Influence of interpersonal distance on collaborative performance in the joint Simon task-An fNIRS-based hyperscanning study.

Collaboration is a critical skill in everyday life. It has been suggested that collaborative performance may be influenced by social factors such as interpersonal distance, which is defined as the perceived psychological distance between individuals. Previous literature has reported that close interpersonal distance may promote the level of self-other integration between interacting members, and in turn, enhance collaborative performance. These studies mainly focused on interdependent collaboration, which requires high levels of shared representations and self-other integration. However, little is known about the effect of interpersonal distance on independent collaboration (e.g., the joint Simon task), in which individuals perform the task independently while the final outcome is determined by the parties. To address this issue, we simultaneously measured the frontal activations of ninety-four pairs of participants using a functional near-infrared spectroscopy (fNIRS)-based hyperscanning technique while they performed a joint Simon task. Behavioral results showed that the Joint Simon Effect (JSE), defined as the RT difference between incongruent and congruent conditions indicating the level of self-other integration between collaborators, was larger in the friend group than in the stranger group. Consistently, the inter-brain neural synchronization (INS) across the dorsolateral and medial parts of the prefrontal cortex was also stronger in the friend group. In addition, INS in the left dorsolateral prefrontal cortex negatively predicted JSE only in the friend group. These results suggest that close interpersonal distance may enhance the shared mental representation among collaborators, which in turn influences their collaborative performance.

Highly-accelerated CEST MRI using frequency-offset-dependent k-space sampling and deep-learning reconstruction.

PURPOSE: To develop a highly accelerated CEST Z-spectral acquisition method using a specifically-designed k-space sampling pattern and corresponding deep-learning-based reconstruction. METHODS: For k-space down-sampling, a customized pattern was proposed for CEST, with the randomized probability following a frequency-offset-dependent (FOD) function in the direction of saturation offset. For reconstruction, the convolution network (CNN) was enhanced with a Partially Separable (PS) function to optimize the spatial domain and frequency domain separately. Retrospective experiments on a self-acquired human brain dataset (13 healthy adults and 15 brain tumor patients) were conducted using k-space resampling. The prospective performance was also assessed on six healthy subjects. RESULTS: In retrospective experiments, the combination of FOD sampling and PS network (FOD + PSN) showed the best quantitative metrics for reconstruction, outperforming three other combinations of conventional sampling with varying density and a regular CNN (nMSE and SSIM, p < 0.001 for healthy subjects). Across all acceleration factors from 4 to 14, the FOD + PSN approach consistently outperformed the comparative methods in four contrast maps including MTRasym, MTRrex, as well as the Lorentzian Difference maps of amide and nuclear Overhauser effect (NOE). In the subspace replacement experiment, the error distribution demonstrated the denoising benefits achieved in the spatial subspace. Finally, our prospective results obtained from healthy adults and brain tumor patients (14×) exhibited the initial feasibility of our method, albeit with less accurate reconstruction than retrospective ones. CONCLUSION: The combination of FOD sampling and PSN reconstruction enabled highly accelerated CEST MRI acquisition, which may facilitate CEST metabolic MRI for brain tumor patients.

Free-breathing abdominal chemical exchange saturation transfer imaging using water presaturation and respiratory gating at 3.0 T.

Free-breathing abdominal chemical exchange saturation transfer (CEST) has great potential for clinical application, but its technical implementation remains challenging. This study aimed to propose and evaluate a free-breathing abdominal CEST sequence. The proposed sequence employed respiratory gating (ResGat) to synchronize the data acquisition with respiratory motion and performed a water presaturation module before the CEST saturation to abolish the influence of respiration-induced repetition time variation. In vivo experiments were performed to compare different respiratory motion-control strategies and B0 offset correction methods, and to evaluate the effectiveness and necessity of the quasi-steady-state (QUASS) approach for correcting the influence of the water presaturation module on CEST signal. ResGat with a target expiratory phase of 0.5 resulted in a higher structural similarity index and a lower coefficient of variation on consecutively acquired CEST S0 images than breath-holding (BH) and respiratory triggering (all p < 0.05). B0 maps derived from the abdominal CEST dataset itself were more stable for B0 correction, compared with the separately acquired B0 maps by a dual-echo time scan and B0 maps derived from the water saturation shift referencing approach. Compared with BH, ResGat yielded more homogeneous magnetization transfer ratio asymmetry maps at 3.5 ppm (standard deviation: 3.96% vs. 3.19%, p = 0.036) and a lower mean squared difference between scan and rescan (27.52‱ vs. 16.82‱, p = 0.004). The QUASS approach could correct the water presaturation-induced CEST signal change, but its necessity for in vivo scanning needs further verification. The proposed free-breathing abdominal CEST sequence using ResGat had an acquisition efficiency of approximately four times that using BH. In conclusion, the proposed free-breathing abdominal CEST sequence using ResGat and water presaturation has a higher acquisition efficiency and image quality than abdominal CEST using BH.

Synthesis of higher-B0 CEST Z-spectra from lower-B0 data via deep learning and singular value decomposition.

Chemical exchange saturation transfer (CEST) MRI at 3 T suffers from low specificity due to overlapping CEST effects from multiple metabolites, while higher field strengths (B0) allow for better separation of Z-spectral "peaks," aiding signal interpretation and quantification. However, data acquisition at higher B0 is restricted by equipment access, field inhomogeneity and safety issues. Herein, we aim to synthesize higher-B0 Z-spectra from readily available data acquired with 3 T clinical scanners using a deep learning framework. Trained with simulation data using models based on Bloch-McConnell equations, this framework comprised two deep neural networks (DNNs) and a singular value decomposition (SVD) module. The first DNN identified B0 shifts in Z-spectra and aligned them to correct frequencies. After B0 correction, the lower-B0 Z-spectra were streamlined to the second DNN, casting into the key feature representations of higher-B0 Z-spectra, obtained through SVD truncation. Finally, the complete higher-B0 Z-spectra were recovered from inverse SVD, given the low-rank property of Z-spectra. This study constructed and validated two models, a phosphocreatine (PCr) model and a pseudo-in-vivo one. Each experimental dataset, including PCr phantoms, egg white phantoms, and in vivo rat brains, was sequentially acquired on a 3 T human and a 9.4 T animal scanner. Results demonstrated that the synthetic 9.4 T Z-spectra were almost identical to the experimental ground truth, showing low RMSE (0.11% ± 0.0013% for seven PCr tubes, 1.8% ± 0.2% for three egg white tubes, and 0.79% ± 0.54% for three rat slices) and high R2 (>0.99). The synthesized amide and NOE contrast maps, calculated using the Lorentzian difference, were also well matched with the experiments. Additionally, the synthesis model exhibited robustness to B0 inhomogeneities, noise, and other acquisition imperfections. In conclusion, the proposed framework enables synthesis of higher-B0 Z-spectra from lower-B0 ones, which may facilitate CEST MRI quantification and applications.

Peptide-Functionalized Prussian Blue Nanomaterial for Antioxidant Stress and NIR Photothermal Therapy against Alzheimer's Disease.

Excessive accumulations of reactive oxygen species (ROS) and amyloid-ß (Aß) protein are closely associated with the complex pathogenesis of Alzheimer's disease (AD). Therefore, approaches that synergistically exert elimination of ROS and dissociation of Aß fibrils are effective therapeutic strategies for correcting the AD microenvironment. Herein, a novel near infrared (NIR) responsive Prussian blue-based nanomaterial (PBK NPs) is established with excellent antioxidant activity and photothermal effect. PBK NPs possess similar activities to multiple antioxidant enzymes, including superoxide dismutase, peroxidase, and catalase, which can eliminate massive ROS and relieve oxidative stress. Under the NIR irradiation, PBK NPs can generate local heat to disaggregate Aß fibrils efficiently. By modifying CKLVFFAED peptide, PBK NPs display obvious targeting ability for blood-brain barrier penetration and Aß binding. Furthermore, in vivo studies demonstrate that PBK NPs have outstanding ability to decompose Aß plaques and alleviate neuroinflammation in AD mouse model. Overall, PBK NPs provide evident neuroprotection by reducing ROS levels and regulating Aß deposition, and may accelerate the development of multifunctional nanomaterials for delaying the progression of AD.

Reassembled saturation transfer (REST) MR images at 2 B1 values for in vivo exchange-dependent imaging of amide and nuclear Overhauser enhancement.

PURPOSE: Design an efficient CEST scheme for exchange-dependent images with high contrast-to-noise ratio. THEORY: Reassembled saturation transfer (REST) signals were defined as Δ $$ \Delta $$ r.Z = r.Zref - r.ZCEST and the reassembled exchange-dependen magnetization transfer ratio r.MTRRex  = r.1/Zref - r.1/ZCEST , utilizing the averages over loosely sampled reference frequency offsets as Zref and over densely sampled target offsets as ZCEST . Using r.MTRRex measured under 2 B1,sat values, exchange rate could be estimated. METHODS: The REST approach was optimized and assessed quantitatively by simulations for various exchange rates, pool concentration, and water T1 . In vivo evaluation was performed on ischemic rat brains at 7 Tesla and human brains at 3 Tesla, in comparison with conventional asymmetrical analysis, Lorentzian difference (LD), an MTRRex_ LD. RESULTS: For a broad choice of Δ ω ref $$ \Delta {\omega}_{ref} $$ ranges and numbers, Δr.Z and r.MTRRex exhibited comparable quantification features with conventional LD and MTRRex _LD, respectively, when B1,sat  ≤ 1 µT. The subtraction of 2 REST values under distinct B1,sat values showed linear relationships with exchange rate and obtained immunity to field inhomogeneity and variation in MT and water T1 . For both rat and human studies, REST images exhibited similar contrast distribution to MTRRex _LD, with superiority in contrast-to-noise ratio and acquisition efficiency. Compared with MTRRex _LD, 2-B1,sat subtraction REST images displayed better resistance to B1 inhomogeneity, with more specific enhanced regions. They also showed higher signals for amide than for nuclear Overhauser enhancement effect in human brain, presumably reflecting the higher increment from faster-exchanging species as B1,sat increased. CONCLUSION: Featuring high contrast-to-noise ratio efficiency, REST could be a practical exchange-dependent approach readily applicable to either retrospective Z-spectra analysis or perspective 6-offset acquisition.

Radiofrequency labeling strategies in chemical exchange saturation transfer MRI.

Chemical exchange saturation transfer (CEST) MRI has generated great interest for molecular imaging applications because it can image low-concentration solute molecules in vivo with enhanced sensitivity. CEST effects are detected indirectly through a reduction in the bulk water signal after repeated perturbation of the solute proton magnetization using one or more radiofrequency (RF) irradiation pulses. The parameters used for these RF pulses-frequency offset, duration, shape, strength, phase, and interpulse spacing-determine molecular specificity and detection sensitivity, thus their judicious selection is critical for successful CEST MRI scans. This review article describes the effects of applying RF pulses on spin systems and compares conventional saturation-based RF labeling with more recent excitation-based approaches that provide spectral editing capabilities for selectively detecting molecules of interest and obtaining maximal contrast.

Frequency importance analysis for chemical exchange saturation transfer magnetic resonance imaging using permuted random forest.

Chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) is a promising molecular imaging tool that allows sensitive detection of endogenous metabolic changes. However, because the CEST spectrum does not display a clear peak like MR spectroscopy, its signal interpretation is challenging, especially under 3-T field strength or with a large saturation B1 . Herein, as an alternative to conventional Z-spectral fitting approaches, a permuted random forest (PRF) method is developed to determine featured saturation frequencies for lesion identification, so-called CEST frequency importance analysis. Briefly, voxels in the CEST dataset were labeled as lesion and control according to multicontrast MR images. Then, by considering each voxel's saturation signal series as a sample, a permutation importance algorithm was employed to rank the contribution of saturation frequency offsets in the differentiation of lesion and normal tissue. Simulations demonstrated that PRF could correctly determine the frequency offsets (3.5 or -3.5 ppm) for classifying two groups of Z-spectra, under a range of B0 , B1 conditions and sample sizes. For ischemic rat brains, PRF only displayed high feature importance around amide frequency at 2 h postischemia, reflecting that the pH changes occurred at an early stage. By contrast, the data acquired at 24 h postischemia exhibited high feature importance at multiple frequencies (amide, water, and lipids), which suggested the complex tissue changes that occur during the later stages. Finally, PRF was assessed using 3-T CEST data from four brain tumor patients. By defining the tumor region on amide proton transfer-weighted images, PRF analysis identified different CEST frequency importance for two types of tumors (glioblastoma and metastatic tumor) (p < 0.05, with each image slice as a subject). In conclusion, the PRF method was able to rank and interpret the contribution of all acquired saturation offsets to lesion identification; this may facilitate CEST analysis in clinical applications, and open up new doors for comprehensive CEST analysis tools other than model-based approaches.

Study on the Controllable Preparation of Nd3+ Doped in Fe3O4 Nanoparticles for Magnetic Protective Fabrics.

Magnetic protective fabrics with fine wearability and great protective properties are highly desirable for aerospace, national defense, and wearable protective applications. The study of the controllable preparation method of Nd3+ doped in Fe3O4 nanoparticles with supposed magnetic properties remains a challenge. The characterization of the microstructure, elemental composition, and magnetic properties of NdFe2O4 nanoparticles was verified. Then, the surface of NdFe2O4 was treated with glyceric acid to provide sufficient -OH. Subsequently, the connection of the nanoparticle by the succinimide group was studied and then grafted onto cotton fabrics as its bridging effect. The optimal loading rate of the functional fabrics with nanoparticles of an average size of 230 nm was 1.37% after a 25% alkali pretreatment. The color fatness to rubbing results showed better stability after washing and drying. The corresponding hysteresis loop indicated that the functional fabrics exhibited typical magnetism behavior with a closed "S" shape and a magnetic saturation value of 17.61 emu.g-1 with a particle size of 230 nm. However, the magnetic saturation value of the cotton fabric of 90 nm was just 4.89 emu.g-1, exhibiting controllable preparation for the aimed electromagnetic properties and great potential in radiation protective fields. The electrochemical properties of the functional fabrics exhibited extremely weak electrical conductivity caused by the movement of the magnetic dipole derived from the NdFe2O4 nanoparticles.

Deep learning-based classification of preclinical breast cancer tumor models using chemical exchange saturation transfer magnetic resonance imaging.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging has shown promise for classifying tumors based on their aggressiveness, but CEST contrast is complicated by multiple signal sources and thus prolonged acquisition times are often required to extract the signal of interest. We investigated whether deep learning could help identify pertinent Z-spectral features for distinguishing tumor aggressiveness as well as the possibility of acquiring only the pertinent spectral regions for more efficient CEST acquisition. Human breast cancer cells, MDA-MB-231 and MCF-7, were used to establish bi-lateral tumor xenografts in mice to represent higher and lower aggressive tumors, respectively. A convolutional neural network (CNN)-based classification model, trained on simulated data, utilized Z-spectral features as input to predict labels of different tissue types, including MDA-MB-231, MCF-7, and muscle tissue. Saliency maps reported the influence of Z-spectral regions on classifying tissue types. The model was robust to noise with an accuracy of more than 91.5% for low and moderate noise levels in simulated testing data (SD of noise less than 2.0%). For in vivo CEST data acquired with a saturation pulse amplitude of 2.0 µT, the model had a superior ability to delineate tissue types compared with Lorentzian difference (LD) and magnetization transfer ratio asymmetry (MTRasym ) analysis, classifying tissues to the correct types with a mean accuracy of 85.7%, sensitivity of 81.1%, and specificity of 94.0%. The model's performance did not improve substantially when using data acquired at multiple saturation pulse amplitudes or when adding LD or MTRasym spectral features, and did not change when using saliency map-based partial or downsampled Z-spectra. This study demonstrates the potential of CNN-based classification to distinguish between different tumor types and muscle tissue, and speed up CEST acquisition protocols.

Flexible Triboelectric Nanogenerators Based on Electrospun Poly(vinylidene fluoride) with MoS2/Carbon Nanotube Composite Nanofibers.

With the miniaturization of wearable smart devices, the demand for portable and sustainable power sources is increasing. Herein, a flexible and lightweight triboelectric nanogenerator (PMC-TENG) was fabricated with MoS2/carbon nanotube (MC)-doped PVDF as the friction substrate based on electrospinning for harvesting random body motion energy under complex mechanical deformations. The charge density on the friction surface of PVDF nanofibers was found to increase significantly as the introduced electron acceptor of the MC composite, and nylon as a clothing material for another friction layer simplifies the structure of the device. Upon optimization of the electrospinning preparation process, the output voltage of the prepared PMC-TENG can reach >300 V and the instantaneous power can reach 0.484 mW (∼6 cm × 6 cm). At the same time, the PMC-TENG remains stable over 3000 cycles and has the ability to charge a capacitor. The flexible device demonstrates an excellent capability of converting mechanical energy to electrical energy. Therefore, this study has good prospects for application in the field of power supply for portable electronic devices and others.

Reporter Genes for Brain Imaging Using MRI, SPECT and PET.

The use of molecular imaging technologies for brain imaging can not only play an important supporting role in disease diagnosis and treatment but can also be used to deeply study brain functions. Recently, with the support of reporter gene technology, optical imaging has achieved a breakthrough in brain function studies at the molecular level. Reporter gene technology based on traditional clinical imaging modalities is also expanding. By benefiting from the deeper imaging depths and wider imaging ranges now possible, these methods have led to breakthroughs in preclinical and clinical research. This article focuses on the applications of magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), and positron emission tomography (PET) reporter gene technologies for use in brain imaging. The tracking of cell therapies and gene therapies is the most successful and widely used application of these techniques. Meanwhile, breakthroughs have been achieved in the research and development of reporter genes and their imaging probe pairs with respect to brain function research. This paper introduces the imaging principles and classifications of the reporter gene technologies of these imaging modalities, lists the relevant brain imaging applications, reviews their characteristics, and discusses the opportunities and challenges faced by clinical imaging modalities based on reporter gene technology. The conclusion is provided in the last section.

Removal of microcystins from water and primary treatment technologies - A comprehensive understanding based on bibliometric and content analysis, 1991-2020.

Microcystins are a group of heptapeptide hepatotoxins produced by a variety of algae and are frequently detected in aquatic ecosystems, posing a global threat to ecological stability and human health. However, it is difficult to eliminate them completely and innocuously from water by conventional water treatment processes. This study comprehensively evaluated a total of 821 original articles retrieved from the Web of Science (1991-2020) about the removal of microcystins using bibliometric and content analysis to provide a qualitative and quantitative research landscape and a global view of research hotspots and future research directions. Furthermore, the primary and promising treatment technologies for microcystin pollution were also summarized and discussed. The results indicated an urgent practical demand to remediate microcystin pollution according to the increasing number of publications since 2005. China had the highest number of publications, whereas the United States was the core country in the international collaboration network. The Chinese Academy of Sciences and University of Cincinnati showed their leading positions considering article amounts and academic cooperation. Dionysiou DD contributed the most articles, and Carmichael WW had the highest number of co-citations. Three treatment technologies, including biodegradation, chemical oxidation and adsorption, were the major strategies to remediate the pollution of microcystins in water. In addition, the toxicity of toxins/their metabolites, degradation kinetics, and elimination mechanism were also important research contents. Bacterial degradation, photocatalytic degradation, and multiple-technologies approach have been identified with great potential and should be given more attention in future studies. This work summarizes the current research status on microcystin management, provides a valuable reference for researchers to identify potential opportunities for collaboration in related fields, and guides future research directions to inter-disciplinary and multi-perspective approaches.

Smart Catalyzed Hairpin Assembly-Induced DNAzyme Nanosystem for Intracellular UDG Imaging.

Uracil DNA glycosylase (UDG) is one of the key initiators for the base excision repair pathway. Since abnormal UDG expression is associated with various diseases, sensitive detection of UDG activity is critical for early clinical diagnosis. Here, a smart catalyzed hairpin assembly (CHA)-DNAzyme nanosystem is developed for intracellular UDG imaging by incorporating CHA and DNAzyme onto MnO2 nanosheets. In this strategy, the biodegradable MnO2 nanosheets are employed as nanocarriers for efficiently adsorbing and delivering five DNA probes into cells by endocytosis. Then, the MnO2 nanosheets are degraded by cellular glutathione to release the DNA modules at the same intracellular position. Liberated Mn2+, an indispensable DNAzyme cofactor, was used to promote catalytic cleavage for facilitating the cascade process in cells. Based on the uracil site-recognition and -excision operation of the target UDG, the activated CHA-DNAzyme nanosystem generates lots of DNAzyme-assisted CHA products, turning on the fluorescence resonance energy transfer response. This autocatalytic CHA-DNAzyme nanosystem provides a detectable minimum UDG concentration of 0.23 mU/mL, which is comparable to some reported UDG detection approaches. As a multiple signal amplification strategy, the CHA-DNAzyme nanosystem realizes the UDG imaging in living cells with enhanced sensitivity, indicating great promise in the prediction and diagnosis of early-stage cancer.

SP8 and SP9 coordinately promote D2-type medium spiny neuron production by activating Six3 expression.

Dopamine receptor DRD1-expressing medium spiny neurons (D1 MSNs) and dopamine receptor DRD2-expressing medium spiny neurons (D2 MSNs) are the principal projection neurons in the striatum, which is divided into dorsal striatum (caudate nucleus and putamen) and ventral striatum (nucleus accumbens and olfactory tubercle). Progenitors of these neurons arise in the lateral ganglionic eminence (LGE). Using conditional deletion, we show that mice lacking the transcription factor genes Sp8 and Sp9 lose virtually all D2 MSNs as a result of reduced neurogenesis in the LGE, whereas D1 MSNs are largely unaffected. SP8 and SP9 together drive expression of the transcription factor Six3 in a spatially restricted domain of the LGE subventricular zone. Conditional deletion of Six3 also prevents the formation of most D2 MSNs, phenocopying the Sp8/9 mutants. Finally, ChIP-Seq reveals that SP9 directly binds to the promoter and a putative enhancer of Six3 Thus, this study defines components of a transcription pathway in a regionally restricted LGE progenitor domain that selectively drives the generation of D2 MSNs.

Multimodal imaging of a rare interventricular septum dissecting aneurysm: A case report.

We report the case of a patient who presented with chest pain and palpitation, and in whom multimodality imaging, including transthoracic echocardiography, computer tomography angiogram, and coronary angiogram led to the diagnosis of interventricular septum dissecting aneurysm resulting from the rupture of a sinus of Valsalva aneurysm and paravalvular aortic root pseudoaneurysm. The patient underwent the modified Cabrol procedure in the cardiac surgery department. His ruptured sinus of Valsalva aneurysm was repaired and its communication with the pseudoaneurysm was closed. This case report highlights the role of multimodality cardiac imaging.

A Brief History and Future Prospects of CEST MRI in Clinical Non-Brain Tumor Imaging.

Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging tool which allows the specific detection of metabolites that contain exchangeable amide, amine, and hydroxyl protons. Decades of development have progressed CEST imaging from an initial concept to a clinical imaging tool that is used to assess tumor metabolism. The first translation efforts involved brain imaging, but this has now progressed to imaging other body tissues. In this review, we summarize studies using CEST MRI to image a range of tumor types, including breast cancer, pelvic tumors, digestive tumors, and lung cancer. Approximately two thirds of the published studies involved breast or pelvic tumors which are sites that are less affected by body motion. Most studies conclude that CEST shows good potential for the differentiation of malignant from benign lesions with a number of reports now extending to compare different histological classifications along with the effects of anti-cancer treatments. Despite CEST being a unique 'label-free' approach with a higher sensitivity than MR spectroscopy, there are still some obstacles for implementing its clinical use. Future research is now focused on overcoming these challenges. Vigorous ongoing development and further clinical trials are expected to see CEST technology become more widely implemented as a mainstream imaging technology.

Furin-mediated intracellular self-assembly of olsalazine nanoparticles for enhanced magnetic resonance imaging and tumour therapy.

Among the strategies used for enhancement of tumour retention of imaging agents or anticancer drugs is the rational design of probes that undergo a tumour-specific enzymatic reaction preventing them from being pumped out of the cell. Here, the anticancer agent olsalazine (Olsa) was conjugated to the cell-penetrating peptide RVRR. Taking advantage of a biologically compatible condensation reaction, single Olsa-RVRR molecules were self-assembled into large intracellular nanoparticles by the tumour-associated enzyme furin. Both Olsa-RVRR and Olsa nanoparticles were readily detected with chemical exchange saturation transfer magnetic resonance imaging by virtue of exchangeable Olsa hydroxyl protons. In vivo studies using HCT116 and LoVo murine xenografts showed that the OlsaCEST signal and anti-tumour therapeutic effect were 6.5- and 5.2-fold increased, respectively, compared to Olsa without RVRR, with an excellent 'theranostic correlation' (R2 = 0.97) between the imaging signal and therapeutic response (normalized tumour size). This furin-targeted, magnetic resonance imaging-detectable platform has potential for imaging tumour aggressiveness, drug accumulation and therapeutic response.

Dlx1/2 are Central and Essential Components in the Transcriptional Code for Generating Olfactory Bulb Interneurons.

Generation of olfactory bulb (OB) interneurons requires neural stem/progenitor cell specification, proliferation, differentiation, and young interneuron migration and maturation. Here, we show that the homeobox transcription factors Dlx1/2 are central and essential components in the transcriptional code for generating OB interneurons. In Dlx1/2 constitutive null mutants, the differentiation of GSX2+ and ASCL1+ neural stem/progenitor cells in the dorsal lateral ganglionic eminence is blocked, resulting in a failure of OB interneuron generation. In Dlx1/2 conditional mutants (hGFAP-Cre; Dlx1/2F/- mice), GSX2+ and ASCL1+ neural stem/progenitor cells in the postnatal subventricular zone also fail to differentiate into OB interneurons. In contrast, overexpression of Dlx1&2 in embryonic mouse cortex led to ectopic production of OB-like interneurons that expressed Gad1, Sp8, Sp9, Arx, Pbx3, Etv1, Tshz1, and Prokr2. Pax6 mutants generate cortical ectopia with OB-like interneurons, but do not do so in compound Pax6; Dlx1/2 mutants. We propose that DLX1/2 promote OB interneuron development mainly through activating the expression of Sp8/9, which further promote Tshz1 and Prokr2 expression. Based on this study, in combination with earlier ones, we propose a transcriptional network for the process of OB interneuron development.

Effects of Air Cavity in Dynamic Pressure Sensors: Experimental Validation.

An air-backed diaphragm is the key structure of most dynamic pressure sensors and plays a critical role in determining the sensor performance. Our previous analytical model investigated the influence of air cavity length on the sensitivity and bandwidth. The model found that as the cavity length decreases, the static sensitivity monotonically decreases, and the fundamental natural frequency shows a three-stage trend: increasing in the long-cavity-length range, reaching a plateau value in the medium-cavity-length range, and decreasing in the short-cavity-length range, which cannot be captured by the widely used lumped model. In this study, we conducted the first experimental measurements to validate these findings. Pressure sensors with a circular polyimide diaphragm and a backing air cavity with an adjustable length were designed, fabricated, and characterized, from which the static sensitivities and fundamental natural frequencies were obtained as a function of the cavity length. A further parametric study was conducted by changing the in-plane tension in the diaphragm. A finite element model was developed in COMSOL to investigate the effects of thermoviscous damping and provide validation for the experimental study. Along with the analytical model, this study provides a new understanding and important design guidelines for dynamic pressure sensors with air-backed diaphragms.