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Bian Z, Guo Y, Lyu XM, Wan NJ, Wang QQ, Yang Z. [Relationship between hand and wrist bone age assessment method and application to male children]. ZHONGHUA WAI KE ZA ZHI [CHINESE JOURNAL OF SURGERY] 2024; 62:1136-1142. [PMID: 39606998 DOI: 10.3760/cma.j.cn112139-20240807-00367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/29/2024]
Abstract
Objective: To explore the interrelationship among three simplified hand and wrist bone age assessment methods and to establish corresponding bone ages for each substage in male children. Methods: This retrospective case series study included 169 left hand and wrist X-rays from 152 male children who underwent bone age assessments at the Pediatric Orthopedics and Pediatrics Departments,Beijing Jishuitan Hospital,Capital Medical University from January 2019 to December 2023. The age at the time of X-ray was (13.7±2.0) years (range:9.1 to 17.9 years). Reasons for bone age assessment included evaluating the progress of adolescent idiopathic scoliosis in 36 cases, predicting limb length discrepancies in 28 cases, and predicting the height of healthy adolescents in 88 cases. Bone age was first graded using the Chinese hand-wrist bone age assessment method. Three simplified hand and wrist bone age assessment methods were then applied:Sanders simplified skeletal maturity staging system(Sanders stage), the distal radius and ulna classification (DRU), and e thumb ossification composite index (TOCI). Somers'delta correlation test was used to analyze the relationship among the results of the three simplified methods. The bone age and standard deviation for each sub-stage were calculated, and gender differences in bone age for the same sub-stage were compared with previous study. Results: The DRU, TOCI and Sanders stages showed a strong correlation when assessing bone age in male children, with Somers'delta correlation coefficients ranging from 0.881 to 0.876 (all P<0.01). The sub-stages with the smallest standard deviations (shorter duration) in each of the three classifications can serve as a quick reference for determining precise bone age, included proximal thumb epiphysis covered, without sesamoid (12.0 years);proximal thumb epiphysis covered with sesamoid or distal radial covered (13.0 years), early capping of the thumb epiphysis, radial epiphysis medial side capping(13.5 years), all phalangeal epiphyses capping (14.0 years), distal phalangeal physes beginning to close (14.5 years), all distal phalangeal physes closed (15.0 years), middle or proximal phalangeal physes beginning to close (15.5 years), all digital epiphyses closed (16.5 years), and nearly complete distal radius fusion with a notch (17.5 years). On average, the bone ages of males were 2 years behind those of females in the same substage. Conclusions: The DRU, TOCI, and Sanders stages can be applied to male children, and it is showed good correlation between them. The subtypes with shorter duration can be used as a quick assessment method to determine the bone age.
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Wang N, Qi BQ, Ruan M, Zhang XY, Zhang RR, Liu TF, Chen YM, Zou Y, Guo Y, Yang WY, Zhang L, Zhu XF, Chen XJ. [Clinical features and long-term prognostic analysis of relapsed pediatric acute lymphoblastic leukemia]. ZHONGHUA ER KE ZA ZHI = CHINESE JOURNAL OF PEDIATRICS 2024; 62:1090-1096. [PMID: 39429082 DOI: 10.3760/cma.j.cn112140-20240914-00643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/22/2024]
Abstract
Objective: To investigate the clinical characteristics and long-term prognostic factors of relapsed pediatric acute lymphoblastic leukemia (ALL). Methods: Clinical data including the age, time from initial diagnosis to relapse, relapse site, and molecular biological features of 217 relapsed ALL children primarily treated by the Chinese Children's Leukemia Group (CCLG)-ALL 2008 protocol in Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences between April 2008 and April 2015 were collected and analyzed in this retrospective cohort study. Kaplan-Meier analysis was used to evaluate the overall survival (OS) rate and event free survival (EFS) rate for univariate analysis, and Cox proportional-hazards regression model was used to evaluate the influencing factors of OS rate and EFS rate for multivariate analysis. Results: The age at initial diagnosis of 217 relapsed patients was 5 (3, 7) years. There were 135 males and 82 females. The time from initial diagnosis to relapse of 217 children was 22 (10, 39) months. After relapse, 136 out of 217 children (62.7%) received treatment and the follow-up time was 65 (47, 90) months. The 5-year OS rate and EFS rate of the 136 relapsed children were (37±4) % and (26±4) %, respectively. The predicted 10-year OS rate and EFS rate were (35±5) % and (20±4) %, respectively. Univariate analysis showed that the 5-year OS rate in the group of patients with late relapse (43 cases) was significantly higher than those with very early (54 cases) and early relapse (39 cases) ((72±7)% vs. (16±5)%, (28±8)%, χ2=35.91, P<0.05), 5-year OS rate of the isolated extramedullary relapse group (20 cases) was significantly higher than isolated bone marrow relapse group (102 cases) and combined relapse group (14 cases) ((69±11)% vs. (31±5)%, (29±12)%, χ2=9.14, P<0.05), 5-year OS rate of high-risk group (80 cases) was significantly lower than standard-risk group (10 cases) and intermediate-risk group (46 cases) ((20±5)% vs. (90±10)%, (54±8)%, χ2=32.88, P<0.05). ETV6::RUNX1 was the most common fusion gene (13.2%, 18/136). The predicted 10-year OS rate of relapsed children with positive ETV6::RUNX1 was significantly higher than those without ETV6::RUNX1 (118 cases) ((83±9)% vs. (26±5)%, χ2=14.04, P<0.05). The 5-year OS for those accepted hematopoietic stem cell transplantation (HSCT) after relapse (42 cases) was higher than those without HSCT (94 cases) ((56±8)% vs. (27±5)%, χ2=15.18, P<0.05). Multivariate analysis identified very early/early relapse (HR=3.91, 95%CI 1.96-7.79; HR=4.15, 95%CI 1.99-8.67), bone marrow relapse including isolated bone marrow relapse and combined relapse (HR=6.50, 95%CI 2.58-16.34; HR=5.19, 95%CI 1.78-15.16), with ETV6::RUNX1 (HR=0.23, 95%CI 0.07-0.74) and HSCT after relapse (HR=0.24, 95%CI 0.14-0.43) as independent prognostic factors for OS (all P<0.05). Conclusions: Relapsed pediatric ALL mainly occurs very early and often affects bone marrow, which confer poor outcome. ETV6::RUNX1 is the most common genetic aberration with a favorable outcome. HSCT could rescue the outcome of relapsed children, though the survival rate is still poor.
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Wang HJ, Shi Y, Cheng WK, Guo Y, Wang YT. [Impact of atrial high-rate episodes on new onset of atrial fibrillation and all-cause mortality in elderly patients over 90 years old with dual-chamber pacemaker implantation]. ZHONGHUA XIN XUE GUAN BING ZA ZHI 2024; 52:1148-1154. [PMID: 39428363 DOI: 10.3760/cma.j.cn112148-20240615-00335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/22/2024]
Abstract
Objective: To investigate the impacts of atrial high-rate episodes (AHRE) on the risks of new onset of atrial fibrillation and all-cause mortality in elderly patients over 90 years old after cardiac dual-chamber pacemaker implantation. Methods: This study was a retrospective study. Patients aged 90 years and above who were implanted with cardiac dual-chamber pacemakers and followed up in the People's Liberation Army General Hospital from January 2017 to June 2022 were enrolled and divided into AHRE≥6 h group and AHRE<6 h group according to the onset time of AHRE. The primary endpoint was new onset of atrial fibrillation, and the secondary endpoints were all-cause mortality and cardiovascular mortality. Kaplan-Meier survival curve was poltted, and log-rank test was used to compare the differences in the incidence of new onset of atrial fibrillation, all-cause death and cardiovascular death between AHRE≥6 h and AHRE<6 h groups. Multivariate Cox survival analysis was used to investigate the factors affecting new onset of atrial fibrillation, all-cause death and cardiovascular death in elderly patients aged 90 years and above with dual-chamber pacemaker implantation. Results: A total of 169 patients were enrolled, aged (93.95±3.28) years, including 18 females (11%). The median follow-up time was 28.9 months. There were 87 and 82 patients in AHRE≥6 h group and AHRE<6 h group, respectively. Kaplan-Meier survival curve analysis showed that the incidence of new onset of atrial fibrillation (log-rank P<0.001), all-cause death (log-rank P=0.004) and cardiovascular death (log-rank P=0.026) in AHRE≥6 h group was significantly higher than that in AHRE<6 h group.After adjusting for traditional risk factors, multivariate Cox survival analysis showed that AHRE≥6 h was an independent risk factor for new onset of atrial fibrillation (HR=4.046, 95%CI 2.402-6.814, P<0.001) and all-cause mortality (HR=1.668, 95%CI 1.119-2.487, P=0.012) in elderly patients over 90 years old with cardiac dual-chamber pacemaker implantation. However, AHRE≥6 h had no effect on cardiovascular mortality (P>0.05). Anemia (HR=3.098, 95%CI 1.342-7.153, P=0.008) and heart failure with reduced ejection fraction (HR=3.028, 95%CI 1.181-7.763, P=0.021) were both independently associated with cardiovascular mortality. Conclusions: AHRE is common in cardiac dual-chamber pacemakers recipients aged 90 years and above, and AHRE≥6 h can be used as a predictor of new onset of atrial fibrillation or all-cause mortality in these patients.
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Aad G, Aakvaag E, Abbott B, Abdelhameed S, Abeling K, Abicht NJ, Abidi SH, Aboelela M, Aboulhorma A, Abramowicz H, Abreu H, Abulaiti Y, Acharya BS, Ackermann A, Adam Bourdarios C, Adamczyk L, Addepalli SV, Addison MJ, Adelman J, Adiguzel A, Adye T, Affolder AA, Afik Y, Agaras MN, Agarwala J, Aggarwal A, Agheorghiesei C, Ahmad A, Ahmadov F, Ahmed WS, Ahuja S, Ai X, Aielli G, Aikot A, Ait Tamlihat M, Aitbenchikh B, Akbiyik M, Åkesson TPA, Akimov AV, Akiyama D, Akolkar NN, Aktas S, Al Khoury K, Alberghi GL, Albert J, Albicocco P, Albouy GL, Alderweireldt S, Alegria ZL, Aleksa M, Aleksandrov IN, Alexa C, Alexopoulos T, Alfonsi F, Algren M, Alhroob M, Ali B, Ali HMJ, Ali S, Alibocus SW, Aliev M, Alimonti G, Alkakhi W, Allaire C, Allbrooke BMM, Allen JF, Allendes Flores CA, Allport PP, Aloisio A, Alonso F, Alpigiani C, Alsolami ZMK, Alvarez Estevez M, Alvarez Fernandez A, Alves Cardoso M, Alviggi MG, Aly M, Amaral Coutinho Y, Ambler A, Amelung C, Amerl M, Ames CG, Amidei D, Amirie KJ, Amor Dos Santos SP, Amos KR, An S, Ananiev V, Anastopoulos C, Andeen T, Anders JK, Anderson AC, Andrean SY, Andreazza A, Angelidakis S, Angerami A, Anisenkov AV, Annovi A, Antel C, Antipov E, Antonelli M, Anulli F, Aoki M, Aoki T, Aparo MA, Aperio Bella L, Appelt C, Apyan A, Arbiol Val SJ, Arcangeletti C, Arce ATH, Arena E, Arguin JF, Argyropoulos S, Arling JH, Arnaez O, Arnold H, Artoni G, Asada H, Asai K, Asai S, Asbah NA, Ashby Pickering RA, Assamagan K, Astalos R, Astrand KSV, Atashi S, Atkin RJ, Atkinson M, Atmani H, Atmasiddha PA, Augsten K, Auricchio S, Auriol AD, Austrup VA, Avolio G, Axiotis K, Azuelos G, Babal D, Bachacou H, Bachas K, Bachiu A, Backman F, Badea A, Baer TM, Bagnaia P, Bahmani M, Bahner D, Bai K, Baines JT, Baines L, Baker OK, Bakos E, Bakshi Gupta D, Balabram Filho LE, Balakrishnan V, Balasubramanian R, Baldin EM, Balek P, Ballabene E, Balli F, Baltes LM, Balunas WK, Balz J, Bamwidhi I, Banas E, Bandieramonte M, Bandyopadhyay A, Bansal S, Barak L, Barakat M, Barberio EL, Barberis D, Barbero M, Barel MZ, Barends KN, Barillari T, Barisits MS, Barklow T, Baron P, Baron Moreno DA, Baroncelli A, Barone G, Barr AJ, Barr JD, Barreiro F, Barreiro Guimarães da Costa J, Barron U, Barros Teixeira MG, Barsov S, Bartels F, Bartoldus R, Barton AE, Bartos P, Basan A, Baselga M, Bassalat A, Basso MJ, Bataju S, Bate R, Bates RL, Batlamous S, Batool B, Battaglia M, Battulga D, Bauce M, Bauer M, Bauer P, Bazzano Hurrell LT, Beacham JB, Beau T, Beaucamp JY, Beauchemin PH, Bechtle P, Beck HP, Becker K, Beddall AJ, Bednyakov VA, Bee CP, Beemster LJ, Beermann TA, Begalli M, Begel M, Behera A, Behr JK, Beirer JF, Beisiegel F, Belfkir M, Bella G, Bellagamba L, Bellerive A, Bellos P, Beloborodov K, Benchekroun D, Bendebba F, Benhammou Y, Benkendorfer KC, Beresford L, Beretta M, Bergeaas Kuutmann E, Berger N, Bergmann B, Beringer J, Bernardi G, Bernius C, Bernlochner FU, Bernon F, Berrocal Guardia A, Berry T, Berta P, Berthold A, Bethke S, Betti A, Bevan AJ, Bhalla NK, Bhatta S, Bhattacharya DS, Bhattarai P, Bhide KD, Bhopatkar VS, Bianchi RM, Bianco G, Biebel O, Bielski R, Biglietti M, Billingsley CS, Bindi M, Bingul A, Bini C, Biondini A, Bird GA, Birman M, Biros M, Biryukov S, Bisanz T, Bisceglie E, Biswal JP, Biswas D, Bloch I, Blue A, Blumenschein U, Blumenthal J, Bobrovnikov VS, Boehler M, Boehm B, Bogavac D, Bogdanchikov AG, Bohm C, Boisvert V, Bokan P, Bold T, Bomben M, Bona M, Boonekamp M, Booth CD, Borbély AG, Bordulev IS, Borecka-Bielska HM, Borissov G, Bortoletto D, Boscherini D, Bosman M, Bossio Sola JD, Bouaouda K, Bouchhar N, Boudet L, Boudreau J, Bouhova-Thacker EV, Boumediene D, Bouquet R, Boveia A, Boyd J, Boye D, Boyko IR, Bozianu L, Bracinik J, Brahimi N, Brandt G, Brandt O, Braren F, Brau B, Brau JE, Brener R, Brenner L, Brenner R, Bressler S, Brianti G, Britton D, Britzger D, Brock I, Brooijmans G, Brooks EM, Brost E, Brown LM, Bruce LE, Bruckler TL, Bruckman de Renstrom PA, Brüers B, Bruni A, Bruni G, Bruschi M, Bruscino N, Buanes T, Buat Q, Buchin D, Buckley AG, Bulekov O, Bullard BA, Burdin S, Burgard CD, Burger AM, Burghgrave B, Burlayenko O, Burr JTP, Burzynski JC, Busch EL, Büscher V, Bussey PJ, Butler JM, Buttar CM, Butterworth JM, Buttinger W, Buxo Vazquez CJ, Buzykaev AR, Cabrera Urbán S, Cadamuro L, Caforio D, Cai H, Cai Y, Cai Y, Cairo VMM, Cakir O, Calace N, Calafiura P, Calderini G, Calfayan P, Callea G, Caloba LP, Calvet D, Calvet S, Calvetti M, Camacho Toro R, Camarda S, Camarero Munoz D, Camarri P, Camerlingo MT, Cameron D, Camincher C, Campanelli M, Camplani A, Canale V, Canbay AC, Canonero E, Cantero J, Cao Y, Capocasa F, Capua M, Carbone A, Cardarelli R, Cardenas JCJ, Carducci G, Carli T, Carlino G, Carlotto JI, Carlson BT, Carlson EM, Carmignani J, Carminati L, Carnelli A, Carnesale M, Caron S, Carquin E, Carrá S, Carratta G, Carroll AM, Carter TM, Casado MP, Caspar M, Castillo FL, Castillo Garcia L, Castillo Gimenez V, Castro NF, Catinaccio A, Catmore JR, Cavaliere T, Cavaliere V, Cavalli N, Caviedes Betancourt LJ, Cekmecelioglu YC, Celebi E, Cella S, Celli F, Centonze MS, Cepaitis V, Cerny K, Cerqueira AS, Cerri A, Cerrito L, Cerutti F, Cervato B, Cervelli A, Cesarini G, Cetin SA, Chakraborty D, Chan J, Chan WY, Chapman JD, Chapon E, Chargeishvili B, Charlton DG, Chatterjee M, Chauhan C, Che Y, Chekanov S, Chekulaev SV, Chelkov GA, Chen A, Chen B, Chen B, Chen H, Chen H, Chen J, Chen J, Chen M, Chen S, Chen SJ, Chen X, Chen X, Chen Y, Cheng CL, Cheng HC, Cheong S, Cheplakov A, Cheremushkina E, Cherepanova E, Cherkaoui El Moursli R, Cheu E, Cheung K, Chevalier L, Chiarella V, Chiarelli G, Chiedde N, Chiodini G, Chisholm AS, Chitan A, Chitishvili M, Chizhov MV, Choi K, Chou Y, Chow EYS, Chu KL, Chu MC, Chu X, Chubinidze Z, Chudoba J, Chwastowski JJ, Cieri D, Ciesla KM, Cindro V, Ciocio A, Cirotto F, Citron ZH, Citterio M, Ciubotaru DA, Clark A, Clark PJ, Clarke Hall N, Clarry C, Clavijo Columbie JM, Clawson SE, Clement C, Clercx J, Coadou Y, Cobal M, Coccaro A, Barrue RFC, Coelho Lopes De Sa R, Coelli S, Cole B, Collot J, Conde Muiño P, Connell MP, Connell SH, Conroy EI, Conventi F, Cooke HG, Cooper-Sarkar AM, Corchia FA, Cordeiro Oudot Choi A, Corpe LD, Corradi M, Corriveau F, Cortes-Gonzalez A, Costa MJ, Costanza F, Costanzo D, Cote BM, Couthures J, Cowan G, Cranmer K, Cremonini D, Crépé-Renaudin S, Crescioli F, Cristinziani M, Cristoforetti M, Croft V, Crosby JE, Crosetti G, Cueto A, Cui H, Cui Z, Cunningham WR, Curcio F, Curran JR, Czodrowski P, Czurylo MM, De Sousa MJDCS, Da Fonseca Pinto JV, Da Via C, Dabrowski W, Dado T, Dahbi S, Dai T, Dal Santo D, Dallapiccola C, Dam M, D'amen G, D'Amico V, Damp J, Dandoy JR, Dannheim D, Danninger M, Dao V, Darbo G, Das SJ, Dattola F, D'Auria S, D'avanzo A, David C, Davidek T, Dawson I, Day-Hall HA, De K, De Asmundis R, De Biase N, De Castro S, De Groot N, de Jong P, De la Torre H, De Maria A, De Salvo A, De Sanctis U, De Santis F, De Santo A, De Vivie De Regie JB, Dedovich DV, Degens J, Deiana AM, Del Corso F, Del Peso J, Del Rio F, Delagrange L, Deliot F, Delitzsch CM, Della Pietra M, Della Volpe D, Dell'Acqua A, Dell'Asta L, Delmastro M, Delsart PA, Demers S, Demichev M, Denisov SP, D'Eramo L, Derendarz D, Derue F, Dervan P, Desch K, Deutsch C, Di Bello FA, Di Ciaccio A, Di Ciaccio L, Di Domenico A, Di Donato C, Di Girolamo A, Di Gregorio G, Di Luca A, Di Micco B, Di Nardo R, Di Petrillo KF, Diamantopoulou M, Dias FA, Vale TDD, Diaz MA, Diaz Capriles FG, Didenko M, Diehl EB, Díez Cornell S, Diez Pardos C, Dimitriadi C, Dimitrievska A, Dingfelder J, Dinu IM, Dittmeier SJ, Dittus F, Divisek M, Djama F, Djobava T, Doglioni C, Dohnalova A, Dolejsi J, Dolezal Z, Domijan K, Dona KM, Donadelli M, Dong B, Donini J, D'Onofrio A, D'Onofrio M, Dopke J, Doria A, Dos Santos Fernandes N, Dougan P, Dova MT, Doyle AT, Draguet MA, Dreyer E, Drivas-Koulouris I, Drnevich M, Drozdova M, Du D, du Pree TA, Dubinin F, Dubovsky M, Duchovni E, Duckeck G, Ducu OA, Duda D, Dudarev A, Duden ER, D'uffizi M, Duflot L, Dührssen M, Duminica I, Dumitriu AE, Dunford M, Dungs S, Dunne K, Duperrin A, Yildiz HD, Düren M, Durglishvili A, Dwyer BL, Dyckes GI, Dyndal M, Dziedzic BS, Earnshaw ZO, Eberwein GH, Eckerova B, Eggebrecht S, Purcino De Souza EE, Ehrke LF, Eigen G, Einsweiler K, Ekelof T, Ekman PA, El Farkh S, El Ghazali Y, El Jarrari H, El Moussaouy A, Ellajosyula V, Ellert M, Ellinghaus F, Ellis N, Elmsheuser J, Elsawy M, Elsing M, Emeliyanov D, Enari Y, Ene I, Epari S, Erland PA, Ernani Martins Neto D, Errenst M, Escalier M, Escobar C, Etzion E, Evans G, Evans H, Evans LS, Ezhilov A, Ezzarqtouni S, Fabbri F, Fabbri L, Facini G, Fadeyev V, Fakhrutdinov RM, Fakoudis D, Falciano S, Falda Ulhoa Coelho LF, Fallavollita F, Falsetti G, Faltova J, Fan C, Fan Y, Fang Y, Fanti M, Faraj M, Farazpay Z, Farbin A, Farilla A, Farooque T, Farrington SM, Fassi F, Fassouliotis D, Faucci Giannelli M, Fawcett WJ, Fayard L, Federic P, Federicova P, Fedin OL, Feickert M, Feligioni L, Fellers DE, Feng C, Feng M, Feng Z, Fenton MJ, Ferencz L, Ferguson RAM, Fernandez Luengo SI, Fernandez Martinez P, Fernoux MJV, Ferrando J, Ferrari A, Ferrari P, Ferrari R, Ferrere D, Ferretti C, Fiacco D, Fiedler F, Fiedler P, Filipčič A, Filmer EK, Filthaut F, Fiolhais MCN, Fiorini L, Fisher WC, Fitschen T, Fitzhugh PM, Fleck I, Fleischmann P, Flick T, Flores M, Flores Castillo LR, Flores Sanz De Acedo L, Follega FM, Fomin N, Foo JH, Formica A, Forti AC, Fortin E, Fortman AW, Foti MG, Fountas L, Fournier D, Fox H, Francavilla P, Francescato S, Franchellucci S, Franchini M, Franchino S, Francis D, Franco L, Franco Lima V, Franconi L, Franklin M, Frattari G, Frid YY, Friend J, Fritzsche N, Froch A, Froidevaux D, Frost JA, Fu Y, Fuenzalida Garrido S, Fujimoto M, Fung KY, De Simas Filho EF, Furukawa M, Fuster J, Gaa A, Gabrielli A, Gabrielli A, Gadow P, Gagliardi G, Gagnon LG, Gaid S, Galantzan S, Gallas EJ, Gallop BJ, Gan KK, Ganguly S, Gao Y, Garay Walls FM, Garcia B, García C, Garcia Alonso A, Garcia Caffaro AG, García Navarro JE, Garcia-Sciveres M, Gardner GL, Gardner RW, Garelli N, Garg D, Garg RB, Gargan JM, Garner CA, Garvey CM, Gassmann VK, Gaudio G, Gautam V, Gauzzi P, Gavranovic J, Gavrilenko IL, Gavrilyuk A, Gay C, Gaycken G, Gazis EN, Geanta AA, Gee CM, Gekow A, Gemme C, Genest MH, Gentry AD, George S, George WF, Geralis T, Gessinger-Befurt P, Geyik ME, Ghani M, Ghorbanian K, Ghosal A, Ghosh A, Ghosh A, Giacobbe B, Giagu S, Giani T, Giannetti P, Giannini A, Gibson SM, Gignac M, Gil DT, Gilbert AK, Gilbert BJ, Gillberg D, Gilles G, Ginabat L, Gingrich DM, Giordani MP, Giraud PF, Giugliarelli G, Giugni D, Giuli F, Gkialas I, Gladilin LK, Glasman C, Gledhill GR, Glemža G, Glisic M, Gnesi I, Go Y, Goblirsch-Kolb M, Gocke B, Godin D, Gokturk B, Goldfarb S, Golling T, Gololo MGD, Golubkov D, Gombas JP, Gomes A, Gomes Da Silva G, Gomez Delegido AJ, Gonçalo R, Gonella L, Gongadze A, Gonnella F, Gonski JL, González Andana RY, González de la Hoz S, Gonzalez Lopez R, Gonzalez Renteria C, Gonzalez Rodrigues MV, Gonzalez Suarez R, Gonzalez-Sevilla S, Goossens L, Gorini B, Gorini E, Gorišek A, Gosart TC, Goshaw AT, Gostkin MI, Goswami S, Gottardo CA, Gotz SA, Gouighri M, Goumarre V, Goussiou AG, Govender N, Grabowska-Bold I, Graham K, Gramstad E, Grancagnolo S, Grant CM, Gravila PM, Gravili FG, Gray HM, Greco M, Green MJ, Grefe C, Grefsrud AS, Gregor IM, Greif KT, Grenier P, Grewe SG, Grillo AA, Grimm K, Grinstein S, Grivaz JF, Gross E, Grosse-Knetter J, Grundy JC, Guan L, Guerrero Rojas JGR, Guerrieri G, Gugel R, Guhit JAM, Guida A, Guilloton E, Guindon S, Guo F, Guo J, Guo L, Guo Y, Gupta R, Gurbuz S, Gurdasani SS, Gustavino G, Guth M, Gutierrez P, Gutierrez Zagazeta LF, Gutsche M, Gutschow C, Gwenlan C, Gwilliam CB, Haaland ES, Haas A, Habedank M, Haber C, Hadavand HK, Hadef A, Hadzic S, Hagan AI, Hahn JJ, Haines EH, Haleem M, Haley J, Hall JJ, Hallewell GD, Halser L, Hamano K, Hamer M, Hamity GN, Hampshire EJ, Han J, Han K, Han L, Han L, Han S, Han YF, Hanagaki K, Hance M, Hangal DA, Hanif H, Hank MD, Hansen JB, Hansen PH, Hara K, Harada D, Harenberg T, Harkusha S, Harris ML, Harris YT, Harrison J, Harrison NM, Harrison PF, Hartman NM, Hartmann NM, Hasan RZ, Hasegawa Y, Hassan S, Hauser R, Hawkes CM, Hawkings RJ, Hayashi Y, Hayashida S, Hayden D, Hayes C, Hayes RL, Hays CP, Hays JM, Hayward HS, He F, He M, He Y, He Y, He Y, Heatley NB, Hedberg V, Heggelund AL, Hehir ND, Heidegger C, Heidegger KK, Heilman J, Heim S, Heim T, Heinlein JG, Heinrich JJ, Heinrich L, Hejbal J, Held A, Hellesund S, Helling CM, Hellman S, Henderson RCW, Henkelmann L, Henriques Correia AM, Herde H, Hernández Jiménez Y, Herrmann LM, Herrmann T, Herten G, Hertenberger R, Hervas L, Hesping ME, Hessey NP, Hidaoui M, Hidic N, Hill E, Hillier SJ, Hinds JR, Hinterkeuser F, Hirose M, Hirose S, Hirschbuehl D, Hitchings TG, Hiti B, Hobbs J, Hobincu R, Hod N, Hodgkinson MC, Hodkinson BH, Hoecker A, Hofer DD, Hofer J, Holm T, Holzbock M, Hommels LBAH, Honan BP, Hong JJ, 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Search for Light Long-Lived Particles in pp Collisions at sqrt[s]=13 TeV Using Displaced Vertices in the ATLAS Inner Detector. PHYSICAL REVIEW LETTERS 2024; 133:161803. [PMID: 39485965 DOI: 10.1103/physrevlett.133.161803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 08/29/2024] [Accepted: 09/11/2024] [Indexed: 11/03/2024]
Abstract
A search for long-lived particles (LLPs) using 140 fb^{-1} of pp collision data with sqrt[s]=13 TeV recorded by the ATLAS experiment at the LHC is presented. The search targets LLPs with masses between 5 and 55 GeV that decay hadronically in the ATLAS inner detector. Benchmark models with LLP pair production from exotic decays of the Higgs boson and models featuring long-lived axionlike particles (ALPs) are considered. No significant excess above the expected background is observed. Upper limits are placed on the branching ratio of the Higgs boson to pairs of LLPs, the cross section for ALPs produced in association with a vector boson, and, for the first time, on the branching ratio of the top quark to an ALP and a u/c quark.
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Search for the Exclusive W Boson Hadronic Decays W^{±}→π^{±}γ, W^{±}→K^{±}γ and W^{±}→ρ^{±}γ with the ATLAS Detector. PHYSICAL REVIEW LETTERS 2024; 133:161804. [PMID: 39485985 DOI: 10.1103/physrevlett.133.161804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 07/15/2024] [Indexed: 11/03/2024]
Abstract
A search for the exclusive hadronic decays W^{±}→π^{±}γ, W^{±}→K^{±}γ, and W^{±}→ρ^{±}γ is performed using up to 140 fb^{-1} of proton-proton collisions recorded with the ATLAS detector at a center-of-mass energy of sqrt[s]=13 TeV. If observed, these rare processes would provide a unique test bench for the quantum chromodynamics factorization formalism used to calculate cross sections at colliders. Additionally, at future colliders, these decays could offer a new way to measure the W boson mass through fully reconstructed decay products. The search results in the most stringent upper limits to date on the branching fractions B(W^{±}→π^{±}γ)<1.9×10^{-6}, B(W^{±}→K^{±}γ)<1.7×10^{-6}, B(W^{±}→ρ^{±}γ)<5.2×10^{-6} at 95% confidence level.
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Combination and summary of ATLAS dark matter searches interpreted in a 2HDM with a pseudo-scalar mediator using 139 fb -1 of s=13 TeV pp collision data. Sci Bull (Beijing) 2024; 69:3005-3035. [PMID: 39179456 DOI: 10.1016/j.scib.2024.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/03/2023] [Accepted: 05/27/2024] [Indexed: 08/26/2024]
Abstract
Results from a wide range of searches targeting different experimental signatures with and without missing transverse momentum (ETmiss) are used to constrain a Two-Higgs-Doublet Model (2HDM) with an additional pseudo-scalar mediating the interaction between ordinary and dark matter (2HDM+a). The analyses use up to 139 fb-1 of proton-proton collision data at a centre-of-mass energy s=13 TeV recorded with the ATLAS detector at the Large Hadron Collider during 2015-2018. The results from three of the most sensitive searches are combined statistically. These searches target signatures with large ETmiss and a leptonically decaying Z boson; large ETmiss and a Higgs boson decaying to bottom quarks; and production of charged Higgs bosons in final states with top and bottom quarks, respectively. Constraints are derived for several common and new benchmark scenarios in the 2HDM+a.
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Mohamed A, Tarem S, Tariq K, Tarna G, Tartarelli GF, Tas P, Tasevsky M, Tassi E, Tate AC, Tateno G, Tayalati Y, Taylor GN, Taylor W, Tee AS, Teixeira De Lima R, Teixeira-Dias P, Teoh JJ, Terashi K, Terron J, Terzo S, Testa M, Teuscher RJ, Thaler A, Theiner O, Themistokleous N, Theveneaux-Pelzer T, Thielmann O, Thomas DW, Thomas JP, Thompson EA, Thompson PD, Thomson E, Tian Y, Tikhomirov V, Tikhonov YA, Timoshenko S, Timoshyn D, Ting EXL, Tipton P, Tlou SH, Tnourji A, Todome K, Todorova-Nova S, Todt S, Togawa M, Tojo J, Tokár S, Tokushuku K, Toldaiev O, Tombs R, Tomoto M, Tompkins L, Topolnicki KW, Torrence E, Torres H, Torró Pastor E, Toscani M, Tosciri C, Tost M, Tovey DR, Traeet A, Trandafir IS, Trefzger T, Tricoli A, Trigger IM, Trincaz-Duvoid S, Trischuk DA, Trocmé B, Troncon C, Truong L, Trzebinski M, Trzupek A, Tsai F, Tsai M, Tsiamis A, Tsiareshka PV, Tsigaridas S, Tsirigotis A, Tsiskaridze V, Tskhadadze EG, Tsopoulou M, Tsujikawa Y, Tsukerman II, Tsulaia V, Tsuno S, Tsuri K, Tsybychev D, Tu Y, Tudorache A, Tudorache V, Tuna AN, Turchikhin S, Turk Cakir I, Turra R, Turtuvshin T, Tuts PM, Tzamarias S, Tzanis P, Tzovara E, Ukegawa F, Ulloa Poblete PA, Umaka EN, Unal G, Unal M, Undrus A, Unel G, Urban J, Urquijo P, Urrejola P, Usai G, Ushioda R, Usman M, Uysal Z, Vacek V, Vachon B, Vadla KOH, Vafeiadis T, Vaitkus A, Valderanis C, Valdes Santurio E, Valente M, Valentinetti S, Valero A, Valiente Moreno E, Vallier A, Valls Ferrer JA, Van Arneman DR, Van Daalen TR, Van Der Graaf A, Van Gemmeren P, Van Rijnbach M, Van Stroud S, Van Vulpen I, Vanadia M, Vandelli W, Vandenbroucke M, Vandewall ER, Vannicola D, Vannoli L, Vari R, Varnes EW, Varni C, Varol T, Varouchas D, Varriale L, Varvell KE, Vasile ME, Vaslin L, Vasquez GA, Vasyukov A, Vazeille F, Vazquez Schroeder T, Veatch J, Vecchio V, Veen MJ, Veliscek I, Veloce LM, Veloso F, Veneziano S, Ventura A, Ventura Gonzalez S, Verbytskyi A, Verducci M, Vergis C, Verissimo De Araujo M, Verkerke W, Vermeulen JC, Vernieri C, Vessella M, Vetterli MC, Vgenopoulos A, Viaux Maira N, Vickey T, Vickey Boeriu OE, Viehhauser GHA, Vigani L, Villa M, Villaplana Perez M, Villhauer EM, Vilucchi E, Vincter MG, Virdee GS, Vishwakarma A, Visibile A, Vittori C, Vivarelli I, Voevodina E, Vogel F, Voigt JC, Vokac P, Volkotrub Y, Von Ahnen J, Von Toerne E, Vormwald B, Vorobel V, Vorobev K, Vos M, Voss K, Vossebeld JH, Vozak M, Vozdecky L, Vranjes N, Vranjes Milosavljevic M, Vreeswijk M, Vu NK, Vuillermet R, Vujinovic O, Vukotic I, Wada S, Wagner C, Wagner JM, Wagner W, Wahdan S, Wahlberg H, Wakida M, Walder J, Walker R, Walkowiak W, Wall A, Wamorkar T, Wang AZ, Wang C, Wang C, Wang H, Wang J, Wang RJ, Wang R, Wang R, Wang SM, Wang S, Wang T, Wang WT, Wang W, Wang X, Wang X, Wang X, Wang Y, Wang Y, Wang Z, Wang Z, Wang Z, Warburton A, Ward RJ, Warrack N, Watson AT, Watson H, Watson MF, Watton E, Watts G, Waugh BM, Weber C, Weber HA, Weber MS, Weber SM, Wei C, Wei Y, Weidberg AR, Weik EJ, Weingarten J, Weirich M, Weiser C, Wells CJ, Wenaus T, Wendland B, Wengler T, Wenke NS, Wermes N, Wessels M, Wharton AM, White AS, White A, White MJ, Whiteson D, Wickremasinghe L, Wiedenmann W, Wielers M, Wiglesworth C, Wilbern DJ, Wilkens HG, Williams DM, Williams HH, Williams S, Willocq S, Wilson BJ, Windischhofer PJ, Winkel FI, Winklmeier F, Winter BT, Winter JK, Wittgen M, Wobisch M, Wolffs Z, Wollrath J, Wolter MW, Wolters H, Wongel AF, Woodward EL, Worm SD, Wosiek BK, Woźniak KW, Wozniewski S, Wraight K, Wu C, Wu J, Wu M, Wu M, Wu SL, Wu X, Wu Y, Wu Z, Wuerzinger J, Wyatt TR, Wynne BM, Xella S, Xia L, Xia M, Xiang J, Xie M, Xie X, Xin S, Xiong A, Xiong J, Xu D, Xu H, Xu L, Xu R, Xu T, Xu Y, Xu Z, Xu Z, Yabsley B, Yacoob S, Yamaguchi Y, Yamashita E, Yamauchi H, Yamazaki T, Yamazaki Y, Yan J, Yan S, Yan Z, Yang HJ, Yang HT, Yang S, Yang T, Yang X, Yang X, Yang Y, Yang Y, Yang Z, Yao WM, Yap YC, Ye H, Ye H, Ye J, Ye S, Ye X, Yeh Y, Yeletskikh I, Yeo BK, Yexley MR, Yin P, Yorita K, Younas S, Young CJS, Young C, Yu C, Yu Y, Yuan M, Yuan R, Yue L, Zaazoua M, Zabinski B, Zaid E, Zak ZK, Zakareishvili T, Zakharchuk N, Zambito S, Zamora Saa JA, Zang J, Zanzi D, Zaplatilek O, Zeitnitz C, Zeng H, Zeng JC, Zenger DT, Zenin O, Ženiš T, Zenz S, Zerradi S, Zerwas D, Zhai M, Zhang DF, Zhang J, Zhang J, Zhang K, Zhang L, Zhang P, Zhang R, Zhang S, Zhang S, Zhang T, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhang Z, Zhao H, Zhao T, Zhao Y, Zhao Z, Zhemchugov A, Zheng J, Zheng K, Zheng X, Zheng Z, Zhong D, Zhou B, Zhou H, Zhou N, Zhou Y, Zhu CG, Zhu J, Zhu Y, Zhu Y, Zhuang X, Zhukov K, Zhulanov V, Zimine NI, Zinsser J, Ziolkowski M, Živković L, Zoccoli A, Zoch K, Zorbas TG, Zormpa O, Zou W, Zwalinski L. Determination of the Relative Sign of the Higgs Boson Couplings to W and Z Bosons Using WH Production via Vector-Boson Fusion with the ATLAS Detector. PHYSICAL REVIEW LETTERS 2024; 133:141801. [PMID: 39423379 DOI: 10.1103/physrevlett.133.141801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 07/09/2024] [Accepted: 08/22/2024] [Indexed: 10/21/2024]
Abstract
The associated production of Higgs and W bosons via vector-boson fusion is highly sensitive to the relative sign of the Higgs boson couplings to W and Z bosons. In this Letter, two searches for this process are presented, using 140 fb^{-1} of proton-proton collision data at sqrt[s]=13 TeV recorded by the ATLAS detector at the LHC. The first search targets scenarios with opposite-sign couplings of the W and Z bosons to the Higgs boson, while the second targets standard model-like scenarios with same-sign couplings. Both analyses consider Higgs boson decays into a pair of b quarks and W boson decays with an electron or muon. The data exclude the opposite-sign coupling hypothesis with a significance beyond 5σ, and the observed (expected) upper limit set on the cross section for vector-boson fusion WH production is 9.0 (8.7) times the standard model value at 95% confidence level.
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Zhang M, Jing M, Li R, Cao Y, Zhang S, Guo Y. Construction and validation of a prediction model for preoperative prediction of Ki-67 expression in endometrial cancer patients by apparent diffusion coefficient. Clin Radiol 2024; 79:e1196-e1204. [PMID: 39129106 DOI: 10.1016/j.crad.2024.05.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 04/07/2024] [Accepted: 05/21/2024] [Indexed: 08/13/2024]
Abstract
AIM Ki-67 is a marker of cell proliferation and is increasingly being used as a primary outcome measure in preoperative window studies of endometrial cancer (EC). This study explored the feasibility of using apparent diffusion coefficient (ADC) values in noninvasive prediction of Ki-67 expression levels in EC patients before surgery, and constructs a nomogram by combining clinical data. MATERIAL AND METHODS This study retrospectively analyzed 280 EC patients who underwent preoperative magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI) in our hospital from January 2017 to February 2023. Evaluate the potential nonlinear relationship between ADC values and Ki-67 expression using the nomogram. The included patients were randomized into a training set (n = 186) and a validation set (n = 84). Using a combination of logistic regression and LASSO regression results, from which the four best predictors were identified for the construction of the nomogram. The accuracy and clinical applicability of the nomogram were assessed using the receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). RESULTS The results of this study showed a nonlinear correlation between ADCmin and Ki-67 expression (nonlinear P = 0.019), and the nonlinear correlation between ADCmean and Ki-67 expression (nonlinear P = 0.019). In addition, this study constructed the nomogram by incorporating ADCmax, International Federation of Gynecology and Obstetrics (FIGO), and chemotherapy. The area under the curve (AUC) values of the ROC for nomogram, ADCmax, FIGO, chemotherapy and grade in the training set were 0.783, 0.718, 0.579, 0.636, and 0.654, respectively. In the validation set, the AUC values for nomogram, ADCmax, FIGO, chemotherapy, and grade were 0.820, 0.746, 0.558, 0.542, and 0.738, respectively. In addition, the calibration curves and the DCA curves suggested a better predictive efficacy of the model. CONCLUSION A nomogram prediction model constructed on the basis of ADCmax values combined with clinical data can be used as an effective method to noninvasively assess Ki-67 expression in EC patients before surgery.
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Hui YM, Guo Y, Li B, Meng YQ, Feng HM, Su ZP, Lin MZ, Chen YZ, Zheng ZZ, Li HT. Comparative analysis of three-dimensional and two-dimensional models for predicting the malignancy probability of subsolid nodules. Clin Radiol 2024; 79:781-790. [PMID: 39068114 DOI: 10.1016/j.crad.2024.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 07/03/2024] [Accepted: 07/04/2024] [Indexed: 07/30/2024]
Abstract
AIM To construct three-dimensional (3D) and two-dimensional (2D) models to predict the malignancy probability of subsolid nodules (SSNs) and compare their effectiveness. MATERIALS AND METHODS A total of 371 SSNs from 332 patients, collected between January 2020 and January 2024, were included in the study. The SSNs were divided into a training set for constructing the models and a test set for validating the models. Models were developed using binary logistic backward regression, based on factors that showed significant differences in univariate analyses. The performance of the models was assessed using the area under the curve (AUC) of the receiver operating characteristic (ROC). The AUCs of different models were compared using the DeLong test. RESULTS The AUCs for the two 3D models, one 2D model, and the Brock model were 0.785 (0.733-0.836), 0.776 (0.723-0.829), 0.764 (0.710-0.818), and 0.738 (0.679-0.798) in the training set. In the test set, these AUCs were 0.817 (0.706-0.928), 0.796 (0.679-0.913), 0.771 (0.647-0.895), and 0.790 (0.678-0.903). The two 3D models demonstrated statistically significant differences from the Brock model in the training set (P=0.024 and P=0.046). None of the four models showed significant differences in the test set (all P>0.05). CONCLUSION The 3D models outperform both the 2D model and the Brock model in predicting the malignancy probability of SSNs, and the 3D model incorporating volume, mean CT attenuation value, and lobulation as factors performed the best.
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Aad G, Aakvaag E, Abbott B, Abdelhameed S, Abeling K, Abicht NJ, Abidi SH, Aboelela M, Aboulhorma A, Abramowicz H, Abreu H, Abulaiti Y, Acharya BS, Ackermann A, Adam Bourdarios C, Adamczyk L, Addepalli SV, Addison MJ, Adelman J, Adiguzel A, Adye T, Affolder AA, Afik Y, Agaras MN, Agarwala J, Aggarwal A, Agheorghiesei C, Ahmadov F, Ahmed WS, Ahuja S, Ai X, Aielli G, Aikot A, Ait Tamlihat M, Aitbenchikh B, Akbiyik M, Åkesson TPA, Akimov AV, Akiyama D, Akolkar NN, Aktas S, Al Khoury K, Alberghi GL, Albert J, Albicocco P, Albouy GL, Alderweireldt S, Alegria ZL, Aleksa M, Aleksandrov IN, Alexa C, Alexopoulos T, Alfonsi F, Algren M, Alhroob M, Ali B, Ali HMJ, Ali S, Alibocus SW, Aliev M, Alimonti G, Alkakhi W, Allaire C, Allbrooke BMM, Allen JF, Allendes Flores CA, Allport PP, Aloisio A, Alonso F, Alpigiani C, Alsolami ZMK, Alvarez Estevez M, Alvarez Fernandez A, Alves Cardoso M, Alviggi MG, Aly M, Amaral Coutinho Y, Ambler A, Amelung C, Amerl M, Ames CG, Amidei D, Amini B, Amirie KJ, Amor Dos Santos SP, Amos KR, Amperiadou D, An S, Ananiev V, Anastopoulos C, Andeen T, Anders JK, Anderson AC, Andrean SY, Andreazza A, Angelidakis S, Angerami A, Anisenkov AV, Annovi A, Antel C, Antipov E, Antonelli M, Anulli F, Aoki M, Aoki T, Aparo MA, Aperio Bella L, Appelt C, Apyan A, Arbiol Val SJ, Arcangeletti C, Arce ATH, Arguin JF, Argyropoulos S, Arling JH, Arnaez O, Arnold H, Artoni G, Asada H, Asai K, Asai S, Asbah NA, Ashby Pickering RA, Assamagan K, Astalos R, Astrand KSV, Atashi S, Atkin RJ, Atkinson M, Atmani H, Atmasiddha PA, Augsten K, Auricchio S, Auriol AD, Austrup VA, Avolio G, Axiotis K, Azuelos G, Babal D, Bachacou H, Bachas K, Bachiu A, Backman F, Badea A, Baer TM, Bagnaia P, Bahmani M, Bahner D, Bai K, Baines JT, Baines L, Baker OK, Bakos E, Bakshi Gupta D, Balabram Filho LE, Balakrishnan V, Balasubramanian R, Baldin EM, Balek P, Ballabene E, Balli F, Baltes LM, Balunas WK, Balz J, Bamwidhi I, Banas E, Bandieramonte M, Bandyopadhyay A, Bansal S, Barak L, Barakat M, Barberio EL, Barberis D, Barbero M, Barel MZ, Barillari T, Barisits MS, Barklow T, Baron P, Baron Moreno DA, Baroncelli A, Barr AJ, Barr JD, Barreiro F, Barreiro Guimarães da Costa J, Barron U, Barros Teixeira MG, Barsov S, Bartels F, Bartoldus R, Barton AE, Bartos P, Basan A, Baselga M, Bassalat A, Basso MJ, Bataju S, Bate R, Bates RL, Batlamous S, Batool B, Battaglia M, Battulga D, Bauce M, Bauer M, Bauer P, Bazzano Hurrell LT, Beacham JB, Beau T, Beaucamp JY, Beauchemin PH, Bechtle P, Beck HP, Becker K, Beddall AJ, Bednyakov VA, Bee CP, Beemster LJ, Beermann TA, Begalli M, Begel M, Behera A, Behr JK, Beirer JF, Beisiegel F, Belfkir M, Bella G, Bellagamba L, Bellerive A, Bellos P, Beloborodov K, Benchekroun D, Bendebba F, Benhammou Y, Benkendorfer KC, Beresford L, Beretta M, Bergeaas Kuutmann E, Berger N, Bergmann B, Beringer J, Bernardi G, Bernius C, Bernlochner FU, Bernon F, Berrocal Guardia A, Berry T, Berta P, Berthold A, Bethke S, Betti A, Bevan AJ, Bhalla NK, Bhatta S, Bhattacharya DS, Bhattarai P, Bhide KD, Bhopatkar VS, Bianchi RM, Bianco G, Biebel O, Bielski R, Biglietti M, Billingsley CS, Bimgdi Y, Bindi M, Bingul A, Bini C, Bird GA, Birman M, Biros M, Biryukov S, Bisanz T, Bisceglie E, Biswal JP, Biswas D, Bloch I, Blue A, Blumenschein U, Blumenthal J, Bobrovnikov VS, Boehler M, Boehm B, Bogavac D, Bogdanchikov AG, Boggia LS, Bohm C, Boisvert V, Bokan P, Bold T, Bomben M, Bona M, Boonekamp M, Booth CD, Borbély AG, Bordulev IS, Borissov G, Bortoletto D, Boscherini D, Bosman M, Bossio Sola JD, Bouaouda K, Bouchhar N, Boudet L, Boudreau J, Bouhova-Thacker EV, Boumediene D, Bouquet R, Boveia A, Boyd J, Boye D, Boyko IR, Bozianu L, Bracinik J, Brahimi N, Brandt G, Brandt O, Braren F, Brau B, Brau JE, Brener R, Brenner L, Brenner R, Bressler S, Brianti G, Britton D, Britzger D, Brock I, Brooijmans G, Brooks EM, Brost E, Brown LM, Bruce LE, Bruckler TL, Bruckman de Renstrom PA, Brüers B, Bruni A, Bruni G, Bruschi M, Bruscino N, Buanes T, Buat Q, Buchin D, Buckley AG, Bulekov O, Bullard BA, Burdin S, Burgard CD, Burger AM, Burghgrave B, Burlayenko O, Burleson J, Burr JTP, Burzynski JC, Busch EL, Büscher V, Bussey PJ, Butler JM, Buttar CM, Butterworth JM, Buttinger W, Buxo Vazquez CJ, Buzykaev AR, Cabrera Urbán S, Cadamuro L, Caforio D, Cai H, Cai Y, Cai Y, Cairo VMM, Cakir O, Calace N, Calafiura P, Calderini G, Calfayan P, Callea G, Caloba LP, Calvet D, Calvet S, Calvetti M, Camacho Toro R, Camarda S, Camarero Munoz D, Camarri P, Camerlingo MT, Cameron D, Camincher C, Campanelli M, Camplani A, Canale V, Canbay AC, Canonero E, Cantero J, Cao Y, Capocasa F, Capua M, Carbone A, Cardarelli R, Cardenas JCJ, Carducci G, Carli T, Carlino G, Carlotto JI, Carlson BT, Carlson EM, Carmignani J, Carminati L, Carnelli A, Carnesale M, Caron S, Carquin E, Carr IB, Carrá S, Carratta G, Carroll AM, Carter TM, Casado MP, Caspar M, Castillo FL, Castillo Garcia L, Castillo Gimenez V, Castro NF, Catinaccio A, Catmore JR, Cavaliere T, Cavaliere V, Cavalli N, Caviedes Betancourt LJ, Cekmecelioglu YC, Celebi E, Cella S, Celli F, Centonze MS, Cepaitis V, Cerny K, Cerqueira AS, Cerri A, Cerrito L, Cerutti F, Cervato B, Cervelli A, Cesarini G, Cetin SA, Chakraborty D, Chan J, Chan WY, Chapman JD, Chapon E, Chargeishvili B, Charlton DG, Chatterjee M, Chauhan C, Che Y, Chekanov S, Chekulaev SV, Chelkov GA, Chen A, Chen B, Chen B, Chen H, Chen H, Chen J, Chen J, Chen M, Chen S, Chen SJ, Chen X, Chen X, Chen Y, Cheng CL, Cheng HC, Cheong S, Cheplakov A, Cheremushkina E, Cherepanova E, Cherkaoui El Moursli R, Cheu E, Cheung K, Chevalier L, Chiarella V, Chiarelli G, Chiedde N, Chiodini G, Chisholm AS, Chitan A, Chitishvili M, Chizhov MV, Choi K, Chou Y, Chow EYS, Chu KL, Chu MC, Chu X, Chubinidze Z, Chudoba J, Chwastowski JJ, Cieri D, Ciesla KM, Cindro V, Ciocio A, Cirotto F, Citron ZH, Citterio M, Ciubotaru DA, Clark A, Clark PJ, Clarke Hall N, Clarry C, Clavijo Columbie JM, Clawson SE, Clement C, Coadou Y, Cobal M, Coccaro A, Barrue RFC, Coelho Lopes De Sa R, Coelli S, Cole B, Collot J, Conde Muiño P, Connell MP, Connell SH, Conroy EI, Conventi F, Cooke HG, Cooper-Sarkar AM, Corchia FA, Cordeiro Oudot Choi A, Corpe LD, Corradi M, Corriveau F, Cortes-Gonzalez A, Costa MJ, Costanza F, Costanzo D, Cote BM, Couthures J, Cowan G, Cranmer K, Cremer L, Cremonini D, Crépé-Renaudin S, Crescioli F, Cristinziani M, Cristoforetti M, Croft V, Crosby JE, Crosetti G, Cueto A, Cui H, Cui Z, Cunningham WR, Curcio F, Curran JR, Czodrowski P, De Sousa MJDCS, Da Fonseca Pinto JV, Da Via C, Dabrowski W, Dado T, Dahbi S, Dai T, Dal Santo D, Dallapiccola C, Dam M, D'amen G, D'Amico V, Damp J, Dandoy JR, Dannheim D, Danninger M, Dao V, Darbo G, Das SJ, Dattola F, D'Auria S, D'avanzo A, David C, Davidek T, Dawson I, Day-Hall HA, De K, De Asmundis R, De Biase N, De Castro S, De Groot N, de Jong P, De la Torre H, De Maria A, De Salvo A, De Sanctis U, De Santis F, De Santo A, De Vivie De Regie JB, Debevc J, Dedovich DV, Degens J, Deiana AM, Del Corso F, Del Peso J, Delagrange L, Deliot F, Delitzsch CM, Della Pietra M, Della Volpe D, Dell'Acqua A, Dell'Asta L, Delmastro M, Delsart PA, Demers S, Demichev M, Denisov SP, D'Eramo L, Derendarz D, Derue F, Dervan P, Desch K, Deutsch C, Di Bello FA, Di Ciaccio A, Di Ciaccio L, Di Domenico A, Di Donato C, Di Girolamo A, Di Gregorio G, Di Luca A, Di Micco B, Di Nardo R, Di Petrillo KF, Diamantopoulou M, Dias FA, Vale TDD, Diaz MA, Diaz Capriles FG, Didenko AR, Didenko M, Diehl EB, Díez Cornell S, Diez Pardos C, Dimitriadi C, Dimitrievska A, Dingfelder J, Dingley T, Dinu IM, Dittmeier SJ, Dittus F, Divisek M, Dixit B, Djama F, Djobava T, Doglioni C, Dohnalova A, Dolejsi J, Dolezal Z, Domijan K, Dona KM, Donadelli M, Dong B, Donini J, D'Onofrio A, D'Onofrio M, Dopke J, Doria A, Dos Santos Fernandes N, Dougan P, Dova MT, Doyle AT, Draguet MA, Dreyer E, Drivas-Koulouris I, Drnevich M, Drozdova M, Du D, du Pree TA, Dubinin F, Dubovsky M, Duchovni E, Duckeck G, Ducu OA, Duda D, Dudarev A, Duden ER, 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Zenger DT, Zenin O, Ženiš T, Zenz S, Zerradi S, Zerwas D, Zhai M, Zhang DF, Zhang J, Zhang J, Zhang K, Zhang L, Zhang L, Zhang P, Zhang R, Zhang S, Zhang S, Zhang T, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhang Z, Zhang Z, Zhao H, Zhao T, Zhao Y, Zhao Z, Zhao Z, Zhemchugov A, Zheng J, Zheng K, Zheng X, Zheng Z, Zhong D, Zhou B, Zhou H, Zhou N, Zhou Y, Zhou Y, Zhou Y, Zhu CG, Zhu J, Zhu X, Zhu Y, Zhu Y, Zhuang X, Zhukov K, Zimine NI, Zinsser J, Ziolkowski M, Živković L, Zoccoli A, Zoch K, Zorbas TG, Zormpa O, Zou W, Zwalinski L. Combination of Searches for Higgs Boson Pair Production in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector. PHYSICAL REVIEW LETTERS 2024; 133:101801. [PMID: 39303265 DOI: 10.1103/physrevlett.133.101801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Accepted: 07/29/2024] [Indexed: 09/22/2024]
Abstract
This Letter presents results from a combination of searches for Higgs boson pair production using 126-140 fb^{-1} of proton-proton collision data at sqrt[s]=13 TeV recorded with the ATLAS detector. At 95% confidence level (CL), the upper limit on the production rate is 2.9 times the standard model (SM) prediction, with an expected limit of 2.4 assuming no Higgs boson pair production. Constraints on the Higgs boson self-coupling modifier κ_{λ}=λ_{HHH}/λ_{HHH}^{SM}, and the quartic HHVV coupling modifier κ_{2V}=g_{HHVV}/g_{HHVV}^{SM}, are derived individually, fixing the other parameter to its SM value. The observed 95% CL intervals are -1.2<κ_{λ}<7.2 and 0.6<κ_{2V}<1.5, respectively, while the expected intervals are -1.6<κ_{λ}<7.2 and 0.4<κ_{2V}<1.6 in the SM case. Constraints obtained for several interaction parameters within Higgs effective field theory are the strongest to date, offering insights into potential deviations from SM predictions.
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Zhang L, Zhang P, Zhang R, Zhang S, Zhang S, Zhang T, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhang Z, Zhao H, Zhao T, Zhao Y, Zhao Z, Zhao Z, Zhemchugov A, Zheng J, Zheng K, Zheng X, Zheng Z, Zhong D, Zhou B, Zhou H, Zhou N, Zhou Y, Zhou Y, Zhu CG, Zhu J, Zhu X, Zhu Y, Zhu Y, Zhuang X, Zhukov K, Zimine NI, Zinsser J, Ziolkowski M, Živković L, Zoccoli A, Zoch K, Zorbas TG, Zormpa O, Zou W, Zwalinski L. Studies of the Energy Dependence of Diboson Polarization Fractions and the Radiation-Amplitude-Zero Effect in WZ Production with the ATLAS Detector. PHYSICAL REVIEW LETTERS 2024; 133:101802. [PMID: 39303233 DOI: 10.1103/physrevlett.133.101802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 05/21/2024] [Accepted: 07/03/2024] [Indexed: 09/22/2024]
Abstract
This Letter presents the first study of the energy dependence of diboson polarization fractions in WZ→ℓνℓ^{'}ℓ^{'}(ℓ,ℓ^{'}=e,μ) production. The dataset used corresponds to an integrated luminosity of 140 fb^{-1} of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the ATLAS detector. Two fiducial regions with an enhanced presence of events featuring two longitudinally polarized bosons are defined. A nonzero fraction of events with two longitudinally polarized bosons is measured with an observed significance of 5.3 standard deviations in the region with 100 200 GeV, where p_{T}^{Z} is the transverse momentum of the Z boson. This Letter also reports the first study of the radiation-amplitude-zero effect. Events with two transversely polarized bosons are analyzed for the ΔY(ℓ_{W}Z) and ΔY(WZ) distributions defined respectively as the rapidity difference between the lepton from the W boson decay and the Z boson and the rapidity difference between the W boson and the Z boson. Significant suppression of events near zero is observed in both distributions. Unfolded ΔY(ℓ_{W}Z) and ΔY(WZ) distributions are also measured and compared to theoretical predictions.
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Strizenec P, Ströhmer R, Strom DM, Stroynowski R, Strubig A, Stucci SA, Stugu B, Stupak J, Styles NA, Su D, Su S, Su W, Su X, Sugizaki K, Sulin VV, Sullivan MJ, Sultan DMS, Sultanaliyeva L, Sultansoy S, Sumida T, Sun S, Sun S, Gudnadottir OS, Sur N, Sutton MR, Suzuki H, Svatos M, Swiatlowski M, Swirski T, Sykora I, Sykora M, Sykora T, Ta D, Tackmann K, Taffard A, Tafirout R, Vargas JST, Takubo Y, Talby M, Talyshev AA, Tam KC, Tamir NM, Tanaka A, Tanaka J, Tanaka R, Tanasini M, Tao Z, Araya ST, Tapprogge S, Mohamed ATA, Tarem S, Tariq K, Tarna G, Tartarelli GF, Tas P, Tasevsky M, Tassi E, Tate AC, Tateno G, Tayalati Y, Taylor GN, Taylor W, Tee AS, De Lima RT, Teixeira-Dias P, Teoh JJ, Terashi K, Terron J, Terzo S, Testa M, Teuscher RJ, Thaler A, Theiner O, Themistokleous N, Theveneaux-Pelzer T, Thielmann O, Thomas DW, Thomas JP, Thompson EA, Thompson PD, Thomson E, Tian Y, Tikhomirov V, Tikhonov YA, Timoshenko S, Timoshyn D, Ting EXL, Tipton P, Tlou SH, Tnourji A, Todome K, Todorova-Nova S, Todt S, Togawa M, Tojo J, Tokár S, Tokushuku K, Toldaiev O, Tombs R, Tomoto M, Tompkins L, Topolnicki KW, Torrence E, Torres H, Pastor ET, Toscani M, Tosciri C, Tost M, Tovey DR, Traeet A, Trandafir IS, Trefzger T, Tricoli A, Trigger IM, Trincaz-Duvoid S, Trischuk DA, Trocmé B, Troncon C, Truong L, Trzebinski M, Trzupek A, Tsai F, Tsai M, Tsiamis A, Tsiareshka PV, Tsigaridas S, Tsirigotis A, Tsiskaridze V, Tskhadadze EG, Tsopoulou M, Tsujikawa Y, Tsukerman II, Tsulaia V, Tsuno S, Tsuri K, Tsybychev D, Tu Y, Tudorache A, Tudorache V, Tuna AN, Turchikhin S, Cakir IT, Turra R, Turtuvshin T, Tuts PM, Tzamarias S, Tzanis P, Tzovara E, Ukegawa F, Poblete PAU, Umaka EN, Unal G, Unal M, Undrus A, Unel G, Urban J, Urquijo P, Urrejola P, Usai G, Ushioda R, Usman M, Uysal Z, Vacek V, Vachon B, Vadla KOH, Vafeiadis T, Vaitkus A, Valderanis C, Santurio EV, Valente M, Valentinetti S, Valero A, Moreno EV, Vallier A, Ferrer JAV, Van Arneman DR, Van Daalen TR, Van Der Graaf A, Van Gemmeren P, Van Rijnbach M, Van Stroud S, Van Vulpen I, Vanadia M, Vandelli W, Vandewall ER, Vannicola D, Vannoli L, Vari R, Varnes EW, Varni C, Varol T, Varouchas D, Varriale L, Varvell KE, Vasile ME, Vaslin L, Vasquez GA, Vasyukov A, Vazeille F, Schroeder TV, Veatch J, Vecchio V, Veen MJ, Veliscek I, Veloce LM, Veloso F, Veneziano S, Ventura A, Gonzalez SV, Verbytskyi A, Verducci M, Vergis C, De Araujo MV, Verkerke W, Vermeulen JC, Vernieri C, Vessella M, Vetterli MC, Vgenopoulos A, Maira NV, Vickey T, Boeriu OEV, Viehhauser GHA, Vigani L, Villa M, Perez MV, Villhauer EM, Vilucchi E, Vincter MG, Virdee GS, Vishwakarma A, Visibile A, Vittori C, Vivarelli I, Voevodina E, Vogel F, Voigt JC, Vokac P, Volkotrub Y, Von Ahnen J, Von Toerne E, Vormwald B, Vorobel V, Vorobev K, Vos M, Voss K, Vozak M, Vozdecky L, Vranjes N, Milosavljevic MV, Vreeswijk M, Vu NK, Vuillermet R, Vujinovic O, Vukotic I, Wada S, Wagner C, Wagner JM, Wagner W, Wahdan S, Wahlberg H, Wakida M, Walder J, Walker R, 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Xiang J, Xie M, Xie X, Xin S, Xiong A, Xiong J, Xu D, Xu H, Xu L, Xu R, Xu T, Xu Y, Xu Z, Xu Z, Yabsley B, Yacoob S, Yamaguchi Y, Yamashita E, Yamauchi H, Yamazaki T, Yamazaki Y, Yan J, Yan S, Yan Z, Yang HJ, Yang HT, Yang S, Yang T, Yang X, Yang X, Yang Y, Yang Y, Yang Z, Yao WM, Ye H, Ye H, Ye J, Ye S, Ye X, Yeh Y, Yeletskikh I, Yeo B, Yexley MR, Yin P, Yorita K, Younas S, Young CJS, Young C, Yu C, Yu Y, Yuan M, Yuan R, Yue L, Zaazoua M, Zabinski B, Zaid E, Zak ZK, Zakareishvili T, Zakharchuk N, Zambito S, Saa JAZ, Zang J, Zanzi D, Zaplatilek O, Zeitnitz C, Zeng H, Zeng JC, Zenger DT, Zenin O, Ženiš T, Zenz S, Zerradi S, Zerwas D, Zhai M, Zhang DF, Zhang J, Zhang J, Zhang K, Zhang L, Zhang P, Zhang R, Zhang S, Zhang S, Zhang T, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhang Z, Zhao H, Zhao T, Zhao Y, Zhao Z, Zhemchugov A, Zheng J, Zheng K, Zheng X, Zheng Z, Zhong D, Zhou B, Zhou H, Zhou N, Zhou Y, Zhou Y, Zhu CG, Zhu J, Zhu Y, Zhu Y, Zhuang X, Zhukov K, Zimine NI, Zinsser J, Ziolkowski M, Živković L, Zoccoli A, Zoch K, Zorbas TG, Zormpa O, Zou W, Zwalinski L. Observation of quantum entanglement with top quarks at the ATLAS detector. Nature 2024; 633:542-547. [PMID: 39294352 PMCID: PMC11410654 DOI: 10.1038/s41586-024-07824-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 07/12/2024] [Indexed: 09/20/2024]
Abstract
Entanglement is a key feature of quantum mechanics1-3, with applications in fields such as metrology, cryptography, quantum information and quantum computation4-8. It has been observed in a wide variety of systems and length scales, ranging from the microscopic9-13 to the macroscopic14-16. However, entanglement remains largely unexplored at the highest accessible energy scales. Here we report the highest-energy observation of entanglement, in top-antitop quark events produced at the Large Hadron Collider, using a proton-proton collision dataset with a centre-of-mass energy of √s = 13 TeV and an integrated luminosity of 140 inverse femtobarns (fb)-1 recorded with the ATLAS experiment. Spin entanglement is detected from the measurement of a single observable D, inferred from the angle between the charged leptons in their parent top- and antitop-quark rest frames. The observable is measured in a narrow interval around the top-antitop quark production threshold, at which the entanglement detection is expected to be significant. It is reported in a fiducial phase space defined with stable particles to minimize the uncertainties that stem from the limitations of the Monte Carlo event generators and the parton shower model in modelling top-quark pair production. The entanglement marker is measured to be D = -0.537 ± 0.002 (stat.) ± 0.019 (syst.) for 340 GeV < m t t ¯ < 380 GeV . The observed result is more than five standard deviations from a scenario without entanglement and hence constitutes the first observation of entanglement in a pair of quarks and the highest-energy observation of entanglement so far.
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Dai JY, Li SQ, Jia X, Wu MY, Song B, Li JY, Guo Y, Gao R. Expression patterns of interleukin-6 and microRNA-146A during orthodontic relapse in a rat model. JOURNAL OF PHYSIOLOGY AND PHARMACOLOGY : AN OFFICIAL JOURNAL OF THE POLISH PHYSIOLOGICAL SOCIETY 2024; 75. [PMID: 39415530 DOI: 10.26402/jpp.2024.4.10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Accepted: 06/30/2024] [Indexed: 10/18/2024]
Abstract
In this study, we established an experimental rat model to simulate orthodontic tooth movement relapse and a human periodontal ligament stem cell (PDLScs) model. Our aim was to explore the relationship between microRNA-146a (miR-146a) expression in periodontal tissue, the inflammatory factor interleukin-6 (IL-6), and orthodontic relapse subsequent to mechanical intervention. In the animal experiment, a total of 30 healthy male Wistar rats were randomly allocated to either the control group (n=6) or the model group (n=24). In the model group, the orthodontic appliance was removed 14 days after force application. Gingival crevicular fluid (GcF) and periodontal tissue samples were collected at intervals of days 0, 7, 14, and 21 following removal of the orthodontic appliance to assess alterations in miR-146a and IL-6 expressions. In the in vitro cell culture study, human premolar tooth tissue was isolated 24 hours following the addition of the transfection reagent to harvest PDLScs. Reverse transcription quantitative polymerase chain reaction was employed to evaluate the expression levels of the miRNA-146a gene, while Western blot analysis was utilized to assess the production of the IL-6 protein. As a result in comparison to the control group, the protein expression of IL-6 notably escalated to its peak value in the model-day 7 group (p<0.05). Subsequently, although experiencing a slight decline, the IL-6 expression in the model-day 14 group remained significantly elevated compared to control group (p<0.05). In the model-day 21 group, the protein expression of IL-6 approached that of the control group, with no significant difference observed (p>0.05). conversely, in relation to the control group, the gene expression of miR-146a drastically decreased to its lowest point in the model-day 7 group (p<0.05). While exhibiting a slight increase, the miR-146a expression in the model-day 14 group remained significantly diminished compared to control group (p<0.05). Following the identification of human periodontal ligament cells (hPDLcs) through immunofluorescence in the in vitro study, a subsequent experiment was conducted to specifically inhibit miR-146a expression. In comparison to the control group, the protein expression of IL-6 demonstrated a significant increase in the anti-miRNA oligodeoxyribonucleotide (AMO) group, where miR-146a expression was effectively suppressed (p<0.05). Throughout the process of orthodontic tooth movement relapse in rats, there was a notable reduction in the gene expression of miR-146a, accompanied by a significant increase in the expression of IL-6.
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Podszus B, Pham J, Dopson E, Trivedi S, Yu V, Guo Y. "A National Review of Crowdfunding for Plagiocephaly Helmets". Cleft Palate Craniofac J 2024:10556656241256728. [PMID: 39051559 DOI: 10.1177/10556656241256728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2024] Open
Abstract
OBJECTIVE Custom prescription helmets for plagiocephaly may be a significant financial burden for families, especially when not covered by insurance. This study aims to identify factors that influence the success of crowdsourcing campaigns for this therapy. DESIGN GoFundMe campaigns were collected by searching terms such as "plagiocephaly" and "baby helmet." Two reviewers analyzed each campaign for variables, including demographic data, story elements, and photo characteristics. Univariate logistic regression was used to determine each variable's impact on success, defined as attaining ≥75% of a campaign goal and significance of p ≤ 0.05. RESULTS Campaign data from 2011 to 2022 were analyzed. Initial search yielded 1464 campaigns; among these 413 met final inclusion criteria. On average, campaigns raised $2005 (range: $0-$7799) and requested $3151 (range: $160-$30,000). In total, 228 (54%) achieved success, 167 (40%) met their goal, and 35 (8%) raised no funds. A total of $828,256 was raised from the requested $1,301,317. The average reported age was six months (range: 2-17 m). Significant factors associated with success were military affiliation, providing multiple images, including a quoted cost, providing campaign updates, indicating a sense of urgency, diagnosis of torticollis, and mentioning possible complications without treatment. Raising additional funds for therapy, multiple helmets, and unrelated medical costs negatively impacted success. Racial disparities were observed between campaigns. Additionally, regional differences were noted between campaigns. CONCLUSIONS Crowdsourcing can be a successful endeavor for some families experiencing financial hardships from helmet therapy. This study highlights current gaps within healthcare coverage for helmet treatment and identifies various factors influencing crowdfunding campaigns.
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Contenti J, Guo Y, Larcher M, Mirabal-Ortega L, Rouleau M, Irondelle M, Tiroille V, Mazzu A, Duranton-Tanneur V, Pedeutour F, Ben-Sahra I, Lago C, Leva G, Tiberi L, Robert G, Pouponnot C, Bost F, Mazure NM. HIF-1 inactivation empowers HIF-2 to drive hypoxia adaptation in aggressive forms of medulloblastoma. Cell Death Discov 2024; 10:338. [PMID: 39048564 PMCID: PMC11269614 DOI: 10.1038/s41420-024-02100-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 07/01/2024] [Accepted: 07/12/2024] [Indexed: 07/27/2024] Open
Abstract
Medulloblastoma (MB) is the most prevalent brain cancer in children. Four subgroups of MB have been identified; of these, Group 3 is the most metastatic. Its genetics and biology remain less clear than the other groups, and it has a poor prognosis and few effective treatments available. Tumor hypoxia and the resulting metabolism are known to be important in the growth and survival of tumors but, to date, have been only minimally explored in MB. Here we show that Group 3 MB tumors do not depend on the canonical transcription factor hypoxia-inducible factor-1α (HIF-1α) to mount an adaptive response to hypoxia. We discovered that HIF-1α is rendered inactive either through post-translational methylation, preventing its nuclear localization specifically in Group 3 MB, or by a low expression that prevents modulation of HIF-target genes. Strikingly, we found that HIF-2 takes over the role of HIF-1 in the nucleus and promotes the activation of hypoxia-dependent anabolic pathways. The exclusion of HIF-1 from the nucleus in Group 3 MB cells enhances the reliance on HIF-2's transcriptional role, making it a viable target for potential anticancer strategies. By combining pharmacological inhibition of HIF-2α with the use of metformin, a mitochondrial complex I inhibitor to block respiration, we effectively induced Group 3 MB cell death, surpassing the effectiveness observed in Non-Group 3 MB cells. Overall, the unique dependence of MB cells, but not normal cells, on HIF-2-mediated anabolic metabolism presents an appealing therapeutic opportunity for treating Group 3 MB patients with minimal toxicity.
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Aad G, Abbott B, Abeling K, Abicht NJ, Abidi SH, Aboulhorma A, Abramowicz H, Abreu H, Abulaiti Y, Acharya BS, Adam Bourdarios C, Adamczyk L, Addepalli SV, Addison MJ, Adelman J, Adiguzel A, Adye T, Affolder AA, Afik Y, Agaras MN, Agarwala J, Aggarwal A, Agheorghiesei C, Ahmad A, Ahmadov F, Ahmed WS, Ahuja S, Ai X, Aielli G, Aikot A, Ait Tamlihat M, Aitbenchikh B, Aizenberg I, Akbiyik M, Åkesson TPA, Akimov AV, Akiyama D, Akolkar NN, Aktas S, Al Khoury K, Alberghi GL, Albert J, Albicocco P, Albouy GL, Alderweireldt S, Alegria ZL, Aleksa M, Aleksandrov IN, Alexa C, Alexopoulos T, Alfonsi F, Algren M, Alhroob M, Ali B, Ali HMJ, Ali S, Alibocus SW, Aliev M, Alimonti G, Alkakhi W, Allaire C, Allbrooke BMM, Allen JF, Allendes Flores CA, Allport PP, Aloisio A, Alonso F, Alpigiani C, Alvarez Estevez M, Alvarez Fernandez A, Alves Cardoso M, Alviggi MG, Aly M, Amaral Coutinho Y, Ambler A, Amelung C, Amerl M, Ames CG, Amidei D, Amor Dos Santos SP, Amos KR, Ananiev V, Anastopoulos C, Andeen T, Anders JK, Andrean SY, Andreazza A, Angelidakis S, Angerami A, Anisenkov AV, Annovi A, Antel C, Anthony MT, Antipov E, Antonelli M, Anulli F, Aoki M, Aoki T, Aparisi Pozo JA, Aparo MA, Aperio Bella L, Appelt C, Apyan A, Aranzabal N, Arbiol Val SJ, Arcangeletti C, Arce ATH, Arena E, Arguin JF, Argyropoulos S, Arling JH, Arnaez O, Arnold H, Artoni G, Asada H, Asai K, Asai S, Asbah NA, Assamagan K, Astalos R, Atashi S, Atkin RJ, Atkinson M, Atmani H, Atmasiddha PA, Augsten K, Auricchio S, Auriol AD, Austrup VA, Avolio G, Axiotis K, Azuelos G, Babal D, Bachacou H, Bachas K, Bachiu A, Backman F, Badea A, Baer TM, Bagnaia P, Bahmani M, Bahner D, Bailey AJ, Bailey VR, Baines JT, Baines L, Baker OK, Bakos E, Bakshi Gupta D, Balakrishnan V, Balasubramanian R, Baldin EM, Balek P, Ballabene E, Balli F, Baltes LM, Balunas WK, Balz J, Banas E, Bandieramonte M, Bandyopadhyay A, Bansal S, Barak L, Barakat M, Barberio EL, Barberis D, Barbero M, Barel MZ, Barends KN, Barillari T, Barisits MS, Barklow T, Baron P, Baron Moreno DA, Baroncelli A, Barone G, Barr AJ, Barr JD, Barranco Navarro L, Barreiro F, Barreiro Guimarães da Costa J, Barron U, Barros Teixeira MG, Barsov S, Bartels F, Bartoldus R, Barton AE, Bartos P, Basan A, Baselga M, Bassalat A, Basso MJ, Basson CR, Bates RL, Batlamous S, Batley JR, Batool B, Battaglia M, Battulga D, Bauce M, Bauer M, Bauer P, Bazzano Hurrell LT, Beacham JB, Beau T, Beaucamp JY, Beauchemin PH, Becherer F, Bechtle P, Beck HP, Becker K, Beddall AJ, Bednyakov VA, Bee CP, Beemster LJ, Beermann TA, Begalli M, Begel M, Behera A, Behr JK, Beirer JF, Beisiegel F, Belfkir M, Bella G, Bellagamba L, Bellerive A, Bellos P, Beloborodov K, Benchekroun D, Bendebba F, Benhammou Y, Benoit M, Bensinger JR, Bentvelsen S, Beresford L, Beretta M, Bergeaas Kuutmann E, Berger N, Bergmann B, Beringer J, Bernardi G, Bernius C, Bernlochner FU, Bernon F, Berrocal Guardia A, Berry T, Berta P, Berthold A, Bertram IA, Bethke S, Betti A, Bevan AJ, Bhalla NK, Bhamjee M, Bhatta S, Bhattacharya DS, Bhattarai P, Bhopatkar VS, Bi R, Bianchi RM, Bianco G, Biebel O, Bielski R, Biglietti M, Bindi M, Bingul A, Bini C, Biondini A, Birch-Sykes CJ, Bird GA, Birman M, Biros M, Biryukov S, Bisanz T, Bisceglie E, Biswal JP, Biswas D, Bitadze A, Bjørke K, Bloch I, Blue A, Blumenschein U, Blumenthal J, Bobbink GJ, Bobrovnikov VS, Boehler M, Boehm B, Bogavac D, Bogdanchikov AG, Bohm C, Boisvert V, Bokan P, Bold T, Bomben M, Bona M, Boonekamp M, Booth CD, Borbély AG, Bordulev IS, Borecka-Bielska HM, Borissov G, Bortoletto D, Boscherini D, Bosman M, Bossio Sola JD, Bouaouda K, Bouchhar N, Boudreau J, Bouhova-Thacker EV, Boumediene D, Bouquet R, Boveia A, Boyd J, Boye D, Boyko IR, Bracinik J, Brahimi N, Brandt G, Brandt O, Braren F, Brau B, Brau JE, Brener R, Brenner L, Brenner R, Bressler S, Britton D, Britzger D, Brock I, Brooijmans G, Brooks WK, Brost E, Brown LM, Bruce LE, Bruckler TL, Bruckman de Renstrom PA, Brüers B, Bruni A, Bruni G, Bruschi M, Bruscino N, Buanes T, 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PR, Ng CW, Ng YWY, Ngair B, Nguyen HDN, Nickerson RB, Nicolaidou R, Nielsen J, Niemeyer M, Niermann J, Nikiforou N, Nikolaenko V, Nikolic-Audit I, Nikolopoulos K, Nilsson P, Ninca I, Nindhito HR, Ninio G, Nisati A, Nishu N, Nisius R, Nitschke JE, Nkadimeng EK, Nobe T, Noel DL, Nommensen T, Norfolk MB, Norisam RRB, Norman BJ, Noury M, Novak J, Novak T, Novotny L, Novotny R, Nozka L, Ntekas K, Nunes De Moura Junior NMJ, Nurse E, Ocariz J, Ochi A, Ochoa I, Oerdek S, Offermann JT, Ogrodnik A, Oh A, Ohm CC, Oide H, Oishi R, Ojeda ML, O'Keefe MW, Okumura Y, Seabra LFO, Olivares Pino SA, Oliveira Damazio D, Oliveira Goncalves D, Oliver JL, Öncel ÖO, O'Neill AP, Onofre A, Onyisi PUE, Oreglia MJ, Orellana GE, Orestano D, Orlando N, Orr RS, O'Shea V, Osojnak LM, Ospanov R, Otero Y Garzon G, Otono H, Ott PS, Ottino GJ, Ouchrif M, Ouellette J, Ould-Saada F, Owen M, Owen RE, Oyulmaz KY, Ozcan VE, Ozturk F, Ozturk N, Ozturk S, Pacey HA, Pacheco Pages A, Padilla Aranda C, Padovano G, Pagan Griso S, Palacino G, Palazzo A, Palestini S, Pan J, Pan T, Panchal DK, Pandini CE, Panduro Vazquez JG, Pandya HD, Pang H, Pani P, Panizzo G, Paolozzi L, Papadatos C, Parajuli S, Paramonov A, Paraskevopoulos C, Paredes Hernandez D, Park KR, Park TH, Parker MA, Parodi F, Parrish EW, Parrish VA, Parsons JA, Parzefall U, Pascual Dias B, Pascual Dominguez L, Pasqualucci E, Passaggio S, Pastore F, Pasuwan P, Patel P, Patel UM, Pater JR, Pauly T, Pearkes J, Pedersen M, Pedro R, Peleganchuk SV, Penc O, Pender EA, Penski KE, Penzin M, Peralva BS, Peixoto APP, Pereira Sanchez L, Perepelitsa DV, Perez Codina E, Perganti M, Perini L, Pernegger H, Perrin O, Peters K, Peters RFY, Petersen BA, Petersen TC, Petit E, Petousis V, Petridou C, Petrukhin A, Pettee M, Pettersson NE, Petukhov A, Petukhova K, Pezoa R, Pezzotti L, Pezzullo G, Pham TM, Pham T, Phillips PW, Piacquadio G, Pianori E, Piazza F, Piegaia R, Pietreanu D, Pilkington AD, Pinamonti M, Pinfold JL, Pereira BCP, Pinto Pinoargote AE, Pintucci L, Piper KM, Pirttikoski A, Pizzi DA, Pizzimento L, Pizzini A, Pleier MA, Plesanovs V, Pleskot V, Plotnikova E, Poddar G, Poettgen R, Poggioli L, Pokharel I, Polacek S, Polesello G, Poley A, Polifka R, Polini A, Pollard CS, Pollock ZB, Polychronakos V, Pompa Pacchi E, Ponomarenko D, Pontecorvo L, Popa S, Popeneciu GA, Poreba A, Portillo Quintero DM, Pospisil S, Postill MA, Postolache P, Potamianos K, Potepa PA, Potrap IN, Potter CJ, Potti H, Poulsen T, Poveda J, Pozo Astigarraga ME, Prades Ibanez A, Pretel J, Price D, Primavera M, Principe Martin MA, Privara R, Procter T, Proffitt ML, Proklova N, Prokofiev K, Proto G, Protopopescu S, Proudfoot J, Przybycien M, Przygoda WW, Puddefoot JE, Pudzha D, Pyatiizbyantseva D, Qian J, Qichen D, Qin Y, Qiu T, Quadt A, Queitsch-Maitland M, Quetant G, Quinn RP, Rabanal Bolanos G, Rafanoharana D, Ragusa F, Rainbolt JL, Raine JA, Rajagopalan S, Ramakoti E, Ramirez-Berend IA, Ran K, Rapheeha NP, Rasheed H, Raskina V, Rassloff DF, Rastogi A, Rave S, Ravina B, Ravinovich I, Raymond M, Read AL, Readioff NP, Rebuzzi DM, Redlinger G, Reed AS, Reeves K, Reidelsturz JA, Reikher D, Rej A, Rembser C, Renardi A, Renda M, Rendel MB, Renner F, Rennie AG, Rescia AL, Resconi S, Ressegotti M, Rettie S, Reyes Rivera JG, Reynolds E, Rezanova OL, Reznicek P, Ribaric N, Ricci E, Richter R, Richter S, Richter-Was E, Ridel M, Ridouani S, Rieck P, Riedler P, Riefel EM, Rieger JO, Rijssenbeek M, Rimoldi A, Rimoldi M, Rinaldi L, Rinn TT, Rinnagel MP, Ripellino G, Riu I, Rivadeneira P, Rivera Vergara JC, Rizatdinova F, Rizvi E, Roberts BA, Roberts BR, Robertson SH, Robinson D, Robles Gajardo CM, Robles Manzano M, Robson A, Rocchi A, Roda C, Rodriguez Bosca S, Rodriguez Garcia Y, Rodriguez Rodriguez A, Rodríguez Vera AM, Roe S, Roemer JT, Roepe-Gier AR, Roggel J, Røhne O, Rojas RA, Roland CPA, Roloff J, Romaniouk A, Romano E, Romano M, Romero Hernandez AC, Rompotis N, Roos L, Rosati S, Rosser BJ, Rossi E, Rossi E, Rossi LP, Rossini L, Rosten R, Rotaru M, Rottler B, Rougier C, Rousseau D, Rousso D, Roy A, Roy-Garand S, Rozanov A, Rozario ZMA, Rozen Y, Ruan X, Rubio Jimenez A, Ruby AJ, Ruelas Rivera VH, Ruggeri TA, Ruggiero A, Ruiz-Martinez A, Rummler A, Rurikova Z, Rusakovich NA, Russell HL, Russo G, Rutherfoord JP, Rutherford Colmenares S, Rybacki K, Rybar M, Rye EB, Ryzhov A, Sabater Iglesias JA, Sabatini P, Sadrozinski HFW, Safai Tehrani F, Safarzadeh Samani B, Safdari M, Saha S, Sahinsoy M, Saibel A, Saimpert M, Saito M, Saito T, Salamani D, Salnikov A, Salt J, Salvador Salas A, Salvatore D, Salvatore F, Salzburger A, Sammel D, Sampsonidis D, Sampsonidou D, Sánchez J, Sanchez Pineda A, Sanchez Sebastian V, Sandaker H, Sander CO, Sandesara JA, Sandhoff M, Sandoval C, Sankey DPC, Sano T, Sansoni A, Santi L, Santoni C, Santos H, Santpur SN, Santra A, Saoucha KA, Saraiva JG, Sardain J, Sasaki O, Sato K, Sauer C, Sauerburger F, Sauvan E, Savard P, Sawada R, Sawyer C, Sawyer L, Sayago Galvan I, Sbarra C, Sbrizzi A, Scanlon T, Schaarschmidt J, Schacht P, Schäfer U, Schaffer AC, Schaile D, Schamberger RD, Scharf C, Schefer MM, Schegelsky VA, Scheirich D, Schenck F, Schernau M, Scheulen C, Schiavi C, Schioppa EJ, Schioppa M, Schlag B, Schleicher KE, Schlenker S, Schmeing J, Schmidt MA, Schmieden K, Schmitt C, Schmitt N, Schmitt S, Schoeffel L, Schoening A, Scholer PG, Schopf E, Schott M, Schovancova J, Schramm S, Schroeder F, Schroer T, Schultz-Coulon HC, Schumacher M, Schumm BA, Schune P, Schuy AJ, Schwartz HR, Schwartzman A, Schwarz TA, Schwemling P, Schwienhorst R, Sciandra A, Sciolla G, Scuri F, Sebastiani CD, Sedlaczek K, Seema P, Seidel SC, Seiden A, Seidlitz BD, Seitz C, Seixas JM, Sekhniaidze G, Sekula SJ, Selem L, Semprini-Cesari N, Sengupta D, Senthilkumar V, Serin L, Serkin L, Sessa M, Severini H, Sforza F, Sfyrla A, Shabalina E, Shaheen R, Shahinian JD, Shaked Renous D, Shan LY, Shapiro M, Sharma A, Sharma AS, Sharma P, Sharma S, Shatalov PB, Shaw K, Shaw SM, Shcherbakova A, Shen Q, Sheppard DJ, Sherwood P, Shi L, Shi X, Shimmin CO, Shinner JD, Shipsey IPJ, Shirabe S, Shiyakova M, Shlomi J, Shochet MJ, Shojaii J, Shope DR, Shrestha B, Shrestha S, Shrif EM, Shroff MJ, Sicho P, Sickles AM, Sideras Haddad E, Sidoti A, Siegert F, Sijacki D, Sili F, Silva JM, Silva Oliveira MV, Silverstein SB, Simion S, Simoniello R, Simpson EL, Simpson H, Simpson LR, Simpson ND, Simsek S, Sindhu S, Sinervo P, Singh S, Sinha S, Sinha S, Sioli M, Siral I, Sitnikova E, Sivoklokov SY, Sjölin J, Skaf A, Skorda E, Skubic P, Slawinska M, Smakhtin V, Smart BH, Smiesko J, Smirnov SY, Smirnov Y, Smirnova LN, Smirnova O, Smith AC, Smith EA, Smith HA, Smith JL, Smith R, Smizanska M, Smolek K, Snesarev AA, Snider SR, Snoek HL, Snyder S, Sobie R, Soffer A, Solans Sanchez CA, Soldatov EY, Soldevila U, Solodkov AA, Solomon S, Soloshenko A, Solovieva K, Solovyanov OV, Solovyev V, Sommer P, Sonay A, Song WY, Sonneveld JM, Sopczak A, Sopio AL, Sopkova F, Sotarriva Alvarez IR, Sothilingam V, Soto Sandoval OJ, Sottocornola S, Soualah R, Soumaimi Z, South D, Soybelman N, Spagnolo S, Spalla M, Sperlich D, Spigo G, Spinali S, Spiteri DP, Spousta M, Staats EJ, Stabile A, Stamen R, Stampekis A, Standke M, Stanecka E, Stange MV, Stanislaus B, Stanitzki MM, Stapf B, Starchenko EA, Stark GH, Stark J, Starko DM, Staroba P, Starovoitov P, Stärz S, Staszewski R, Stavropoulos G, Steentoft J, Steinberg P, Stelzer B, Stelzer HJ, Stelzer-Chilton O, Stenzel H, Stevenson TJ, Stewart GA, Stewart JR, Stockton MC, Stoicea G, Stolarski M, Stonjek S, Straessner A, Strandberg J, Strandberg S, Stratmann M, Strauss M, Strebler T, Strizenec P, Ströhmer R, Strom DM, Stroynowski R, Strubig A, Stucci SA, Stugu B, Stupak J, Styles NA, Su D, Su S, Su W, Su X, Sugizaki K, Sulin VV, Sullivan MJ, Sultan DMS, Sultanaliyeva L, Sultansoy S, Sumida T, Sun S, Sun S, Gudnadottir OS, Sur N, Sutton MR, Suzuki H, Svatos M, Swiatlowski M, Swirski T, Sykora I, Sykora M, Sykora T, Ta D, Tackmann K, Taffard A, Tafirout R, Tafoya Vargas JS, Takeva EP, Takubo Y, Talby M, Talyshev AA, Tam KC, Tamir NM, Tanaka A, Tanaka J, Tanaka R, Tanasini M, Tao Z, Tapia Araya S, Tapprogge S, Tarek Abouelfadl Mohamed A, Tarem S, Tariq K, Tarna G, Tartarelli GF, Tas P, Tasevsky M, Tassi E, Tate AC, Tateno G, Tayalati Y, Taylor GN, Taylor W, Tee AS, Teixeira De Lima R, Teixeira-Dias P, Teoh JJ, Terashi K, Terron J, Terzo S, Testa M, Teuscher RJ, Thaler A, Theiner O, Themistokleous N, Theveneaux-Pelzer T, Thielmann O, Thomas DW, Thomas JP, Thompson EA, Thompson PD, Thomson E, Tian Y, Tikhomirov V, Tikhonov YA, Timoshenko S, Timoshyn D, Ting EXL, Tipton P, Tlou SH, Tnourji A, Todome K, Todorova-Nova S, Todt S, Togawa M, Tojo J, Tokár S, Tokushuku K, Toldaiev O, Tombs R, Tomoto M, Tompkins L, Topolnicki KW, Torrence E, Torres H, Torró Pastor E, Toscani M, Tosciri C, Tost M, Tovey DR, Traeet A, Trandafir IS, Trefzger T, Tricoli A, Trigger IM, Trincaz-Duvoid S, Trischuk DA, Trocmé B, Troncon C, Truong L, Trzebinski M, Trzupek A, Tsai F, Tsai M, Tsiamis A, Tsiareshka PV, Tsigaridas S, Tsirigotis A, Tsiskaridze V, Tskhadadze EG, Tsopoulou M, Tsujikawa Y, Tsukerman II, Tsulaia V, Tsuno S, Tsuri K, Tsybychev D, Tu Y, Tudorache A, Tudorache V, Tuna AN, Turchikhin S, Turk Cakir I, Turra R, Turtuvshin T, Tuts PM, Tzamarias S, Tzanis P, Tzovara E, Ukegawa F, Ulloa Poblete PA, Umaka EN, Unal G, Unal M, Undrus A, Unel G, Urban J, Urquijo P, Urrejola P, Usai G, Ushioda R, Usman M, Uysal Z, Vacek V, Vachon B, Vadla KOH, Vafeiadis T, Vaitkus A, Valderanis C, Valdes Santurio E, Valente M, Valentinetti S, Valero A, Valiente Moreno E, Vallier A, Valls Ferrer JA, Van Arneman DR, Van Daalen TR, Van Der Graaf A, Van Gemmeren P, Van Rijnbach M, Van Stroud S, Van Vulpen I, Vanadia M, Vandelli W, Vandenbroucke M, Vandewall ER, Vannicola D, Vannoli L, Vari R, Varnes EW, Varni C, Varol T, Varouchas D, Varriale L, Varvell KE, Vasile ME, Vaslin L, Vasquez GA, Vasyukov A, Vazeille F, Vazquez Schroeder T, Veatch J, Vecchio V, Veen MJ, Veliscek I, Veloce LM, Veloso F, Veneziano S, Ventura A, Ventura Gonzalez S, Verbytskyi A, Verducci M, Vergis C, Verissimo De Araujo M, Verkerke W, Vermeulen JC, Vernieri C, Vessella M, Vetterli MC, Vgenopoulos A, Viaux Maira N, Vickey T, Vickey Boeriu OE, Viehhauser GHA, Vigani L, Villa M, Villaplana Perez M, Villhauer EM, Vilucchi E, Vincter MG, Virdee GS, Vishwakarma A, Visibile A, Vittori C, Vivarelli I, Voevodina E, Vogel F, Voigt JC, Vokac P, Volkotrub Y, Von Ahnen J, Von Toerne E, Vormwald B, Vorobel V, Vorobev K, Vos M, Voss K, Vossebeld JH, Vozak M, Vozdecky L, Vranjes N, Vranjes Milosavljevic M, Vreeswijk M, Vuillermet R, Vujinovic O, Vukotic I, Wada S, Wagner C, Wagner JM, Wagner W, Wahdan S, Wahlberg H, Wakida M, Walder J, Walker R, Walkowiak W, Wall A, Wamorkar T, Wang AZ, Wang C, Wang C, Wang H, Wang J, Wang RJ, Wang R, Wang R, Wang SM, Wang S, Wang T, Wang WT, Wang W, Wang X, Wang X, Wang X, Wang Y, Wang Y, Wang Z, Wang Z, Wang Z, Warburton A, Ward RJ, Warrack N, Watson AT, Watson H, Watson MF, Watton E, Watts G, Waugh BM, Weber C, Weber HA, Weber MS, Weber SM, Wei C, Wei Y, Weidberg AR, Weik EJ, Weingarten J, Weirich M, Weiser C, Wells CJ, Wenaus T, Wendland B, Wengler T, Wenke NS, Wermes N, Wessels M, Wharton AM, White AS, White A, White MJ, Whiteson D, Wickremasinghe L, Wiedenmann W, Wiel C, Wielers M, Wiglesworth C, Wilbern DJ, Wilkens HG, Williams DM, Williams HH, Williams S, Willocq S, Wilson BJ, Windischhofer PJ, Winkel FI, Winklmeier F, Winter BT, Winter JK, Wittgen M, Wobisch M, Wolffs Z, Wollrath J, Wolter MW, Wolters H, Wongel AF, Woodward EL, Worm SD, Wosiek BK, Woźniak KW, Wozniewski S, Wraight K, Wu C, Wu J, Wu M, Wu M, Wu SL, Wu X, Wu Y, Wu Z, Wuerzinger J, Wyatt TR, Wynne BM, Xella S, Xia L, Xia M, Xiang J, Xie M, Xie X, Xin S, Xiong A, Xiong J, Xu D, Xu H, Xu L, Xu R, Xu T, Xu Y, Xu Z, Xu Z, Yabsley B, Yacoob S, Yamaguchi Y, Yamashita E, Yamauchi H, Yamazaki T, Yamazaki Y, Yan J, Yan S, Yan Z, Yang HJ, Yang HT, Yang S, Yang T, Yang X, Yang X, Yang Y, Yang Y, Yang Z, Yao WM, Yap YC, Ye H, Ye H, Ye J, Ye S, Ye X, Yeh Y, Yeletskikh I, Yeo BK, Yexley MR, Yin P, Yorita K, Younas S, Young CJS, Young C, Yu C, Yu Y, Yuan M, Yuan R, Yue L, Zaazoua M, Zabinski B, Zaid E, Zak ZK, Zakareishvili T, Zakharchuk N, Zambito S, Zamora Saa JA, Zang J, Zanzi D, Zaplatilek O, Zeitnitz C, Zeng H, Zeng JC, Zenger DT, Zenin O, Ženiš T, Zenz S, Zerradi S, Zerwas D, Zhai M, Zhang B, Zhang DF, Zhang J, Zhang J, Zhang K, Zhang L, Zhang P, Zhang R, Zhang S, Zhang S, Zhang T, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhang Z, Zhao H, Zhao T, Zhao Y, Zhao Z, Zhemchugov A, Zheng J, Zheng K, Zheng X, Zheng Z, Zhong D, Zhou B, Zhou H, Zhou N, Zhou Y, Zhu CG, Zhu J, Zhu Y, Zhu Y, Zhuang X, Zhukov K, Zhulanov V, Zimine NI, Zinsser J, Ziolkowski M, Živković L, Zoccoli A, Zoch K, Zorbas TG, Zormpa O, Zou W, Zwalinski L. Statistical Combination of ATLAS Run 2 Searches for Charginos and Neutralinos at the LHC. PHYSICAL REVIEW LETTERS 2024; 133:031802. [PMID: 39094132 DOI: 10.1103/physrevlett.133.031802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 06/07/2024] [Indexed: 08/04/2024]
Abstract
Statistical combinations of searches for charginos and neutralinos using various decay channels are performed using 139 fb^{-1} of pp collision data at sqrt[s]=13 TeV with the ATLAS detector at the Large Hadron Collider. Searches targeting pure-wino chargino pair production, pure-wino chargino-neutralino production, or Higgsino production decaying via standard model W, Z, or h bosons are combined to extend the mass reach to the produced supersymmetric particles by 30-100 GeV. The depth of the sensitivity of the original searches is also improved by the combinations, lowering the 95% C.L. cross-section upper limits by 15%-40%.
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Li XL, Zhao BB, Wan Y, An WB, Liu F, Liu LP, Wang SC, Qi BQ, Liu TF, Liu XM, Ruan M, Zhang L, Zou Y, Chen XJ, Chen YM, Guo Y, Zhu XF, Yang WY. [The safety and efficacy of blinatumomab in the treatment of B-cell acute lymphoblastic leukemia in children]. ZHONGHUA YI XUE ZA ZHI 2024; 104:2563-2567. [PMID: 38978382 DOI: 10.3760/cma.j.cn112137-20240224-00392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
To explore the safety and efficacy of blinatumomab in the treatment of CD19 positive (CD19+) B-cell acute lymphoblastic leukemia (B-ALL) in children. A retrospective analysis was conducted on the clinical data of pediatric B-ALL patients who received blinatumomab treatment from Hematology & Blood Diseases Hospital of Chinese Academy of Medical Sciences from August 2021 to October 2023. Based on their disease status, the patients were divided into refractory/relapsed(RR) group, minimal residual disease clearance (MC) group, and chemotherapy intolerance (IC) group. Clinical data of the children were collected to evaluate the adverse drug reactions, therapeutic efficacy and survival of the children. In total, 35 patients were included, with 20 males and 15 females, aged from 0.6 to 16.4 (9.9±4.2) years old. There were 10 cases in the RR group, 20 cases in the MC group and 5 cases in the IC group. A total of 56 cycles of infusion were completed, with one cycle in 24 cases, two cycles in 5 cases, three cycles in 2 cases and four cycles in 4 cases. The median infusion time [M (Q1, Q3)] from the first to the fourth cycle was 14 (14, 28) days, 28 (28, 28) days, 28 (28, 28) days and 28 (26, 28) days, respectively. In terms of adverse reactions, the incidence of grade 1-2 cytokine release syndrome(CRS) was 57.1% (32/56), with grade 1 CRS accounting for 84.4% (27/32). The incidence rate of immune effector cell-associated neurotoxicity syndrome(ICANS) (grade 4) was 1.8% (1/56). In the RR group, 6 cases were treated effectively, and minimal residual disease(MRD) turned negative, before treatment, MRD levels were all less than 20%. Among them, 3 cases had MRD turning positive again 14 to 42 days after discontinuation of Belintoumab. Four cases were treated ineffectively, with MRD >20% before treatment. All MRD positive cases in MC group turned negative and all MRD negative cases in the IC group remained negative after treatment. The median follow-up time of RR group was 5.7 (3.8, 9.4) months, and 1 year median survival rate and event-free survival rate were 40.0%±21.9% and 33.3%±19.2%, respectively. The median follow-up time for MC and IC group patients was 6.7 (5.2, 12.5) months and 7.1 (5.1, 7.6) months, respectively, with an event free survival rate of 100%. The safety and efficacy of using belintoumab in partial RR, MRD clearance, and chemotherapy intolerance are good.
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Liu CM, Chen YL, Wang XC, Li XL, An WB, Wan Y, Ren YY, Chen X, Liu F, Guo Y, Chen XJ, Zhang L, Zou Y, Chen YM, Li J, Guo XJ, Zhu XF, Yang WY. [Clinical features and prognostic factors of advanced myelodysplastic syndromes in children]. ZHONGHUA YI XUE ZA ZHI 2024; 104:2529-2534. [PMID: 38978377 DOI: 10.3760/cma.j.cn112137-20240102-00011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Objective: To investigate the clinical features and prognostic factors of advanced myelodysplastic syndromes (MDS) in children. Methods: Clinical data of children diagnosed with advanced MDS in the Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, between September 2009 and April 2022 were retrospectively collected. Follow-up assessments were performed through telephone interviews and the review of medical records until May 1, 2023. The clinical features of children with advanced MDS were summarized by analyzing chromosomal karyotype tests, second-generation gene sequencing results. Multivariate Cox regression analysis was used to investigate the prognostic factors of advanced MDS in children. Results: A total of 69 children, comprising 49 males and 20 females, aged [M (Q1, Q3)] 8 (5, 10) years, were enrolled in the study. Sixty-seven cases underwent chromosomal karyotype testing, of which 42 cases (62.7%) had abnormal karyotypes, with monosomy 7 the most common in 17 cases (25.4%). Forty-three cases underwent next-generation sequencing, with mutations in the SETBP1, NRAS, PTPN11 and RUNX1 genes more common, identified in 12 cases (27.9%), 9 cases (20.9%), 8 cases(18.6%), and 8 cases(18.6%), respectively. The follow-up time [M (Q1, Q3)] was 26 (13, 56) months and the 5-year overall survival rate was 56%(95%CI: 44.4%-70.5%). The 5-year overall survival rate for children who underwent hematopoietic stem cell transplantation (HSCT) was higher than that of children who did not undergo HSCT (73.9% vs 29.1%, P<0.001). HSCT (HR=0.118, 95%CI: 0.037-0.372, P<0.001) was a protective factor for the overall survival rate of children with advanced MDS. Serum ferritin level>356.3 μg/L (HR=6.497, 95%CI: 2.068-20.415, P=0.001) and moderate to severe splenomegaly (HR=4.075, 95%CI: 1.174-14.141, P=0.027) were risk factors for the overall survival rate of children with advanced MDS. Conclusions: Monosomy 7 was the most common abnormal karyotype and SETBP1 was the gene that had the highest mutation frequency in children with advanced MDS. HSCT, increased ferritin and moderate to severe splenomegaly are prognostic factors influencing the overall survival rate of children with advanced MDS.
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Song B, Wang K, Na S, Yao J, Fattah FJ, von Itzstein MS, Yang DM, Liu J, Xue Y, Liang C, Guo Y, Raman I, Zhu C, Dowell JE, Homsi J, Rashdan S, Yang S, Gwin ME, Hsiehchen D, Gloria-McCutchen Y, Raj P, Bai X, Wang J, Conejo-Garcia J, Xie Y, Gerber DE, Huang J, Wang T. Cmai: Predicting Antigen-Antibody Interactions from Massive Sequencing Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.27.601035. [PMID: 39005456 PMCID: PMC11244862 DOI: 10.1101/2024.06.27.601035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
The interaction between antigens and antibodies (B cell receptors, BCRs) is the key step underlying the function of the humoral immune system in various biological contexts. The capability to profile the landscape of antigen-binding affinity of a vast number of BCRs will provide a powerful tool to reveal novel insights at unprecedented levels and will yield powerful tools for translational development. However, current experimental approaches for profiling antibody-antigen interactions are costly and time-consuming, and can only achieve low-to-mid throughput. On the other hand, bioinformatics tools in the field of antibody informatics mostly focus on optimization of antibodies given known binding antigens, which is a very different research question and of limited scope. In this work, we developed an innovative Artificial Intelligence tool, Cmai, to address the prediction of the binding between antibodies and antigens that can be scaled to high-throughput sequencing data. Cmai achieved an AUROC of 0.91 in our validation cohort. We devised a biomarker metric based on the output from Cmai applied to high-throughput BCR sequencing data. We found that, during immune-related adverse events (irAEs) caused by immune-checkpoint inhibitor (ICI) treatment, the humoral immunity is preferentially responsive to intracellular antigens from the organs affected by the irAEs. In contrast, extracellular antigens on malignant tumor cells are inducing B cell infiltrations, and the infiltrating B cells have a greater tendency to co-localize with tumor cells expressing these antigens. We further found that the abundance of tumor antigen-targeting antibodies is predictive of ICI treatment response. Overall, Cmai and our biomarker approach filled in a gap that is not addressed by current antibody optimization works nor works such as AlphaFold3 that predict the structures of complexes of proteins that are known to bind.
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Ge Z, Liu X, Jing X, Wang J, Guo Y, Yang H, Cui X. Logistic regression model predicts early surgical site infection after spinal fusion: a retrospective cohort study. J Hosp Infect 2024; 149:65-76. [PMID: 38754784 DOI: 10.1016/j.jhin.2024.04.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 02/27/2024] [Accepted: 04/28/2024] [Indexed: 05/18/2024]
Abstract
OBJECTIVE This study aimed to develop a diagnostic model for predicting early surgical site infection (SSI) based on postoperative inflammatory markers after spinal fusion surgery. METHODS In this retrospective study, we analysed the trends of inflammatory markers between SSI and non-SSI groups. The data were randomly divided into training cohort and validation cohort (ratio 7:3). The variables for SSI were analysed using stepwise logistic regression to develop the prediction model. To evaluate the model, we analysed its sensitivity, specificity, positive predictive value, negative predictive value, as well as the area under the curve in the validation cohort. Calibration plots and decision curve analysis were employed to assess the calibration and clinical usefulness of the model. FINDINGS We observed significant changes in inflammatory markers on the seventh day after surgery. The prediction model included four variables on the seventh day after surgery: body temperature, C-reactive protein, erythrocyte sedimentation rate and neutrophil counts. After binary processing of these data, the simplified model achieved an area under the curve of 0.86 (95% confidence interval (CI): 0.81-0.92) in the training cohort and 0.9 (95% CI: 0.82-0.98) in the validation cohort. Calibration plots and decision curve analysis demonstrated that the proposed model was effective for the diagnosis of SSI. CONCLUSION We developed and validated a prediction model for diagnosing early infection after spinal fusion.
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Duan L, Qu L, Guo Y, Gu W, Lü S, Zhang Y, Zhou X. [Molecular tracing of Biomphalaria straminea in China]. ZHONGGUO XUE XI CHONG BING FANG ZHI ZA ZHI = CHINESE JOURNAL OF SCHISTOSOMIASIS CONTROL 2024; 36:272-278. [PMID: 38952313 DOI: 10.16250/j.32.1374.2024069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/03/2024]
Abstract
OBJECTIVE To investigate the origin of Biomphalaria straminea in China, so as to provide insights into assessment of schistosomiasis mansoni transmission risk and B. straminea control. METHODS Guanlan River, Dasha River, Shenzhen Reservoir, upper and lower reaches of Kuiyong River, and Xinzhen River in Shenzhen, China, were selected as sampling sites. Ten Biomphalaria samples were collected from each site, and genomic DNA was extracted from Biomphalaria samples. DNA samples were obtained from 15 B. straminea sampled from 5 sampling sites in Minas Gerais State, Pará State, Federal District, Pernambuco State, and Sao Paulo State in Brazil, South America. Cytochrome c oxidase I (COI) and mitochondrial 16S ribosomal RNA (16S rRNA) genes were sampled using the above DNA templates, and the amplified products were sequenced. The COI and 16S rRNA gene sequences were downloaded from GenBank, and the sampling sites were acquired. All COI and 16S rRNA gene sequences were aligned and evolutionary trees of B. straminea were created based on COI and 16S rRNA gene sequences to identify the genetic similarity and evolutionary relationship between B. straminea samples from China and South America. RESULTS A total of 60 COI gene sequences with a length of 529 bp and 3 haplotypes were obtained from B. straminea sampled from China. There were 165 COI gene sequences of B. straminea retrieved from GenBank, and following alignment with the above 60 gene sequences, a total of 33 haplotypes were obtained. Phylogenetic analysis showed that the three haplotypes of B. straminea from China were clustered into one clade, among which the haplotype China11 and three B. straminea samples from Brazil retrieved from GenBank belonged to the same haplotype. Geographical evolution analysis showed that the B. straminea samples from three sampling sites along eastern coasts of Brazil had the same haplotype with China11, and B. straminea samples from other two sampling sites were closely, genetically related to China11. A total of 60 16S rDNA gene sequences with approximately 322 bp in length were amplified from B. straminea in China, with 2 haplotypes identified. A total of 70 16S rDNA gene sequences of B. straminea were captured from GenBank. Phylogenetic analysis showed that Biomphalaria snails collected from China were clustered into a clade, and the haplotype China64 and the haplotype 229BS from Brazil shared the same haplotype. The 49 16S rDNA gene sequences of B. straminea from 25 sampling sites in southern Brazil, which were captured from GenBank, were included in the present analysis, and the B. straminea from 3 sampling sites shared the same haplotype with China64 in China. Geographical evolution analysis based on COI and 16S rRNA gene sequences showed that B. straminea sampled from eastern coastal areas of Brazil shared the same haplotypes in two gene fragment sequences with Biomphalaria snails collected from China. CONCLUSIONS The Biomphalaria snails in China are characterized as B. straminea, which have a low genetic diversity. The Biomphalaria snails in China have a high genetic similarity with B. straminea sampled from eastern coastal areas of Brazil, which may have originated from the eastern coastal areas of Brazil.
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Guo Y, Cheng YL, Yang XX, Meng HX. [Research progress of microsatellite instability in head and neck squamous cell carcinoma]. ZHONGHUA BING LI XUE ZA ZHI = CHINESE JOURNAL OF PATHOLOGY 2024; 53:647-650. [PMID: 38825918 DOI: 10.3760/cma.j.cn112151-20230913-00166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
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AS, Cerri A, Cerrito L, Cerutti F, Cervato B, Cervelli A, Cesarini G, Cetin SA, Chakraborty D, Chan J, Chan WY, Chapman JD, Chapon E, Chargeishvili B, Charlton DG, Chatterjee M, Chauhan C, Che Y, Chekanov S, Chekulaev SV, Chelkov GA, Chen A, Chen B, Chen B, Chen H, Chen H, Chen J, Chen J, Chen M, Chen S, Chen SJ, Chen X, Chen X, Chen Y, Cheng CL, Cheng HC, Cheong S, Cheplakov A, Cheremushkina E, Cherepanova E, Cherkaoui El Moursli R, Cheu E, Cheung K, Chevalier L, Chiarella V, Chiarelli G, Chiedde N, Chiodini G, Chisholm AS, Chitan A, Chitishvili M, Chizhov MV, Choi K, Chou Y, Chow EYS, Chu KL, Chu MC, Chu X, Chudoba J, Chwastowski JJ, Cieri D, Ciesla KM, Cindro V, Ciocio A, Cirotto F, Citron ZH, Citterio M, Ciubotaru DA, Clark A, Clark PJ, Clarry C, Clavijo Columbie JM, Clawson SE, Clement C, Clercx J, Coadou Y, Cobal M, Coccaro A, Barrue RFC, Coelho Lopes De Sa R, Coelli S, Cole B, Collot J, Conde Muiño P, Connell MP, Connell SH, Conroy EI, Conventi F, Cooke HG, Cooper-Sarkar AM, 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R, Xu T, Xu Y, Xu Z, Xu Z, Yabsley B, Yacoob S, Yamaguchi Y, Yamashita E, Yamauchi H, Yamazaki T, Yamazaki Y, Yan J, Yan S, Yan Z, Yang HJ, Yang HT, Yang S, Yang T, Yang X, Yang X, Yang Y, Yang Y, Yang Z, Yao WM, Ye H, Ye H, Ye J, Ye S, Ye X, Yeh Y, Yeletskikh I, Yeo BK, Yexley MR, Yin P, Yorita K, Younas S, Young CJS, Young C, Yu C, Yu Y, Yuan M, Yuan R, Yue L, Zaazoua M, Zabinski B, Zaid E, Zak ZK, Zakareishvili T, Zakharchuk N, Zambito S, Zamora Saa JA, Zang J, Zanzi D, Zaplatilek O, Zeitnitz C, Zeng H, Zeng JC, Zenger DT, Zenin O, Ženiš T, Zenz S, Zerradi S, Zerwas D, Zhai M, Zhang DF, Zhang J, Zhang J, Zhang K, Zhang L, Zhang P, Zhang R, Zhang S, Zhang S, Zhang T, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhang Z, Zhao H, Zhao T, Zhao Y, Zhao Z, Zhemchugov A, Zheng J, Zheng K, Zheng X, Zheng Z, Zhong D, Zhou B, Zhou H, Zhou N, Zhou Y, Zhou Y, Zhu CG, Zhu J, Zhu Y, Zhu Y, Zhuang X, Zhukov K, Zimine NI, Zinsser J, Ziolkowski M, Živković L, Zoccoli A, Zoch K, Zorbas TG, Zormpa O, Zou W, Zwalinski L. Combination of Searches for Resonant Higgs Boson Pair Production Using pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector. PHYSICAL REVIEW LETTERS 2024; 132:231801. [PMID: 38905640 DOI: 10.1103/physrevlett.132.231801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 05/07/2024] [Indexed: 06/23/2024]
Abstract
A combination of searches for a new resonance decaying into a Higgs boson pair is presented, using up to 139 fb^{-1} of pp collision data at sqrt[s]=13 TeV recorded with the ATLAS detector at the LHC. The combination includes searches performed in three decay channels: bb[over ¯]bb[over ¯], bb[over ¯]τ^{+}τ^{-}, and bb[over ¯]γγ. No excess above the expected Standard Model background is observed and upper limits are set at the 95% confidence level on the production cross section of Higgs boson pairs originating from the decay of a narrow scalar resonance with mass in the range 251 GeV-5 TeV. The observed (expected) limits are in the range 0.96-600 fb (1.2-390 fb). The limits are interpreted in the type-I two-Higgs-doublet model and the minimal supersymmetric standard model, and constrain parameter space not previously excluded by other searches.
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Wang Z, Chen S, Guo Y, Zhang R, Zhang Q, Jiang X, Li M, Jiang Y, Ye L, Guo X, Li C, Zhang G, Li D, Chen L, Chen W. Intestinal carcinogenicity screening of environmental pollutants using organoid-based cell transformation assay. Arch Toxicol 2024; 98:1937-1951. [PMID: 38563870 DOI: 10.1007/s00204-024-03729-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 03/07/2024] [Indexed: 04/04/2024]
Abstract
The high incidence of colorectal cancer (CRC) is closely associated with environmental pollutant exposure. To identify potential intestinal carcinogens, we developed a cell transformation assay (CTA) using mouse adult stem cell-derived intestinal organoids (mASC-IOs) and assessed the transformation potential on 14 representative chemicals, including Cd, iPb, Cr-VI, iAs-III, Zn, Cu, PFOS, BPA, MEHP, AOM, DMH, MNNG, aspirin, and metformin. We optimized the experimental protocol based on cytotoxicity, amplification, and colony formation of chemical-treated mASC-IOs. In addition, we assessed the accuracy of in vitro study and the human tumor relevance through characterizing interdependence between cell-cell and cell-matrix adhesions, tumorigenicity, pathological feature of subcutaneous tumors, and CRC-related molecular signatures. Remarkably, the results of cell transformation in 14 chemicals showed a strong concordance with epidemiological findings (8/10) and in vivo mouse studies (12/14). In addition, we found that the increase in anchorage-independent growth was positively correlated with the tumorigenicity of tested chemicals. Through analyzing the dose-response relationship of anchorage-independent growth by benchmark dose (BMD) modeling, the potent intestinal carcinogens were identified, with their carcinogenic potency ranked from high to low as AOM, Cd, MEHP, Cr-VI, iAs-III, and DMH. Importantly, the activity of chemical-transformed mASC-IOs was associated with the degree of cellular differentiation of subcutaneous tumors, altered transcription of oncogenic genes, and activated pathways related to CRC development, including Apc, Trp53, Kras, Pik3ca, Smad4 genes, as well as WNT and BMP signaling pathways. Taken together, we successfully developed a mASC-IO-based CTA, which might serve as a potential alternative for intestinal carcinogenicity screening of chemicals.
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Jiang F, Guo Y, Ma H, Na S, Zhong W, Han Y, Wang T, Huang J. GTE: a graph learning framework for prediction of T-cell receptors and epitopes binding specificity. Brief Bioinform 2024; 25:bbae343. [PMID: 39007599 PMCID: PMC11247411 DOI: 10.1093/bib/bbae343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 05/15/2024] [Accepted: 07/01/2024] [Indexed: 07/16/2024] Open
Abstract
The interaction between T-cell receptors (TCRs) and peptides (epitopes) presented by major histocompatibility complex molecules (MHC) is fundamental to the immune response. Accurate prediction of TCR-epitope interactions is crucial for advancing the understanding of various diseases and their prevention and treatment. Existing methods primarily rely on sequence-based approaches, overlooking the inherent topology structure of TCR-epitope interaction networks. In this study, we present $GTE$, a novel heterogeneous Graph neural network model based on inductive learning to capture the topological structure between TCRs and Epitopes. Furthermore, we address the challenge of constructing negative samples within the graph by proposing a dynamic edge update strategy, enhancing model learning with the nonbinding TCR-epitope pairs. Additionally, to overcome data imbalance, we adapt the Deep AUC Maximization strategy to the graph domain. Extensive experiments are conducted on four public datasets to demonstrate the superiority of exploring underlying topological structures in predicting TCR-epitope interactions, illustrating the benefits of delving into complex molecular networks. The implementation code and data are available at https://github.com/uta-smile/GTE.
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