Role of cosyntropin in the prevention of post-dural puncture headache: a propensity-matched retrospective analysis

BACKGROUND

Post-dural puncture headache (PDPH) is a well-documented complication of accidental dural puncture in obstetric patients. Reports have shown successful treatment with adrenocorticotropic hormone (ACTH) but evidence remains low and limited. In this retrospective analysis, we assessed whether prophylactic administration of cosyntropin, a synthetic derivative of ACTH, reduced the incidence of PDPH after accidental dural puncture in parturients.

METHOD

The study population included 132 women with an accidental dural puncture over a three-year period (June 1, 2018 to Oct 31, 2021) at a large tertiary-care center. Patient electronic medical records were reviewed for patient characteristics, prophylactic administration of cosyntropin, PDPH diagnosis, and need for epidural blood patch. Typically, 1 mg of cosyntropin was administered as an intravenous bolus or infusion post-delivery. The propensity score was calculated based on the following factors: age, body mass index, and placement of an intrathecal catheter. Patients were matched allowing 10% variation in scores to reduce potential treatment assignment bias.

RESULTS

A total of 115 patients were included in the final analysis. Intravenous cosyntropin was administered to 65 patients (55.6%). Among those who received cosyntropin, 37 (56.9%) developed PDPH compared with 29 patients (58%) in the no-cosyntropin group (P = 0.08). Epidural blood patch was performed in 21 patients (56.8%) who received cosyntropin and 13 patients (61.7%) who did not (P = 0.70).

CONCLUSION

Prophylactic administration of cosyntropin is not associated with a reduced incidence of PDPH.

A prognostic nomogram for predicting recurrence-free survival of stage I-III colon cancer based on immune-infiltrating Treg-related genes

PURPOSE

A high postoperative recurrence rate seriously impedes colon cancer (CC) patients from achieving long-term survival. Here, we aimed to develop a Treg-related classifier that can help predict recurrence-free survival (RFS) and therapy benefits of stage I-III colon cancer.

METHODS

A Treg-related prognostic classifier was built through a variety of bioinformatic methods, whose performance was assessed by KM survival curves, time-dependent receiver operating characteristic (tROC), and Harrell's concordance index (C-index). A prognostic nomogram was generated using this classifier and other traditional clinical parameters. Moreover, the predictive values of this classifier for immunotherapy and chemotherapy therapeutic efficacy were tested using multiple immunotherapy sets and R package "pRRophetic".

RESULTS

A nine Treg-related classifier categorized CC patients into high- and low-risk groups with distinct RFS in the multiple datasets (all p < 0.05). The AUC values of 5-year RFS were 0.712, 0.588, 0.669, and 0.662 in the training, 1st, 2nd, and entire validation sets, respectively. Furthermore, this classifier was identified as an independent predictor of RFS. Finally, a nomogram combining this classifier and three clinical variables was generated, the analysis of tROC, C-index, calibration curves, and the comparative analysis with other signatures confirmed its predictive performance. Moreover, KM analysis exhibited an obvious discrepancy in the subgroups, especially in different TNM stages and with adjuvant chemotherapy. We detected the difference between the two risk subsets of immune cell sub-population and the response to immunotherapy and chemotherapy.

CONCLUSIONS

We built a robust Treg-related classifier and generated a prognostic nomogram that predicts recurrence-free survival in stage I-III colon cancer that can identify high-risk patients for more personalized and effective therapy.

Comparison of the clinical characteristics of SARS-CoV-2 Delta (B.1.617.2) and Omicron (B.1.1.529) infected patients from a single hospitalist service

BACKGROUND

While existing evidence suggests less severe clinical manifestations and lower mortality are associated with the Omicron variant as compared to the Delta variant. However, these studies fail to control for differences in health systems facilities and providers. By comparing patients hospitalized on a single medical service during the Delta and Omicron surges we were able to conduct a more accurate comparison of the two varaints' clinical manifestations and outcomes.

METHODS

We conducted a prospective study of 364 Omicron (BA.1) infected patients on a single hospitalist service and compared these findings to a retrospective analysis of 241 Delta variant infected patients managed on the same service. We examined differences in symptoms, laboratory measures, and clinical severity between the two variants and assessed potential risk drivers for case mortality.

FINDINGS

Patients infected with Omicron were older and had more underlying medical conditions increasing their risk of death. Although they were less severely ill and required less supplemental oxygen and dexamethasone, in-hospital mortality was similar to Delta cases, 7.14% vs. 4.98% for Delta (q-value = 0.38). Patients older than 60 years or with immunocompromised conditions had much higher risk of death during hospitalization, with estimated odds ratios of 17.46 (95% CI: 5.05, 110.51) and 2.80 (1.03, 7.08) respectively. Neither vaccine history nor variant type played a significant role in case fatality. The Rothman score, NEWS-2 score, level of neutrophils, level of care, age, and creatinine level at admission were highly predictive of in-hospital death.

INTERPRETATION

In hospitalized patients, the Omicron variant is less virulent than the Delta variant but is associated with a comparable mortality. Clinical and laboratory features at admission are informative about the risk of death.

Long-cycle Zn-air batteries at high depth of discharge enabled by a robust Zn|electrolyte interface

It is an urgent need to improve the depth of discharge (DOD) of Zn-air batteries (ZABs), considering that most reported ZABs with long cycle life are realized at low DOD (<1%). In this work, our solid-state ZABs achieved a long cycle life of more than 220 h at 3.2% DOD (the discharge capacity of 10 mA h cm-2 per cycle). Moreover, benefiting from excellent bifunctional oxygen electrocatalysts (Fe@BNC) and robust Zn|electrolyte interface, the ZABs displayed a long cycle life of 120 h even at high DOD of 23.4% and large discharge capacity of 72 mA h cm-2. Additionally, the impact of Zn|electrolyte interface on the cycle time at different DODs is analysed and discussed. The unstable interface exacerbated the dendrite growth and uneven deposition of Zn at high DOD, leading to the decay of the cycle life. The work gives insights into the mechanism of the effect of DOD on the cycle life of the batteries.

Measurement of Suppression of Large-Radius Jets and Its Dependence on Substructure in Pb+Pb Collisions at sqrt[s_{NN}]=5.02 TeV with the ATLAS Detector

This letter presents a measurement of the nuclear modification factor of large-radius jets in sqrt[s_{NN}]=5.02  TeV Pb+Pb collisions by the ATLAS experiment. The measurement is performed using 1.72  nb^{-1} and 257  pb^{-1} of Pb+Pb and pp data, respectively. The large-radius jets are reconstructed with the anti-k_{t} algorithm using a radius parameter of R=1.0, by reclustering anti-k_{t} R=0.2 jets, and are measured over the transverse momentum (p_{T}) kinematic range of 158 Collapse

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Measurement of the top quark mass using a profile likelihood approach with the lepton + jets final states in proton-proton collisions at s=13TeV

The mass of the top quark is measured in 36.3fb - 1 of LHC proton-proton collision data collected with the CMS detector at s = 13 Te V . The measurement uses a sample of top quark pair candidate events containing one isolated electron or muon and at least four jets in the final state. For each event, the mass is reconstructed from a kinematic fit of the decay products to a top quark pair hypothesis. A profile likelihood method is applied using up to four observables per event to extract the top quark mass. The top quark mass is measured to be 171.77 ± 0.37 Ge V . This approach significantly improves the precision over previous measurements.

Measurement of the Sensitivity of Two-Particle Correlations in pp Collisions to the Presence of Hard Scatterings

A key open question in the study of multiparticle production in high-energy pp collisions is the relationship between the "ridge"-i.e., the observed azimuthal correlations between particles in the underlying event that extend over all rapidities-and hard or semihard scattering processes. In particular, it is not known whether jets or their soft fragments are correlated with particles in the underlying event. To address this question, two-particle correlations are measured in pp collisions at sqrt[s]=13  TeV using data collected by the ATLAS experiment at the LHC, with an integrated luminosity of 15.8  pb^{-1}, in two different configurations. In the first case, charged particles associated with jets are excluded from the correlation analysis, while in the second case, correlations are measured between particles within jets and charged particles from the underlying event. Second-order flow coefficients, v_{2}, are presented as a function of event multiplicity and transverse momentum. These measurements show that excluding particles associated with jets does not affect the measured correlations. Moreover, particles associated with jets do not exhibit any significant azimuthal correlations with the underlying event, ruling out hard processes contributing to the ridge.

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Cox PT, Erbacher R, Haza G, Jensen F, Kukral O, Mocellin G, Mulhearn M, Pellett D, Regnery B, Yao Y, Zhang F, Bachtis M, Cousins R, Datta A, Hauser J, Ignatenko M, Iqbal M, Lam T, Manca E, Nash WA, Saltzberg D, Stone B, Valuev V, Clare R, Gary JW, Gordon M, Hanson G, Long OR, Manganelli N, Si W, Wimpenny S, Branson JG, Cittolin S, Cooperstein S, Diaz D, Duarte J, Gerosa R, Giannini L, Guiang J, Kansal R, Krutelyov V, Lee R, Letts J, Masciovecchio M, Mokhtar F, Pieri M, Quinnan M, Sathia Narayanan BV, Sharma V, Tadel M, Vourliotis E, Würthwein F, Xiang Y, Yagil A, Campagnari C, Citron M, Collura G, Dorsett A, Incandela J, Kilpatrick M, Kim J, Li AJ, Masterson P, Mei H, Oshiro M, Richman J, Sarica U, Schmitz R, Setti F, Sheplock J, Siddireddy P, Stuart D, Wang S, Bornheim A, Cerri O, Dutta I, Latorre A, Lawhorn JM, Mao J, Newman HB, Nguyen TQ, Spiropulu M, Vlimant JR, Wang C, Xie S, Zhu RY, Alison J, An S, Andrews MB, Bryant P, Dutta V, Ferguson T, Harilal A, Liu C, Mudholkar T, Murthy S, Paulini M, Roberts A, Sanchez A, Terrill W, Cumalat JP, Ford WT, Hassani A, Karathanasis G, MacDonald E, Marini F, Perloff A, Savard C, Schonbeck N, Stenson K, Ulmer KA, Wagner SR, Zipper N, Alexander J, Bright-Thonney S, Chen X, Cranshaw DJ, Fan J, Fan X, Gadkari D, Hogan S, Monroy J, Patterson JR, Reichert J, Reid M, Ryd A, Thom J, Wittich P, Zou R, Albrow M, Alyari M, Apollinari G, Apresyan A, Bauerdick LAT, Berry D, Berryhill J, Bhat PC, Burkett K, Butler JN, Canepa A, Cerati GB, Cheung HWK, Chlebana F, Di Petrillo KF, Dickinson J, Elvira VD, Feng Y, Freeman J, Gandrakota A, Gecse Z, Gray L, Green D, Grünendahl S, Guerrero D, Gutsche O, Harris RM, Heller R, Herwig TC, Hirschauer J, Horyn L, Jayatilaka B, Jindariani S, Johnson M, Joshi U, Klijnsma T, Klima B, Kwok KHM, Lammel S, Lincoln D, Lipton R, Liu T, Madrid C, Maeshima K, Mantilla C, Mason D, McBride P, Merkel P, Mrenna S, Nahn S, Ngadiuba J, Noonan D, Norberg S, Papadimitriou V, Pastika N, Pedro K, Pena C, Ravera F, Hall AR, Ristori L, Sexton-Kennedy E, Smith N, Soha A, Spiegel L, Strait J, Taylor L, Tkaczyk S, Tran NV, Uplegger L, Vaandering EW, Zoi I, Avery P, Bourilkov D, Cadamuro L, Chang P, Cherepanov V, Field RD, Koenig E, Kolosova M, Konigsberg J, Korytov A, Kuznetsova E, Lo KH, Matchev K, Menendez N, Mitselmakher G, Muthirakalayil Madhu A, Rawal N, Rosenzweig D, Rosenzweig S, Shi K, Wang J, Wu Z, Adams T, Askew A, Bower N, Habibullah R, Hagopian V, Kolberg T, Martinez G, Prosper H, Viazlo O, Wulansatiti M, Yohay R, Zhang J, Baarmand MM, Butalla S, Elkafrawy T, Hohlmann M, Kumar Verma R, Rahmani M, Yumiceva F, Adams MR, Cavanaugh R, Dittmer S, Evdokimov O, Gerber CE, Hofman DJ, Lemos DS, Merrit AH, Mills C, Oh G, Roy T, Rudrabhatla S, Tonjes MB, Varelas N, Wang X, Ye Z, Yoo J, Alhusseini M, Dilsiz K, Emediato L, Karaman G, Köseyan OK, Merlo JP, Mestvirishvili A, Nachtman J, Neogi O, Ogul H, Onel Y, Penzo A, Snyder C, Tiras E, Amram O, Blumenfeld B, Corcodilos L, Davis J, Gritsan AV, Kyriacou S, Maksimovic P, Roskes J, Sekhar S, Swartz M, Vámi T, Abreu A, Alcerro Alcerro LF, Anguiano J, Baringer P, Bean A, Flowers Z, King J, Krintiras G, Lazarovits M, Le Mahieu C, Lindsey C, Marquez J, Minafra N, Murray M, Nickel M, Rogan C, Royon C, Salvatico R, Sanders S, Smith C, Wang Q, Wilson G, Allmond B, Duric S, Ivanov A, Kaadze K, Kalogeropoulos A, Kim D, Maravin Y, Mitchell T, Modak A, Nam K, Roy D, Rebassoo F, Wright D, Adams E, Baden A, Baron O, Belloni A, Bethani A, Eno SC, Hadley NJ, Jabeen S, Kellogg RG, Koeth T, Lai Y, Lascio S, Mignerey AC, Nabili S, Palmer C, Papageorgakis C, Wang L, Wong K, Busza W, Cali IA, Chen Y, D’Alfonso M, Eysermans J, Freer C, Gomez-Ceballos G, Goncharov M, Harris P, Kovalskyi D, Krupa J, Lee YJ, Long K, Mironov C, Paus C, Rankin D, Roland C, Roland G, Shi Z, Stephans GSF, Wang J, Wang Z, Wyslouch B, Yang TJ, Chatterjee RM, Crossman B, Hiltbrand J, Joshi BM, Kapsiak C, Krohn M, Kubota Y, Mahon D, Mans J, Revering M, Rusack R, Saradhy R, Schroeder N, Strobbe N, Wadud MA, Cremaldi LM, Bloom K, Bryson M, Claes DR, Fangmeier C, Finco L, Golf F, Joo C, Kamalieddin R, Kravchenko I, Reed I, Siado JE, Snow GR, Tabb W, Wightman A, Yan F, Zecchinelli AG, Agarwal G, Bandyopadhyay H, Hay L, Iashvili I, Kharchilava A, McLean C, Morris M, Nguyen D, Pekkanen J, Rappoccio S, Williams A, Alverson G, Barberis E, Haddad Y, Han Y, Krishna A, Li J, Lidrych J, Madigan G, Marzocchi B, Morse DM, Nguyen V, Orimoto T, Parker A, Skinnari L, Tishelman-Charny A, Wamorkar T, Wang B, Wisecarver A, Wood D, Bhattacharya S, Bueghly J, Chen Z, Gilbert A, Hahn KA, Liu Y, Odell N, Schmitt MH, Velasco M, Band R, Bucci R, Cremonesi M, Das A, Goldouzian R, Hildreth M, Hurtado Anampa K, Jessop C, Lannon K, Lawrence J, Loukas N, Lutton L, Mariano J, Marinelli N, Mcalister I, McCauley T, Mcgrady C, Mohrman K, Moore C, Musienko Y, Ruchti R, Townsend A, Wayne M, Yockey H, Zarucki M, Zygala L, Bylsma B, Carrigan M, Durkin LS, Hill C, Joyce M, Lesauvage A, Nunez Ornelas M, Wei K, Winer BL, Yates BR, Addesa FM, Das P, Dezoort G, Elmer P, Frankenthal A, Greenberg B, Haubrich N, Higginbotham S, Kopp G, Kwan S, Lange D, Loeliger A, Marlow D, Ojalvo I, Olsen J, Stickland D, Tully C, Malik S, Bakshi AS, Barnes VE, Chawla R, Das S, Gutay L, Jones M, Jung AW, Kondratyev D, Koshy AM, Liu M, Negro G, Neumeister N, Paspalaki G, Piperov S, Purohit A, Schulte JF, Stojanovic M, Thieman J, Virdi AK, Wang F, Xiao R, Xie W, Dolen J, Parashar N, Acosta D, Baty A, Carnahan T, Dildick S, Ecklund KM, Fernández Manteca PJ, Freed S, Gardner P, Geurts FJM, Kumar A, Li W, Padley BP, Redjimi R, Rotter J, Yang S, Yigitbasi E, Zhang Y, Bodek A, de Barbaro P, Demina R, Dulemba JL, Fallon C, Garcia-Bellido A, Hindrichs O, Khukhunaishvili A, Parygin P, Popova E, Taus R, Van Onsem GP, Goulianos K, Chiarito B, Chou JP, Gershtein Y, Halkiadakis E, Hart A, Heindl M, Jaroslawski D, Karacheban O, Laflotte I, Lath A, Montalvo R, Nash K, Osherson M, Routray H, Salur S, Schnetzer S, Somalwar S, Stone R, Thayil SA, Thomas S, Wang H, Acharya H, Delannoy AG, Fiorendi S, Holmes T, Nibigira E, Spanier S, Bouhali O, Dalchenko M, Delgado A, Eusebi R, Gilmore J, Huang T, Kamon T, Kim H, Luo S, Malhotra S, Mueller R, Overton D, Rathjens D, Safonov A, Akchurin N, Damgov J, Hegde V, Lamichhane K, Lee SW, Mengke T, Muthumuni S, Peltola T, Volobouev I, Whitbeck A, Appelt E, Greene S, Gurrola A, Johns W, Melo A, Romeo F, Sheldon P, Tuo S, Velkovska J, Viinikainen J, Cardwell B, Cox B, Cummings G, Hakala J, Hirosky R, Ledovskoy A, Li A, Neu C, Perez Lara CE, Karchin PE, Aravind A, Banerjee S, Black K, Bose T, Dasu S, De Bruyn I, Everaerts P, Galloni C, He H, Herndon M, Herve A, Koraka CK, Lanaro A, Loveless R, Madhusudanan Sreekala J, Mallampalli A, Mohammadi A, Mondal S, Parida G, Pinna D, Savin A, Shang V, Sharma V, Smith WH, Teague D, Tsoi HF, Vetens W, Warden A, Afanasiev S, Andreev V, Andreev Y, Aushev T, Azarkin M, Babaev A, Belyaev A, Blinov V, Boos E, Borshch V, Budkouski D, Bunichev V, Chadeeva M, Chekhovsky V, Danilov M, Dermenev A, Dimova T, Dremin I, Dubinin M, Dudko L, Epshteyn V, Ershov A, Gavrilov G, Gavrilov V, Gninenko S, Golovtcov V, Golubev N, Golutvin I, Gorbunov I, Ivanov Y, Kachanov V, Kardapoltsev L, Karjavine V, Karneyeu A, Kim V, Kirakosyan M, Kirpichnikov D, Kirsanov M, Klyukhin V, Kodolova O, Konstantinov D, Korenkov V, Kozyrev A, Krasnikov N, Lanev A, Levchenko P, Litomin A, Lychkovskaya N, Makarenko V, Malakhov A, Matveev V, Murzin V, Nikitenko A, Obraztsov S, Oskin A, Ovtin I, Palichik V, Perelygin V, Perfilov M, Petrushanko S, Popov V, Radchenko O, Rusinov V, Savina M, Savrin V, Shalaev V, Shmatov S, Shulha S, Skovpen Y, Slabospitskii S, Smirnov V, Sosnov D, Sulimov V, Tcherniaev E, Terkulov A, Teryaev O, Tlisova I, Toropin A, Uvarov L, Uzunian A, Vorobyev A, Voytishin N, Yuldashev BS, Zarubin A, Zhizhin I, Zhokin A. A search for decays of the Higgs boson to invisible particles in events with a top-antitop quark pair or a vector boson in proton-proton collisions at s=13TeV

A search for decays to invisible particles of Higgs bosons produced in association with a top-antitop quark pair or a vector boson, which both decay to a fully hadronic final state, has been performed using proton-proton collision data collected at s = 13 Te V by the CMS experiment at the LHC, corresponding to an integrated luminosity of 138fb - 1 . The 95% confidence level upper limit set on the branching fraction of the 125Ge V Higgs boson to invisible particles, B ( H → inv ) , is 0.54 (0.39 expected), assuming standard model production cross sections. The results of this analysis are combined with previous B ( H → inv ) searches carried out at s = 7 , 8, and 13Te V in complementary production modes. The combined upper limit at 95% confidence level on B ( H → inv ) is 0.15 (0.08 expected).

A novel web-based prognostic nomogram and the features influencing the curative effect of chemotherapy and radiotherapy for Paget's disease with invasive ductal carcinoma

Paget's disease (PD) of the breast is a rare underlying malignant tumor. Approximately 50% to 60% of patients with mammary PD are concurrently diagnosed with invasive ductal carcinoma (PD-IDC), a condition associated with a worse prognosis than IDC without PD. Thus far, there has been a lack of an accurate and efficient prognostic model for PD-IDC, and the factors influencing the effectiveness of chemotherapy and radiotherapy for these patients remain unknown. In this study, we developed a web-based nomogram based on the data from the Surveillance Epidemiology and End Results (SEER) database. We subjected the model to a series of validation methods, including area under the curve (AUC) values, receiver operating characteristic curve (ROC) analysis, calibration curves, and decision curve analysis (DCA). Our results demonstrated that our model exhibited high discrimination, accuracy, and clinical applicability in predicting the overall survival (OS) of patients with PD-IDC (testing set: three- and five-year AUCs, 0.831 and 0.841, respectively). To further validate our nomogram, we used external data from both our institution and sister hospitals (external data: three- and five-year AUCs, 0.892 and 0.914, respectively). Multivariable Cox regression analysis identified several independent unfavorable prognostic factors for the OS of patients with PD-IDC, including increasing age, high grade, widowed status, higher T stages, and the presence of bone metastases. Furthermore, propensity score matching (PSM)-adjusted analysis was conducted, revealing that chemotherapy did not significantly improve the survival of patients with PD-IDC across molecular subtypes, except for those in the grade III/IV group, where it improved both OS and breast cancer-specific survival (BCSS). Additionally, our findings indicated that only patients with PD-IDC with T4 and N3 stages benefited from radiotherapy, leading to improvements in both OS and BCSS. In conclusion, we have comprehensively analyzed the clinical characteristics and prognosis of patients with PD-IDC, culminating in the development of a user-friendly web-based nomogram for predicting their survival. Our predictive model is not only highly accurate but also offers simplicity, making it accessible for healthcare providers and patients. Furthermore, our stratified analysis highlights that the pathological grade, rather than the molecular subtype, plays a pivotal role in determining the efficacy of chemotherapy in improving the prognosis for patients with PD-IDC, while radiotherapy confers survival benefits to patients with PD-IDC in T4 and N3 stages.

Observation of τ Lepton Pair Production in Ultraperipheral Pb-Pb Collisions at sqrt[s_{NN}]=5.02 TeV

We present an observation of photon-photon production of τ lepton pairs in ultraperipheral lead-lead collisions. The measurement is based on a data sample with an integrated luminosity of 404  μb^{-1} collected by the CMS experiment at a center-of-mass energy per nucleon pair of sqrt[s_{NN}]=5.02  TeV. The γγ→τ^{+}τ^{-} process is observed for τ^{+}τ^{-} events with a muon and three charged hadrons in the final state. The measured fiducial cross section is σ(γγ→τ^{+}τ^{-})=4.8±0.6(stat)±0.5(syst)  μb, where the second (third) term corresponds to the statistical (systematic) uncertainty in σ(γγ→τ^{+}τ^{-}) in agreement with leading-order QED predictions. Using σ(γγ→τ^{+}τ^{-}), we estimate a model-dependent value of the anomalous magnetic moment of the τ lepton of a_{τ}=0.001_{-0.089}^{+0.055}.

Observation of an Excess of Dicharmonium Events in the Four-Muon Final State with the ATLAS Detector

A search is made for potential ccc[over ¯]c[over ¯] tetraquarks decaying into a pair of charmonium states in the four muon final state using proton-proton collision data at sqrt[s]=13  TeV, corresponding to an integrated luminosity of 140  fb^{-1} recorded by the ATLAS experiment at LHC. Two decay channels, J/ψ+J/ψ→4μ and J/ψ+ψ(2S)→4μ, are studied. Backgrounds are estimated based on a hybrid approach involving Monte Carlo simulations and data-driven methods. Statistically significant excesses with respect to backgrounds dominated by the single parton scattering are seen in the di-J/ψ channel consistent with a narrow resonance at 6.9 GeV and a broader structure at lower mass. A statistically significant excess is also seen in the J/ψ+ψ(2S) channel. The fitted masses and decay widths of the structures are reported.

Observation of the γγ→ττ Process in Pb+Pb Collisions and Constraints on the τ-Lepton Anomalous Magnetic Moment with the ATLAS Detector

This Letter reports the observation of τ-lepton-pair production in ultraperipheral lead-lead collisions Pb+Pb→Pb(γγ→ττ)Pb and constraints on the τ-lepton anomalous magnetic moment a_{τ}. The dataset corresponds to an integrated luminosity of 1.44  nb^{-1} of LHC Pb+Pb collisions at sqrt[s_{NN}]=5.02  TeV recorded by the ATLAS experiment in 2018. Selected events contain one muon from a τ-lepton decay, an electron or charged-particle track(s) from the other τ-lepton decay, little additional central-detector activity, and no forward neutrons. The γγ→ττ process is observed in Pb+Pb collisions with a significance exceeding 5 standard deviations and a signal strength of μ_{ττ}=1.03_{-0.05}^{+0.06} assuming the standard model value for a_{τ}. To measure a_{τ}, a template fit to the muon transverse-momentum distribution from τ-lepton candidates is performed, using a dimuon (γγ→μμ) control sample to constrain systematic uncertainties. The observed 95% confidence-level interval for a_{τ} is -0.057 Collapse

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Insight on Atomically Dispersed Cu Catalysts for Electrochemical CO2 Reduction

Electrochemical CO2 reduction (ECO2R) with renewable electricity is an advanced carbon conversion technology. At present, copper is the only metal to selectively convert CO2 into multicarbon (C2+) products. Among them, atomically dispersed (AD) Cu catalysts have received great attention due to the relatively single chemical environment, which are able to minimize the negative impact of morphology, valence state, and crystallographic properties, etc. on product selectivity. Furthermore, the completely exposed atomic Cu sites not only provide space and bonding electrons for the adsorption of reactants in favor of better catalytic activity but also provide an ideal platform for studying its reaction mechanism. This review summarizes the recent progress of AD Cu catalysts as a chemically tunable platform for ECO2R, including the atomic Cu sites dynamic evolution, the catalytic performance, and mechanism. Furthermore, the prospects and challenges of AD Cu catalysts for ECO2R are carefully discussed. We sincerely hope that this review can contribute to the rational design of AD Cu catalysts with enhanced performance for ECO2R.

[Differential expression of LLGL2 in prostate ductal adenocarcinoma and acinar adenocarcinoma and its significance]

Objective: To investigate the expression differences of LLGL2 between prostatic ductal adenocarcinoma (PDA) and prostatic acinar adenocarcinoma, and its potential clinical significance. Methods: Eighteen patients diagnosed of PDA or prostatic acinar adenocarcinoma with PDA component by histopathology during January 2015 and December 2019 in the Beijing Hospital, China were retrospectively studied. The transcriptome analysis was conducted using the tissue of PDA and prostatic acinar adenocarcinoma. Differentially expressed genes and the differences in expression profiles were identified. Further, differentially expressed proteins were verified by immunohistochemistry. Results: The tissue from 8 of the 18 patients were used for transcriptome analysis, the results of which were compared with data from public databases. 129 differentially expressed genes were identified. 45 of them were upregulated while 84 were downregulated. The results of gene enrichment analysis and gene oncology (GO) analysis revealed that the differentially expressed genes were mostly enriched in the hypertrophic cardiomyopathy and interleukin-17 related pathways. GPAT2, LLGL2, MAMDC4, PCSK9 and SMIM6 were differentially expressed between PDA and prostatic acinar adenocarcinoma. Moreover, LLGL2 was more likely expressed in the cytoplasm (P=0.04) than the nucleus (P<0.01) in PDA, compared with prostatic acinar adenocarcinoma. Conclusions: The gene expression profiling indicates that PDA are very similar to prostatic acinar adenocarcinoma. Among the differentially expressed proteins screened and verified in this study, the expression of GPAT2, LLGL2, MAMDC4 and PCSK9 is increased in PDA, while that of SMIM6 is reduced in PDA. The expression of LLGL2 shows significantly different patterns between PDA and prostatic acinar carcinoma, and thus may help differentiate PDA from prostatic acinar adenocarcinoma in clinical practice.

Mechanisms of Intrinsic Radioresistance in Breast Cancer Identify Potential Therapeutic Vulnerabilities

PURPOSE/OBJECTIVE(S)

Clinical management of breast cancer (BC) includes radiation therapy (RT) for most women, though the molecular mechanisms that underly RT response and intrinsic radioresistance are poorly understood. Both in vitro and in vivo models aid in our understanding of radiobiology, and we hypothesized that transcriptional changes caused by radiation in vitro in BC cell lines would be recapitulated in an in vivo mouse xenograft model and uncover targetable mechanisms of radioresistance in BC.

MATERIALS/METHODS

Radiosensitivity was measured with clonogenic survival assays in 16 cell lines. RNA-seq experiments in vitro and in vivo were performed in an RT resistant (SUM-159) and RT sensitive (ZR-75) cell line 24 hrs after 4 Gy or after 2 Gy x 6 fractions, respectively. Differentially expressed genes (DEGs) were identified from RNA-seq data with DeSeq2 followed by pathway analysis with iPathwayGuide.

RESULTS

RT sensitivity was subtype independent in 16 BC cell lines, with SUM-159 radioresistant (SF 0.88) and ZR-75-1 radiosensitive (SF 0.29). There were 75 unique pathways that were significantly altered after RT in SUM-159 cells (53 pathways in vivo only, 36 pathways in vitro only, 14 both conditions; adjusted p-value < 0.05) and 85 unique pathways that were significantly altered after RT in ZR-75-1 cells (16 pathways in vivo only, 72 in vivo only, 3 both conditions; adjusted p-value < 0.05). Pathways that were significantly affected in both cell lines exclusively in the in vitro condition include canonical RT response pathways such as cell cycle, cellular senescence, and DNA replication, though the direction of DEGs were opposite in the two cell lines for each of these pathways. The IL-17 signaling pathway was significantly altered for both cell lines in vivo. Of the pathways that were significantly altered in both conditions for SUM-159 cells, inflammation, including chemokine signaling pathway and cytokine-cytokine receptor interaction, were among the most significant. Significantly more cytokines were upregulated following RT in vivo than in vitro. Cytokines were not upregulated in ZR-75-1 cells in vitro or in vivo.

CONCLUSION

Taken together, the significant changes in the IL-17 pathway and the upregulation of cytokines only in vivo indicate a potential of the tumor microenvironment in the in vivo condition that the in vitro condition lacks. Increased heterogeneity in vivo relative to in vitro may also explain the absence of several canonical RT response pathways in the in vivo conditions for each cell line. Notably, the opposite direction of DEG changes in the canonical RT response pathways between the 2 cell lines with disparate radiosensitivity levels may point to important biologic vulnerabilities that may be targeted in the resistant SUM-159 cells. Future studies are underway using additional BC cell lines and single-cell analysis to better understand RT response heterogeneity.

Influence of Contrast Materials on Dose Accuracy of MR-Linac in Patients with SBRT Liver Cancer

PURPOSE/OBJECTIVE(S)

Objective: Intravenous injection of contrast agent during CT scanning can improve the accuracy of target area contouring, however the contrast agent will cause dose bias due to the high relative electron density. This study aims to explore the influence of contrast agent on the accuracy of dose calculation of the planning system during SBRT based on MRI-Linac for liver cancer treatment.

MATERIALS/METHODS

Methods: In this study, 20 patients undergoing stereotactic body radiation therapy (SBRT) for liver cancer were selected, and their complete unenhanced CT, contrast-enhanced CT, and corresponding structures were imported into Monaco V.5.4. The target and organs at risk (OARs) in the unenhanced CT and contrast-enhanced CT were additionally contoured according to the target contouring guidelines and OARs were ranked. The average relative electron densities of OARs (lung, spinal cord, heart, rib, etc.) were calculated with Monaco TPS. The reference plan is based on unenhanced CT for plan calculation (plan1). To compare the dosimetry errors caused by the synthetic CT, the average relative electron density of all structures in unenhanced CT was forced and the plans were recalculated (plan2). To investigate dosimetric differences caused by the changes of relative electron density due to the contrast agent, the average relative electron density of all structures in contrast-enhanced CT was forced and the plans were recalculated(plan3). The dosimetric differences in groups A (plan 1 and plan2), B (plan 1 and plan3), and C (plan2 and plan3) were compared, respectively.

RESULTS

There were not significant difference between three groups in the affected lung, heart, liver, blood, all within 3%. However, differences were significantly different in the group B. The maximum deviation of spinal cord Dmax reached 4.78%. In addition, the deviation of the dose parameters in the target area was small, except that the maximum deviation of the CI value in group B was 3.23%.

CONCLUSION

For SBRT planning of liver cancer based on magnetic resonance accelerator, synthetic CT has little influence on the calculation of planned dose. The dose difference caused by contrast materials is also relatively small, although the deviation of the CI value of the target area exceeds 3%, which is also within the clinical acceptance range. However, the deviation of the maximum value of the spinal cord is relatively large, exceeding the clinically acceptable range. Therefore, when optimizing the SBRT plan for liver cancer, attention should be paid to important organs such as the spinal cord, and should be avoided as far as possible when setting the fields.

Dosimetric Advantages of Online Adaptative Radiotherapy for Cervical Cancer on 1.5T MR-Linac

PURPOSE/OBJECTIVE(S)

Online adaptative radiotherapy (ART) strategy can be applied to account for inter-fraction organ motion while limiting organ at risk (OAR) dose. This study aims to evaluate tumor target and OARs inter- and intrafraction motion using online MRI during the full course of MR-Linac radiotherapy fractions. Furthermore, quantify the dosimetric consequences of online adaptative compared with non-adaptative radiotherapy (non-ART) in cervical cancer.

MATERIALS/METHODS

Six cervix cancer patients were treated with 150 fractions on the 1.5 T Unity MR-Linac. Each fraction, pre-treatment MRI scans were obtained at the start of every treatment session, and post-treatment MRI scans were obtained at the end of every treatment session. A total 300 MR images were included in this study and the CTV, bladder and rectum were delineated on each MRI by the same radiation oncologist. The inter-fraction and intrafraction changes of contours were evaluated by dice similarity coefficient (DSC), Hausdorff distance (HD), volume difference (ΔV). The reference treatment plans were generated using step-and-shoot IMRT and utilized 9 beam groups on original CT. Then, the online adaptative treatment plans were obtained by re-optimizing based on the contours on daily pre-treatment MRI by "adapt to shape" workflow using the same beam parameters and optimization objectives from the reference plans. Non-ART plans for each patient were generated by recalculating the dose from the reference plans on daily online MRI by "adapt to position" workflow. CTV coverage and OARs constraints were used to compare ART and non-ART plans.

RESULTS

The results showed that large inter-fraction anatomical changes limited the efficacy of radiation therapy (CTV: DSC: 0.89±0.03, HD: 20.83±5.05mm, ΔV: 1.21%±5.44%; Bladder: DSC: 0.68±0.18, HD: 30.58±15.75mm, ΔV: -10.17%±61.19%; Rectum: DSC: 0.69±0.09, HD: 22.98±12.03mm, ΔV: 21.01%±20.59%).The intrafraction anatomical changes were smaller (CTV: DSC: 0.96±0.01, HD: 8.85±3.54mm, ΔV: -0.64%±1.90%; Bladder: DSC: 0.90±0.07, HD: 14.62±9.56mm, ΔV: 19.83%±21.71%; Rectum: DSC: 0.98±0.04, HD: 2.90±4.27mm, ΔV: 0.13%±5.04%) . Non-ART showed inadequate primary CTV coverage in 30% of the daily fractions. Online adaptative plans improved CTV coverage significantly (p<0.001) to 99%. Compared with non-ART, online ART decreased the fraction dose to bladder and rectum indicated by significant (p<0.001) improvements for daily D50%, D2% and Dmean.

CONCLUSION

In cervical cancer radiotherapy, a non-adaptive strategy led to inadequate target coverage for individual patients. Online adaptative radiotherapy corrected for day-to-day anatomical variations and resulted in adequate target coverage in all fractions. The dose to rectum and bladder was decreased significantly when applying online adaptative radiotherapy.

Challenges of Treating Lung Cancer Patients at MR-Linac Using MR-Based Synthetic CT Calculation in the Adaptive Workflow

PURPOSE/OBJECTIVE(S)

Magnetic Resonance guided adaptive radiotherapy (MRgART) allows plan adaptation according to the new patient anatomy; the contours of the structures are adjusted based on the patient's daily MRI, and in the adapt to shape (ATS) workflow, the adapted plan is recalculated on the MRI-based synthetic CT (sCT) generated by bulk density assignment. For sites where there is a high electronic density (ED) gradient between the target and surrounding tissues, such as in lung cancer treatments, the assignment of an average ED may not be able to reproduce an accurate dose calculation. This study evaluates the accuracy of the sCT adapted plan calculation for lung cancer patients and assesses whether the assignment of an optimized ED can reduce dosimetric differences should they arise MATERIALS/METHODS: Nine lung cancer patients treated at Unity 1.5 MR-Linac were selected for this retrospective study. The patient's target and organs at risk (OARs) were contoured, and a CT reference plan containing the ED bulk assignment information i.e., the contours to use in the ATS workflow, and their corresponding average ED was generated. To assess the accuracy of the dosimetry of the adapted plan calculated on the sCT, the plan was recalculated on an ideal sCT (sCTref) obtained from the reference CT by forcing the drawn contours to the average ED as defined on the CT reference plan. Targets and OARs dose-volume histogram (DVH) of the CT and sCTref plans and the dose distributions using gamma (γ) analysis with 2%-2mm criteria were compared. In the case of a discrepancy between the DVHs, the average Eds used for the recalculation on the sCTref were adjusted by several attempts to obtain a sCT optimized (sCTopt) for which a superposition of DVHs on CT and sCTopt was achieved.

RESULTS

For 7 of the 9 patients CT and sCTref target DVHs were not comparable, with a mean dosimetric difference of 5.55% (range 2.35%-7.46%) in the target volume receiving the prescription dose (VDpre), while OARs DVH dose differences remained below 1% for the nine patients. The adjustment of the ED of the homolateral lung in the sCTopt, reduced the mean target VDpre dosimetric difference between CT and sCTopt to 0.66% (range 0.17%-1.64%). In addition, the results of the gamma analysis increased from values ranging between 39.5%-70.3% to 88.5%-93.2%, as shown in the Table.

CONCLUSION

Dosimetric errors in the use of the sCT calculation for targets in high ED gradient areas may arise; the use of optimized ED for sCT calculation may be a promising strand to investigate in order to proceed with MR-based sCT plan adaptation for lung cancer treatment.

Partial Stereotactic Ablative Radiotherapy in Bulky Urinary Tract Malignancy: An Update Clinical Outcomes and Dosimetric Analysis

PURPOSE/OBJECTIVE(S)

Patients with bulky urinary tract malignancy have poor prognosis. Stereotactic ablative radiotherapy (SABR) needs careful consideration in abdominopelvic bulky tumors because of dose constraints on the OARs. We reported updated clinical outcomes to evaluate the safety and efficacy of partial stereotactic ablative radiotherapy(P-SABR) in bulky urinary tract malignancy. The study also aims to investigate the feasibility of P-SABR in dose and biologic effective dose (BED) escalation inside the tumors with equivalent toxicity.

MATERIALS/METHODS

A total of 26 patients with urinary tract malignancy underwent P-SABR radiotherapy from January 2013 to September 2018 were retrospectively analyzed in this study. All the patients were in inoperable locally advanced or metastatic stage with tumor diameter > 4.0 cm. The P-SABR plan consisted of the SABR for gross tumor volume boost (GTVb) and following conventionally fractionated radiotherapy for planning target volume (PTV). The first SABR plan to GTVb was delivered in 15-32Gy/3-5f. The second conventionally fractionated radiotherapy plan to PTV was delivered in 40.0-58.08Gy/15-26f. The total P-SABR plan met the OARs constraints. Local control and overall survival were estimated. Acute and late toxicity were evaluated according to RTOG criteria. Paired conventionally fractionated radiotherapy (CFRT) plans were re-designed for all patients, with the same OARs dose constraints and total dose of PTV margin. Dosimetric and BED parameters were compared in P-SABR and paired CFRT plans.

RESULTS

Median age of the patients was 66.5 years (range, 46-90 years). The tumor treated by P-SABR had a median diameter of 8.4 cm (4.1-19.5 cm) and a median volume of 99.2 cc (23.9-631.8 cc). Median follow-up time was 19.1 months. The local control at 1 and 2 years were 83.2%, 77.3%, respectively. The overall survival at 1 and 2 years were 72.2% ,45.5%, respectively. 6 cases have no local recurrence after 36 months. 4 cases remained alive after 60 months. Local symptoms improved in 15/16 cases after P-SABR. Multivariate analysis showed tumor diameter (≥8cm vs. <8cm) was the independent factor affecting local control and overall survival (P=0.033, P=0.016). No patient was observed radiotherapy directly induced ≥grade 3 toxicity. Compared with the paired CFRT plans, the P-SABR plans had no significant difference in most OAR dose parameters, except for the small intestine/colon V15, V45 with an increase of 14.6 cc, 3.4 cc. However, P-SABR plans increased the dose of PTV Dmean, Dmax by 8.7Gy, 14.4Gy (P < 0.001), respectively. In addition, the dose and BED of GTVb had a significant escalation of 15.8Gy and 30.2Gy (P<0.001) respectively in P-SABR plans.

CONCLUSION

We had reported P-SABR is well-tolerated in bulky urinary tract malignancy in previous study. Updated outcomes showed P-SABR may have long-term local control in these people. Compared with traditional CFRT plans, P-SABR plans escalated the dose and BED inside bulky tumors with equivalent toxicity.

A Nomogram to Predict Pathological Axillary Status in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy

PURPOSE/OBJECTIVE(S)

This study aimed to identify factors influencing axillary pathological complete response (pCR) and to develop a predictive nomogram to evaluate axillary pCR rate in breast cancer patients treated with neoadjuvant chemotherapy (NAC).

MATERIALS/METHODS

A total of 2368 patients who received NAC and mastectomy between 2000 and 2014 from 12 grade A tertiary hospitals in China were analyzed retrospectively. The patients treated in three cancer hospitals (training set, n = 1629) were used to construct the nomogram based on multivariate logistic regression analyses. The nomograph was validated by the area under the receiver operating characteristic curve (AUC) and calibration curve in patients from 9 other general hospitals (validation set, n = 739).

RESULTS

The nomogram incorporated seven predicting factors including NACT cycles, response to NACT, clinical T stage, clinical N stage, grade, LVI, and molecular subtype. The AUC for the training set and validation set were 0.762 and 0.802, respectively. In addition, the calibration curve also showed good agreement between the nomogram-based predictions and the actual observations.

CONCLUSION

A nomogram was established to predict the status of axillary lymph nodes in breast cancer patients after NAC. The predictive model performed well both in the training set and external validation set.

Inter-fractional Assessment during MR-guided Online Adaptive Radiotherapy for Glioblastoma

PURPOSE/OBJECTIVE(S)

Magnetic resonance image (MRI) guided radiation therapy has the potential to improve outcomes for glioblastoma by adapting to tumor changes during radiation therapy. This study aimed to assess the feasibility and potential benefits of MR-guided online adaptive radiotherapy (MRgOART) for patients with glioblastoma.

MATERIALS/METHODS

Twenty consecutive patients with glioblastoma were treated with MRgOART of 60 Gy in 30 fractions by the 1.5 T MR-Linac. The MRgOART fractions employed daily MR scans and the contours were utilized to create each adapted plan. The gross tumor volume (GTV) and clinical target volume (CTV) were delineated on MRI of pre-treatment simulation (Fx0) and all fractions (Fx1, Fx2, Fx3 ... Fx30) to evaluate the inter-fractional changes. These changes were quantified using absolute/relative volume (∆V), Dice similarity coefficient (DSC) and Hausdorff distance (HD) metrics. The reference treatment plans were generated using step-and-shoot IMRT and utilized 7-9 beam groups on original CT. Before the treatment, a synthetic CT (sCT) quality assurance (QA) process was performed to assess the dose accuracy of bulk relative electron density (rED) assignment for online MRI based treatment plan in terms of gamma analysis, point dose comparison and dose volume histogram (DVH) parameters. Then, the online adaptative treatment plans were obtained by re-optimizing based on the contours on daily pre-treatment MRI by "adapt to shape" workflow. Non-adaptive plans for each patient were generated by recalculating the dose from the reference plans on daily online MRI by "adapt to position" workflow. GTV and CTV coverage and organ at risk (OAR) constraints were used to compare non-adaptive and adaptive plans.

RESULTS

For both criteria, the 1%/1mm (98.58%±0.15%) and 2%/2mm (99.88%±0.18%) gamma passing rate results were always clinically acceptable in sCT QA process. The differences on point dose and DVH parameters between the plans based on sCT and original CT were less than 1%. A total of 20 patients with 600 fractions were evaluated. The results showed that large inter-fractional changes for GTV limited the efficacy of radiation therapy (DSC: 0.78±0.08, HD: 20.94±3.64mm, ∆V: 2.92%±6.36%). The inter-fractional CTV changes were smaller (DSC: 0.91±0.04, HD: 15.31±3.09mm, ∆V: 1.41%±1.29%). GTV coverage of non-adaptive plans was below the prescribed coverage in 228/600 fractions (38%), with 90 (15%) failing by more than 10%. For CTV coverage of non-adaptive plans, the changes were less than 5%. Online adaptative plans improved GTV and CTV coverage significantly (p<0.001) to 99%. The adaptive plans also had lower dose to whole brain than non-adaptive plans (p<0.001).

CONCLUSION

Significant inter-fractional tumor changes could be found during radiotherapy in patients with glioblastoma treated by the 1.5 T MR-Linac. Daily MR-guided re-optimization of treatment plans corrected for day-to-day anatomical variations and resulted in adequate target coverage in all fractions.

Leveraging Quantitative Imaging and Machine Learning to Differentiate Radionecrosis from Disease Recurrence in Patients with Brain Metastases

PURPOSE/OBJECTIVE(S)

Radiation necrosis can be difficult to non-invasively discern from tumor progression after stereotactic radiosurgery (SRS). In this work, we investigate the utility of radiomics (computerized features) and machine learning to capture per-voxel lesion heterogeneity on routine MRI scans, to differentiate radionecrosis from tumor recurrence in patients with brain metastases treated with SRS.

MATERIALS/METHODS

A retrospective analysis was conducted of patients with brain metastases treated with SRS. Eighty-three lesions (n = 56 intact; n = 27 surgical cavity) from 69 patients were identified with median age 68.8 years (range 40.2 - 91.0), of whom 53.6% were male and 33.3% received prior whole-brain radiotherapy (WBRT). Lesion histology included lung (60.2%), renal cell (15.7%), melanoma (10.8%), breast (9.6%), and other (3.6%). Pathologic confirmation was available in 73.5% of lesions. Both intact and resection cavity lesions were included and individually segmented. Image preprocessing and radiomic feature extraction were done using ANTsPy and open-source software. A total of 210 features were extracted from post-contrast T1-weighted (T1w) and T2/FLAIR MRIs. Highly correlated features were removed. Univariate logistic regression was conducted on the remaining T1w and T2/FLAIR features as well as on clinical variables. Multivariate analysis was implemented with various classifiers (Random Forest, Ridge, Lasso, Support Vector Machine [SVM]) on the top-performing features found on univariate logistic regression. Models were assessed using cross-validation to select the best model by area under ROC curve (AUC). Specificity and sensitivity were calculated.

RESULTS

On univariate analysis, the top 10 radiomics features consisted of 6 T1w features and 4 T2/FLAIR features (4 GLCM, 3 first order, 1 GLSZM, 1 GLRLM, and 1 shape feature). Age, gender, disease site, prior WBRT, prior fractionated SRS, planning tumor volume, brain-GTV V12 Gy, and immunotherapy before or after SRS were not predictive (AUC less than 62.0%) on univariate analysis compared to radiomic features. Multivariate analysis of top performing radiomic features on both intact and surgical cavities yielded an AUC of 72.0% (standard deviation [SD] ±8.8%). Multivariate analysis of top features on intact lesions alone improved the AUC to 80.5% (SD ±10.8%), with sensitivity of 77.8%, specificity of 72.4%, and positive likelihood ratio of 2.82 in differentiating radionecrosis from recurrence.

CONCLUSION

Radiomics and machine learning tools may improve diagnostic ability of distinguishing radiation necrosis from tumor recurrence after SRS. Further work is needed to deploy this in a larger multi-institutional cohort and prospectively evaluate its efficacy as a decision-support tool to personalize care in patients with brain metastases.

Baicalein enhances immune response in TNBC by inhibiting leptin expression of adipocytes

Triple-negative breast cancer (TNBC) is a special pathological type of breast cancer (BC) with poor prognosis. Obesity is shown to be involved in TNBC tumor progression. The interaction between obesity and BC has generated great attention in recent years, however, the mechanism is still unclear. Here, we showed that leptin secreted by adipocytes upregulated PD-L1 expression in TNBC through the p-STAT3 signaling pathway and that baicalein inhibited PD-L1 expression in tumor microenvironment by suppressing leptin transcription of adipocytes. Collectively, our findings suggest that leptin may be the key factor participating in obesity-related tumor progression and that baicalein can break through the dilemma to boost the anti-tumor immune response.

Adaptive Auto-Segmentation for MRI-Guided Online Adaptive Radiotherapy of Cervical Carcinoma

PURPOSE/OBJECTIVE(S)

Accurate and efficient delineation of organs and targets on session images is critical in MRI-guided online adaptive radiotherapy (MRgOART). This study proposes a registration-guided deep learning image segmentation framework to assist online delineation of cervical carcinoma.

MATERIALS/METHODS

A total of 300 T2-weighted MR images were acquired for patients with cervical carcinoma treated by a 1.5T Unity MR-Linac. The CTV, bladder, rectum, pelvic bone and femoral joints were delineated on each MRI by the same radiation oncologist. To overcome these obstacles to online MRI segmentation, we propose a registration-guided DL (RgDL) segmentation framework that integrates image registration algorithms and DL segmentation models. Firstly, the DL segmentation model was trained using nnU-net. Then, for each treatment fraction, the deformable image registration (DIR) algorithm generates initial contours from previous treatment fraction, which were used as guidance by DL model to obtain the accurate current segmentation. The segmentation accuracy of alone DIR, DL and RgDL were evaluated by dice similarity coefficients (DSC) and other distance-based metrics.

RESULTS

Compared to the baseline approaches using the DIR and the DL alone, RgDL achieved a DSC of 91.12% on CTV, higher than DIR and DL alone by 15.54% and 10.13%. The DSC of RgDL were improved to 95.58%, 93.65%, 87.8% and 94.84% for bladder, pelvic bone, rectum and femoral joints, higher than DIR and DL alone by 9.61% on average.

CONCLUSION

The proposed adaptive auto-segmentation method can achieve accurate and efficient segmentation and potentially overcome these obstacles to MRgOART.