Quantifying local field potential dynamics with amplitude and frequency stability between ON and OFF medication and stimulation in Parkinson's disease.

Neural oscillations are critical to understanding the synchronisation of neural activities and their relevance to neurological disorders. For instance, the amplitude of beta oscillations in the subthalamic nucleus has gained extensive attention, as it has been found to correlate with medication status and the therapeutic effects of continuous deep brain stimulation in people with Parkinson's disease. However, the frequency stability of subthalamic nucleus beta oscillations, which has been suggested to be associated with dopaminergic information in brain states, has not been well explored. Moreover, the administration of medicine can have inverse effects on changes in frequency and amplitude. In this study, we proposed a method based on the stationary wavelet transform to quantify the amplitude and frequency stability of subthalamic nucleus beta oscillations and evaluated the method using simulation and real data for Parkinson's disease patients. The results suggest that the amplitude and frequency stability quantification has enhanced sensitivity in distinguishing pathological conditions in Parkinson's disease patients. Our quantification shows the benefit of combining frequency stability information with amplitude and provides a new potential feedback signal for adaptive deep brain stimulation.

Effects of Training and Calibration Data on Surface Electromyogram-Based Recognition for Upper Limb Amputees.

Surface electromyogram (sEMG)-based gesture recognition has emerged as a promising avenue for developing intelligent prostheses for upper limb amputees. However, the temporal variations in sEMG have rendered recognition models less efficient than anticipated. By using cross-session calibration and increasing the amount of training data, it is possible to reduce these variations. The impact of varying the amount of calibration and training data on gesture recognition performance for amputees is still unknown. To assess these effects, we present four datasets for the evaluation of calibration data and examine the impact of the amount of training data on benchmark performance. Two amputees who had undergone amputations years prior were recruited, and seven sessions of data were collected for analysis from each of them. Ninapro DB6, a publicly available database containing data from ten healthy subjects across ten sessions, was also included in this study. The experimental results show that the calibration data improved the average accuracy by 3.03%, 6.16%, and 9.73% for the two subjects and Ninapro DB6, respectively, compared to the baseline results. Moreover, it was discovered that increasing the number of training sessions was more effective in improving accuracy than increasing the number of trials. Three potential strategies are proposed in light of these findings to enhance cross-session models further. We consider these findings to be of the utmost importance for the commercialization of intelligent prostheses, as they demonstrate the criticality of gathering calibration and cross-session training data, while also offering effective strategies to maximize the utilization of the entire dataset.

Efficacy-specific herbal group detection from traditional Chinese medicine prescriptions via hierarchical attentive neural network model.

BACKGROUND: Mining massive prescriptions in Traditional Chinese Medicine (TCM) accumulated in the lengthy period of several thousand years to discover essential herbal groups for distinct efficacies is of significance for TCM modernization, thus starting to draw attentions recently. However, most existing methods for the task treat herbs with different surface forms orthogonally and determine efficacy-specific herbal groups based on the raw frequencies an herbal group occur in a collection of prescriptions. Such methods entirely overlook the fact that prescriptions in TCM are formed empirically by different people at different historical stages, and thus full of herbs with different surface forms expressing the same material, or even noisy and redundant herbs. METHODS: We propose a two-stage approach for efficacy-specific herbal group detection from prescriptions in TCM. For the first stage we devise a hierarchical attentive neural network model to capture essential herbs in a prescription for its efficacy, where herbs are encoded with dense real-valued vectors learned automatically to identify their differences on the semantical level. For the second stage, frequent patterns are mined to discover essential herbal groups for an efficacy from distilled prescriptions obtained in the first stage. RESULTS: We verify the effectiveness of our proposed approach from two aspects, the first one is the ability of the hierarchical attentive neural network model to distill a prescription, and the second one is the accuracy in discovering efficacy-specific herbal groups. CONCLUSION: The experimental results demonstrate that the hierarchical attentive neural network model is capable to capture herbs in a prescription essential to its efficacy, and the distilled prescriptions significantly could improve the performance of efficacy-specific herbal group detection.

Lack of TAK1 in dendritic cells inhibits the contact hypersensitivity response induced by trichloroethylene in local lymph node assay.

Trichloroethylene (TCE) is a ubiquitous environmental contaminant. Occupational TCE exposure has been associated with severe, generalized contact hypersensitivity (CHS) skin disorder. The development of CHS depends on innate and adaptive immune functions. Transforming growth factor-ß activated kinase-1 (TAK1) controls the survival of dendritic cells (DCs) that affect the immune system homeostasis. We aimed to investigate the role of TAK1 activity in DC on TCE-induced CHS response. Control mice and DC-specific TAK1 deletion mice were treated with 80% (v/v) TCE using local lymph node assay (LLNA) to establish a TCE-induced CHS model. The draining lymph nodes (DLNs) were excised and the lymphocytes were measure for proliferation by BrdU-ELISA, T-cell phenotype analysis by flow cytometry and signaling pathway activation by western blot. The ears were harvested for histopathological analysis. Control mice in the 80% TCE group displayed an inflammatory response in the ears, increased lymphocyte proliferation, elevated regulatory T-cell and activated T-cell percentages, and more IFN-γ producing CD8(+) T cells in DLNs. In contrast to control mice, DC-specific TAK1 deletion mice in the 80% TCE group showed an abolished CHS response and this was associated with defective T-cell expansion, activation and IFN-γ production. This effect may occur through Jnk and NF-κB signaling pathways. Overall, this study demonstrates a pivotal role of TAK1 in DCs in controlling TCE-induced CHS response and suggests that targeting TAK1 function in DCs may be a viable approach to preventing and treating TCE-related occupational health hazards.

Nasopharyngeal carcinoma patients with retropharyngeal lymph node metastases: a minimum axial diameter of 6 mm is a more accurate prognostic predictor than 5 mm.

OBJECTIVE: The criteria for the diagnosis of metastatic retropharyngeal lymph nodes (RLNs) have not yet been resolved and are not included in the current edition of the American Joint Committee on Cancer (AJCC) staging system (seventh edition) for the staging of nasopharyngeal carcinoma (NPC). The aim of this study was to use MRI to identify an RLN size criterion that can accurately predict prognosis in patients with NPC. MATERIALS AND METHODS: Eight hundred seventeen patients with newly diagnosed localized NPC were identified. All of the patients underwent MRI before treatment with definitive radiation therapy. All the MRI studies and medical records were reviewed retrospectively. Overall survival (OS), distant metastasis-free survival (DMFS), and local relapse-free survival (LRFS) were assessed using SPSS software (version 17.0). RESULTS: RLN size cutoffs of ≥ 5 mm and of ≥ 6 mm were used. There was no significant difference in OS (p = 0.216), DMFS (p = 0.081), or LRFS (p = 0.067) in patients with RLNs ≥ 5 mm and in those with RLNs < 5 mm. When 6 mm was used as a size cutoff, significant differences in OS (p = 0.000) and DMFS (p = 0.001) were identified; there was no significant difference observed for LRFS (p = 0.380). CONCLUSION: A minimum axial RLN diameter of 6 mm was a more accurate prognostic predictor in NPC patients with RLN metastases than 5 mm.

CT Characterization of Duodenal Gastrointestinal Stromal Tumors.

OBJECTIVE: Diagnosis and staging of duodenal gastrointestinal stromal tumors (GISTs) by noninvasive imaging is critical for effective treatment, but the imaging features of duodenal GISTs remain largely undefined because of their rarity. The purpose of this article was to characterize duodenal GISTs using CT. MATERIALS AND METHODS: Thirty-four patients with duodenal GISTs were analyzed by clinical symptom evaluation, pathologic examination, and CT in this retrospective study. Unenhanced and contrast-enhanced examinations were performed in all patients. Imaging characteristics, including the lesion location, size, growth pattern, ulceration, internal components, arterial blood supply, intratumoral arterioportal shunting, intratumoral vessels, rim enhancement, and enhancement patterns were reviewed. RESULTS: The duodenal GISTs were solitary masses with well-defined margins. The average diameter was 7.1 cm. The second portion was the most common site (20/34). Ulceration was a common feature (15/34). Calcification was uncommon (3/34), and mixed growth pattern was more common (26/34). Rim enhancement (24/34) and mixed enhancement pattern (15/34) were common. Arterial blood supply, intratumoral vasculature, and draining veins were all detected and were obvious on the arterial phase. The portal venous trunk and superior mesenteric vein were the main veins into which early arterioportal shunting drained. CONCLUSION: Primary duodenal GISTs are generally large, well-defined, heterogeneously enhancing, and hypervascular masses with a prominent mixed growth pattern on CT images. Our findings suggest that CT can help depict the origin of the tumoral arteries and draining veins on the arterial phase and may be a key defining diagnostic feature for duodenal GISTs.

Simple measurements on diffusion-weighted MR imaging for assessment of complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

PURPOSE: To determine diagnostic performance of simple measurements on diffusion-weighted MR imaging (DWI) for assessment of complete tumour response (CR) after neoadjuvant chemoradiotherapy (CRT) in patients with locally advanced rectal cancer (LARC) by signal intensity (SI) and apparent diffusion coefficient (ADC) measurements. MATERIALS AND METHODS: Sixty-five patients with LARC who underwent neoadjuvant CRT and subsequent surgery were included. Patients underwent pre-CRT and post-CRT 3.0 T MRI. Regions of interest of the highest brightness SI were included in the tumour volume on post-CRT DWI to calculate the SIlesion, rSI, ADClesion and rADC; diagnostic performance was compared by using the receiver operating characteristic (ROC) curves. In order to validate the accuracy and reproducibility of the current strategy, the same procedure was reproduced in 80 patients with LARC at 1.5 T MRI. RESULTS: Areas under the ROC curve for identification of a CR, based on SIlesion, rSI, ADClesion, and rADC, respectively, were 0.86, 0.94, 0.66, and 0.71 at 3.0 T MRI, and 0.92, 0.91, 0.64, and 0.61 at 1.5 T MRI. CONCLUSION: Post-CRT DWI SIlesion and rSI provided high diagnostic performance in assessing CR and were significantly more accurate than ADClesion, and rADC at 3.0 T MRI and 1.5 T MRI. KEY POINTS: • Signal intensity (SI lesion ) and rSI are accurate for assessment of complete response. • rSI seems to be superior to SI lesion at 3.0 T MRI. • ADC or rADC measurements are not accurate for assessment of complete response.

Engineering a PtCu Alloy to Improve N2 Selectivity of NH3-SCO over the Pt/SSZ-13 Catalyst.

Improving the N2 selectivity is always a great challenge for the selective catalytic oxidation of ammonia (NH3-SCO) over noble-metal-based (especially Pt) catalysts. In this work, Cu as an efficient promoter was introduced into the Pt/SSZ-13 catalyst to significantly improve the N2 selectivity of the NH3-SCO reaction. A PtCu alloy was formed in the PtCu/SSZ-13 catalyst, as confirmed by X-ray diffraction, transmission electron microscopy, energy dispersive spectrometry mapping, and X-ray absorption spectroscopy results. As indicated by the X-ray photoelectron spectroscopy analysis, the Pt species in the alloyed PtCu nanoparticle was mainly present in the electron-rich state on PtCu/SSZ-13, while the electron-deficient Cu and isolated Cu2+ species were both present on the surface of PtCu/SSZ-13. Due to such a unique alloyed structure with an altered oxidation state, the N2 selectivity of NH3-SCO on the PtCu/SSZ-13 catalyst was remarkably improved, while the NH3-SCO activity was kept comparable to that on Pt/SSZ-13. The reaction path was changed from the NH mechanism on Pt/SSZ-13 to both NH and internal selective catalytic reduction mechanisms on the PtCu/SSZ-13 catalyst, which was considered the main reason for the enhanced N2 selectivity. This work provides a new route to synthesize efficient alloy catalysts for optimizing the N2 selectivity of NH3-SCO for NH3 slip control in diesel exhaust purification.

FPGA-based Lightweight QDS-CNN System for sEMG Gesture and Force Level Recognition.

Deep learning (DL) has been used for electromyographic (EMG) signal recognition and achieved high accuracy for multiple classification tasks. However, implementation in resource-constrained prostheses and human-computer interaction devices remains challenging. To overcome these problems, this paper implemented a low-power system for EMG gesture and force level recognition using Zynq architecture. Firstly, a lightweight network model structure was proposed by Ultra-lightweight depth separable convolution (UL-DSC) and channel attention-global average pooling (CA-GAP) to reduce the computational complexity while maintaining accuracy. A wearable EMG acquisition device for real-time data acquisition was subsequently developed with size of 36mm×28mm×4mm. Finally, a highly parallelized dedicated hardware accelerator architecture was designed for inference computation. 18 gestures were tested, including force levels from 22 healthy subjects. The results indicate that the average accuracy rate was 94.92% for a model with 5.0k parameters and a size of 0.026MB. Specifically, the average recognition accuracy for static and force-level gestures was 98.47% and 89.92%, respectively. The proposed hardware accelerator architecture was deployed with 8-bit precision, a single-frame signal inference time of 41.9µs, a power consumption of 0.317W, and a data throughput of 78.6 GOP/s.

Enhanced antifouling and antibacterial performances of novel UV-curable polysiloxane/microcapsules/Ag composite coatings for marine applications.

Marine biological fouling is a widespread phenomenon encountered by various oceanic ships and naval vessels, resulting in enormous economic losses. Herein, novel 4,5-dichloro-2-octyl-isothiazolone@sodium alginate/chitosan microcapsules (DCOIT@ALG/CS) were prepared through composite gel method using DCOIT as core materials, ALG and CS as shells, and CaCl2 as the cross-linking agent. The formed microcapsules (MCs) with Ag nanoparticles (AgNPs) were then filled in UV-curable polysiloxane (UV-PDMS), followed by UV irradiation to yield UV-PDMS/microcapsules/AgNPs (UV-PDMS/MCs/Ag) composite coatings. The constructed micro-nano dual-scale surface using the MCs and AgNPs improved the antifouling and antibacterial properties of UV-PDMS/MCs/Ag coatings. The as-obtained UV-PDMS/MCs/Ag coatings exhibited a static contact angle of about 160°, shear strength of 2.24 MPa, tensile strength of 3.32 MPa and elongation at break of 212%. The synergistic bacteriostatic effects of DCOIT and AgNPs in UV-PDMS/MCs/Ag coatings resulted in a bactericidal rate of 200 µg ml-1 towards Escherichia coli and Staphylococcus aureus with saturation at 100% within 10 min. In sum, the proposed composite coatings look promising for future marine transportation, pipeline networks and undersea facilities.

CT and MRI of radiation-induced sarcomas of the head and neck following radiotherapy for nasopharyngeal carcinoma.

AIM: To investigate the radiological findings of head and neck radiation-induced sarcomas (RISs) following radiotherapy for nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS: Fifty-nine patients with RISs were identified. Imaging characteristics on computed tomography (CT) and magnetic resonance imaging (MRI), including lesion location, extent, size, margin, internal architecture, pattern, and degree of enhancement, together with patient characteristics at NPC diagnosis and latency periods, were reviewed. RESULTS: The study included 20 women and 39 men, with a median age of 49 years (range 30-71 years). The median latency was 9 years (range 3-37 years). The median radiation dose at the site of RIS was 66 Gy (range 44-78 Gy). The most common histological RIS types were fibrosarcoma (44.1%) and osteosarcoma (30.5%). The most common RIS sites were the paranasal sinuses and the nasal cavity (39%), the neck (16.9%), and the mandible (15.3%). The mean size was 5.1 cm (range 1.2-8.6 cm). Overall, 78% of lesions extended to adjacent spaces and 66.1% were accompanied by bone destruction. Heterogeneous density/signal intensity before and after enhancement was seen in all lesions on imaging. Marked lesion enhancement was noted in 49 cases (76.3%). CONCLUSIONS: The radiologist should be aware of the different sites at which RISs occur and the radiological appearance of the wide variety of RIS subtypes. Careful imaging follow-up is necessary for early detection of RISs in patients with NPC after radiotherapy.

Hepatic angiomyolipoma: CT and MR imaging findings with clinical-pathologic comparison.

OBJECTIVE: The objective of this study is to evaluate the clinical, pathologic, and computed tomography (CT) and/or magnetic resonance imaging (MRI) findings of hepatic angiomyolipoma (HAML) and to improve the diagnostic efficacy of the tumor. MATERIALS AND METHODS: Clinical, pathologic, and imaging findings were retrospectively evaluated in 18 patients with HAML. Two patients underwent both CT and MRI, ten underwent CT alone, and six underwent MRI alone. Unenhanced and contrast-enhanced examinations were performed in all patients. Imaging characteristics, such as the lesion location, lesion diameter, presence of early draining veins, attenuation/signal intensity of the lesions on imaging, and enhancement pattern were reviewed. RESULTS: There were 3 male and 15 female patients. HAML was seen as a well-defined, solitary mass on imaging with medium size (mean diameter, 5.9 cm). Fat was detected in ten patients. Calcification was noted in two patients and cystic degeneration was seen in one patient. Hepatic cirrhosis and capsule were not detected in all patients. The mean attenuation values exceeded 120 hounsfield units (HU) in 11 patients (91.7%). Peripherally decreasing enhancement rim as well as early draining vein was seen in 15 patients (83.3%). The early draining veins were all hepatic veins. Tumor vessels were noted in all patients. CONCLUSION: The presence of early draining vein, peripheral decreasing enhancement rim, and the absence of tumor capsule in the hypervascular hepatic tumor on CT and/or MRI together with normal alpha fetal protein may be helpful for the diagnosis of HAML in non-cirrhotic liver.

Abnormal baseline brain activity in patients with HBV-related cirrhosis without overt hepatic encephalopathy revealed by resting-state functional MRI.

Neurocognitive dysfunction of varying degrees is common in patients with hepatitis B virus-related cirrhosis (HBV-RC) without overt hepatic encephalopathy (OHE). However, the neurobiological mechanisms underlying these dysfunctions are not well understood. We sought to identify changes in the neural activity of patients with HBV-RC without OHE in the resting state by using the amplitude of low-frequency fluctuation (ALFF) method and to determine whether these changes were related to impaired cognition. Resting-state functional MRI data from 30 patients with HBV-RC and 30 healthy controls matched for age, sex, and years of education were compared to determine any differences in the ALFF between the two groups. Cognition was measured with the psychometric hepatic encephalopathy score (PHES), and the relationship between these scores and ALFF variation was assessed. Compared with controls, patients showed widespread lower standardized ALFF (mALFF) values in visual association areas (bilateral lingual gyrus, middle occipital gyrus, and left inferior temporal gyrus), motor-related areas (bilateral precentral gyrus, paracentral lobule, and right postcentral gyrus), and the default mode network (bilateral cuneus/precuneus and inferior parietal lobule). Higher mALFF values were found in the bilateral orbital gyrus/rectal gyrus. In patients, mALFF values were significantly positive correlated with the PHES in the right middle occipital gyrus and bilateral precentral gyrus. Our findings of resting-state abnormalities in patients with HBV-RC without OHE suggest that neurocognitive dysfunction in patients with HBV-RC without OHE may be caused by abnormal neural activity in multiple brain regions.

Multichannel Flexible Pulse Perception Array for Intelligent Disease Diagnosis System.

Pressure sensors with high sensitivity, a wide linear range, and a quick response time are critical for building an intelligent disease diagnosis system that directly detects and recognizes pulse signals for medical and health applications. However, conventional pressure sensors have limited sensitivity and nonideal response ranges. We proposed a multichannel flexible pulse perception array based on polyimide/multiwalled carbon nanotube-polydimethylsiloxane nanocomposite/polyimide (PI/MPN/PI) sandwich-structure pressure sensor that can be applied for remote disease diagnosis. Furthermore, we established a mechanical model at the molecular level and guided the preparation of MPN. At the structural level, we achieved high sensitivity (35.02 kPa-1) and a broad response range (0-18 kPa) based on a pyramid-like bilayer microstructure with different upper and lower surfaces. A 27-channel (3 × 9) high-density sensor array was integrated at the device level, which can extract the spatial and temporal distribution information on a pulse. Furthermore, two intelligent algorithms were developed for extracting six-dimensional pulse information and automatic pulse recognition (the recognition rate reaches 97.8%). The results indicate that intelligent disease diagnosis systems have great potential applications in wearable healthcare devices.

Solid neuroendocrine breast carcinoma: mammographic and sonographic features in thirteen cases.

This study aimed to determine and quantitate the mammographic and sonographic characteristics in 13 cases of solid neuroendocrine breast carcinoma (NEBC) and to analyze the association of radiological findings with the clinical and histopathologic findings. The clinical data and imaging findings of 13 female patients with histologically confirmed solid NEBC were reviewed. Imaging data were evaluated by two radiologists for a consensual diagnosis. All patients presented with one palpable mass; only 1 experienced occasional breast pain, and 5 complained of fluid discharge. In 7 patients, the masses were firm and mobile. Regional lymph node metastasis was noted in only 1 patient. For the 10 patients who underwent mammography, 6 had a mass, 1 had clustered small nodules with clustered punctuate microcalcifications, 2 had asymmetric focal density, and 1 had solitary punctuate calcification. Most of the masses had irregular shape with indistinct or microlobulated margins. For the 9 patients who underwent ultrasonography (US), 9 masses were depicted, all of which were hypoechoic, mostly with irregular shape and without acoustic phenomena. Different types of acoustic phenomena were also identified. One patient had developed distant metastases during follow-up. NEBC has a variety of presentations, but it is mostly observed on mammograms as a dense, irregular mass with indistinct or microlobulated margins. Sonographically, it typically presents as an irregular, heterogeneously hypoechoic mass with normal sound transmission. Histories of nipple discharge and calcification observed using imaging are not rare.

An iEEG Recording and Adjustable Shunt-Current Conduction Platform for Epilepsy Treatment.

This paper proposes a compact bioelectronics sensing platform, including a multi-channel electrode, intracranial electroencephalogram (iEEG) recorder, adjustable galvanometer, and shunt-current conduction circuit pathway. The developed implantable electrode made of polyurethane-insulated stainless-steel materials is capable of recording iEEG signals and shunt-current conduction. The electrochemical impedance of the conduction, ground/reference, and working electrode were characterized in phosphate buffer saline solution, revealing in vitro results of 517.2 Ω@1 kHz (length of 0.1 mm, diameter of 0.8 mm), 1.374 kΩ@1 kHz (length of 0.3 mm, diameter of 0.1 mm), and 3.188 kΩ@1 kHz (length of 0.1 mm, diameter of 0.1 mm), respectively. On-bench measurement of the system revealed that the input noise of the system is less than 2 µVrms, the signal frequency bandwidth range is 1 Hz~10 kHz, and the shunt-current detection range is 0.1~3000 µA with an accuracy of above 99.985%. The electrode was implanted in the CA1 region of the right hippocampus of rats for the in vivo experiments. Kainic acid (KA)-induced seizures were detected through iEEG monitoring, and the induced shunt-current was successfully measured and conducted out of the brain through the designed circuit-body path, which verifies the potential of current conduction for the treatment of epilepsy.

Multi-Dimensional Feature Combination Method for Continuous Blood Pressure Measurement Based on Wrist PPG Sensor.

The cuff-less blood pressure (BP) monitoring method based on photoplethysmo- gram (PPG) makes it possible for long-term BP monitoring to prevent and treat cardiovascular and cerebrovascular events. In this paper, a portable BP prediction system based on feature combination and artificial neural network (ANN) is implemented. The robustness of the model is improved from three aspects. Firstly, an adaptive peak extraction algorithm was used to improve the accuracy of peaks and troughs detection. Secondly, multi-dimensional features were extracted and fused, including three groups of PPG-based features and one group of demographics-based features. Finally, a two-layer feedforward artificial neural networks algorithm was used for regression. Thirty-three subjects distributed in the three BP groups were recruited. The proposed method passed the European Society of Hypertension International Protocol revision 2010 (ESP-IP2). Experimental results show that the proposed method exhibits good accuracy for a diverse population with an estimation error of -0.07 ± 4.47 mmHg for SBP and 0.00 ± 3.61 mmHg for DBP. Moreover, the model tracked the BP of two subjects for half a month, laying the foundation work for daily BP monitoring. This work will contribute to the long-term wellness management and rehabilitation process, enabling timely detection and improvement of the user's physical health.

Radiocolloid in combination with methylene dye localization, rather than wire localization, is a preferred procedure for excisional biopsy of nonpalpable breast lesions.

BACKGROUND: Wire localization (WL) is traditionally performed before excisional biopsy for patients with nonpalpable breast lesions, but it has several disadvantages. Our current study examines whether the method of radiocolloid combined with methylene dye localization (RCML) has an advantage over WL. MATERIALS AND METHODS: From August 2006 to May 2009, 157 patients with nonpalpable breast lesions classified as BI-RADS category 5 were enrolled in our study. Of the 157 patients, 78 were assigned to WL and 79 to RCML. The status of surgical margins, weight of specimens, length of incisions, and duration of operation were compared between these two groups. RESULTS: All patients were diagnosed after first excisional biopsy. The patients with malignancy accounted for 55.1% in WL group, and 53.2% in RCML group. For malignant lesions, fewer patients undergoing RCML had close or involved surgical margins than did those who had WL (19.0% vs. 39.5%, P = .038). The mean weight of specimen was 45.2 g in WL group and 39.0 g in RCML group (P < .001). The mean length of incision was 44.8 mm in WL group and 36.3 mm in RCML group (P < .001). The mean time of operation was 16.3 min for WL and 14.7 min for RCML (P = .001). CONCLUSIONS: RCML provides precise identification of the site of the nonpalpable lesion and a visible marker to the lesion for surgeons and allows rapid, easy, and accurate excision of nonpalpable breast lesions. Therefore, RCML is a promising alternative to WL.

Characterizing the clustered microcalcifications on mammograms to predict the pathological classification and grading: a mathematical modeling approach.

In this study, we explore a mathematical model to characterize the clustered microcalcifications on mammograms for predicting the pathological classification and grading. Our database consists of both retrospective cases (78 cases) and prospective cases (31 cases) with pathologically diagnosed clusters of microcalcifications on mammograms. The microcalcifications were divided into four grades: grade 0, benign breast disease including mastopathies (n = 12) and fibroadenomas (n = 20); grade 1, well-differentiated infiltrating ductal carcinoma (n = 12); grade 2, moderately differentiated infiltrating ductal carcinoma (n = 38); grade 3, poorly differentiated infiltrating ductal carcinoma (n = 27). A feature parameter, defined as the pattern form factor of microcalcification cluster θ by us, combines five computer-extracted image parameters of microcalcification clusters of those mammograms. In every case, only one imaging was selected for modeling analysis. A total of 109 imagings were adopted in current study. We find the existence of a positive relationship between the feature parameter θ and pathological grading G of microcalcifications in retrospective cases, which was expressed as G = 6.438 + 1.186 × Ln <θ>. The model above has been verified further by the prospective study with a comparative evaluation accuracy of approximately 77.42%. The binary predication simply for both benignancy and malignancy was also included using same but reshuffled data, and the receiver operating characteristic (ROC) analysis was performed with ROC value 0.74351∼0.79891. As one candidate for feature parameter in computer-aided diagnosis, the pattern form factor θ of clustered microcalcifications may be useful to predict the pathological grading and classification of microcalcification clusters on mammography in breast cancer.

Dentate granule cells encode auditory decisions after reinforcement learning in rats.

Auditory-cued goal-oriented behaviors requires the participation of cortical and subcortical brain areas, but how neural circuits associate sensory-based decisions with goal locations through learning remains poorly understood. The hippocampus is critical for spatial coding, suggesting its possible involvement in transforming sensory inputs to the goal-oriented decisions. Here, we developed an auditory discrimination task in which rats learned to navigate to goal locations based on the frequencies of auditory stimuli. Using in vivo calcium imaging in freely behaving rats over the course of learning, we found that dentate granule cells became more active, spatially tuned, and responsive to task-related variables as learning progressed. Furthermore, only after task learning, the activity of dentate granule cell ensembles represented the navigation path and predicts auditory decisions as early as when rats began to approach the goals. Finally, chemogenetic silencing of dentate gyrus suppressed task learning. Our results demonstrate that dentate granule cells gain task-relevant firing pattern through reinforcement learning and could be a potential link of sensory decisions to spatial navigation.