Non-invasive neuromodulation technology is important for the treatment of brain diseases. The effects of focused ultrasound on neuronal activity have been investigated since the 1920s. Low intensity ...transcranial focused ultrasound (tFUS) can exert non-destructive mechanical pressure effects on cellular membranes and ion channels and has been shown to modulate the activity of peripheral nerves, spinal reflexes, the cortex, and even deep brain nuclei, such as the thalamus. It has obvious advantages in terms of security and spatial selectivity. This technology is considered to have broad application prospects in the treatment of neurodegenerative disorders and neuropsychiatric disorders. This review synthesizes animal and human research outcomes and offers an integrated description of the excitatory and inhibitory effects of tFUS in varying experimental and disease conditions.
Although promising results have been achieved in the areas of traffic-sign detection and classification, few works have provided simultaneous solutions to these two tasks for realistic real world ...images. We make two contributions to this problem. Firstly, we have created a large traffic-sign benchmark from 100000 Tencent Street View panoramas, going beyond previous benchmarks. It provides 100000 images containing 30000 traffic-sign instances. These images cover large variations in illuminance and weather conditions. Each traffic-sign in the benchmark is annotated with a class label, its bounding box and pixel mask. We call this benchmark Tsinghua-Tencent 100K. Secondly, we demonstrate how a robust end-to-end convolutional neural network (CNN) can simultaneously detect and classify trafficsigns. Most previous CNN image processing solutions target objects that occupy a large proportion of an image, and such networks do not work well for target objects occupying only a small fraction of an image like the traffic-signs here. Experimental results show the robustness of our network and its superiority to alternatives. The benchmark, source code and the CNN model introduced in this paper is publicly available1.
Raising triplet exciton utilization of pure organic luminescent materials is of significant importance for efficiency advancement of organic light-emitting diodes (OLEDs). Herein, by introducing ...bromine atom(s) onto a typical molecule (bis(carbazol-9-yl)-4,5-dicyanobenzene) with thermally activated delayed fluorescence, we demonstrate that the heavy atom effect of bromine can increase spin–orbit coupling and promote the reverse intersystem crossing, which endow the molecules with more distinct delayed fluorescence. In consequence, the triplet exciton utilization is improved greatly with the increase of bromine atoms, affording apparently advanced external quantum efficiencies of OLEDs. Utilizing the enhancement effect of bromine atoms on delayed fluorescence should be a simple and promising design concept for efficient organic luminogens with high exciton utilization.
Clonal cytogenetic evolution with additional chromosomal abnormalities (ACAs) in chronic myelogenous leukemia (CML) is generally associated with decreased response to tyrosine kinase inhibitor (TKI) ...therapy and adverse survival. Although ACAs are considered as a sign of disease progression and have been used as one of the criteria for accelerated phase, the differential prognostic impact of individual ACAs in CML is unknown, and a classification system to reflect such prognostic impact is lacking. In this study, we aimed to address these questions using a large cohort of CML patients treated in the era of TKIs. We focused on cases with single chromosomal changes at the time of ACA emergence and stratified the 6 most common ACAs into 2 groups: group 1 with a relatively good prognosis including trisomy 8, −Y, and an extra copy of Philadelphia chromosome; and group 2 with a relatively poor prognosis including i(17)(q10), −7/del7q, and 3q26.2 rearrangements. Patients in group 1 showed much better treatment response and survival than patients in group 2. When compared with cases with no ACAs, ACAs in group 2 conferred a worse survival irrelevant to the emergence phase and time. In contrast, ACAs in group 1 had no adverse impact on survival when they emerged from chronic phase or at the time of CML diagnosis. The concurrent presence of 2 or more ACAs conferred an inferior survival and can be categorized into the poor prognostic group.
•Based on their impact on treatment and survival, ACAs in CML were stratified into good and poor prognostic groups.•ACAs in the good prognostic group showed no adverse impact on survival when they emerged from chronic phase or at the initial CML diagnosis.
We propose a localization refinement approach for candidate traffic signs. Previous traffic sign localization approaches, which place a bounding rectangle around the sign, do not always give a ...compact bounding box, making the subsequent classification task more difficult. We formulate localization as a segmentation problem, and incorporate prior knowledge concerning color and shape of traffic signs. To evaluate the effectiveness of our approach, we use it as an intermediate step between a standard traffic sign localizer and a classifier. Our experiments use the well-known German Traffic Sign Detection Benchmark (GTSDB) as well as our new Chinese Traffic Sign Detection Benchmark. This newly created benchmark is publicly available, 1 and goes beyond previous benchmark data sets: it has over 5000 high-resolution images containing more than 14 000 traffic signs taken in realistic driving conditions. Experimental results show that our localization approach significantly improves bounding boxes when compared with a standard localizer, thereby allowing a standard traffic sign classifier to generate more accurate classification results. 1 http://cg.cs.tsinghua.edu.cn/ctsdb/.
Diffuse large B-cell lymphoma (DLBCL) is stratified into prognostically favorable germinal center B-cell (GCB)–like and unfavorable activated B-cell (ABC)–like subtypes based on gene expression ...signatures. In this study, we analyzed 893 de novo DLBCL patients treated with R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone). We show that MYC/BCL2 protein coexpression occurred significantly more commonly in the ABC subtype. Patients with the ABC or GCB subtype of DLBCL had similar prognoses with MYC/BCL2 coexpression and without MYC/BCL2 coexpression. Consistent with the notion that the prognostic difference between the 2 subtypes is attributable to MYC/BCL2 coexpression, there is no difference in gene expression signatures between the 2 subtypes in the absence of MYC/BCL2 coexpression. DLBCL with MYC/BCL2 coexpression demonstrated a signature of marked downregulation of genes encoding extracellular matrix proteins, those involving matrix deposition/remodeling and cell adhesion, and upregulation of proliferation-associated genes. We conclude that MYC/BCL2 coexpression in DLBCL is associated with an aggressive clinical course, is more common in the ABC subtype, and contributes to the overall inferior prognosis of patients with ABC-DLBCL. In conclusion, the data suggest that MYC/BCL2 coexpression, rather than cell-of-origin classification, is a better predictor of prognosis in patients with DLBCL treated with R-CHOP.
•DLBCL patients with MYC/BCL2 coexpression demonstrate inferior prognosis and high-risk gene expression signatures.
The Internet of Things (IoT) and sensors are becoming increasingly popular, especially in monitoring large and ambient environments. Applications that embrace IoT and sensors often require mining the ...data feeds that are collected at frequent intervals for intelligence. Despite the fact that such sensor data are massive, most of the data contents are identical and repetitive; for example, human traffic in a park at night. Most of the traditional classification algorithms were originally formulated decades ago, and they were not designed to handle such sensor data effectively. Hence, the performance of the learned model is often poor because of the small granularity in classification and the sporadic patterns in the data. To improve the quality of data mining from the IoT data, a new pre-processing methodology based on subspace similarity detection is proposed. Our method can be well integrated with traditional data mining algorithms and anomaly detection methods. The pre-processing method is flexible for handling similar kinds of sensor data that are sporadic in nature that exist in many ambient sensing applications. The proposed methodology is evaluated by extensive experiment with a collection of classical data mining models. An improvement over the precision rate is shown by using the proposed method.
The university curriculum is a systematic and organic study complex with some immediate associated steps; the initial learning of each semester’s course is crucial, and significantly impacts the ...learning process of subsequent courses and further studies. However, the low teacher–student ratio makes it difficult for teachers to consistently follow up on the detail-oriented learning situation of individual students. The extant learning early warning system is committed to automatically detecting whether students have potential difficulties—or even the risk of failing, or non-pass reports—before starting the course. Previous related research has the following three problems: first of all, it mainly focused on e-learning platforms and relied on online activity data, which was not suitable for traditional teaching scenarios; secondly, most current methods can only proffer predictions when the course is in progress, or even approaching the end; thirdly, few studies have focused on the feature redundancy in these learning data. Aiming at the traditional classroom teaching scenario, this paper transforms the pre-class student performance prediction problem into a multi-label learning model, and uses the attribute reduction method to scientifically streamline the characteristic information of the courses taken and explore the important relationship between the characteristics of the previously learned courses and the attributes of the courses to be taken, in order to detect high-risk students in each course before the course begins. Extensive experiments were conducted on 10 real-world datasets, and the results proved that the proposed approach achieves better performance than most other advanced methods in multi-label classification evaluation metrics.
Follicular dendritic cell sarcoma (FDCS) is a low-grade malignant neoplasm that tends to be under-recognized owing to its rarity and wide pathologic spectrum. Knowledge of the atypical morphology and ...immunophenotype of FDCS is critical to avoid misdiagnosis. Here we presented a case of extranodal FDCS with an unusual morphology and a previously unreported immunophenotype leading to misdiagnosis. A 32-years-old man presented with a tonsilar mass that showed epithelioid cells in nested and alveolar patterns. Immunohistochemistry study revealed that the tumor cells were positive for CD4 and CD30, and were negative for cytokeratin, CD3, CD20, CD68, CD163, lysozyme, ALK, S-100, and desmin. Multiple outside expert consultations rendered a consensus diagnosis of ALK-negative anaplastic large cell lymphoma (ALCL). The patient received multiple lines of chemotherapy and radiotherapy. However, the residual tumor progressively enlarged eight months later and a more complex morphology was presented in the re-excised tumor: including spindle cells with vesicular nuclei and nuclear pseudoinclusions in fascicles or a whorled pattern, and plump ovoid cells arranged in meningioma-like whorls as well as epithelioid tumor cells similar to the initial biopsy. All these three components were positive for CD4, CD21, CD23, and CD35. The diagnosis was revised to FDCS after a positive immunostaining for CD21, CD23, and CD35 on the initial specimen was confirmed retrospectively. A literature review identified 57 cases of FDCS published from 2009 through 2019, and 13 (22.8%) of them were misdiagnosed at initial presentation. Among these misdiagnosed cases, all except one case were extranodal, and the incorrect initial diagnosis was mostly location-related. These cases expand the pathologic spectrum of FDCS, and further emphasize the necessity for pathologists to stay alert for this rare entity, bringing FDCS into the differentials for any spindle cell tumors, undifferentiated epithelioid cell tumors, and ALCL to avoid misdiagnosis.
This study focused on the effects of biochar (BC) application on soil chemical properties and mobilization of cadmium (Cd) and lead (Pb) in the paddy soil. BC was applied at the rate of 0, 10, 20 and ...40 t ha−1, respectively. BC application caused a significant increase in soil organic carbon contents (SOC), pH, nitrate–nitrogen (NO3−‐N),and available phosphorus contents (AP) in the top and subsurface soil, while SOC contents in the subsurface soil decreased with increasing rate of BC. BC40 effectively reduced the mobility of Cd and Pb from the top layer to the subsurface soil, while concentrations of Cd and Pb in the topsoil remained unchanged. Path analysis showed that the direct path coefficient AP was highest; SOC, NH4+‐N and AP had a negative direct effect on the Cd and Pb in subsurface soil. Soil pH and NO3−‐N had a high negative indirect effect through AP. The decision coefficient decreased in the following order: pH, AP, SOC, NH4+‐N and NO3−‐N. Regression analysis showed that soil Cd and Pb had a significant linear correlation with soil AP, whereas soil Pb also had a significant linear correlation with soil pH. In conclusion, BC40 can alter soil chemical properties and reduce the mobility of Cd and Pb from the top layer to the lower subsurface of the paddy soil.
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