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Shao L, Yang X, Sun Z, Tan X, Lu Z, Hu S, Dou W, Duan S. Three-dimensional pseudo-continuous arterial spin-labelled perfusion imaging for diagnosing upper cervical lymph node metastasis in patients with nasopharyngeal carcinoma: a whole-node histogram analysis. Clin Radiol 2024; 79:e736-e743. [PMID: 38341343 DOI: 10.1016/j.crad.2024.01.017] [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: 08/02/2023] [Revised: 01/11/2024] [Accepted: 01/16/2024] [Indexed: 02/12/2024]
Abstract
AIM To evaluate whole-node histogram parameters of blood flow (BF) maps derived from three-dimensional pseudo-continuous arterial spin-labelled (3D pCASL) imaging in discriminating metastatic from benign upper cervical lymph nodes (UCLNs) for nasopharyngeal carcinoma (NPC) patients. MATERIALS AND METHODS Eighty NPC patients with a total of 170 histologically confirmed UCLNs (67 benign and 103 metastatic) were included retrospectively. Pre-treatment 3D pCASL imaging was performed and whole-node histogram analysis was then applied. Histogram parameters and morphological features, such as minimum axis diameter (MinAD), maximum axis diameter (MaxAD), and location of UCLNs, were assessed and compared between benign and metastatic lesions. Predictors were identified and further applied to establish a combined model by multivariate logistic regression in predicting the probability of metastatic UCLNs. Receiver operating characteristic (ROC) curves were used to analyse the diagnostic performance. RESULTS Metastatic UCLNs had larger MinAD and MinAD/MaxAD ratio, greater energy and entropy values, and higher incidence of level II (upper jugular group), but lower BF10th value than benign nodes (all p<0.05). MinAD, BF10th, energy, and entropy were validated as independent predictors in diagnosing metastatic UCLNs. The combined model yielded an area under the curve (AUC) of 0.932, accuracy of 84.42 %, sensitivity of 80.6 %, and specificity of 90.29 %. CONCLUSIONS Whole-node histogram analysis on BF maps is a feasible tool to differentiate metastatic from benign UCLNs in NPC patients, and the combined model can further improve the diagnostic efficacy.
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Hu S, Guinan E, Mockler D, O'Neill L. Retention rates and reasons for non-retention in exercise oncology trials in the post-treatment phase-a systematic review. J Cancer Surviv 2024:10.1007/s11764-024-01569-4. [PMID: 38570403 DOI: 10.1007/s11764-024-01569-4] [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: 08/22/2023] [Accepted: 03/12/2024] [Indexed: 04/05/2024]
Abstract
PURPOSE Retention is a key marker of trial success. Poor retention can induce bias, reduce statistical power and minimise the validity of trials. This review examined retention rates in exercise trials in cancer survivors, reasons for non-retention and retention strategies utilised. METHODS A systematic review was conducted using a predefined search strategy in EMBASE RCTs, MEDLINE OVID, CINAHL, Web of Science-Core Collection and Cochrane Central Register of Controlled Trials (CENTRAL). The search was conducted on 27/03/2023. Title and abstract screening, full text review and data extraction were completed in duplicate. RESULTS Of 17,524 studies identified, 67 trials involving 6093 participants were included. The median overall retention rate immediately post-intervention was 89.85%, range (52.94-100%) and mean 87.36% (standard deviation 9.89%). Trials involving colorectal cancer survivors only had the highest median retention rate (94.61%), followed by breast (92.74%), prostate (86.00%) and haematological cancers (85.49%). Studies involving mixed cancer cohorts had the lowest retention rate (80.18%). The most common retention strategies were wait-list control groups, regular check-ins/reminders and free exercise equipment. Common reasons for non-retention were lost to follow-up, health problems, personal reasons including family/work commitments and travel burden, and disease progression. CONCLUSIONS Retention rates in exercise oncology trials are approximately 90% immediately post-interventions. Our previous work highlighted variable suboptimal recruitment rates of median 38% (range 0.52-100%). Recruitment rather than retention should be prioritised for methodology research in exercise oncology. IMPLICATIONS FOR CANCER SURVIVORS Optimising the quality of exercise oncology trials is critical to informing high quality survivorship care. PROSPERO registration number: CRD42023421359.
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Kim S, Morris K, Talke F, Makale MT, Li B, Chen J, Hu S, Paracuellos R, Rash DL, Mayadev JS. Quantifying Radiation Induced Vaginal Stenosis for the Development of a Novel Dilator Device: A Prospective Cohort Study of Patients with Cervical Cancer Treated with Definitive Chemoradiation Therapy. Int J Radiat Oncol Biol Phys 2023; 117:e522-e523. [PMID: 37785627 DOI: 10.1016/j.ijrobp.2023.06.1794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Chemoradiation therapy (CRT) is the standard of care for the treatment of locally advanced cervical cancer (LACC). Vaginal stenosis (VS) is a common side effect of CRT and leads to sexual dysfunction, pain, and difficulty with vaginal intercourse, resulting in decreasing quality-of-life (QOL). However, there is scant data on the timeline of VS development, and patient use and satisfaction with a standard vaginal dilator (VD). In this study, we plan to develop a standardized technique to assess VS using physical exam measurements at specified timepoints after CRT. Secondarily, we will assess patient preferences and use of available VDs with the goal of developing a novel VD device with our multidisciplinary engineering team. We report the rationale, methods, and objectives of this clinical study. MATERIALS/METHODS Patients with LACC treated with CRT and brachytherapy are eligible. CT-based imaging pre-CRT and 3-months post-CRT to assess radiographic changes in the vaginal length and width will be collected. Vaginal measurements and physical exam will be recorded at baseline and 3-, 6-, and 12-months following CRT. Patients will also be given a set of VDs that range in diameter and length. Patient vaginal capacity, defined as the largest VD that can be comfortably accommodated in the vagina during pelvic exam, and compliance with VD use will be recorded at each visit. Patients will be given the EORTC Sexual Health Questionnaire (EORTC SHQ-22). Toxicity grading will use the CTCAE v5. We plan to assess patient preference using a VD-specific questionnaire to help guide the development of a personalized VD. RESULTS For the primary analysis, we will examine the VS CTCAE v5 toxicity at baseline vs 1 year for 20 patients. The sample size we propose is sufficient to achieve at least 80% power at 5% significance level for detecting a significant non-zero proportion with a margin of 20%. For the secondary analysis, we will test the Spearman's coefficient and Kendall's tau between VS CTCAE and EORTC questions: "has the treatment affected your sexual activity?"; "have you felt pain during/after sexual activity?"; "have you been sexually active?" We will use permutation tests in which the ID will be permuted for vaginal stricture but kept as original for the EORTC questions. We will test the null hypothesis of no correlation by comparing the observed Spearman's coefficient and Kendall's tau to the permutation distributions. We plan to incorporate the specific VD questionnaire responses into the development of a novel device using qualitative measures. CONCLUSION This clinical trial is an observational cohort study that aims to quantify CRT-induced VS, obtain patient reported sexual health, and understand specific preferences and compliance with VD use for the development of a novel engineered device.
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Mao HY, Yu YX, Zhang JY, Zhang T, Fan YF, Hu S, Wang XM, Hu CH. [The application value of Gd-EOB-DTPA enhanced MRI based radiomics in the differential diagnosis of iso-or hyperintensity HCC and focal nodular hyperplasia in hepatobiliary phase]. ZHONGHUA YI XUE ZA ZHI 2023; 103:2599-2606. [PMID: 37650206 DOI: 10.3760/cma.j.cn112137-20230117-00095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
Objective: To investigate the application value of Gd-EOB-DTPA enhanced MRI based radiomics model in the differential diagnosis of iso-or hyperintensity HCC and focal nodular hyperplasia (FNH) in hepatobiliary phase. Methods: A total of 88 patients with HCC or FNH confirmed by surgical or puncture pathology who underwent preoperative Gd-EOB-DTPA enhanced MRI (all lesions showed iso-or hyperintensity in hepatobiliary phase) between January 2015 and February 2023 in The First Affiliated Hospital of Soochow University and Nantong No.3 People's Hospital were retrospectively evaluated, which including 58 males and 30 females, aged [M(Q1, Q3)]56 (40, 67) years, including 61 patients with HCC and 27 patients with FNH. The included cases were divided into training (43 cases of HCC, 19 cases of FNH) and validation cohort (18 cases of HCC, 8 cases of FNH) in the ratio of 7∶3 using the random seeding method. A total of 1 781 radiomics features were extracted from Gd-EOB-DTPA enhanced MRI in the arterial, portal and hepatobiliary phases, respectively. The independent three phase models, combined three phases model and combined clinical-radiomics model was established using Auto-Encoder (AE) and Native Bayes (NB) classifier, respectively. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of these models. DeLong test was used to compare the areas under curve (AUC). Results: In the validation cohort, the combined clinical-radiomics model had the highest AUC (AUC=0.938, 95%CI: 0.828-1.000). The AUC, accuracy, sensitivity, specificity of the clinical-radiomics combined model using AE classifier in the validation cohort were 0.896 (95%CI: 0.760-1.000), 88.5%, 88.9%, 87.5%. The AUC of the clinical-radiomics combined model using NB classifier in the validation cohort were 0.938 (95%CI: 0.828-1.000), 92.3%, 88.9%, 100.0%. Conclusion: Gd-EOB-DTPA enhanced MRI combined clinical-radiomics model has certain value in preoperative differentiation of iso-or hyperintensity in the hepatobiliary phase HCC and FNH, with a high accuracy, sensitivity and specificity.
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Aad G, Abbott B, Abbott DC, Abed Abud A, Abeling K, Abhayasinghe DK, Abidi SH, Aboulhorma A, Abramowicz H, Abreu H, Abulaiti Y, Abusleme Hoffman AC, Acharya BS, Achkar B, Adam L, Adam Bourdarios C, Adamczyk L, Adamek L, Addepalli SV, Adelman J, Adiguzel A, Adorni S, Adye T, Affolder AA, Afik Y, Agaras MN, Agarwala J, Aggarwal A, Agheorghiesei C, Aguilar-Saavedra JA, Ahmad A, Ahmadov F, Ahmed WS, Ai X, Aielli G, Aizenberg I, Akbiyik M, Åkesson TPA, Akimov AV, Al Khoury K, Alberghi GL, Albert J, Albicocco P, Alconada Verzini MJ, Alderweireldt S, Aleksa M, Aleksandrov IN, Alexa C, Alexopoulos T, Alfonsi A, Alfonsi F, Alhroob M, Ali B, Ali S, Aliev M, Alimonti G, Allaire C, Allbrooke BMM, Allport PP, Aloisio A, Alonso F, Alpigiani C, Alunno Camelia E, Alvarez Estevez M, Alviggi MG, Amaral Coutinho Y, Ambler A, Ambroz L, Amelung C, Amidei D, Amor Dos Santos SP, Amoroso S, Amos KR, Amrouche CS, Ananiev V, Anastopoulos C, Andari N, Andeen T, Anders JK, Andrean SY, Andreazza A, Angelidakis S, Angerami A, Anisenkov AV, Annovi A, Antel C, Anthony MT, Antipov E, Antonelli M, Antrim DJA, Anulli F, Aoki M, Aparisi Pozo JA, Aparo MA, Aperio Bella L, Appelt C, Aranzabal N, Araujo Ferraz V, Arcangeletti C, Arce ATH, Arena E, Arguin JF, Argyropoulos S, Arling JH, Armbruster AJ, Arnaez O, Arnold H, Arrubarrena Tame ZP, Artoni G, Asada H, Asai K, Asai S, Asbah NA, Asimakopoulou EM, Assahsah J, Assamagan K, Astalos R, Atkin RJ, Atkinson M, Atlay NB, Atmani H, Atmasiddha PA, Augsten K, Auricchio S, Austrup VA, Avner G, Avolio G, Ayoub MK, Azuelos G, Babal D, Bachacou H, Bachas K, Bachiu A, Backman F, Badea A, Bagnaia P, Bahmani M, Bailey AJ, Bailey VR, Baines JT, Bakalis C, Baker OK, Bakker PJ, Bakos E, Bakshi Gupta D, Balaji S, 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, Barberio EL, Barberis D, Barbero M, Barbour G, Barends KN, Barillari T, Barisits MS, Barkeloo J, Barklow T, Barnett RM, Baron P, Baroncelli A, Barone G, Barr AJ, Barranco Navarro L, Barreiro F, Barreiro Guimarães da Costa J, Barron U, Barsov S, Bartels F, Bartoldus R, Bartolini G, Barton AE, Bartos P, Basalaev A, Basan A, Baselga M, Bashta I, Bassalat A, Basso MJ, Basson CR, Bates RL, Batlamous S, Batley JR, Batool B, Battaglia M, Bauce M, Bauer F, Bauer P, Bayirli A, Beacham JB, Beau T, Beauchemin PH, Becherer F, Bechtle P, Beck HP, Becker K, Becot C, Beddall AJ, Bednyakov VA, Bee CP, Beemster LJ, Beermann TA, Begalli M, Begel M, Behera A, Behr JK, Beirao Da Cruz E Silva C, Beirer JF, Beisiegel F, Belfkir M, Bella G, Bellagamba L, Bellerive A, Bellos P, Beloborodov K, Belotskiy K, Belyaev NL, Benchekroun D, Benhammou Y, Benjamin DP, Benoit M, Bensinger JR, Bentvelsen S, Beresford L, Beretta M, Berge D, Bergeaas Kuutmann E, Berger N, Bergmann B, Beringer J, Berlendis S, Bernardi G, Bernius C, Bernlochner FU, Berry T, Berta P, Berthold A, Bertram IA, Bessidskaia Bylund O, Bethke S, Betti A, Bevan AJ, Bhatta S, Bhattacharya DS, Bhattarai P, Bhopatkar VS, Bi R, Bi R, Bianchi RM, Biebel O, Bielski R, Biesuz NV, Biglietti M, Billoud TRV, Bindi M, Bingul A, Bini C, Biondi S, Biondini A, Birch-Sykes CJ, Bird GA, Birman M, Bisanz T, Biswas D, Bitadze A, Bjørke K, Bloch I, Blocker C, Blue A, Blumenschein U, Blumenthal J, Bobbink GJ, Bobrovnikov VS, Boehler M, Bogavac D, Bogdanchikov AG, Bohm C, Boisvert V, Bokan P, Bold T, Bomben M, Bona M, Boonekamp M, Booth CD, Borbély AG, Borecka-Bielska HM, Borgna LS, Borissov G, Bortoletto D, Boscherini D, Bosman M, Bossio Sola JD, Bouaouda K, 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, Breaden Madden WD, Brendlinger K, Brener R, Brenner L, Brenner R, Bressler S, Brickwedde B, Britton D, Britzger D, Brock I, Brooijmans G, Brooks WK, Brost E, Bruckman de Renstrom PA, Brüers B, Bruncko D, Bruni A, Bruni G, Bruschi M, Bruscino N, Bryngemark L, Buanes T, Buat Q, Buchholz P, Buckley AG, Budagov IA, Bugge MK, Bulekov O, Bullard BA, Burdin S, Burgard CD, Burger AM, Burghgrave B, Burr JTP, Burton CD, Burzynski JC, Busch EL, Büscher V, Bussey PJ, Butler JM, Buttar CM, Butterworth JM, Buttinger W, Buxo Vazquez CJ, Buzykaev AR, Cabras G, Cabrera Urbán S, Caforio D, Cai H, Cai Y, Cairo VMM, Cakir O, Calace N, Calafiura P, Calderini G, Calfayan P, Callea G, Caloba LP, Calvet D, Calvet S, Calvet TP, Calvetti M, Camacho Toro R, Camarda S, Camarero Munoz D, Camarri P, Camerlingo MT, Cameron D, Camincher C, Campanelli M, Camplani A, Canale V, Canesse A, Cano Bret M, Cantero J, Cao Y, Capocasa F, Capua M, Carbone A, Cardarelli R, Cardenas JCJ, Cardillo F, Carli T, Carlino G, Carlson BT, Carlson EM, Carminati L, Carnesale M, Caron S, Carquin E, Carrá S, Carratta G, Carter JWS, Carter TM, Casadei D, Casado MP, Casha AF, Castiglia EG, Castillo FL, Castillo Garcia L, Castillo Gimenez V, Castro NF, Catinaccio A, Catmore JR, Cavaliere V, Cavalli N, Cavasinni V, Celebi E, Celli F, Centonze MS, Cerny K, Cerqueira AS, Cerri A, Cerrito L, Cerutti F, Cervelli A, Cetin SA, Chadi Z, Chakraborty D, Chala M, Chan J, Chan WS, Chan WY, Chapman JD, Chargeishvili B, Charlton DG, Charman TP, Chatterjee M, Chekanov S, Chekulaev SV, Chelkov GA, Chen A, Chen B, Chen B, Chen C, Chen H, Chen H, Chen J, Chen J, Chen S, Chen SJ, Chen X, Chen X, Chen Y, Cheng CL, Cheng HC, Cheplakov A, Cheremushkina E, Cherepanova E, Cherkaoui El Moursli R, Cheu E, Cheung K, Chevalier L, Chiarella V, Chiarelli G, Chiodini G, Chisholm AS, Chitan A, Chiu YH, Chizhov MV, Choi K, Chomont AR, Chou Y, Chow EYS, Chowdhury T, Christopher LD, Chu MC, Chu X, Chudoba J, Chwastowski JJ, Cieri D, Ciesla KM, Cindro V, Ciocio A, Cirotto F, Citron ZH, Citterio M, Ciubotaru DA, Ciungu BM, Clark A, Clark PJ, Clavijo Columbie JM, Clawson SE, Clement C, Clissa L, Coadou Y, Cobal M, Coccaro A, Barrue RFC, Coelho Lopes De Sa R, Coelli S, Cohen H, Coimbra AEC, Cole B, Collot J, Conde Muiño P, Connell SH, Connelly IA, Conroy EI, Conventi F, Cooke HG, Cooper-Sarkar AM, Cormier F, Corpe LD, Corradi M, Corrigan EE, Corriveau F, Costa MJ, Costanza F, Costanzo D, Cote BM, Cowan G, Cowley JW, Cranmer K, Crépé-Renaudin S, Crescioli F, Cristinziani M, Cristoforetti M, Croft V, Crosetti G, Cueto A, Cuhadar Donszelmann T, Cui H, Cui Z, Cukierman AR, Cunningham WR, Curcio F, Czodrowski P, Czurylo MM, De Sousa MJDCS, Da Fonseca Pinto JV, Da Via C, Dabrowski W, Dado T, Dahbi S, Dai T, Dallapiccola C, Dam M, D'amen G, D'Amico V, Damp J, Dandoy JR, Daneri MF, Danninger M, Dao V, Darbo G, Darmora S, Dattagupta A, D'Auria S, David C, Davidek T, Davis DR, Davis-Purcell B, Dawson I, De K, De Asmundis R, De Beurs M, De Castro S, De Groot N, de Jong P, De la Torre H, De Maria A, De Salvo A, De Sanctis U, De Santis M, De Santo A, De Vivie De Regie JB, Dedovich DV, Degens J, Deiana AM, Del Peso J, Del Rio F, 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, Dette K, Deutsch C, Deviveiros PO, 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, Diaconu C, Dias FA, Vale TDD, Diaz MA, Diaz Capriles FG, Didenko M, Diehl EB, Díez Cornell S, Diez Pardos C, Dimitriadi C, Dimitrievska A, Ding W, Dingfelder J, Dinu IM, Dittmeier SJ, Dittus F, Djama F, Djobava T, Djuvsland JI, Dodsworth D, Doglioni C, Dolejsi J, Dolezal Z, Donadelli M, Dong B, Donini J, D'Onofrio A, D'Onofrio M, Dopke J, Doria A, Dova MT, Doyle AT, Drechsler E, Dreyer E, Drobac AS, Du D, du Pree TA, Dubinin F, Dubovsky M, Duchovni E, Duckeck G, Ducu OA, Duda D, Dudarev A, D'uffizi M, Duflot L, Dührssen M, Dülsen C, Dumitriu AE, Dunford M, Dungs S, Dunne K, Duperrin A, Yildiz HD, Düren M, Durglishvili A, Dutta B, Dwyer BL, Dyckes GI, Dyndal M, Dysch S, Dziedzic BS, Eckerova B, Eggleston MG, Purcino De Souza EE, Ehrke LF, Eigen G, Einsweiler K, Ekelof T, El Ghazali Y, El Jarrari H, El Moussaouy A, Ellajosyula V, Ellert M, Ellinghaus F, Elliot AA, Ellis N, Elmsheuser J, Elsing M, Emeliyanov D, Emerman A, Enari Y, Ene I, Erdmann J, Ereditato A, Erland PA, Errenst M, Escalier M, Escobar C, Etzion E, Evans G, Evans H, Evans MO, Ezhilov A, Ezzarqtouni S, Fabbri F, Fabbri L, Facini G, Fadeyev V, Fakhrutdinov RM, Falciano S, Falke PJ, Falke S, Faltova J, Fan Y, Fang Y, Fanourakis G, Fanti M, Faraj M, Farbin A, Farilla A, Farooque T, Farrington SM, Fassi F, Fassouliotis D, Faucci Giannelli M, Fawcett WJ, Fayard L, Fedin OL, Fedotov G, Feickert M, Feligioni L, Fell A, Fellers DE, Feng C, Feng M, Fenton MJ, Fenyuk AB, Ferguson SW, Pretel J, Ferrando J, Ferrari A, Ferrari P, Ferrari R, Ferrere D, Ferretti C, Fiedler F, Filipčič A, Filmer EK, Filthaut F, Fiolhais MCN, Fiorini L, Fischer F, Fisher WC, Fitschen T, Fleck I, Fleischmann P, Flick T, Flores L, Flores M, Flores Castillo LR, Follega FM, Fomin N, Foo JH, Forland BC, Formica A, Forti AC, Fortin E, Fortman AW, Foti MG, Fountas L, Fournier D, Fox H, Francavilla P, Francescato S, Franchini M, Franchino S, Francis D, Franco L, Franconi L, Franklin M, Frattari G, Freegard AC, Freeman PM, Freund WS, Freundlich EM, Froidevaux D, Frost JA, Fu Y, Fujimoto M, Fullana Torregrosa E, Fuster J, Gabrielli A, Gabrielli A, Gadow P, Gagliardi G, Gagnon LG, Galantzan S, Gallardo GE, Gallas EJ, Gallop BJ, Gamboa Goni R, Gan KK, Ganguly S, Gao J, Gao Y, Garay Walls FM, Garcia B, García C, García Navarro JE, García Pascual JA, Garcia-Sciveres M, Gardner RW, Garg D, Garg RB, Gargiulo S, Garner CA, Garonne V, Gasiorowski SJ, Gaspar P, Gaudio G, Gauzzi P, Gavrilenko IL, Gavrilyuk A, Gay C, Gaycken G, Gazis EN, Geanta AA, Gee CM, Geisen J, Geisen M, Gemme C, Genest MH, Gentile S, George S, George WF, Geralis T, Gerlach LO, Gessinger-Befurt P, Ghasemi Bostanabad M, Ghneimat M, Ghosal A, Ghosh A, Ghosh A, Giacobbe B, Giagu S, Giangiacomi N, Giannetti P, Giannini A, Gibson SM, Gignac M, Gil DT, Gilbert BJ, Gillberg D, Gilles G, Gillwald NEK, Ginabat L, Gingrich DM, Giordani MP, Giraud PF, Giugliarelli G, Giugni D, Giuli F, Gkialas I, Gkountoumis P, Gladilin LK, Glasman C, Gledhill GR, Glisic M, Gnesi I, Go Y, Goblirsch-Kolb M, Godin D, Goldfarb S, Golling T, Gololo MGD, Golubkov D, Gombas JP, Gomes A, Gomez Delegido AJ, Goncalves Gama R, Gonçalo R, Gonella G, Gonella L, Gongadze A, Gonnella F, Gonski JL, González de la Hoz S, Gonzalez Fernandez S, Gonzalez Lopez R, Gonzalez Renteria C, Gonzalez Suarez R, Gonzalez-Sevilla S, Gonzalvo Rodriguez GR, González Andana RY, Goossens L, Gorasia NA, Gorbounov PA, Gorini B, Gorini E, Gorišek A, Goshaw AT, Gostkin MI, Gottardo CA, Gouighri M, Goumarre V, Goussiou AG, Govender N, Goy C, Grabowska-Bold I, Graham K, Gramstad E, Grancagnolo S, Grandi M, Gratchev V, Gravila PM, Gravili FG, Gray HM, Grefe C, Gregor IM, Grenier P, Grevtsov K, Grieco C, Grillo AA, Grimm K, Grinstein S, Grivaz JF, Groh S, Gross E, Grosse-Knetter J, Grud C, Grummer A, Grundy JC, Guan L, Guan W, Gubbels C, Guerrero Rojas JGR, Guescini F, Gugel R, Guida A, Guillemin T, Guindon S, Guo F, Guo J, Guo L, Guo Y, Gupta R, Gurbuz S, Gustavino G, Guth M, Gutierrez P, Gutierrez Zagazeta LF, Gutschow C, Guyot C, Gwenlan C, Gwilliam CB, Haaland ES, Haas A, Habedank M, Haber C, Hadavand HK, Hadef A, Hadzic S, Haleem M, Haley J, Hall JJ, Hallewell GD, Halser L, Hamano K, Hamdaoui H, Hamer M, Hamity GN, Han J, Han K, Han L, Han L, Han S, Han YF, Hanagaki K, Hance M, Hangal DA, Hank MD, Hankache R, Hansen E, Hansen JB, Hansen JD, Hansen PH, Hara K, Harada D, Harenberg T, Harkusha S, Harris YT, Harrison PF, Hartman NM, Hartmann NM, Hasegawa Y, Hasib A, Haug S, Hauser R, Havranek M, Hawkes CM, Hawkings RJ, Hayashida S, Hayden D, Hayes C, Hayes RL, Hays CP, Hays JM, Hayward HS, He F, He Y, He Y, Heath MP, Hedberg V, Heggelund AL, Hehir ND, Heidegger C, Heidegger KK, Heidorn WD, Heilman J, Heim S, Heim T, Heinemann B, Heinlein JG, Heinrich JJ, Heinrich L, Hejbal J, Helary L, Held A, Hellesund S, Helling CM, Hellman S, Helsens C, Henderson RCW, Henkelmann L, Henriques Correia AM, Herde H, Hernández Jiménez Y, Herr H, Herrmann MG, Herrmann T, Herten G, Hertenberger R, Hervas L, Hessey NP, Hibi H, Higón-Rodriguez E, Hillier SJ, Hinchliffe I, Hinterkeuser F, Hirose M, Hirose S, Hirschbuehl D, Hiti B, Hladik O, Hobbs J, Hobincu R, Hod N, Hodgkinson MC, Hodkinson BH, Hoecker A, Hofer J, Hohn D, Holm T, Holzbock M, Hommels LBAH, Honan BP, Hong J, Hong TM, Hong Y, Honig JC, Hönle A, Hooberman BH, Hopkins WH, Horii Y, Horyn LA, Hou S, Howarth J, Hoya J, Hrabovsky M, Hrynevich A, Hryn'ova T, Hsu PJ, Hsu SC, Hu Q, Hu S, Hu YF, Huang DP, Huang X, Huang Y, Huang Y, Hubacek Z, Huebner M, Huegging F, Huffman TB, Huhtinen M, Huiberts SK, Hulsken R, Huseynov N, Huston J, Huth J, Hyneman R, Hyrych S, Iacobucci G, Iakovidis G, Ibragimov I, Iconomidou-Fayard L, Iengo 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Sykora I, Sykora M, Sykora T, Ta D, Tackmann K, Taffard A, Tafirout R, Taibah RHM, Takashima R, Takeda K, Takeva EP, Takubo Y, Talby M, Talyshev AA, Tam KC, Tamir NM, Tanaka A, Tanaka J, Tanaka R, Tang J, 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, Tastet JL, Tateno G, Tayalati Y, Taylor GN, Taylor W, Teagle H, Tee AS, Teixeira De Lima R, Teixeira-Dias P, Teoh JJ, Terashi K, Terron J, Terzo S, Testa M, Teuscher RJ, Themistokleous N, Theveneaux-Pelzer T, Thielmann O, Thomas DW, Thomas JP, Thompson EA, Thompson PD, Thomson E, Thorpe EJ, Tian Y, Tikhomirov V, Tikhonov YA, Timoshenko S, Ting EXL, Tipton P, Tisserant S, Tlou SH, Tnourji A, Todome K, Todorova-Nova S, Todt S, Togawa M, Tojo J, Tokár S, Tokushuku K, Tombs R, Tomoto M, Tompkins L, Tornambe P, Torrence E, Torres H, Torró Pastor E, Toscani M, Tosciri C, Tovey DR, Traeet A, Trandafir IS, Treado CJ, Trefzger T, Tricoli A, Trigger IM, Trincaz-Duvoid S, Trischuk DA, Trocmé B, Trofymov A, Troncon C, Trovato F, Truong L, Trzebinski M, Trzupek A, Tsai F, Tsai M, Tsiamis A, Tsiareshka PV, Tsirigotis A, Tsiskaridze V, Tskhadadze EG, Tsopoulou M, Tsujikawa Y, Tsukerman II, Tsulaia V, Tsuno S, Tsur O, Tsybychev D, Tu Y, Tudorache A, Tudorache V, Tuna AN, Turchikhin S, Turk Cakir I, Turra R, Tuts PM, Tzamarias S, Tzanis P, Tzovara E, Uchida K, Ukegawa F, Ulloa Poblete PA, Unal G, Unal M, Undrus A, Unel G, Uno K, Urban J, Urquijo P, Usai G, Ushioda R, Usman M, Uysal Z, Vacek V, Vachon B, Vadla KOH, Vafeiadis T, Valderanis C, Valdes Santurio E, Valente M, Valentinetti S, Valero A, Vallier A, Valls Ferrer JA, Van Daalen TR, Van Gemmeren P, 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, Varvell KE, Vasile ME, Vaslin L, Vasquez GA, Vazeille F, Vazquez Furelos D, Vazquez Schroeder T, Veatch J, Vecchio V, Veen MJ, Veliscek I, Veloce LM, Veloso F, Veneziano S, Ventura A, Verbytskyi A, Verducci M, Vergis C, Verissimo De Araujo M, Verkerke W, Vermeulen JC, Vernieri C, Verschuuren PJ, Vessella M, Vesterbacka ML, 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, Vittori C, Vivarelli I, Vladimirov V, Voevodina E, Vogel M, Vokac P, Von Ahnen J, Von Toerne E, Vormwald B, Vorobel V, Vorobev K, Vos M, Vossebeld JH, Vozak M, Vozdecky L, Vranjes N, Vranjes Milosavljevic M, Vrba V, Vreeswijk M, Vuillermet R, Vujinovic O, Vukotic I, Wada S, Wagner C, Wagner W, Wahdan S, Wahlberg H, Wakasa R, Wakida M, Walbrecht VM, Walder J, Walker R, Walkowiak W, Wang AM, Wang AZ, Wang C, Wang C, Wang H, Wang J, Wang P, Wang RJ, Wang R, Wang R, Wang SM, Wang S, Wang T, Wang WT, Wang WX, Wang X, Wang X, Wang X, Wang Y, Wang Z, Wang Z, Wang Z, Warburton A, Ward RJ, Warrack N, Watson AT, Watson MF, Watts G, Waugh BM, Webb AF, Weber C, Weber MS, Weber SA, Weber SM, Wei C, Wei Y, Weidberg AR, Weingarten J, Weirich M, Weiser C, Wenaus T, Wendland B, Wengler T, Wenke NS, Wermes N, Wessels M, Whalen K, Wharton AM, White AS, White A, White MJ, Whiteson D, Wickremasinghe L, Wiedenmann W, Wiel C, Wielers M, Wieseotte N, Wiglesworth C, Wiik-Fuchs LAM, Wilbern DJ, Wilkens HG, Williams DM, Williams HH, Williams S, Willocq S, Windischhofer PJ, Winklmeier F, Winter BT, Wittgen M, Wobisch M, Wolf A, Wölker R, Wollrath J, Wolter MW, Wolters H, Wong VWS, Wongel AF, Worm SD, Wosiek BK, Woźniak KW, Wraight K, Wu J, Wu SL, Wu X, Wu Y, Wu Z, Wuerzinger J, Wyatt TR, Wynne BM, Xella S, Xia L, Xia M, Xiang J, Xiao X, Xie M, Xie X, Xiotidis I, Xu D, Xu H, Xu H, Xu L, Xu R, Xu T, Xu W, Xu Y, Xu Z, Xu Z, Yabsley B, Yacoob S, Yamaguchi N, Yamaguchi Y, 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 Z, Yao WM, Yap YC, Ye H, Ye J, Ye S, Ye X, Yeletskikh I, Yexley MR, Yin P, Yorita K, Young CJS, Young C, Yuan M, Yuan R, Yue X, Zaazoua M, Zabinski B, Zacharis G, Zaid E, Zakareishvili T, Zakharchuk N, Zambito S, Zanzi D, Zaplatilek O, Zeißner SV, Zeitnitz C, Zeng JC, Zenger DT, Zenin O, Ženiš T, Zenz S, Zerradi S, Zerwas D, Zhang B, Zhang DF, Zhang G, Zhang J, Zhang K, Zhang L, Zhang M, Zhang R, Zhang S, Zhang X, Zhang X, Zhang Z, Zhao H, Zhao P, Zhao T, Zhao Y, Zhao Z, Zhemchugov A, Zheng Z, Zhong D, Zhou B, Zhou C, Zhou H, Zhou N, Zhou Y, Zhu CG, Zhu C, Zhu HL, Zhu H, Zhu J, Zhu Y, Zhuang X, Zhukov K, Zhulanov V, Zieminska D, Zimine NI, Zimmermann S, Zinsser J, Ziolkowski M, Živković L, Zoccoli A, Zoch K, Zorbas TG, Zormpa O, Zou W, Zwalinski L. Search for Heavy Neutral Leptons in Decays of W Bosons Using a Dilepton Displaced Vertex in sqrt[s]=13 TeV pp Collisions with the ATLAS Detector. PHYSICAL REVIEW LETTERS 2023; 131:061803. [PMID: 37625051 DOI: 10.1103/physrevlett.131.061803] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 08/08/2022] [Indexed: 08/27/2023]
Abstract
A search for a long-lived, heavy neutral lepton (N) in 139 fb^{-1} of sqrt[s]=13 TeV pp collision data collected by the ATLAS detector at the Large Hadron Collider is reported. The N is produced via W→Nμ or W→Ne and decays into two charged leptons and a neutrino, forming a displaced vertex. The N mass is used to discriminate between signal and background. No signal is observed, and limits are set on the squared mixing parameters of the N with the left-handed neutrino states for the N mass range 3 GeV
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Zeng L, Hu S, Zeng L, Chen R, Li H, Yu J, Yang H. Animal Models of Ischemic Stroke with Different Forms of Middle Cerebral Artery Occlusion. Brain Sci 2023; 13:1007. [PMID: 37508939 PMCID: PMC10377124 DOI: 10.3390/brainsci13071007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 06/24/2023] [Accepted: 06/26/2023] [Indexed: 07/30/2023] Open
Abstract
Ischemic stroke is a common type of stroke that significantly affects human well-being and quality of life. In order to further characterize the pathophysiology of ischemic stroke and develop new treatment strategies, ischemic stroke models with controllable and consistent response to potential clinical treatments are urgently needed. The middle cerebral artery occlusion (MCAO) model is currently the most widely used animal model of ischemic stroke. This review discusses various methods for constructing the MCAO model and compares their advantages and disadvantages in order to provide better approaches for studying ischemic stroke.
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Zhang XR, Ma T, Wang YC, Hu S, Yang Y. Development of a Novel Method for the Clinical Visualization and Rapid Identification of Multidrug-Resistant Candida auris. Microbiol Spectr 2023; 11:e0491222. [PMID: 37098907 PMCID: PMC10269898 DOI: 10.1128/spectrum.04912-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 03/25/2023] [Indexed: 04/27/2023] Open
Abstract
Outbreaks of multidrug-resistant Candida auris infections, associated with a mortality rate of 30% to 60%, are of serious global concern. Candida auris demonstrates high transmission rates in hospital settings; however, its rapid and accurate identification using currently available clinical identification techniques is challenging. In this study, we developed a rapid and effective method for detecting C. auris based on recombinase-aided amplification combined with lateral flow strips (RAA-LFS). We also screened the appropriate reaction conditions. Furthermore, we investigated the specificity and sensitivity of the detection system and its ability to distinguish other fungal strains. Candida auris was accurately identified and differentiated from related species at 37°C within 15 min. The minimum detection limit was 1 CFU (or 10 fg/reaction) and was not affected by high concentrations of related species or host DNA. The simple and cost-efficient detection method established in this study exhibited high specificity and sensitivity and successfully detected C. auris in simulated clinical samples. Compared with other traditional detection methods, this method greatly reduces the time and cost of testing and is thus suitable for hospitals or clinics in remote underfunded areas for screening C. auris infection and colonization. IMPORTANCE Candida auris is a highly lethal, multidrug-resistant, invasive fungus. However, conventional methods of C. auris identification are time-consuming and laborious and have low sensitivity and high error rates. In this study, a new molecular diagnostic method based on recombinase-aided amplification combined with lateral flow strips (RAA-LFS) was developed, and accurate results could be obtained by catalyzing the reaction at body temperature for 15 min. This method can be used for rapid clinical detection of C. auris, consequently saving valuable treatment time for patients.
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Qiao XM, Hu CH, Hu S, Hu CH, Wang XM, Shen JK, Ji LB, Song Y, Bao J. [The value of machine learning models based on biparametric MRI for diagnosis of prostate cancer and clinically significant prostate cancer]. ZHONGHUA YI XUE ZA ZHI 2023; 103:1446-1454. [PMID: 37198106 DOI: 10.3760/cma.j.cn112137-20221018-02174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Objective: To evaluate the value of machine learning (ML) models based on biparametric magnetic resonance imaging (bpMRI) for diagnosis of prostate cancer (PCa) and clinically significant prostate cancer (csPCa). Methods: A total of 1 368 patients, aged from 30 to 92 (69.4±8.2) years, from 3 tertiary medical centers in Jiangsu Province were retrospectively collected from May 2015 to December 2020, including 412 cases of csPCa, 242 cases of clinically insignificant prostate cancer (ciPCa) and 714 cases of benign prostate lesions. The data of center 1 and center 2 were randomly divided into training cohort and internal testing cohort at a ratio of 7∶3 by random number sampling without replacement using Python Random package, and the data of center 3 were used as the independent external testing cohort. The training cohort includs 243 cases of csPCa, 135 cases of ciPCa and 384 cases of benign lesions, the internal testing cohort includs 104 cases of csPCa, 58 cases of ciPCa and 165 cases of benign lesions, and the external testing cohort includs 65 cases of csPCa, 49 cases of ciPCa and 165 cases of benign lesions. The radiomics features were extracted on T2-weighted imaging, diffusion-weighted imaging and apparent diffusion coefficient map, and optimal radiomics features were selected by using Pearson correlation coefficient method and analysis of variance. The ML models were built using two ML algorithms, including support vector machine and random forest (RF) and were further tested in the internal testing cohort and external testing cohort. Finally, the PI-RADS scores evaluated by the radiologists were adjusted by the ML models which had superior diagnostic performance, namely adjusted PI-RADS. The receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of the ML models and PI-RADS. DeLong test was used to compare the areas under curve (AUC) of models with those of PI-RADS. Results: For PCa diagnosis, in internal testing cohort, the AUC of ML model using RF algorithm and PI-RADS were 0.869 (95%CI: 0.830-0.908) and 0.874 (95%CI: 0.836-0.913), respectively, and the difference between the model and PI-RADS did not reach to the statistical significance (P=0.793). In the external testing cohort, the AUC of model and PI-RADS were 0.845 (95%CI: 0.794-0.897) and 0.915 (95%CI: 0.880-0.951), respectively, and the difference was statistically significant (P=0.01). For csPCa diagnosis, the AUC of ML model using RF algorithm and PI-RADS were 0.874 (95%CI: 0.834-0.914) and 0.892 (95%CI: 0.857-0.927), respectively, in internal testing cohort, and the difference between the model and PI-RADS was not statistically significant (P=0.341). In the external testing cohort, the AUC of model and PI-RADS were 0.876 (95%CI: 0.831-0.920) and 0.884 (95%CI: 0.841-0.926), respectively, and the difference between the model and PI-RADS was not statistically significant (P=0.704). When PI-RADS assessment was adjusted with the assistance of ML models, the specificities increased from 63.0% to 80.0% in the internal testing cohort and from 92.7% to 93.3% in the external test group in diagnosing PCa. In diagnosing csPCa, the specificities increased from 52.5% to 72.6% in the internal testing cohort and from 75.2% to 79.9% in the external testing cohort. Conclusions: The ML models based on bpMRI showed comparable diagnostic performance to PI-RADS assessed by senior radiologists and achieved good generalization ability in both diagnosing PCa and csPCa. The specificities of the PI-RADS were improved by ML models.
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Ren S, Wang X, Han B, Pan Y, Zhao J, Cheng Y, Hu S, Liu T, Li Y, Cheng Y, Feng J, Yi S, Gu S, Gao S, Luo Y, Liu Y, Liu C, Duan H, Zhou C, Fan J. 43P Camrelizumab plus famitinib as first-line treatment in advanced NSCLC patients with PD-L1 TPS ≥1%: A report from a multicenter, open-label, phase II basket trial. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00297-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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Deng D, Li W, Li L, Yuan X, Li L, Wang J, Han C, Hu S. Molecular characterisation and expression profile of the PRLR gene during goose ovarian follicle development. Br Poult Sci 2023:1-10. [PMID: 36628626 DOI: 10.1080/00071668.2022.2163154] [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: 01/12/2023]
Abstract
1. Although PRL-PRLR signalling plays important roles in regulating avian reproduction, there is a paucity of information regarding the functional significance of PRLR in goose ovarian follicle development.2. The full-length 2,496 bp coding sequence of PRLR was obtained from Sichuan White goose (Anser cygnoides) for the first time and was seen to encode a polypeptide containing 831 amino acids. Goose PRLR shares similar sequence characteristics and conserved functional domains to other avian species and was phylogenetically clustered into the avian clade.3. The qPCR results suggested that the mRNA levels of PRLR significantly increased in primary follicles during weeks 3 to 4 of age and were higher in secondary- than in primordial follicles at week 5 post-hatching, which suggested that the PRLR-mediated signalling could be involved in regulation of early folliculogenesis.4. The PRLR mRNA was expressed at the highest levels in the prehierarchical 8-10 mm granulosa layers throughout goose ovarian follicle development, indicating a role for PRLR in the process of follicle selection.5. PRLR mRNA was differentially expressed in the three cohorts of in vitro cultured granulosa cells harvested from different sized goose ovarian follicles, which suggested that PRLR was involved in regulating granulosa cell functions depending on the stage of follicle development. These data provide novel insights into the role of PRLR during goose ovarian follicle development, although the underlying mechanisms await further investigations.
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Zeng L, Yu J, Chen R, Yang H, Li H, Zeng L, Wang J, Xu W, Hu S, Chen K. Modified Valsalva maneuver after burr-hole drainage of chronic subdural hematomas: A single-center cohort study. Front Neurol 2023; 13:1069708. [PMID: 36793801 PMCID: PMC9924088 DOI: 10.3389/fneur.2022.1069708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 12/28/2022] [Indexed: 01/31/2023] Open
Abstract
Background Previous studies on the management of chronic subdural hematoma (cSDH) mainly focused on the risk of postoperative recurrence and measures to prevent it. In this study, we propose the use of a non-invasive postoperative treatment method, the modified Valsalva maneuver (MVM), as a means of reducing the recurrence of cSDH. This study aims to clarify the effects of MVM on functional outcomes and recurrence rates. Methods A prospective study was conducted at the Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from November 2016 to December 2020. The study included 285 adult patients who underwent burr-hole drainage for the treatment of cSDH and received subdural drains. These patients were divided into two groups: the MVM group (n = 117) and the control group (n = 98). In the MVM group, patients received treatment with a customized MVM device for at least 10 times per hour, 12 h per day. The study's primary endpoint was the recurrence rate of SDH, while functional outcomes and morbidity 3 months after surgery were the secondary outcomes. Results In the current study, 9 out of 117 patients (7.7%) in the MVM group experienced a recurrence of SDH, while 19 out of 98 patients (19.4%, p < 0.05) in the HC group experienced a recurrence of SDH. Additionally, the infection rate of diseases such as pneumonia (1.7%) was significantly lower in the MVM group compared to the HC group (9.2%, p < 0.001, odds ratio (OR = 0.1). After 3 months of the surgery, 109 out of 117 patients (93.2%) in the MVM group achieved a favorable prognosis, compared to 80 out of 98 patients (81.6%) in the HC group (p = 0.008, with an OR of 2.9). Additionally, infection rate (with an OR of 0.2) and age (with an OR of 0.9) are independent predictors of a favorable prognosis at the follow-up stage. Conclusions The use of MVM in the postoperative management of cSDHs has been shown to be safe and effective, resulting in reduced rates of cSDH recurrence and infection following burr-hole drainage. These findings suggest that MVM treatment may lead to a more favorable prognosis at the follow-up stage.
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Lin L, Li S, Hu S, Yu W, Jiang B, Mao C, Li G, Yang R, Miao X, Jin M, Gu Y, Lu E. UCHL1 Impairs Periodontal Ligament Stem Cell Osteogenesis in Periodontitis. J Dent Res 2023; 102:61-71. [PMID: 36112902 DOI: 10.1177/00220345221116031] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Periodontitis comprises a series of inflammatory responses resulting in alveolar bone loss. The suppression of osteogenesis of periodontal ligament stem cells (PDLSCs) by inflammation is responsible for impaired alveolar bone regeneration, which remains an ongoing challenge for periodontitis therapy. Ubiquitin C-terminal hydrolase L1 (UCHL1) belongs to the family of deubiquitinating enzymes, which was found to play roles in inflammation previously. In this study, the upregulation of UCHL1 was identified in inflamed PDLSCs isolated from periodontitis patients and in healthy PDLSCs treated with tumor necrosis factor-α or interleukin-1β, and the higher expression level of UCHL1 was accompanied with the impaired osteogenesis of PDLSCs. Then UCHL1 was inhibited in PDLSCs using the lentivirus or inhibitor, and the osteogenesis of PDLSCs suppressed by inflammation was rescued by UCHL1 inhibition. Mechanistically, the negative effect of UCHL1 on the osteogenesis of PDLSCs was attributable to its negative regulation of mitophagy-dependent bone morphogenetic protein 2/Smad signaling pathway in periodontitis-associated inflammation. Furthermore, a ligature-induced murine periodontitis model was established, and the specific inhibitor of UCHL1 was administrated to periodontitis mice. The histological results showed increased active osteoblasts on alveolar bone surface and enhanced alveolar bone regeneration when UCHL1 was inhibited in periodontitis mice. Besides, the therapeutic effects of UCHL1 inhibition on ameliorating periodontitis were verified, as indicated by less bone loss and reduced inflammation. Altogether, our study proved UCHL1 to be a key negative regulator of the osteogenesis of PDLSCs in periodontitis and suggested that UCHL1 inhibition holds promise for alveolar bone regeneration in periodontitis treatment.
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Guo W, Zhao X, Cheng D, Liang X, Miao M, Li X, Lu J, Xu N, Hu S, Zhang Q. Muscle Fat Content Is Associated with Nonalcoholic Fatty Liver Disease and Liver Fibrosis in Chinese Adults. J Nutr Health Aging 2023; 27:960-965. [PMID: 37997716 DOI: 10.1007/s12603-023-2015-9] [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: 08/08/2023] [Accepted: 10/09/2023] [Indexed: 11/25/2023]
Abstract
OBJECTIVES Several studies have linked myosteatosis with nonalcoholic fatty liver disease (NAFLD) in individuals with obesity. The clinical significance of myosteatosis in individuals with NAFLD in the general population has not been well investigated. Here, we wanted to explore and compare the associations of NAFLD and liver fibrosis with muscle fat content and skeletal muscle mass (SMM) in a relatively large general population in China. METHODS We retrospectively included all participants who underwent abdominal CT scans in our health promotion center between April 2021 and October 2021. Muscle fat content was assessed by abdomen quantitative computed tomography (QCT) scans, and SMM was evaluated by bioelectrical impedance. NAFLD was assessed by ultrasonography. The NAFLD fibrosis score (NFS) and Fibrosis-4 Index (FIB-4) score were calculated to assess liver fibrosis. RESULTS Compared with participants without NAFLD, patients with NAFLD showed significantly increased intermuscular adipose tissue (IMAT%) (7.40±3.37% vs. 6.76±2.66%, P <0.01). According to a multiple logistic regression model, IMAT% (OR=1.091, 95% CI 1.030-1.155, P=0.003) was only independently correlated with NAFLD in obese participants. Mediation analysis showed that BMI mediated the association between IMAT% and NAFLD. In participants with NAFLD, increased IMAT% was independently associated with an increased intermediate to high risk of advanced fibrosis assessed by the NFS or FIB-4 score after adjusting for multiple potential confounders. However, SMM was only independently correlated with an intermediate to high risk for advanced fibrosis evaluated by the NFS and not by the FIB-4 score. CONCLUSION Increased muscle fat content is positively correlated with NAFLD and intermediate to high risk for advanced fibrosis in the general Chinese population.
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Zhang X, Gao M, Hu S. Letter to the Editor: Comment on «Frailty Is a Risk Factor for Falls in the Older Adults: A Systematic Review and Meta-Analysis». J Nutr Health Aging 2023; 27:1284-1285. [PMID: 38151881 DOI: 10.1007/s12603-023-2049-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 09/24/2023] [Indexed: 12/29/2023]
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Cao Z, Aharonian F, An Q, Bai LX, Bai YX, Bao YW, Bastieri D, Bi XJ, Bi YJ, Cai JT, Cao Z, Chang J, Chang JF, Chen ES, Chen L, Chen L, Chen L, Chen MJ, Chen ML, Chen QH, Chen SH, Chen SZ, Chen TL, Chen Y, Cheng HL, Cheng N, Cheng YD, Cui SW, Cui XH, Cui YD, D'Ettorre Piazzoli B, Dai BZ, Dai HL, Dai ZG, Della Volpe D, Duan KK, Fan JH, Fan YZ, Fan ZX, Fang J, Fang K, Feng CF, Feng L, Feng SH, Feng XT, Feng YL, Gao B, Gao CD, Gao LQ, Gao Q, Gao W, Gao WK, Ge MM, Geng LS, Gong GH, Gou QB, Gu MH, Guo FL, Guo JG, Guo XL, Guo YQ, Guo YY, Han YA, He HH, He HN, He SL, He XB, He Y, Heller M, Hor YK, Hou C, Hou X, Hu HB, Hu Q, Hu S, Hu SC, Hu XJ, Huang DH, Huang WH, Huang XT, Huang XY, Huang Y, Huang ZC, Ji XL, Jia HY, Jia K, Jiang K, Jiang ZJ, Jin M, Kang MM, Ke T, Kuleshov D, Levochkin K, Li BB, Li C, Li C, Li F, Li HB, Li HC, Li HY, Li J, Li J, Li J, Li K, Li WL, Li XR, Li X, Li X, Li YZ, Li Z, Li Z, Liang EW, Liang YF, Lin SJ, Liu B, Liu C, Liu D, Liu H, Liu HD, Liu J, Liu JL, Liu JS, Liu JY, Liu MY, Liu RY, Liu SM, Liu W, Liu Y, Liu YN, Long WJ, Lu R, Luo Q, Lv HK, Ma BQ, Ma LL, Ma XH, Mao JR, Masood A, Min Z, Mitthumsiri W, Nan YC, Ou ZW, Pang BY, Pattarakijwanich P, Pei ZY, Qi MY, Qi YQ, Qiao BQ, Qin JJ, Ruffolo D, Sáiz A, Shao CY, Shao L, Shchegolev O, Sheng XD, Shi JY, Song HC, Stenkin YV, Stepanov V, Su Y, Sun QN, Sun XN, Sun ZB, Tam PHT, Tang ZB, Tian WW, Wang BD, Wang C, Wang H, Wang HG, Wang JC, Wang JS, Wang LP, Wang LY, Wang R, Wang RN, Wang W, Wang XG, Wang XY, Wang Y, Wang YD, Wang YJ, Wang YP, Wang ZH, Wang ZX, Wang Z, Wang Z, Wei DM, Wei JJ, Wei YJ, Wen T, Wu CY, Wu HR, Wu S, Wu XF, Wu YS, Xi SQ, Xia J, Xia JJ, Xiang GM, Xiao DX, Xiao G, Xin GG, Xin YL, Xing Y, Xiong Z, Xu DL, Xu RX, Xue L, Yan DH, Yan JZ, Yang CW, Yang FF, Yang HW, Yang JY, Yang LL, Yang MJ, Yang RZ, Yang SB, Yao YH, Yao ZG, Ye YM, Yin LQ, Yin N, You XH, You ZY, Yu YH, Yuan Q, Yue H, Zeng HD, Zeng TX, Zeng W, Zeng ZK, Zha M, Zhai XX, Zhang BB, Zhang F, Zhang HM, Zhang HY, Zhang JL, Zhang LX, Zhang L, Zhang L, Zhang PF, Zhang PP, Zhang R, Zhang SB, Zhang SR, Zhang SS, Zhang X, Zhang XP, Zhang YF, Zhang YL, Zhang Y, Zhang Y, Zhao B, Zhao J, Zhao L, Zhao LZ, Zhao SP, Zheng F, Zheng Y, Zhou B, Zhou H, Zhou JN, Zhou P, Zhou R, Zhou XX, Zhu CG, Zhu FR, Zhu H, Zhu KJ, Zuo X, Ando S, Chianese M, Fiorillo DFG, Miele G, Ng KCY. Constraints on Heavy Decaying Dark Matter from 570 Days of LHAASO Observations. PHYSICAL REVIEW LETTERS 2022; 129:261103. [PMID: 36608208 DOI: 10.1103/physrevlett.129.261103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 08/19/2022] [Accepted: 10/27/2022] [Indexed: 06/17/2023]
Abstract
The kilometer square array (KM2A) of the large high altitude air shower observatory (LHAASO) aims at surveying the northern γ-ray sky at energies above 10 TeV with unprecedented sensitivity. γ-ray observations have long been one of the most powerful tools for dark matter searches, as, e.g., high-energy γ rays could be produced by the decays of heavy dark matter particles. In this Letter, we present the first dark matter analysis with LHAASO-KM2A, using the first 340 days of data from 1/2-KM2A and 230 days of data from 3/4-KM2A. Several regions of interest are used to search for a signal and account for the residual cosmic-ray background after γ/hadron separation. We find no excess of dark matter signals, and thus place some of the strongest γ-ray constraints on the lifetime of heavy dark matter particles with mass between 10^{5} and 10^{9} GeV. Our results with LHAASO are robust, and have important implications for dark matter interpretations of the diffuse astrophysical high-energy neutrino emission.
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Hu S, Khoury P, Akuthota P, Baylis L, Chang S, Wechsler M, Bentley J. Efficacité du mépolizumab chez les patients atteints de GEPA en fonction de l’impact du traitement à l’inclusion, de la durée de la maladie et du statut réfractaire. Rev Med Interne 2022. [DOI: 10.1016/j.revmed.2022.10.338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Duggal M, Gizani S, Albadri S, Krämer N, Stratigaki E, Tong HJ, Seremidi K, Kloukos D, BaniHani A, Santamaría RM, Hu S, Maden M, Amend S, Boutsiouki C, Bekes K, Lygidakis N, Frankenberger R, Monteiro J, Anttonnen V, Leith R, Sobczak M, Rajasekharan S, Parekh S. Best clinical practice guidance for treating deep carious lesions in primary teeth: an EAPD policy document. Eur Arch Paediatr Dent 2022; 23:659-666. [PMID: 36219336 PMCID: PMC9637614 DOI: 10.1007/s40368-022-00718-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 05/05/2022] [Indexed: 11/25/2022]
Abstract
Purpose The European Academy of Paediatric Dentistry (EAPD) has developed this best clinical practice guidance to help clinicians manage deep carious lesions in primary teeth. Methods Three expert groups conducted systematic reviews of the relevant literature. The topics were: (1) conventional techniques (2) Minimal Intervention Dentistry (MID) and (3) materials. Workshops were held during the corresponding EAPD interim seminar in Oslo in April 2021. Several clinical based recommendations and statements were agreed upon, and gaps in our knowledge were identified. Results There is strong evidence that indirect pulp capping and pulpotomy techniques, and 38% Silver Diamine Fluoride are shown to be effective for the management of caries in the primary dentition. Due to the strict criteria, it is not possible to give clear recommendations on which materials are most appropriate for restoring primary teeth with deep carious lesions. Atraumatic Restorative Technique (ART) is not suitable for multi-surface caries, and Pre-formed Metal Crowns (PMCs) using the Hall technique reduce patient discomfort. GIC and RMGIC seem to be more favourable given the lower annual failure rate compared to HVGIC and MRGIC. Glass carbomer cannot be recommended due to inferior marginal adaptation and fractures. Compomers, hybrid composite resins and bulk-fill composite resins demonstrated similar values for annual failure rates. Conclusion The management of deep carious lesions in primary teeth can be challenging and must consider the patient’s compliance, operator skills, materials and costs. There is a clear need to increase the use of MID techniques in managing carious primary teeth as a mainstream rather than a compromise option.
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Alnemy S, Rajagopal N, Perera P, Shawgo R, Dworakowski W, LaPlaca D, Carulli J, Chuaqui C, Hu S, Moebius D. Combination of CDK12 inhibition and olaparib enhances genomic instability in cancer models. Eur J Cancer 2022. [DOI: 10.1016/s0959-8049(22)00943-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Aharonian F, An Q, Axikegu, Bai LX, Bai YX, Bao YW, Bastieri D, Bi XJ, Bi YJ, Cai JT, Cao Z, Cao Z, Chang J, Chang JF, Chen ES, Chen L, Chen L, Chen L, Chen MJ, Chen ML, Chen QH, Chen SH, Chen SZ, Chen TL, Chen Y, Cheng HL, Cheng N, Cheng YD, Cui SW, Cui XH, Cui YD, D’Ettorre Piazzoli B, Dai BZ, Dai HL, Dai ZG, Danzengluobu, della Volpe D, Duan KK, Fan JH, Fan YZ, Fan ZX, Fang J, Fang K, Feng CF, Feng L, Feng SH, Feng XT, Feng YL, Gao B, Gao CD, Gao LQ, Gao Q, Gao W, Gao WK, Ge MM, Geng LS, Gong GH, Gou QB, Gu MH, Guo FL, Guo JG, Guo XL, Guo YQ, Guo YY, Han YA, He HH, He HN, He SL, He XB, He Y, Heller M, Hor YK, Hou C, Hou X, Hu HB, Hu Q, Hu S, Hu SC, Hu XJ, Huang DH, Huang WH, Huang XT, Huang XY, Huang Y, Huang ZC, Ji XL, Jia HY, Jia K, Jiang K, Jiang ZJ, Jin M, Kang MM, Ke T, Kuleshov D, Levochkin K, Li BB, Li C, Li C, Li F, Li HB, Li HC, Li HY, Li J, Li J, Li J, Li K, Li WL, Li XR, Li X, Li X, Li YZ, Li Z, Li Z, Liang EW, Liang YF, Lin SJ, Liu B, Liu C, Liu D, Liu H, Liu HD, Liu J, Liu JL, Liu JS, Liu JY, Liu MY, Liu RY, Liu SM, Liu W, Liu Y, Liu YN, Long WJ, Lu R, Luo Q, Lv HK, Ma BQ, Ma LL, Ma XH, Mao JR, Masood A, Min Z, Mitthumsiri W, Nan YC, Ou ZW, Pang BY, Pattarakijwanich P, Pei ZY, Qi MY, Qi YQ, Qiao BQ, Qin JJ, Ruffolo D, Sáiz A, Shao CY, Shao L, Shchegolev O, Sheng XD, Shi JY, Song HC, Stenkin YV, Stepanov V, Su Y, Sun QN, Sun XN, Sun ZB, Tam PHT, Tang ZB, Tian WW, Wang BD, Wang C, Wang H, Wang HG, Wang JC, Wang JS, Wang LP, Wang LY, Wang R, Wang RN, Wang W, Wang XG, Wang XY, Wang Y, Wang YD, Wang YJ, Wang YP, Wang ZH, Wang ZX, Wang Z, Wang Z, Wei DM, Wei JJ, Wei YJ, Wen T, Wu CY, Wu HR, Wu S, Wu XF, Wu YS, Xi SQ, Xia J, Xia JJ, Xiang GM, Xiao DX, Xiao G, Xin GG, Xin YL, Xing Y, Xiong Z, Xu DL, Xu RX, Xue L, Yan DH, Yan JZ, Yang CW, Yang FF, Yang HW, Yang JY, Yang LL, Yang MJ, Yang RZ, Yang SB, Yao YH, Yao ZG, Ye YM, Yin LQ, Yin N, You XH, You ZY, Yu YH, Yuan Q, Yue H, Zeng HD, Zeng TX, Zeng W, Zeng ZK, Zha M, Zhai XX, Zhang BB, Zhang F, Zhang HM, Zhang HY, Zhang JL, Zhang LX, Zhang L, Zhang L, Zhang PF, Zhang PP, Zhang R, Zhang SB, Zhang SR, Zhang SS, Zhang X, Zhang XP, Zhang YF, Zhang YL, Zhang Y, Zhang Y, Zhao B, Zhao J, Zhao L, Zhao LZ, Zhao SP, Zheng F, Zheng Y, Zhou B, Zhou H, Zhou JN, Zhou P, Zhou R, Zhou XX, Zhu CG, Zhu FR, Zhu H, Zhu KJ, Zuo X. Reconstruction of Cherenkov image by multiple telescopes of LHAASO-WFCTA. RADIATION DETECTION TECHNOLOGY AND METHODS 2022. [DOI: 10.1007/s41605-022-00342-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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Zhou C, Huang D, Fan Y, Yu X, Liu Y, Shu Y, Ma Z, Wang Z, Cheng Y, Wang J, Hu S, Liu Z, Poddubskaya E, Disel U, Akopov A, Dvorkin M, Wang Y, Li S, Yu C, Rivalland G. EP08.01-014 Tislelizumab versus Docetaxel in Previously Treated Advanced Non-Small Cell Lung Cancer: Final Analysis of RATIONALE-303. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Zhao Y, Chen G, Li X, Wu J, Chang B, Hu S, Yang S, Liu Y, Wang N, Huang Y, Zhang L. 1029P Two-year follow-up from KN046 in combination with platinum doublet chemotherapy as first-line (1L) treatment for NSCLC: An open-label, multi-center phase II trial. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.1155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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Zhou C, Huang D, Fan Y, Yu X, Liu Y, Shu Y, Ma Z, Wang Z, Cheng Y, Wang J, Hu S, Poddubskaya E, Disel U, Akopov A, Dvorkin M, Wang Y, Ghassemifar S, Li S, Rivalland G. 1031P Tislelizumab (TIS) versus docetaxel (TAX) as second- or third-line therapy in previously treated patients (pts) with locally advanced non-small cell lung cancer (NSCLC): Asian versus non-Asian subgroup analysis of the RATIONALE-303 study. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.1157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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Quek JS, Lai B, Yap AU, Hu S. Non-pharmacological management of dental fear and anxiety in children and adolescents: An umbrella review. EUROPEAN JOURNAL OF PAEDIATRIC DENTISTRY 2022; 23:230-242. [PMID: 36172904 DOI: 10.23804/ejpd.2022.23.03.11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
AIM To synthesise knowledge on the relative efficacies of non-pharmacological strategies for managing dental fear and anxiety (DFA) in children and adolescents, specifically their effects on behaviour, anxiety levels and pain perception. METHODS An umbrella review on non-pharmacological strategies used to manage DFA in children and adolescents was conducted based the Joanna Briggs Institute methodology. Searches were performed in 5 main electronic databases and the grey-literature. Two independent reviewers selected and appraised the included studies using the AMSTAR2 tool. Disagreements were resolved by a third reviewer. CONCLUSION Audio-visual distraction was effective in reducing anxiety during a variety of dental procedures including those requiring local anaesthesia. A combination of techniques may be more effective in managing DFA in children and adolescents, possibly improving pain perception and cooperative behaviour.
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Zhao GY, Dai P, Hu S, Jiao ZH, Kong XD. [Analysis of the factors influencing positive predictive value of noninvasive prenatal testing for chromosome aneuploidies]. ZHONGHUA YI XUE ZA ZHI 2022; 102:2452-2457. [PMID: 36000375 DOI: 10.3760/cma.j.cn112137-20211215-02802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To investigate the influence of Z-score and different risk factors on positive predictive value (PPV) of noninvasive prenatal testing (NIPT) for chromosome aneuploidies. Methods: A total of 81 838 NIPT samples from January 1, 2016 to May 31, 2021 in the First Affiliated Hospital of Zhengzhou University were retrospectively analyzed. Invasive prenatal diagnosis was applied to verify the diagnosis of NIPT-positive results and the corresponding PPV was calculated. The PPV of the samples with different Z-score were compared. The women were divided into high-risk group and non-high-risk group: high-risk group (n=39 114) included those with ultrasound soft index abnormalities, advanced maternal age or high risk for maternal serum screening, while non-high-risk group (n=42 724) included those with intermediate risk for maternal serum screening or no indications. The differences of the PPV between these two groups were compared. Finally, the comprehensive influence of Z-score and different risk factors on PPV were analyzed. Results: A total of 471 high-risk cases were detected by NIPT results, including 362 cases of trisomy 21, 77 cases of trisomy 18 and 32 cases of trisomy 13. For trisomy 21, trisomy 18 and trisomy 13, there were 226 cases, 46 cases and 6 cases which were confirmed via invasive prenatal diagnosis respectively. The corresponding PPV were 79.3% (226/285), 82.1% (46/56) and 27.3% (6/22), respectively. PPV of trisomy 21 and trisomy 18 were positively correlated with the corresponding Z-score (r=0.92, 0.62, all P<0.05), while trisomy 13 could not be analyzed due to the small sample size. The PPV of high-risk group was 85.2% (207/243), which was higher than that of the non-high-risk group with PPV of 59.2%(71/120, χ2=30.30, P<0.01). When the Z-score was between 3-<4 and 4-<5, the PPV of the high-risk group were 46.2%(12/26)and 62.5%(15/24) respectively, which were higher than those of the non-high-risk group [16.0%(4/25) and 14.3%(3/21), χ2=4.10, 8.90, all P<0.05]. With the increase of Z-score, there was no significant difference in PPV between the two groups (all P>0.05). Conclusions: The PPV of trisomy 21 and trisomy 18 are positively correlated with Z-score. The PPV of high-risk group is higher than that of non-high-risk group. The combination of Z-score and other risk factors may provide more accurate genetic counseling for those with NIPT positive results.
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Aad G, Abbott B, Abbott DC, Abed Abud A, Abeling K, Abhayasinghe DK, Abidi SH, Aboulhorma A, Abramowicz H, Abreu H, Abulaiti Y, Abusleme Hoffman AC, Acharya BS, Achkar B, Adam L, Adam Bourdarios C, Adamczyk L, Adamek L, Addepalli SV, Adelman J, Adiguzel A, Adorni S, Adye T, Affolder AA, Afik Y, Agapopoulou C, Agaras MN, Agarwala J, Aggarwal A, Agheorghiesei C, Aguilar-Saavedra JA, Ahmad A, Ahmadov F, Ahmed WS, Ai X, Aielli G, Aizenberg I, Akbiyik M, Åkesson TPA, Akimov AV, Al Khoury K, Alberghi GL, Albert J, Albicocco P, Alconada Verzini MJ, Alderweireldt S, Aleksa M, Aleksandrov IN, Alexa C, Alexopoulos T, Alfonsi A, Alfonsi F, Alhroob M, Ali B, Ali S, Aliev M, Alimonti G, Allaire C, Allbrooke BMM, Allport PP, Aloisio A, Alonso F, Alpigiani C, Alunno Camelia E, Alvarez Estevez M, Alviggi MG, Amaral Coutinho Y, Ambler A, Ambroz L, Amelung C, Amidei D, Amor Dos Santos SP, Amoroso S, Amos KR, Amrouche CS, Ananiev V, Anastopoulos C, Andari N, Andeen T, Anders JK, Andrean SY, Andreazza A, Angelidakis S, Angerami A, Anisenkov AV, Annovi A, Antel C, Anthony MT, Antipov E, Antonelli M, Antrim DJA, Anulli F, Aoki M, Aparisi Pozo JA, Aparo MA, Aperio Bella L, Aranzabal N, Araujo Ferraz V, Arcangeletti C, Arce ATH, Arena E, Arguin JF, Argyropoulos S, Arling JH, Armbruster AJ, Arnaez O, Arnold H, Arrubarrena Tame ZP, Artoni G, Asada H, Asai K, Asai S, Asbah NA, Asimakopoulou EM, Assahsah J, Assamagan K, Astalos R, Atkin RJ, Atkinson M, Atlay NB, Atmani H, Atmasiddha PA, Augsten K, Auricchio S, Austrup VA, Avner G, Avolio G, Ayoub MK, Azuelos G, Babal D, Bachacou H, Bachas K, Bachiu A, Backman F, Badea A, Bagnaia P, Bahmani M, Bailey AJ, Bailey VR, Baines JT, Bakalis C, Baker OK, Bakker PJ, Bakos E, Bakshi Gupta D, Balaji S, 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, Barberio EL, Barberis D, Barbero M, Barbour G, Barends KN, Barillari T, Barisits MS, Barkeloo J, Barklow T, Barnett RM, Baron P, Baroncelli A, Barone G, Barr AJ, Barranco Navarro L, Barreiro F, Barreiro Guimarães da Costa J, Barron U, Barsov S, Bartels F, Bartoldus R, Bartolini G, Barton AE, Bartos P, Basalaev A, Basan A, Baselga M, Bashta I, Bassalat A, Basso MJ, Basson CR, Bates RL, Batlamous S, Batley JR, Batool B, Battaglia M, Bauce M, Bauer F, Bauer P, Bayirli A, Beacham JB, Beau T, Beauchemin PH, Becherer F, Bechtle P, Beck HP, Becker K, Becot C, Beddall AJ, Bednyakov VA, Bee CP, Beemster LJ, Beermann TA, Begalli M, Begel M, Behera A, Behr JK, Beirao Da Cruz E Silva C, Beirer JF, Beisiegel F, Belfkir M, Bella G, Bellagamba L, Bellerive A, Bellos P, Beloborodov K, Belotskiy K, Belyaev NL, Benchekroun D, Benhammou Y, Benjamin DP, Benoit M, Bensinger JR, Bentvelsen S, Beresford L, Beretta M, Berge D, Bergeaas Kuutmann E, Berger N, Bergmann B, Bergsten LJ, Beringer J, Berlendis S, Bernardi G, Bernius C, Bernlochner FU, Berry T, Berta P, Bertram IA, Bessidskaia Bylund O, Bethke S, Betti A, Bevan AJ, Bhatta S, Bhattacharya DS, Bhattarai P, Bhopatkar VS, Bi R, Bi R, Bianchi RM, Biebel O, Bielski R, Biesuz NV, Biglietti M, Billoud TRV, Bindi M, Bingul A, Bini C, Biondi S, Biondini A, Birch-Sykes CJ, Bird GA, Birman M, Bisanz T, Biswal JP, Biswas D, Bitadze A, Bjørke K, Bloch I, Blocker C, Blue A, Blumenschein U, Blumenthal J, Bobbink GJ, Bobrovnikov VS, Boehler M, Bogavac D, Bogdanchikov AG, Bohm C, Boisvert V, Bokan P, Bold T, Bomben M, Bona M, Boonekamp M, Booth CD, Borbély AG, Borecka-Bielska HM, Borgna LS, Borissov G, Bortoletto D, Boscherini D, Bosman M, Bossio Sola JD, Bouaouda K, 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, Breaden Madden WD, Brendlinger K, Brener R, Brenner L, Brenner R, Bressler S, Brickwedde B, Britton D, Britzger D, Brock I, Brooijmans G, Brooks WK, Brost E, Bruckman de Renstrom PA, Brüers B, Bruncko D, Bruni A, Bruni G, Bruschi M, Bruscino N, Bryngemark L, Buanes T, Buat Q, Buchholz P, Buckley AG, Budagov IA, Bugge MK, Bulekov O, Bullard BA, Burdin S, Burgard CD, Burger AM, Burghgrave B, Burr JTP, Burton CD, Burzynski JC, Busch EL, Büscher V, Bussey PJ, Butler JM, Buttar CM, Butterworth JM, Buttinger W, Buxo Vazquez CJ, Buzykaev AR, Cabras G, Cabrera Urbán S, Caforio D, Cai H, Cairo VMM, Cakir O, Calace N, Calafiura P, Calderini G, Calfayan P, Callea G, Caloba LP, Calvet D, Calvet S, Calvet TP, Calvetti M, Camacho Toro R, Camarda S, Camarero Munoz D, Camarri P, Camerlingo MT, Cameron D, Camincher C, Campanelli M, Camplani A, Canale V, Canesse A, Cano Bret M, Cantero J, Cao Y, Capocasa F, Capua M, Carbone A, Cardarelli R, Cardenas JCJ, Cardillo F, Carducci G, Carli T, Carlino G, Carlson BT, Carlson EM, Carminati L, Carnesale M, Caron S, Carquin E, Carrá S, Carratta G, Carter JWS, Carter TM, Casadei D, Casado MP, Casha AF, Castiglia EG, Castillo FL, Castillo Garcia L, Castillo Gimenez V, Castro NF, Catinaccio A, Catmore JR, Cavaliere V, Cavalli N, Cavasinni V, Celebi E, Celli F, Centonze MS, Cerny K, Cerqueira AS, Cerri A, Cerrito L, Cerutti F, Cervelli A, Cetin SA, Chadi Z, Chakraborty D, Chala M, Chan J, Chan WS, Chan WY, Chapman JD, Chargeishvili B, Charlton DG, Charman TP, Chatterjee M, Chekanov S, Chekulaev SV, Chelkov GA, Chen A, Chen B, Chen B, Chen C, Chen H, Chen H, Chen J, Chen J, Chen S, Chen SJ, Chen X, Chen X, Chen Y, Cheng CL, Cheng HC, Cheplakov A, Cheremushkina E, Cherepanova E, Cherkaoui El Moursli R, Cheu E, Cheung K, Chevalier L, Chiarella V, Chiarelli G, Chiodini G, Chisholm AS, Chitan A, Chiu YH, Chizhov MV, Choi K, Chomont AR, Chou Y, Chow EYS, Chowdhury T, Christopher LD, Chu MC, Chu X, Chudoba J, Chwastowski JJ, Cieri D, Ciesla KM, Cindro V, Ciocio A, Cirotto F, Citron ZH, Citterio M, Ciubotaru DA, Ciungu BM, Clark A, Clark PJ, Clavijo Columbie JM, Clawson SE, Clement C, Clissa L, Coadou Y, Cobal M, Coccaro A, Barrue RFC, Coelho Lopes De Sa R, Coelli S, 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Observation of WWW Production in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector. PHYSICAL REVIEW LETTERS 2022; 129:061803. [PMID: 36018638 DOI: 10.1103/physrevlett.129.061803] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 06/23/2022] [Indexed: 06/15/2023]
Abstract
This Letter reports the observation of WWW production and a measurement of its cross section using 139 fb^{-1} of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. Events with two same-sign leptons (electrons or muons) and at least two jets, as well as events with three charged leptons, are selected. A multivariate technique is then used to discriminate between signal and background events. Events from WWW production are observed with a significance of 8.0 standard deviations, where the expectation is 5.4 standard deviations. The inclusive WWW production cross section is measured to be 820±100 (stat)±80 (syst) fb, approximately 2.6 standard deviations from the predicted cross section of 511±18 fb calculated at next-to-leading-order QCD and leading-order electroweak accuracy.
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