Premature leakage of photosensitizer (PS) from nanocarriers significantly reduces the accumulation of PS within a tumor, thereby enhancing nonspecific accumulation in normal tissues, which inevitably leads to a limited efficacy for photodynamic therapy (PDT) and the enhanced systematic phototoxicity. Moreover, local hypoxia of the tumor tissue also seriously hinders the PDT. To overcome these limitations, an acidic H2O2‐responsive and O2‐evolving core–shell PDT nanoplatform is developed by using MnO2 shell as a switchable shield to prevent the premature release of loaded PS in core and elevate the O2 concentration within tumor tissue. The inner core SiO2‐methylene blue obtained by co‐condensation has a high PS payload and the outer MnO2 shell shields PS from leaking into blood after intravenous injection until reaching tumor tissue. Moreover, the shell MnO2 simultaneously endows the theranostic nanocomposite with redox activity toward H2O2 in the acidic microenvironment of tumor tissue to generate O2 and thus overcomes the hypoxia of cancer cells. More importantly, the Mn(ΙΙ) ion reduced from Mn(ΙV) is capable of in vivo magnetic resonance imaging selectively in response to overexpressed acidic H2O2. The facile incorporation of the switchable MnO2 shell into one multifunctional diagnostic and therapeutic nanoplatform has great potential for future clinical application.

Chaos and the natural evolution of tumor systems can lead to the failure of tumor therapies.H erein, we demonstrate that iridium oxide nanoparticles (IrO x )p ossess acid-activated oxidase and peroxidase-like functions and wide pH-dependent catalase-like properties.T he integration of glucose oxidase (GOD) unlocked the oxidase and peroxidase activities of IrO x by the production of gluconic acid from glucose by GOD catalysis in cancer cells,a nd the produced H 2 O 2 was converted into O 2 to compensate its consumption in GOD catalysis owing to the catalase-like function of the nanozyme,t hus resulting in the continual consumption of glucose and the self-supply of substrates to generate superoxide anion and hydroxyl radical. Moreover,I rO x can constantly consume glutathione (GSH) by self-cyclic valence alternation of Ir IV and Ir III .T hese cascade reactions lead to a" butterfly effect" of initial starvation therapyand the subsequent pressure of multiple reactive oxygen species (ROS) to completely break the self-adaption of cancer cells.Supportinginformation and the ORCID identification number(s) for the author(s) of this article can be found under: https://doi.

Local hypoxia in tumors, as well as the short lifetime and limited action region of O , are undesirable impediments for photodynamic therapy (PDT), leading to a greatly reduced effectiveness. To overcome these adversities, a mitochondria-targeting, H O -activatable, and O -evolving PDT nanoplatform is developed based on Fe -doped two-dimensional C N nanofusiform for highly selective and efficient cancer treatment. The ultrahigh surface area of 2D nanosheets enhances the photosensitizer (PS) loading capacity and the doping of Fe leads to peroxidase mimetics with excellent catalytic performance towards H O in cancer cells to generate O . As such tumor hypoxia can be overcome and the PDT efficacy is improved, whilst at the same time endowing the PDT theranostic agent with an effective T -weighted in vivo magnetic resonance imaging (MRI) ability. Conjugation with a mitochondria-targeting agent could further increase the sensitivity of cancer cells to O by enhanced mitochondria dysfunction. In vitro and in vivo anticancer studies demonstrate an outstanding therapeutic effectiveness of the developed PDT agent, leading to almost complete destruction of mouse cervical tumor. This development offers an attractive theranostic agent for in vivo MRI and synergistic photodynamic therapy toward clinical applications.

We examine the lepton-specific 2HDM as a solution of muon g − 2 anomaly under various theoretical and experimental constraints, especially the direct search limits from the LHC and the requirement of a strong first-order phase transition in the early universe. We find that the muon g-2 anomaly can be explained in the region of 32 < tan β < 80, 10 GeV < m A < 65 GeV, 260GeV < m H < 620 GeV and 180 GeV < m H ± < 620 GeV after imposing the joint constraints from the theory, the precision electroweak data, the 125 GeV Higgs data, the leptonic/semi-hadronic τ decays, the leptonic Z decays and Br(B s → µ + µ − ). The direct searches from the h → AA channels can impose stringent upper limits on Br(h → AA) and the multi-lepton event searches can sizably reduce the allowed region of m A and tan β (10 GeV < m A < 44 GeV and 32 < tan β < 60). Finally, we find that the model can produce a strong first-order phase transition in the region of 14 GeV < m A < 25 GeV, 310 GeV < m H < 355 GeV and 250 GeV < m H ± < 295 GeV, allowed by the explanation of the muon g − 2 anomaly.

Many standard model extensions, including composite Goldstone Higgs models, predict vectorlike fermionic top-partners at the TeV scale. The intensive search programmes by ATLAS and CMS focus on decays into a 3 rd generation quark and an electroweak boson (W, Z, h). However, underlying models of partial compositeness contain additional states that give rise to exotic top partner decays. We consider a well-motivated scenario in which a charge-2/3 top-partner decays into a pseudo-scalar, T → t a, with a → gg or bb dominating below the tt threshold. We show that the constraints on the top partner mass from QCD pair production are substantially weakened, still allowing a top partner mass as light as 400 GeV.

In some supersymmetric models like split supersymmetry or models with non-universal gaugino mass, bino (LSP) and winos (NLSP) may have rather small mass splitting in order to provide the correct dark matter relic density through bino/wino co-annihilation. Such a scenario with the compressed bino/wino is difficult to explore at the LHC. In this work we propose to probe this scenario from pp → jχ 0 2χ ± 1 followed byχ 0 2 → γχ 0 1 andχ ± 1 → W * χ0 1 → ℓ ± νχ 0 1 (this method is also applicable to the compressed bino/higgsino scenario). Through a detailed Monte Carlo simulation for both the signal and the backgrounds, we find that for a mass splitting ∆M ∼ 5 − 15 GeV between bino (LSP) and wino (NLSP), the 14 TeV LHC with luminosity of 500f b −1 can probe the wino up to 150 GeV (the sensitivity can reach 5σ for ∆M = 5 GeV and 2σ for ∆M = 15 GeV). We also investigate the dark matter detection sensitivities for this scenario and find that the planned XENON-1T(2017) cannot fully cover the parameter space with wino below 150 GeV allowed by relic density and the LUX limits.

Background: To explore whether radiomics combined with computed tomography (CT) images can be used to establish a model for differentiating high grade (International Society of Urological Pathology [ISUP] grade III–IV) from low-grade (ISUP I–II) clear cell renal cell carcinoma (ccRCC). Methods: For this retrospective study, 3-phase contrast-enhanced CT images were collected from 227 patients with pathologically confirmed ISUP-grade ccRCC (155 cases in the low-grade group and 72 cases in the high-grade group). First, we delineated the largest dimension of the tumor in the corticomedullary and nephrographic CT images to obtain the region of interest. Second, variance selection, single variable selection, and the least absolute shrinkage and selection operator were used to select features in the corticomedullary phase, nephrographic phase, and 2-phase union samples, respectively. Finally, a model was constructed using the optimal features, and the receiver operating characteristic curve and area under the curve (AUC) were used to evaluate the predictive performance of the features in the training and validation queues. A Z test was employed to compare the differences in AUC values. Results: The support vector machine (SVM) model constructed using the screening features for the 2-stage joint samples can effectively distinguish between high- and low-grade ccRCC, and obtained the highest prediction accuracy. Its AUC values in the training queue and the validation queue were 0.88 and 0.91, respectively. The results of the Z test showed that the differences between the 3 groups were not statistically significant. Conclusion: The SVM model constructed by CT-based radiomic features can effectively identify the ISUP grades of ccRCC.

The phenomenology of dark matter is complicated if dark matter is a composite particle as a hadron under a dark gauge group. Once a dark parton is produced at a high energy collider, it showers and evolves to a jet-like object, eventually it provides a collider signature depending on interactions with particles of the Standard Model (SM). For example, a finite lifetime of dark hadron would provide a displaced vertex. Thus by considering features in various subdetectors, one can identify a jet from a dark parton ("dark jet") with analysis methods in conventional exotic searches. However if the lifetime of the dark hadron is collidernegligible (too short to manifest a displaced vertex), it would be hard to tag a dark jet over Quantum Chromodynamics (QCD) jets of SM. Thus conventional analyses with information from various sub-detectors are not enough to probe dark matter physics in general at colliders. We propose an analysis to utilize a combination of jet-substructure variables to identify dark jets over backgrounds. We study features of jet-substructure variables for a dark jet. We identify what parameters in dark jet are relevant to performance of a given jet-substructure variable. To maximize performance we apply a boost decision tree (BDT) to jet-substructure variables in tagging dark QCD jet over QCD jets. As an illustration, we perform the LHC fourjet analysis with / without jet-substructure variables. Our result shows that by combining various jet-substructure variables, one could get a good discrimination performance to identify a dark jet over QCD backgrounds. We also discuss systematic uncertainties from the choice of parameters in a Monte Carlo simulation in estimating tagging efficiency.