-proton collision data collected with the CMS detector at the LHC at root s = 13 TeV, corresponding to an integrated luminosity of 138 fb(-1). In this search, a flavor-changing neutral current produces a single top quark or antiquark and an invisible state nonresonantly. The invisible state consists of a hypothetical spin-1 particle acting as a new mediator and decaying to two spin-1/2 dark matter candidates. The analysis searches for events in which the top quark or antiquark decays hadronically. No significant excess of events compatible with that signature is observed. Exclusion limits at 95% confidence level are placed on the masses of the spin-1 mediator and the dark matter candidates, and are compared to constraints from the dark matter relic density measurements. In a vector (axial-vector) coupling scenario, masses of the spin-1 mediator are excluded up to 1.85 (1.85) TeV with an expectation of 2.0 (2.0) TeV, whereas masses of the dark matter candidates are excluded up to 0.75 (0.55) TeV with an expectation of 0.85 (0.65) TeV.FWF (Belgium); FNRS (Belgium); FWO (Belgium); CNPq; CAPES (Brazil); FAPERJ (Brazil); FAPERGS (Brazil); FAPESP (Brazil); BNSF (Bulgaria); MoST (China); NSFC (China); CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG [MoER TK202]; Academy of Finland; MEC (France); CEA (France); CNRS/IN2P3 (France); SRNSF (Germany); BMBF (Germany); DFG (Germany); HGF (Germany); NKFIH (Hungary); DAE (Ireland); DST (Ireland); IPM (Ireland); SFI (Ireland); INFN (Italy); NRF (Republic of Korea); MES (Latvia); MOE (Malaysia); UM (Malaysia); BUAP (Mexico); CONACYT (Mexico); UASLP-FAI (Mexico); PAEC (Pakistan); FCT (Portugal); MESTD (Serbia); PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); NSTDA; TUBITAK; DOE; NSF; Marie-Curie program; European Research Council; Horizon 2020 Grant [675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207]; COST Action [CA16108]; Leventis Foundation; Alfred P. Sloan Foundation; Alexander von Humboldt Foundation; Science Committee [22rl-037]; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); Beijing Municipal Science & Technology Commission [Z191100007219010]; Fundamental Research Funds for the Central Universities (China); Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; Shota Rustaveli National Science Foundation [FR-22-985]; Deutsche Forschungsgemeinschaft (DFG) [EXC 2121, 390833306, 400140256 - GRK2497]; Hellenic Foundation for Research and Innovation (HFRI) [2288]; Hungarian Academy of Sciences [K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64, 2021-4.1.2-NEMZ_KI-2024-00036]; Council of Science and Industrial Research, India - NextGenerationEU program (Italy); Latvian Council of Science; Ministry of Education and Science [2022/WK/14]; National Science Center [Opus 2021/41/B/ST2/01369, 2021/43/B/ST2/01552]; Fundacao para a Ciencia e a Tecnologia [CEECIND/01334/2018]; National Priorities Research Program by Qatar National Research Fund [MICIU/AEI/10.13039/501100011033]; ERDF/EU; Programa Severo Ochoa del Principado de Asturias (Spain); National Science, Research and Innovation Fund via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation [B39G670016]; Kavli Foundation; Nvidia Corporation; SuperMicro Corporation; Welch Foundation [C-1845]; Weston Havens Foundation (U.S.A.)We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid and other centers for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: SC (Armenia), BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG, RVTT3 and MoER TK202 (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); SRNSF (Georgia); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LMTLT (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal); MESTD (Serbia); MICIU/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TENMAK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (U.S.A.). Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Science Committee, project no. 22rl-037 (Armenia); the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Beijing Municipal Science & Technology Commission, No. Z191100007219010 and Fundamental Research Funds for the Central Universities (China); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Shota Rustaveli National Science Foundation, grant FR-22-985 (Georgia); the Deutsche Forschungsgemeinschaft (DFG), among others, under Germany's Excellence Strategy - EXC 2121 "Quantum Universe" - 390833306, and under project number 400140256 - GRK2497; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Hungarian Academy of Sciences, the New National Excellence Program - UNKP, the NKFIH research grants K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64, and 2021-4.1.2-NEMZ_KI-2024-00036 (Hungary); the Council of Science and Industrial Research, India; ICSC - National Research Center for High Performance Computing, Big Data and Quantum Computing and FAIR - Future Artificial Intelligence Research, funded by the NextGenerationEU program (Italy); the Latvian Council of Science; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Center, contracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the Fundacao para a Ciencia e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; MICIU/AEI/10.13039/501100011033, ERDF/EU, "European Union NextGenerationEU/PRTR", and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation, grant B39G670016 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (U.S.A.).Science Citation Index Expande
Personalized Alginate Encapsulation: The Role of Autologous Blood Additives in Parathyroid Cell Transplantation
No full textThe only therapeutic intervention for hypoparathyroidism is parathyroid transplantation, but graft rejection is a concern. This study sought to mitigate this problem by utilizing the patient's blood, serum, or plasma in the transplant. To accomplish this objective, blood additives derived from Sprague–Dawley rats are incorporated within alginate, and human parathyroid cells are encapsulated. The prepared microbeads are monitored for mechanical properties, followed by xenotransplantation into rats for the evaluation of cell function and immunological response. Biodegradation data showed that the structural integrity of the microbeads containing blood and plasma is superior to serum, while the durability of plasma-including microbeads is only comparable to that of the alginate-only group. Plasma-including microbeads released the highest levels of parathyroid hormone (PTH), both in vitro and in vivo. This behavior could be attributed to the beneficial impact of plasma on cellular function while regulating immune response. Blood incorporation provoked an elevated immune response while concurrently offering minimal support to the encapsulated cells. A notable elevation in CCL2 (MCP-1) chemokine levels is observed in both blood and alginate-only microbead groups, correlating with CD68 expression. These findings demonstrated that autologous plasma addition may regulate the immune system, thereby diminishing the risk of rejection in cell transplantations. © 2025 Elsevier B.V., All rights reserved.Science Citation Index Expande
Innovations in Cancer Treatment: Evaluating Drug Resistance with Lab-On Technologies
No full textLab-on-a-chip (LoC) technologies have emerged as transformative tools in cancer research, particularly in evaluating drug resistance, which remains a significant barrier to effective treatment. These miniaturized platforms allow for the integration of multiple laboratory functions onto a single chip, facilitating high-throughput screening and real-time monitoring of cellular responses to therapeutic agents. Despite their potential, several challenges hinder the widespread adoption of LoC systems in clinical settings. Key issues include the complexity of accurately replicating the tumor microenvironment (TME), which is critical for understanding cancer biology and drug interactions. Additionally, variability in chip design and fabrication raises concerns about standardization and reproducibility of results, complicating comparisons across studies. The integration of LoC technologies into clinical practice is further complicated by the need for translation from laboratory findings to patient-specific applications. High costs asSociated with advanced microfabrication techniques and the requirement for specialized technical expertise also limit accessibility for many researchers and clinicians. However, the future perspectives for LoC technologies are promising. Advancements in three-dimensional (3D) bioprinting and tissue engineering are expected to enhance TME modeling, while patient-derived tumor spheroids (PDTS) integrated into LoC platforms could facilitate personalized medicine approaches. Coupling LoC systems with omics technologies will provide deeper insights into the molecular mechanisms of drug resistance and help identify novel biomarkers. Furthermore, the integration of artificial intelligence and nanotechnology with LoC platforms has significantly enhanced their diagnostic accuracy, automation, and potential for personalized cancer treatment. As regulatory bodies increasingly accept LoC technologies as viable preclinical models, their integration into pharmaceutical development pipelines is likely to accelerate. This review aims to explore these challenges and future perspectives, highlighting the potential of LoC technologies in advancing cancer treatment paradigms. By examining the innovative applications of LoC systems, we aim to highlight their potential for enhancing our understanding of the complex interactions within the TME and their implications for personalized medicine. Additionally, it seeks to identify and discuss the key challenges that currently limit the widespread adoption of LoC technologies in clinical settings, including issues related to model complexity, standardization, and integration into existing drug development pipelines.Science Citation Index Expande
Compressed Air Energy Storage (CAES) Systems: Technological Progress, Challenges, and Future Prospects in Renewable Energy Grids
No full textThe intermittent nature of renewable sources injects uncertainty into power systems, often resulting in supply and demand mismatches. CAES is therefore seen as a feasible answer to this issue due to its technical, economic, and environmental advantages of a clean storage medium; scaling possibility; long duration for discharge; low rate of self-discharge; and inexpensive properties. There have been several studies in recent times aimed at improving the performance of the CAES technologies, there is however, no detailed bibliometric review that presents a comprehensive overview of the advances made on the technology. This review paper fills that gap by performing a comprehensive literature review on the subject from 2000 to 2024. The bibliometric analysis highlights the global escalation in interest in CAES-related fields, with an observed annual growth rate of 20.68%. From a technological perspective, major developments include the consideration of adiabatic and hybrid systems, integration with solid oxide fuel cells and organic Rankine cycles and improved thermal storage options. On the economic side, interest in hybrid CAES systems coupled with RES is rising due to strong performance indicators such as round-trip efficiencies up to 90% and levelized costs as low as $0.22/kWh. The techno-economic and lifecycle evaluations confirm CAES as a potential candidate for cost reductions and resilience in energy supply. However, other deployment issues are still present: high capital costs, site-specific restrictions, and regulatory processes. Future studies should concentrate on creating adaptable CAES designs, including intelligent control systems, and creating frameworks for supporting policies. In order to establish CAES as a key technology in the shift to low-carbon, sustainable energy systems, interdisciplinary cooperation will be essential.Emerging Sources Citation Inde
Okul Öncesi Öğretmenlerinin Fen Kavramı Öğretiminde Kullandıkları Yöntemler
No full textBu çalışmanın amacı, okul öncesi öğretmenlerinin fene yönelik tutumları ile okul öncesi öğretmenlerinin fen kavramı öğretiminde kullandıkları yöntem ve tekniklerin incelenmesidir. Araştırmanın çalışma grubu, bağımsız anaokulu ve anasınıflarında görev yapan 63 okul öncesi öğretmeninden oluşmaktadır. Araştırmada veri toplama aracı olarak, Öğretmen Kişisel Bilgi Formu, Okul Öncesi Öğretmenlerinin Fen Öğretimine Yönelik Tutum Ölçeği, Okul Öncesi Sınıf Fen Bilimleri Malzeme Kontrol Listesi ve 6 adet yarı yapılandırılmış görüşme soruları kullanılmıştır. Nicel veriler SPSS 31.0 programı ile analiz edilmiş; betimsel analizlerin yanı sıra normal dağılıma uygun olmayan veriler için Mann-Whitney U ve Kruskal-Wallis H testleri gibi non-parametrik testler kullanılmıştır. Okul öncesi öğretmenlerinin fen öğretimine yönelik tutumları ile fen kavramları öğretim yöntemlerini belirlemek amacıyla betimsel analiz yapılarak ölçekten alınan puanların aritmetik ortalamaları ve standart sapmaları bulunmuştur. Görüşme soruları, tümdengelimsel içerik analizi kullanılarak değerlendirilmiştir. Kontrol listesi bulguları ise betimsel olarak sunulmuştur. Araştırmadan elde edilen bulgulara göre, öğretmenlerin fene yönelik olumlu tutumlarının olduğu, fene yönelik tutum ölçeğinin kendini geliştirme ve öz yeterlik alt boyutları incelendiğinde aralarındaki ilişkinin yüksek olduğu tespit edilmiştir. Bu iki alt boyut arasında istatistiksel olarak anlamlı ve pozitif bir ilişki bulunmuştur (ρ = .441, p < .001). Okul öncesi öğretmenlerinin öğrenim durumunun, okul türünün, kıdem yılının, çalışılan yaş grubunun ve mezun olunan bölümün fene yönelik tutum puanlarında etkisiz bir rol oynadığı tespit edilmiş ve fene yönelik tutum puanlarında istatistiksel olarak anlamlı bir farklılık görülmemiştir (p > .05). Öğretmenlerin en sık kullandıkları yöntemler arasında deney (%100), gezi-gözlem (%96,8) ve oyun (%95,2) yer alırken; kavram haritası ve problem çözme gibi yöntemlere daha az yer verildiği belirlenmiştir. Öğretmenlerin fen kavramı öğretirken büyük bir kısmının deney, oyun, düz anlatım ve gezi gözleme yer verdikleri, proje, problem çözme ve kavram haritasına ise daha az yer verdikleri veya hiç yer vermedikleri tespit edilmiştir. Araştırma sonuçlarına bağlı olarak bazı önerilerde bulunulmuştur
Performance Evaluation of Teachers by Using Fermatean Fuzzy Based MCDM Approach
No full textPurpose: The purpose of this paper is to present a systematic approach for evaluating teachers’ performance within an educational framework. In every progressive country, establishing a well-organized and efficient educational system is essential. Teachers play a pivotal role in enhancing the quality of education and can create a student-centric learning environment that supports the holistic development of learners. Therefore, it is crucial to conduct a periodic evaluation of teachers’ performance to ensure continuous improvement in educational quality. Methodology: In this study, three primary factors—teaching, research, and administrative activities—are considered as the key criteria for assessing teachers’ overall performance, each further divided into several sub-criteria. To address the uncertainty and vagueness inherent in the evaluation data, Fermatean Fuzzy Numbers (FFN) are utilized. The CRITIC method, a well-known Multi-Criteria Decision-Making (MCDM) technique, is applied to determine the weights of the criteria. Five teachers are selected as alternatives, and the MULTIMOORA method is employed to rank them according to their performance levels. Findings: The analysis reveals that combining Fermatean fuzzy logic with MCDM techniques provides an effective framework for conducting a more accurate and fair evaluation of teachers’ performance. Furthermore, a sensitivity analysis is performed by removing certain criteria to test the robustness and validity of the obtained results. Originality/Value: The originality of this study lies in the integration of Fermatean fuzzy logic with MCDM approaches for teacher performance evaluation. This innovative combination allows for more precise consideration of qualitative and subjective aspects of teacher assessment. The proposed model can serve as a valuable tool for educational administrators and policymakers in making data-driven decisions and formulating strategies to enhance teaching effectiveness. © 2025, Research Expansion Alliance (REA). All rights reserved