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Protectıve Effects Of Dırect Oral Antıcoagulants In An Experimental Ischemıa-Reperfusıon Model
No full textObjective The aim of this study was to investigate the protective effect of direct oral anticoagulants on skeletal muscle reperfusion injury in an experimental ischemia-reperfusion (IR) model. Methods 40 female Wistar albino rats were randomly divided into five groups: control, sham, apixaban, rivaroxaban and dabigatran. Sham group underwent only anesthesia and median laparotomy. Control group underwent the IR procedure. Apixaban group received 10 mg/kg twice daily, dabigatran group received 15 mg/kg once daily and rivaroxaban group received 3 mg/kg once daily by oral gavage for one week. IR procedure was performed as infrarenal aorta clamping for 60 min followed by 120 min of reperfusion. After the procedure, 2-3 cc intracardiac blood and bilateral gastrocnemius muscle samples were obtained from each group. Biochemical markers TAC,TOS,IL-1,IL-6 and TNF-alpha levels were analyzed in muscle tissue and blood. Histopathologically, inflammation, necrosis,congestion,fibrosis and atrophy levels in muscle tissue were examined. Results IL-6 levels were significantly lower in muscle and serum samples in the dabigatran group (p < 0.001). In addition, TNF-a levels were significantly lower in the dabigatran group (p = 0.003). Inflammation was also reduced in the rivaroxaban and apixaban groups, but not as markedly as in the dabigatran group. In histopathologic evaluations, muscle tissue damage was found to be the lowest in the dabigatran group. Antioxidant capacity (TAC) was higher in the dabigatran group (p = 0.009), but there was no significant difference in TOS levels between the groups. Conclusion Direct oral anticoagulants showed anti-inflammatory and antioxidant effects against IR injury. In particular, dabigatran offered a more pronounced protective effect compared to other drugs with its effects on inflammation and oxidative stress.Scientific and Technological Research Council of Turkiye (TUBITAK)Open access funding provided by the Scientific and Technological Research Council of Turkiye (TUBITAK)
The Impact of Artificial Intelligence on Healthcare Industry: Volume 2: Clinical Applications
No full textThe healthcare sector is highly dependent on technological innovations, much more than most other industries. The positive side is the potential to implement these technological innovations for major improvements and benefits. There has been a significant increase in the use of artificial intelligence techniques in clinical and non-clinical areas in healthcare. The chapters in this book are presented by professionals who are experts in healthcare and have academic experience. The aim of this volume is to add to the literature and to present the current state of clinical and non-clinical applications in the healthcare industry and areas open to development, as well as to provide recommendations to policymakers. © 2025 Elsevier B.V., All rights reserved
Women with metastatic breast cancer supportive care needs
No full textBackground: Supportive care needs may increase in women with metastatic breast cancers concerning disease burden. The study's purpose was to determine the supportive care needs of women with metastatic breast cancer.The study was conducted in a cross-sectional design between January and December 2022.The sample of the study consisted of 92 women with metastatic breast cancer who met the inclusion criteria. Data were collected using the Individual Descriptive Information Form and the Supportive Care Needs Scale.A significant majority of the women with metastatic breast cancer reported having supportive care needs. The participants' supportive care needs were as follows: 93.5% for physical and daily life, 88% for spiritual/psychological needs, 86% for healthcare system and information, 56.5% for sexuality and 43.5% for patient care and support. This study determined the supportive care needs of women with metastatic breast cancer and revealed that the majority of patients have support needs related to physical, psychological, access to information, sexuality and patient care. The findings emphasise the necessity for individualised care processes and the importance of nurses taking an active role in symptom management, psychological support and information services. The effectiveness of digital health solutions and multidisciplinary care approaches should be investigated to ensure the creation of evidence-based health policies. It is recommended that future studies evaluate the changing care needs of patients in the long term, thereby contributing to the development of evidence-based health policies
Collaboration in Voice Therapy: Development of a Vocal Health Daily Tracking Form
No full textBackground: Voice disorders are a major cause of difficulties in many areas of social life, as they can disrupt communication. Voice therapy, including vocal hygiene education, has an important role in the treatment of voice disorders, especially if applied in an individualised manner. Aim: The aim of this study was to develop and validate a reliable and practical self-report tool, the Vocal Health Daily Tracking Form, for use in monitoring patients’ daily compliance with vocal hygiene practices and home-based voice therapy exercises. Methods and Procedures: A total of 266 volunteering participants, including 212 women and 54 men aged 18 and over who were university students from departments of speech and language therapy and audiology, participated in the research. The 12-item Vocal Health Daily Tracking Form, developed based on traditional voice therapy principles, was completed at least once by all 266 participants and twice by 60 of the participants. The validity and reliability of the form were evaluated in line with the statistical analysis of the obtained data. Outcomes and Results: Statistical analyses confirmed that the Vocal Health Daily Tracking Form is a reliable and valid tool. While the Kaiser-Meyer-Olkin test value of the form was found to be very good at 0.799, the Bartlett test result was 961.473 (p < 0.05), confirming a strong correlation between the items of the form. The Cronbach alpha value of the study was found to be sufficient at 0.809. The total correlation values were between 0.326 and 0.651, and the amount of explained variance was sufficient at 33.28%. These findings confirmed that the scale is well constructed both conceptually and structurally and is a valid and reliable measurement tool. Conclusions and Implications: In addition to vocal hygiene recommendations, the individualisation of the therapy process and the use of methods based on behavioural techniques may contribute positively to the voice rehabilitation processes of individuals with voice disorders. The Vocal Health Daily Tracking Form has high validity and reliability values, confirming that it can be considered an important tool for monitoring and improving voice therapy processes. It may also help patients experience more regular and effective therapy processes by increasing their self-regulation and motivation during voice therapy. WHAT THIS PAPER ADDS: What is already known on this subject Voice disorders are major health issues that negatively affect individuals’ communication abilities and quality of life (Cohen et al., 2006). These disorders may arise due to organic, neurological, or functional causes and may lead to abnormal changes in voice quality, pitch height, or intensity (Behrman, 2007). Voice therapy and various treatment methods, including vocal hygiene education and training, play an important role in the rehabilitation processes of individuals with voice disorders (Garabet et al., 2024). Homework assigned during the therapy process, including vocal exercises and hygiene practices, is of critical importance in increasing the effectiveness of the treatment (Desjardins et al., 2017). What this paper adds to the existing knowledge This study aimed to develop and validate a reliable and practical self-report tool, the Vocal Health Daily Tracking Form, to monitor patients’ daily compliance with vocal hygiene practices and home-based voice therapy exercises during voice rehabilitation. With that aim, the Vocal Health Daily Tracking Form was developed to allow patients to record their daily engagement with voice hygiene practices and vocal exercises. The validity and reliability of this new form were also evaluated. This study has presented the validity and reliability analysis of a voice monitoring form developed to increase patients’ compliance with voice therapy. Steady compliance with vocal hygiene and prescribed exercises conducted at home significantly affects treatment results, and the voice monitoring form proposed in this study was shown to have high validity (KMO = 0.799, p < 0.001) and reliability, indicating that it can be considered an important tool for monitoring daily practices that affect the outcomes of therapy processes. What are the potential or actual clinical implications for this work? This study is expected to serve as guidance for future research and clinical practices addressing patient compliance and behavioural management throughout the course of voice therapy. © 2025 Elsevier B.V., All rights reserved
Search for heavy neutral resonances decaying to tau lepton pairs in proton-proton collisions at ?s=13 TeV
No full textA search for heavy neutral gauge bosons (Z ') decaying into a pair of tau leptons is performed in proton-proton collisions at root s =13 TeV at the CERN LHC. The data were collected with the CMS detector and correspond to an integrated luminosity of 138 fb(-1). The observations are found to be in agreement with the expectation from standard model processes. Limits at 95% confidence level are set on the product of the Z ' production cross section and its branching fraction to tau lepton pairs for a range of Z ' boson masses. For a narrow resonance in the sequential standard model scenario, a Z ' boson with a mass below 3.5 TeV is excluded. This is the most stringent limit to date from this type of search
From Sensitization to Tolerance: A Retrospective Study of Tree Nut and Peanut Allergy in Pediatric Patients
No full textIntroduction: Tree nut/peanut (TN/PN) allergies are among the most common pediatric food allergies, often persisting into later life and posing significant clinical risks. The likelihood of tolerance acquisition varies, and predictive factors remain inadequately defined in clinical practice. This study was conducted to evaluate clinical and laboratory features associated with anaphylaxis risk and tolerance development in pediatric patients with TN/PN allergy, while also examining the potential influence of aeroallergen sensitization, coexisting atopic diseases, and skin test reactivity on these outcomes. Methods: In this retrospective, cross-sectional study, 121 children (0-18 years) diagnosed with TN/PN allergy at a tertiary allergy centre between 2016 and 2024 were analyzed. Data included allergic reaction history, comorbidities, total IgE, eosinophil counts, and prick-to-prick (PTP) test wheal sizes. Tolerance acquisition was defined based on oral food challenge, absence of reactions upon re-exposure, and clinical follow-up. Results: Multiple nut allergy was present in 81% of patients, with hazelnut (67%) and pistachio (62%) being the most common. IgE-mediated reactions were predominant (91%), including urticaria (79%) and anaphylaxis (36%). During follow-up, 25% of patients developed tolerance, while 13% continued to experience anaphylaxis. Aeroallergen sensitization, particularly to pollens, was significantly associated with reduced tolerance in almond and walnut allergy (p < 0.05). Persistent multi-nut allergy correlated with higher anaphylaxis risk (p < 0.01). Strong co-sensitization was observed between pistachio-cashew (r = 0.686) and almond-walnut (r = 0.579). Notably, smaller PTP wheal sizes predicted tolerance acquisition (p < 0.05). Conclusion: Pediatric TN/PN allergy is frequently severe and persistent. Multiple nut allergy, aeroallergen sensitization, and larger PTP wheal sizes are significant risk factors for prolonged allergy and anaphylaxis. Early identification of these markers may improve risk stratification and guide individualized follow-up strategies. (c) 2025 S. Karger AG, Base
Differential cross section measurements for the production of top quark pairs and of additional jets using dilepton events from pp collisions at ?s=13 TeV
No full textDifferential cross sections for top quark pair (t (t) over bar) production are measured in proton-proton collisions at a center-of-mass energy of 13 TeV using a sample of events containing two oppositely charged leptons. The data were recorded with the CMS detector at the CERN Large Hadron Collider and correspond to an integrated luminosity of 138 fb(-1). The differential cross sections are measured as functions of kinematic observables of the t (t) over bar system, the top quark and antiquark and their decay products, as well as of the number of additional jets in the event. The results are presented as functions of up to three variables and are corrected to the parton and particle levels. When compared to standard model predictions based on quantum chromodynamics at different levels of accuracy, it is found that the calculations do not always describe the observed data. The deviations are found to be largest for the multi-differential cross sections.FWF; FNRS; FWO (Belgium); CNPq; CAPES; FAPERJ; FAPERGS; FAPESP (Brazil); BNSF (Bulgaria); MoST; NSFC (China); CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG [TK202]; Academy of Finland; MEC; CEA; CNRS/IN2P3 (France); SRNSF; BMBF; HGF (Germany); NKFIH (Hungary); DAE; DST; SFI (Ireland); INFN (Italy); NRF (Republic of Korea); MES (Latvia); MOE; UM (Malaysia); BUAP; CONACYT; UASLP-FAI (Mexico); PAEC (Pakistan); FCT (Portugal); MESTD (Serbia); PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); NSTDA; TUBITAK; NASU (Ukraine); DOE; NSF; Marie-Curie program; European Research Council; Horizon 2020 Grant [675440, 724704, 752730, 758316, 765710, 824093]; COST Action [CA16108]; Leventis Foundation; Alfred P. Sloan Foundation; Alexander von Humboldt Foundation; Science Committee [22rl-037]; Belgian Federal Science Policy Office; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); FWO (Belgium) under the Excellence of Science - EOS [30820817]; 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 124845, K 124850, K 128713, K 128786, K 129058, K 131991, K 133046, K 138136, K 143460, K 143477, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64]; Council of Science and Industrial Research, India - EU NexGeneration 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, CEECIND/01334/2018]; National Priorities Research Program by Qatar National Research Fund; ERDF a way of making Europe [MDM-2017-0765]; 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 [B37G660013]; 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 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); LAS (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); MCIN/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, 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 Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the Excellence of Science - EOS - be.h project n. 30820817; 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), 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 124845, K 124850, K 128713, K 128786, K 129058, K 131991, K 133046, K 138136, K 143460, K 143477, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64 (Hungary); the Council of Science and Industrial Research, India; ICSC - National Research Center for High Performance Computing, Big Data and Quantum Computing, funded by the EU NexGeneration 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; MCIN/AEI/10.13039/501100011033, ERDF a way of making Europe, and the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2017-0765 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 B37G660013 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (U.S.A.)
The Integration of Cellulose-Based Materials in Orthotic Devices as Flexible and Biodegradable Sensors
No full text23rd Italian Conference on Sensors and Microsystems, AISEM 2025 -- -- Trento -- 342249Cellulose (CE), a biodegradable and biocompatible biopolymer, can be used as a functional element in systems such as orthotics, where both high strength and flexibility are required. They can also be rapidly produced as embedded flexible sensors that can monitor pressure, strain, humidity and temperature in real time in orthoses produced using patient-specific anatomical data and additive manufacturing. These ‘smart’ orthotic devices not only improve user comfort and treatment outcomes but also align with the growing demand for environmentally friendly healthcare solutions. In this study, the applications of CE as both the main structure and sensor material in reverse engineering and 3D printing applications in medical devices, especially in the design and manufacturing of personalized orthotics are discussed. The promising performance of cellulose-based sensors in experimental settings suggests a bright future for their clinical applications, particularly in rehabilitation, sports medicine, and long-term care. © 2025 Elsevier B.V., All rights reserved
Parameter Predicting Postoperative Atrial Fibrillation in Coronary Artery Bypass Grafting Patients: Triglyceride-Cholesterol-Body Weight Index
No full textBackground: Postoperative atrial fibrillation (POAF) is a common complication after cardiac surgery, particularly coronary artery bypass grafting (CABG). Despite advances in surgical techniques, POAF remains a significant cause of morbidity and mortality. Objectives: This study investigates the potential of the Triglyceride-Cholesterol-Body weight Index (TCBI) as a predictor of POAF, focusing on the impact of nutritional status on surgical outcomes. Methods: This retrospective study included 321 patients who underwent CABG surgery between January 2010 and January 2024. TCBI was calculated using preoperative blood samples and compared between those who developed POAF and those who did not. Statistical analyses, including Cox regression and ROC analysis, were performed to assess the predictive value of TCBI for POAF. P<0.05 was considered statistically significant. Results: Patients who developed POAF had significantly lower TCBI (1790.8 ± 689, 3413.3±1232, p<0.001, respectively) levels compared to those without POAF. Also, age (p<0.001), the frequency of hypertension (p=0.009), CRP (p=0.03), and WBC (p=0.02) values were also significantly higher in patients who developed POAF.TCBI was identified as an independent predictor of POAF (OR: 0.998, 95% CI: 0.997-0.999, p<0.001), with a cut-off value of 1932.4 predicting POAF with 75% sensitivity and 78% specificity. Conclusion: The TCBI is a reliable indicator for predicting POAF in CABG patients. Preoperative identification of patients with low TCBI could lead to targeted interventions, reducing postoperative complications and improving outcomes. Optimizing nutritional status before surgery may mitigate the risk of POAF. © 2025 Elsevier B.V., All rights reserved
Measurement of the Drell-Yan forward-backward asymmetry and of the evffective leptonic weak mixing angle in proton-proton collisions at ?s=13TeV
No full textThe forward-backward asymmetry in Drell-Yan production and the effective leptonic electroweak mixing angle are measured in proton-proton collisions at root s= 13 TeV, collected by the CMS experiment and corresponding to an integrated luminosity of 138 fb(-1). The measurement uses both dimuon and dielectron events, and is performed as a function of the dilepton mass and rapidity. The unfolded angular coefficient A(4) is also extracted, as a function of the dilepton mass and rapidity. Using the CT18Z set of parton distribution functions, we obtain sin(2) theta(l)(eff)= 0.23152 +/- 0.00031, where the uncertainty includes the experimental and theoretical contributions. The measured value agrees with the standard model fit result to global experimental data. This is the most precise sin(2) theta(l)(eff) measurement at a hadron collider, with a precision comparable to the results obtained at LEP and SLD.FWF; FNRS; FWO (Belgium); CNPq; CAPES; FAPERJ; FAPERGS; FAPESP (Brazil); BNSF (Bulgaria); MOST; NSFC (China); CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG [MoER TK202]; Academy of Finland; MEC; CEA; CNRS/IN2P3 (France); SRNSF; BMBF; DFG; HGF (Germany); NKFIH (Hungary); DAE; DST; IPM; SFI (Ireland); INFN (Italy); NRF (Republic of Korea); MES (Latvia); MOE; UM (Malaysia); BUAP; CONACYT; UASLP-FAI (Mexico); PAEC (Pakistan); FCT (Portugal); MESTD (Serbia); PCTI (Spain); Swiss Funding Agencies (Switzerland); NSTDA; TUBITAK; DOE; NSF (USA); 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]; Belgian Federal Science Policy Office; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); FWO (Belgium) under the Excellence of Science - EOS [30820817]; 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, 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-NKTA64]; Council of Science and Industrial Research, India; ICSC - National Research Center for High Performance Computing - 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; ERDF a way of making Europe [MDM-2017-0765]; 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; Welch Foundation [C-1845]; Weston Havens Foundation (USA)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); MCIN/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 (USA). 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 Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the Excellence of Science - EOS'' - be.h project n. 30820817; 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, and TKP2021-NKTA64 (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; MCIN/AEI/10.13039/501100011033, ERDF a way of making Europe'', and the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2017-0765 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 Super-Micro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA)