Explore the vast range of titles available.

Quantum geometric properties of Bloch wave functions in solids, that is, Berry curvature and the quantum metric, are known to significantly influence the ground- and excited-state behaviour of electrons 1 – 5 . The bulk photovoltaic effect (BPVE), a nonlinear phenomenon depending on the polarization of excitation light, is largely governed by the quantum geometric properties in optical transitions 6 – 10 . Infrared BPVE has yet to be observed in graphene or moiré systems, although exciting strongly correlated phenomena related to quantum geometry have been reported in this emergent platform 11 – 14 . Here we report the observation of tunable mid-infrared BPVE at 5 µm and 7.7 µm in twisted double bilayer graphene (TDBG), arising from the moiré-induced strong symmetry breaking and quantum geometric contribution. The photoresponse depends substantially on the polarization state of the excitation light and is highly tunable by external electric fields. This wide tunability in quantum geometric properties enables us to use a convolutional neural network 15 , 16 to achieve full-Stokes polarimetry together with wavelength detection simultaneously, using only one single TDBG device with a subwavelength footprint of merely 3 × 3 µm 2 . Our work not only reveals the unique role of moiré engineered quantum geometry in tunable nonlinear light–matter interactions but also identifies a pathway for future intelligent sensing technologies in an extremely compact, on-chip manner. Tunable quantum geometric properties of moiré graphene enable the use of a convolutional neural network to simultaneously decipher the light polarization, power and wavelength in a subwavelength-scale smart device.

In a flat band superconductor, the charge carriers’ group velocity v F is extremely slow. Superconductivity therein is particularly intriguing, being related to the long-standing mysteries of high-temperature superconductors 1 and heavy-fermion systems 2 . Yet the emergence of superconductivity in flat bands would appear paradoxical, as a small v F in the conventional Bardeen–Cooper–Schrieffer theory implies vanishing coherence length, superfluid stiffness and critical current. Here, using twisted bilayer graphene 3 – 7 , we explore the profound effect of vanishingly small velocity in a superconducting Dirac flat band system 8 – 13 . Using Schwinger-limited non-linear transport studies 14 , 15 , we demonstrate an extremely slow normal state drift velocity v n  ≈ 1,000 m s –1 for filling fraction ν between −1/2 and −3/4 of the moiré superlattice. In the superconducting state, the same velocity limit constitutes a new limiting mechanism for the critical current, analogous to a relativistic superfluid 16 . Importantly, our measurement of superfluid stiffness, which controls the superconductor’s electrodynamic response, shows that it is not dominated by the kinetic energy but instead by the interaction-driven superconducting gap, consistent with recent theories on a quantum geometric contribution 8 – 12 . We find evidence for small Cooper pairs, characteristic of the Bardeen–Cooper–Schrieffer to Bose–Einstein condensation crossover 17 – 19 , with an unprecedented ratio of the superconducting transition temperature to the Fermi temperature exceeding unity and discuss how this arises for ultra-strong coupling superconductivity in ultra-flat Dirac bands. The authors investigate the effect of small velocity in a superconducting Dirac flat band system, finding evidence for small pairs and that superfluid stiffness is not dominated by kinetic energy.

This retrospective study explores two radiomics methods combined with other clinical variables for predicting recurrence free survival (RFS) and overall survival (OS) in patients with pulmonary metastases treated with stereotactic body radiotherapy (SBRT). 111 patients with 163 metastases treated with SBRT were included with a median follow-up time of 927 days. First-order radiomic features were extracted using two methods: 2D CT texture analysis (CTTA) using TexRAD software, and a data-driven technique: functional principal components analysis (FPCA) using segmented tumoral and peri-tumoural 3D regions. Using both Kaplan-Meier analysis with its log-rank tests and multivariate Cox regression analysis, the best radiomic features of both methods were selected: CTTA-based \"entropy\" and the FPCA-based first mode of variation of tumoural CT density histogram: \"F1.\" Predictive models combining radiomic variables and age showed a C-index of 0.62 95% with a CI of (0.57-0.67). \"Clinical indication for SBRT\" and \"lung primary cancer origin\" were strongly associated with RFS and improved the RFS C-index: 0.67 (0.62-0.72) when combined with the best radiomic features. The best multivariate Cox model for predicting OS combined CTTA-based features-skewness and kurtosis-with size and \"lung primary cancer origin\" with a C-index of 0.67 (0.61-0.74). In conclusion, concise predictive models including CT density-radiomics of metastases, age, clinical indication, and lung primary cancer origin can help identify those patients with probable earlier recurrence or death prior to SBRT treatment so that more aggressive treatment can be applied.

Studies of complications resulting from surgery or radiotherapy for prostate cancer have mainly focused on incontinence and erectile dysfunction. We aimed to assess other important complications associated with these treatments for prostate cancer. We did a population-based retrospective cohort study, in which we used administrative hospital data, physician billing codes, and cancer registry data for men who underwent either surgery or radiotherapy alone for prostate cancer between 2002 and 2009 in Ontario, Canada. We measured the 5-year cumulative incidence of five treatment-related complication endpoints: hospital admissions; urological, rectal, or anal procedures; open surgical procedures; and secondary malignancies. In the 32 465 patients included in the study, the 5-year cumulative incidence of admission to hospital for a treatment-related complication was 22·2% (95% CI 21·7–22·7), but was 2·4% (2·2–2·6) for patients whose length of stay was longer than 1 day. The 5-year cumulative incidence of needing a urological procedure was 32·0% (95% CI 31·4–32·5), that of a rectal or anal procedure was 13·7% (13·3–14·1), and that of an open surgical procedure was 0·9% (0·8–1·1). The 5-year cumulative incidence of a second primary malignancy was 3·0% (2·6–3·5). These risks were significantly higher than were those of 32 465 matched controls with no history of prostate cancer. Older age and comorbidity at the time of index treatment were important predictors for a complication in all outcome categories, but the type of treatment received was the strongest predictor for complications. Patients who were given radiotherapy had higher incidence of complications for hospital admissions, rectal or anal procedures, open surgical procedures, and secondary malignancies at 5 years than did those who underwent surgery (adjusted hazard ratios 2·08–10·8, p<0·0001). However, the number of urological procedures was lower in the radiotherapy than in the surgery group (adjusted hazard ratio 0·66, 95% CI 0·63–0·69; p<0·0001) Complications after prostate cancer treatment are frequent and dependent on age, comorbidity, and the type of treatment. Patients and physicians should be aware of these risks when choosing treatment for prostate cancer, and should balance them with the clinical effectiveness of each therapy. Ajmera Family Chair in Urologic Oncology.

Electrons hopping in two-dimensional honeycomb lattices possess a valley degree of freedom in addition to charge and spin. In the absence of inversion symmetry, these systems were predicted to exhibit opposite Hall effects for electrons from different valleys. Such valley Hall effects have been achieved only by extrinsic means, such as substrate coupling, dual gating, and light illuminating. Here we report the first observation of intrinsic valley Hall transport without any extrinsic symmetry breaking in the non-centrosymmetric monolayer and trilayer MoS 2 , evidenced by considerable nonlocal resistance that scales cubically with local resistance. Such a hallmark survives even at room temperature with a valley diffusion length at micron scale. By contrast, no valley Hall signal is observed in the centrosymmetric bilayer MoS 2 . Our work elucidates the topological origin of valley Hall effects and marks a significant step towards the purely electrical control of valley degree of freedom in topological valleytronics. Electrons hopping in two-dimensional honeycomb lattices possess a valley degree of freedom. Here, the authors observe room-temperature valley Hall transport without any extrinsic symmetry breaking in the non-centrosymmetric monolayer and trilayer MoS 2 by purely electronic means, whereas no valley signal is detected for centrosymmetric bilayer MoS 2 .

Background Brain imaging is recommended for girls with central precocious puberty (CPP) that begins before the age of six; however, its necessity remains controversial for those with onset between the ages of six and eight. We aim to evaluate the role of brain imaging in girls experiencing the onset of puberty within this age range. Methods This retrospective observational study evaluated 162 girls diagnosed with CPP in Hong Kong from January 2010 to December 2020. Brain magnetic resonance imaging (MRI) findings for 139 of these girls were reviewed. Clinical findings of 125 girls who entered puberty between the ages of six and eight were analyzed. Results 15.8% (22 of 139) of girls with CPP had abnormal MRI findings. The incidence was lower in girls who began puberty between six and eight years of age (13.6%, 17 of 125 girls) compared to those who started puberty before the age of six (35.7%, 5 of 14 girls), with a statistically significant difference ( p  = 0.047). Abnormal MRI findings in the 17 girls who started puberty between six and eight years of age included: a RCC ( n  = 6), a pituitary microadenoma ( n  = 4), a pituitary macroadenoma ( n  = 1), either a RCC or a pituitary microadenoma ( n  = 2), a pineal cyst ( n  = 1), an arachnoid cyst in the right posterior fossa with a RCC ( n  = 1), pituitary hyperplasia along with a RCC and an arachnoid cyst in the right middle fossa ( n  = 1), and a duplicated posterior pituitary gland ( n  = 1). None of the girls had neurological concerns or required neurosurgical interventions during the follow-up period of 4.6 ± 1.9 years. Among the 125 girls who began puberty between the ages of six and eight, no significant differences in clinical findings were observed between those with normal and abnormal MRIs. Conclusions The likelihood of identifying clinically significant intracranial pathologies through routine brain imaging in girls who started puberty between the ages of six and eight is low. In the absence of neurological concerns, watchful observation may be appropriate, provided that parents are fully informed of the minimal risk of overlooking underlying intracranial pathology.

Background and purpose This study aimed to summarize the clinical outcomes of patients with metastatic melanoma who received high‐dose radiation prior to or during systemic therapy at a single academic institution. Methods We identified patients with metastatic melanoma who underwent high‐dose radiation therapy (HDRT) for extracranial metastases prior to or during systemic therapy from 2010 to 2018. Treatment indications included oligometastases, oligoprogression, and local control. Using the Kaplan‐Meier method, we plotted overall survival (OS), progression‐free survival‐1 (PFS1), and PFS2. Competing risk analysis determined the cumulative incidence of local failure (LF) and the time to start or change systemic therapy (SCST). Univariate and multivariable analyses were used to identify predictive factors. Results We analyzed 34 patients with 79 lesions, with a median follow‐up of 17.4 months. Sixty‐eight percent of patients received systemic therapy after the first HDRT. The median OS was 22 months, with brain metastases before HDRT being a significant predictor in multivariable analysis. The median PFS1 for first‐line HDRT was 4.1 months, and the median PFS2 was 3.9 months. Rates of LF were 10.3% at 12 months and 11.7% at 24 months. The incidence of SCST following HDRT was 59.8% at 12 months and 76.1% at 24 months, with radiation targeted at the lung associated with a lower incidence of SCST. Conclusion HDRT for treating metastatic lesions in melanoma demonstrated excellent local control and may play a role in delaying SCST. Additional courses of HDRT may provide cumulative benefits. Patients with metastatic melanoma receiving high dose radiotherapy (HDRT) for oligoprogression, oligometastases or improved local control were retrospectively reviewed. The 1 year rate of local failure was 10.3%, and 1 year incidence of starting or changing systemic therapy after HDRT was 59.8%.

Background Although MRI is a radiation-free imaging modality, it has historically been limited in lung imaging due to inherent technical restrictions. The aim of this study is to explore the performance of lung MRI in detecting solid and subsolid pulmonary nodules using T1 gradient-echo (GRE) (VIBE, Volumetric interpolated breath-hold examination), ultrashort time echo (UTE) and T2 Fast Spin Echo (HASTE, Half fourier Single-shot Turbo spin-Echo). Methods Patients underwent a lung MRI in a 3 T scanner as part of a prospective research project. A baseline Chest CT was obtained as part of their standard of care. Nodules were identified and measured on the baseline CT and categorized according to their density (solid and subsolid) and size (> 4 mm/ ≤ 4 mm). Nodules seen on the baseline CT were classified as present or absent on the different MRI sequences by two thoracic radiologists independently. Interobserver agreement was determined using the simple Kappa coefficient. Paired differences were compared using nonparametric Mann-Whitney U tests. The McNemar test was used to evaluate paired differences in nodule detection between MRI sequences. Results Thirty-six patients were prospectively enrolled. One hundred forty-nine nodules (100 solid/49 subsolid) with mean size 10.8 mm (SD = 9.4) were included in the analysis. There was substantial interobserver agreement (k = 0.7, p  = 0.05). Detection for all nodules, solid and subsolid nodules was respectively; UTE: 71.8%/71.0%/73.5%; VIBE: 61.6%/65%/55.1%; HASTE 72.4%/72.2%/72.7%. Detection rate was higher for nodules > 4 mm in all groups: UTE 90.2%/93.4%/85.4%, VIBE 78.4%/88.5%/63.4%, HASTE 89.4%/93.8%/83.8%. Detection of lesions ≤4 mm was low for all sequences. UTE and HASTE performed significantly better than VIBE for detection of all nodules and subsolid nodules (diff = 18.4 and 17.6%, p  = < 0.01 and p  = 0.03, respectively). There was no significant difference between UTE and HASTE. There were no significant differences amongst MRI sequences for solid nodules. Conclusions Lung MRI shows adequate performance for the detection of solid and subsolid pulmonary nodules larger than 4 mm and can serve as a promising radiation-free alternative to CT.

Background To evaluate computed tomography (CT) patterns of post-SBRT lung injury in lung cancer and identify time points of serial CT changes. Materials and methods One hundred eighty-three tumors in 170 patients were evaluated on sequential CTs within 29 months (median). Frequencies of post-SBRT CT patterns and time points of initiation and duration were assessed. Duration of increase of primary lesion or surrounding injury without evidence of local recurrence and time to stabilization or local recurrence were evaluated. Results Post-SBRT CT patterns could overlap in the same patient and were nodule-like pattern (69%), consolidation with ground glass opacity (GGO) (41%), modified conventional pattern (39%), peribronchial/patchy consolidation (42%), patchy GGO (24%), diffuse consolidation (16%), “orbit sign” (21%), mass-like pattern (19%), scar-like pattern (15%) and diffuse GGO (3%). Patchy GGO started at 4 months post-SBRT. Peribronchial/patchy consolidation and consolidation with GGO started at 4 and 5 months respectively. Diffuse consolidation, diffuse GGO and orbit sign started at 5, 6 and 8 months respectively. Mass-like, modified conventional and scar-like pattern started at 8, 12 and 12 months respectively. Primary lesion ( n  = 11) or surrounding injury ( n  = 85) increased up to 13 months. Primary lesion ( n  = 119) or surrounding injury ( n  = 115) started to decrease at 4 and 9 months respectively. Time to stabilization was 20 months. The most common CT pattern at stabilization was modified conventional pattern (49%), scar-like pattern (23%) and mass-like pattern (12%). Local recurrence ( n  = 15) occurred at a median time of 18 months. Conclusion Different CT patterns of lung injury post-SBRT appear in predictable time points and have variable but predictable duration. Familiarity with these patterns and timeframes of appearance helps differentiate them from local recurrence.

Hand-crafted radiomics has been used for developing models in order to predict time-to-event clinical outcomes in patients with lung cancer. Hand-crafted features, however, are pre-defined and extracted without taking the desired target into account. Furthermore, accurate segmentation of the tumor is required for development of a reliable predictive model, which may be objective and a time-consuming task. To address these drawbacks, we propose a deep learning-based radiomics model for the time-to-event outcome prediction, referred to as DRTOP that takes raw images as inputs, and calculates the image-based risk of death or recurrence, for each patient. Our experiments on an in-house dataset of 132 lung cancer patients show that the obtained image-based risks are significant predictors of the time-to-event outcomes. Computed Tomography (CT)-based features are predictors of the overall survival (OS), with the hazard ratio (HR) of 1.35, distant control (DC), with HR of 1.06, and local control (LC), with HR of 2.66. The Positron Emission Tomography (PET)-based features are predictors of OS and recurrence free survival (RFS), with hazard ratios of 1.67 and 1.18, respectively. The concordance indices of$$68\\%$$68 % ,$$63\\%$$63 % , and$$64\\%$$64 % for predicting the OS, DC, and RFS show that the deep learning-based radiomics model is as accurate or better in predicting predefined clinical outcomes compared to hand-crafted radiomics, with concordance indices of$$51\\%$$51 % ,$$64\\%$$64 % , and$$47\\%$$47 % , for predicting the OS, DC, and RFS, respectively. Deep learning-based radiomics has the potential to offer complimentary predictive information in the personalized management of lung cancer patients.