Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data.

Activity recognition is one of the significant technologies accompanying the development of the Internet of Things (IoT). It can help in recording daily life activities or reporting emergencies, thus improving the user's quality of life and safety, and even easing the workload of caregivers. This study proposes a human activity recognition (HAR) system based on activity data obtained via the micro-Doppler effect, combining a two-stream one-dimensional convolutional neural network (1D-CNN) with a bidirectional gated recurrent unit (BiGRU). Initially, radar sensor data are used to generate information related to time and frequency responses using short-time Fourier transform (STFT). Subsequently, the magnitudes and phase values are calculated and fed into the 1D-CNN and Bi-GRU models to extract spatial and temporal features for subsequent model training and activity recognition. Additionally, we propose a simple cross-channel operation (CCO) to facilitate the exchange of magnitude and phase features between parallel convolutional layers. An open dataset collected through radar, named Rad-HAR, is employed for model training and performance evaluation. Experimental results demonstrate that the proposed 1D-CNN+CCO-BiGRU model demonstrated superior performance, achieving an impressive accuracy rate of 98.2%. This outperformance of existing systems with the radar sensor underscores the proposed model's potential applicability in real-world scenarios, marking a significant advancement in the field of HAR within the IoT framework.

Modelling porcine NAFLD by deletion of leptin and defining the role of AMPK in hepatic fibrosis.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is the most prevalent cause of chronic hepatic disease and results in non-alcoholic steatohepatitis (NASH), which progresses to fibrosis and cirrhosis. Although the Leptin deficient rodent models are widely used in study of metabolic syndrome and obesity, they fail to develop liver injuries as in patients. METHODS: Due to the high similarity with humans, we generated Leptin-deficient (Leptin-/-) pigs to investigate the mechanisms and clinical trials of obesity and NAFLD caused by Leptin. RESULTS: The Leptin-/- pigs showed increased body fat and significant insulin resistance at the age of 12 months. Moreover, Leptin-/- pig developed fatty liver, non-alcoholic steatohepatitis and hepatic fibrosis with age. Absence of Leptin in pig reduced the phosphorylation of JAK2-STAT3 and AMPK. The inactivation of JAK2-STAT3 and AMPK enhanced fatty acid ß-oxidation and leaded to mitochondrial autophagy respectively, and both contributed to increased oxidative stress in liver cells. In contrast with Leptin-/- pig, although Leptin deletion in rat liver inhibited JAK2-STAT3 phosphorylation, the activation of AMPK pathway might prevent liver injury. Therefore, ß-oxidation, mitochondrial autophagy and hepatic fibrosis did not occurred in Leptin-/- rat livers. CONCLUSIONS: The Leptin-deficient pigs presents an ideal model to illustrate the full spectrum of human NAFLD. The activity of AMPK signaling pathway suggests a potential target to develop new strategy for the diagnosis and treatment of NAFLD.

Clinical and imaging characteristics of patients with bronchogenic cysts: a single-center retrospective analysis.

BACKGROUND: Bronchogenic cysts (BCs) are rare and usually asymptomatic malformations detected during imaging examinations. We aimed to investigate the clinical and imaging characteristics of patients with BCs. METHODS: We retrospectively evaluated patients who received surgery to remove their BCs from January 2015 to January 2019. Their baseline characteristics, clinical information, and imaging results were reviewed. RESULTS: Our study included 129 patients, with 57 males and 72 females and a mean age of 42.7 years old. The most common location for BCs was the mediastinum (67 patients, 51.9%). Fewer than half of the patients (53 patients, 41.1%) reported clinical symptoms, with chest pain being the most common (16 patients, 30.2%). Neck BCs were more frequently observed in young patients (P = 0.002) and were more often associated with thyroid cancer (P = 0.007). A computed tomography scan was the most commonly used method to diagnose BCs in the lung and mediastinum, whereas ultrasound was the most commonly used diagnostic method for neck BCs. The characteristic images were well-defined, thin-wall cystic lesions in varying densities. A few lesions showed small, calcified spots along the rim or cavities. CONCLUSIONS: Although most BCs were found in the mediastinum, their locations could vary in different sex and age groups. Particular attention should be paid to young patients with BCs in the neck to rule out thyroid cancer.

CRB3 navigates Rab11 trafficking vesicles to promote γTuRC assembly during ciliogenesis.

The primary cilium plays important roles in regulating cell differentiation, signal transduction, and tissue organization. Dysfunction of the primary cilium can lead to ciliopathies and cancer. The formation and organization of the primary cilium are highly associated with cell polarity proteins, such as the apical polarity protein CRB3. However, the molecular mechanisms by which CRB3 regulates ciliogenesis and the location of CRB3 remain unknown. Here, we show that CRB3, as a navigator, regulates vesicle trafficking in γ-tubulin ring complex (γTuRC) assembly during ciliogenesis and cilium-related Hh and Wnt signaling pathways in tumorigenesis. Crb3 knockout mice display severe defects of the primary cilium in the mammary ductal lumen and renal tubule, while mammary epithelial-specific Crb3 knockout mice exhibit the promotion of ductal epithelial hyperplasia and tumorigenesis. CRB3 is essential for lumen formation and ciliary assembly in the mammary epithelium. We demonstrate that CRB3 localizes to the basal body and that CRB3 trafficking is mediated by Rab11-positive endosomes. Significantly, CRB3 interacts with Rab11 to navigate GCP6/Rab11 trafficking vesicles to CEP290, resulting in intact γTuRC assembly. In addition, CRB3-depleted cells are unresponsive to the activation of the Hh signaling pathway, while CRB3 regulates the Wnt signaling pathway. Therefore, our studies reveal the molecular mechanisms by which CRB3 recognizes Rab11-positive endosomes to facilitate ciliogenesis and regulates cilium-related signaling pathways in tumorigenesis.

Tribulus terrestris L. induces cell apoptosis of breast cancer by regulating sphingolipid metabolism signaling pathways.

BACKGROUND: Tribulus terrestris L. (TT) was initially documented in Shen-Nong-Ben-Cao-Jing and has been used for thousands of years in China as a herb to calm liver, dispel melancholy and wind, promote blood circulation, improve eyesight, and relieve itching. Moreover, it was also used to treat breast cancer in ancient China. However, the pharmacological activities of TT extract on breast cancer have received little attention. PURPOSE: In this study, we investigated the anti-breast cancer effects and possible mechanisms of action of this herbal drug. METHODS: Network pharmacology analysis the study of network pharmacology was done to analyze the possibility of TT's anti-breast cancer effect. And then, molecular docking between TT7/TT8 and vascular endothelial growth factor receptor 2 (VEGFR2) were performed by Autodock software as well as the related protein expressions were analyzed by western blot to verify this effect. In vivo experiment: The mouse model of breast cancer was established by injection of 4T1 cells. Then drugs were intragastrically administered to the mice once daily for fourteen days. Body weight, tumor size, and tumor weight were recorded at the end of the experiment. Moreover, tumor inhibitory rate was calculated. Finally, pathological changes and apoptosis of breast cancer tissues were respectively evaluated by HE and Hoechst staining. Proteomics and metabonomics analyses: The tumor tissues were chosen to perform conjoint analysis. Firstly, differential proteins and metabolites were found. Furthermore, the functional analyses of them were analyzed by software. At the last, immunofluorescent staining of SGPP1, SPHK1 and p-SPHK1 in tumor tissue were done. RESULTS: 12 active ingredients of TT, 127 targets of active ingredients, 15,253 targets of breast cancer, 1,225 targets of Ru yan, and 123 overlapping genes were obtained in the network pharmacology study. There was firm conjunction between TT7/TT8 and VEGFR2. Besides, tumor size and weight were markedly reduced in TT groups compared to the model group. The tumor inhibitory rate was more than 26% in TTM group. After drug treatment, many adipocytes and cracks between tumor and apoptosis were discovered. The western blot results showed that TT aqueous extract lowered the levels of VEGFR2, ERK1/2, p-ERK1/2 (Thr202, Tyr204) and Bcl2, while increasing the levels of Bax and the ratio of Bax/Bcl2. Furthermore, 495 differential proteins and 76 differential metabolites were found between TTM and model groups with the sphingolipid metabolism pathway being enriched. At last, TT treatment significantly reduced the levels of SGPP1, SPHK1 and p-SPHK1 in tumor tissue. CONCLUSIONS: In conclusion, TT demonstrates therapeutic effects in a mouse model of breast cancer, and its mechanism of action involves the regulations of sphingolipid metabolism signaling pathways. This study lends credence to the pharmacological potential of TT extract as a breast cancer therapy.

Promoting liver cancer cell apoptosis effect of Tribulus terrestris L. via reducing sphingosine level was confirmed by network pharmacology with metabolomics.

Background: Tribulus terrestris L. (TT) is one of the most common Chinese herbs and distributes in various regions in China. TT was first documented to treat breast cancer in Shen-Nong-Ben-Cao-Jing. However, the pharmacological activities of TT extract on liver cancer have not been reported. In this study, we investigated its anti-liver cancer activity and underlying mechanism. Methods: Traditional Chinese Medicine Systems Pharmacology (TCMSP) and PharmMapper databases were used to obtain the active ingredients and the targets of TT. Genecards database was employed to acquire TT targets in liver cancer. Furthermore, Venny 2.1, Cytoscape 3.8.2, DAVID 6.8 software were utilized to analyze the relationship between TT and liver cancer. In vivo experiment: The animal model of liver cancer was established by injection of H22 cells into Balb/c mice. After five days, drugs were intragastrically administered to the mice daily for 10 days. Body weight, tumor size and tumor weight were recorded. Tumor inhibitory rate was calculated. Protein levels were examined by Western blotting. Pathological changes of liver cancer tissues were evaluated by HE and Tunel staining. Metabolomics study: LC-MS was used to analyze different metabolites between model and TTM groups. Results: 12 active ingredients of TT, 127 targets of active ingredients, 17,378 targets of liver cancer, and 125 overlapping genes were obtained. And then, 118 items of GO biological processes (BP), 54 items of GO molecular function (MF), 35 items of GO cellular component (CC) and 128 pathways of KEGG were gotten (P < 0.05). Moreover, 47 differential metabolites were affirmed and 66 pathways of KEGG (P < 0.05) were obtained. In addition, after TT and sorafenib treatment, tumor size was markedly reduced, respectively, compared with model group. Tumor weight was significantly decreased and tumor inhibitory rate was more than 44% in TTM group. After TT treatment, many adipocytes, cracks between tumor cells and apoptosis were found. The levels of pro-Cathepsin B, Cathepsin B, Bax, Bax/Bcl2, Caspase3 and Caspase7 were markedly increased, but the level of Bcl2 was significantly reduced after TT treatment. Conclusion: TT has a broad range of effects on various signaling pathways and biological processes, including the regulation of apoptosis. It exhibits antitumor activity in an animal model of liver cancer and activates the apoptotic pathway by decreasing Sph level. This study provides valuable information regarding the potential use of TT extract in the treatment of liver cancer and highlights the importance of investigating the underlying molecular mechanisms of traditional medicines for the development of new therapeutic drugs in liver cancer.

Extracellular RNA profiles in non-small cell lung cancer plasma.

Background: Non-small cell lung cancer (NSCLC) has a high mortality rate and poor prognosis. The early detection of high-risk patients is essential to improve patient prognosis. Thus, the identification of a non-invasive, non-radiative, convenient, and fast diagnostic approach should be a top priority in NSCLC research. Circulating extracellular RNAs (exRNAs) in the plasma are potential biomarkers for NSCLC. Methods: We used RNA-sequencing (RNA-seq) technology to explore the NSCLC-related RNAs, especially the circular RNAs (circRNAs). The circRNA-targeted micro RNAs (miRNAs) were predicted using 3 circRNA databases [i.e., the Cancer-Specific CircRNA Database (CSCD), circBank, and Circular RNA Interactome]. The circRNA-miRNA-messenger RNA (mRNA) network was constructed using Cytoscape V3.8.0 (Cytoscape Consortium, San Diego, CA, USA). The expression levels of some differentially expressed genes were validated by a quantitative real-time polymerase chain reaction (qRT-PCR) analysis. Results: The results showed that the RNA biotypes of the mitochondrial ribosomal RNAs (mt-rRNAs) and mitochondrial transfer RNAs (mt-tRNAs) were upregulated in the NSCLC plasma. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms of the differentially expressed transcripts of NSCLC included oxidative phosphorylation, proton transmembrane transport, and the response to oxidative stress. Additionally, the qRT-PCR validation indicated that hsa_circ_0000722 had significantly higher expression in the NSCLC plasma than the control plasma, but hsa_circ_0006156 did not differ between the NSCLC plasma and the control plasma. The expression levels of miR-324-5p and miR-326 were higher in the NSCLC plasma than the control plasma. Conclusions: In this study, an exRNA-sequencing strategy was used to identify the expression of NSCLC-specific transcription factors in clinical plasma samples, and hsa_circ_0000722 and hsa-miR-324-5p were identified as potential biomarkers in NSCLC.

Voluntary Deep Inspiration Breath-Hold (VDIBH) Whole-Breast Irradiation Assisted by Optical Surface Monitoring System (OSMS) in Patients With Left-Sided Breast Cancer: A Prospective Phase II Study.

Objectives: To investigate the dosimetric advantages of the voluntary deep inspiration breath-hold technique assisted by optical surface monitoring system for whole breast irradiation in left breast cancer after breast-conserving surgery and verify the reproducibility and acceptability of this technique. Methods: Twenty patients with left breast cancer receiving whole breast irradiation after breast-conserving surgery were enrolled in this prospective phase II study. Computed tomography simulation was performed during both free breathing and voluntary deep inspiration breath-hold for all patients. Whole breast irradiation plans were designed, and the volumes and doses of the heart, left anterior descending coronary artery, and lung were compared between free breathing and voluntary deep inspiration breath-hold. Cone beam computed tomography was performed for the first 3 treatments, then weekly during voluntary deep inspiration breath-hold treatment to evaluate the accuracy of the optical surface monitoring system technique. The acceptance of this technique was evaluated with in-house questionnaires completed by patients and radiotherapists. Results: The median age was 45 (27-63) years. All patients received hypofractionated whole breast irradiation using intensity-modulated radiation therapy up to a total dose of 43.5 Gy/2.9 Gy/15f. Seventeen of the 20 patients received concomitant tumor bed boost to a total dose of 49.5 Gy/3.3 Gy/15f. Voluntary deep inspiration breath-hold showed a significant decrease in the heart mean dose (262 ± 163 cGy vs 515 ± 216 cGy, P < .001) and left anterior descending coronary artery (1191 ± 827 cGy vs 1794 ± 833 cGy, P < .001). The median delivery time of radiotherapy was 4 (1.5-11) min. The median deep breathing cycles were 4 (2-9) times. The average score for acceptance of voluntary deep inspiration breath-hold by patients and radiotherapists was 8.7 ± 0.9 (out of 12) and 10.6 ± 3.2 (out of 15), respectively, indicating good acceptance by both. Conclusions: The voluntary deep inspiration breath-hold technique for whole breast irradiation after breast-conserving surgery in patients with left breast cancer significantly reduces the cardiopulmonary dose. Optical surface monitoring system-assisted voluntary deep inspiration breath-hold is reproducible and feasible and showed good acceptance by both patients and radiotherapists.

Effect of circ_0000009 on lung adenocarcinoma progression by regulating PDZD2 in a ceRNA- and RBP- dependent manner.

Accumulating evidence now demonstrated that circular RNAs (circRNAs) are closely related to the pathogenesis of lung adenocarcinoma (LUAD). Through GEO2R online analysis, we screened hsa_circ_0000009 (circ_0000009) from the GEO database (GSE158695), and its expression in LUAD cancer tissues and cell lines was detected by RT-qPCR. The looping structure of circ_0000009 was tested by RNase R and actinomycin D experiments. The changes of proliferation were tested by CCK-8 or EdU assay. And the changes of apoptosis in A549 and H1299 cells were measured via flow cytometry. The A549 BALB/c tumor model was established to evaluate the influence of circ_0000009 on LUAD cell growth in vivo. In addition, experiments connected with ceRNA direction (mainly including bioinformatics prediction and luciferase reporter assay) and RNA Binding Protein (RBP) direction (mainly including RNA pull-down assay, RIP assay and mRNA stability assay) were further developed to reveal the regulatory mechanism of circ_0000009. The gene and protein levels in this project were assessed by RT-qPCR and western blotting analysis, respectively. The data manifested that circ_0000009 was in low expression in LUAD. The in vitro and in vivo experiments threw light on that overexpression of circ_0000009 dramatically suppressing LUAD tumorigenesis. Mechanistically, circ_0000009 promoted the expression of PDZD2 by sponging miR-154-3p. Furthermore, circ_0000009 stabilized PDZD2 by recruiting IGF2BP2. This study illustrated the mechanism that overexpressing of circ_0000009 suppressed LUAD progression by upregulating PDZD2 expression, providing an original treatment direction for LUAD.

Correction: Alkhaleefah et al. Connected-SegNets: A Deep Learning Model for Breast Tumor Segmentation from X-ray Images. Cancers 2022, 14, 4030.

In the original publication [...].

Development of Low-Contact-Impedance Dry Electrodes for Electroencephalogram Signal Acquisition.

Dry electroencephalogram (EEG) systems have a short set-up time and require limited skin preparation. However, they tend to require strong electrode-to-skin contact. In this study, dry EEG electrodes with low contact impedance (<150 kΩ) were fabricated by partially embedding a polyimide flexible printed circuit board (FPCB) in polydimethylsiloxane and then casting them in a sensor mold with six symmetrical legs or bumps. Silver-silver chloride paste was used at the exposed tip of each leg or bump that must touch the skin. The use of an FPCB enabled the fabricated electrodes to maintain steady impedance. Two types of dry electrodes were fabricated: flat-disk electrodes for skin with limited hair and multilegged electrodes for common use and for areas with thick hair. Impedance testing was conducted with and without a custom head cap according to the standard 10-20 electrode arrangement. The experimental results indicated that the fabricated electrodes exhibited impedance values between 65 and 120 kΩ. The brain wave patterns acquired with these electrodes were comparable to those acquired using conventional wet electrodes. The fabricated EEG electrodes passed the primary skin irritation tests based on the ISO 10993-10:2010 protocol and the cytotoxicity tests based on the ISO 10993-5:2009 protocol.

Performance Comparison of Machine Learning Approaches on Hepatitis C Prediction Employing Data Mining Techniques.

Hepatitis C is a liver infection caused by the hepatitis C virus (HCV). Due to the late onset of symptoms, early diagnosis is difficult in this disease. Efficient prediction can save patients before permeant liver damage. The main objective of this study is to employ various machine learning techniques to predict this disease based on common and affordable blood test data to diagnose and treat patients in the early stages. In this study, six machine learning algorithms (Support Vector Machine (SVM), K-nearest Neighbors (KNN), Logistic Regression, decision tree, extreme gradient boosting (XGBoost), artificial neural networks (ANN)) were utilized on two datasets. The performances of these techniques were compared in terms of confusion matrix, precision, recall, F1 score, accuracy, receiver operating characteristics (ROC), and the area under the curve (AUC) to identify a method that is appropriate for predicting this disease. The analysis, on NHANES and UCI datasets, revealed that SVM and XGBoost (with the highest accuracy and AUC among the test models, >80%) can be effective tools for medical professionals using routine and affordable blood test data to predict hepatitis C.

Loss of MuRF1 in Duroc pigs promotes skeletal muscle hypertrophy.

Muscle mass development depends on increased protein synthesis and reduced muscle protein degradation. Muscle ring-finger protein-1 (MuRF1) plays a key role in controlling muscle atrophy. Its E3 ubiquitin ligase activity recognizes and degrades skeletal muscle proteins through the ubiquitin-proteasome system. The loss of Murf1, which encodes MuRF1, in mice leads to the accumulation of skeletal muscle proteins and alleviation of muscle atrophy. However, the function of Murf1 in agricultural animals remains unclear. Herein, we bred F1 generation Murf1+/- and F2 generation Murf1-/- Duroc pigs from F0 Murf1-/- pigs to investigate the effect of Murf1 knockout on skeletal muscle development. We found that the Murf1+/- pigs retained normal levels of muscle growth and reproduction, and their percentage of lean meat increased by 6% compared to that of the wild type (WT) pigs. Furthermore, the meat color, pH, water-holding capacity, and tenderness of the Murf1+/- pigs were similar to those of the WT pigs. The drip loss rate and intramuscular fat decreased slightly in the Murf1+/- pigs. However, the cross-sectional area of the myofibers in the longissimus dorsi increased in the adult Murf1+/- pigs. The skeletal muscle proteins MYBPC3 and actin, which are targeted by MuRF1, accumulated in the Murf1+/- and Murf1-/- pigs. Our findings show that inhibiting muscle protein degradation in MuRF1-deficient Duroc pigs increases the size of their myofibers and their percentage of lean meat without influencing their growth or pork quality. Our study demonstrates that Murf1 is a target gene for promoting skeletal muscle hypertrophy in pig breeding.

Using a Hybrid Neural Network and a Regularized Extreme Learning Machine for Human Activity Recognition with Smartphone and Smartwatch.

Mobile health (mHealth) utilizes mobile devices, mobile communication techniques, and the Internet of Things (IoT) to improve not only traditional telemedicine and monitoring and alerting systems, but also fitness and medical information awareness in daily life. In the last decade, human activity recognition (HAR) has been extensively studied because of the strong correlation between people's activities and their physical and mental health. HAR can also be used to care for elderly people in their daily lives. This study proposes an HAR system for classifying 18 types of physical activity using data from sensors embedded in smartphones and smartwatches. The recognition process consists of two parts: feature extraction and HAR. To extract features, a hybrid structure consisting of a convolutional neural network (CNN) and a bidirectional gated recurrent unit GRU (BiGRU) was used. For activity recognition, a single-hidden-layer feedforward neural network (SLFN) with a regularized extreme machine learning (RELM) algorithm was used. The experimental results show an average precision of 98.3%, recall of 98.4%, an F1-score of 98.4%, and accuracy of 98.3%, which results are superior to those of existing schemes.

High Accuracy and Cost-Effective Fiber Optic Liquid Level Sensing System Based on Deep Neural Network.

In this paper, a novel liquid level sensing system is proposed to enhance the capacity of the sensing system, as well as reduce the cost and increase the sensing accuracy. The proposed sensing system can monitor the liquid level of several points at the same time in the sensing unit. Additionally, for cost efficiency, the proposed system employs only one sensor at each spot and all the sensors are multiplexed. In multiplexed systems, when changing the liquid level inside the container, the float position is changed and leads to an overlap or cross-talk between two sensors. To solve this overlap problem and to accurately predict the liquid level of each container, we proposed a deep neural network (DNN) approach to properly identify the water level. The performance of the proposed DNN model is evaluated via two different scenarios and the result proves that the proposed DNN model can accurately predict the liquid level of each point. Furthermore, when comparing the DNN model with the conventional machine learning schemes, including random forest (RF) and support vector machines (SVM), the DNN model exhibits the best performance.

Developing Low-Cost Mobile Device and Apps for Accurate Skin Spectrum Measurement via Low-Cost Spectrum Sensors and Deep Neural Network Technology.

In recent years, skin spectral information has been gradually applied in various fields, such as the cosmetics industry and clinical medicine. However, the high price and the huge size of the skin spectrum measurement device make the related applications of the skin spectrum unable to be widely used in practical applications. We used convolutional neural network (CNN) to achieve a satisfying accuracy of the Fitzpatrick skin-type classification by using a simple self-developed device in 2018. Leveraging on the hardware, firmware, and software app-developing experience, a low-cost miniature skin spectrum measurement system (LMSSMS) using deep neural network (DNN) technology was further studied, and the feasibility of the system is verified in this paper. The developed LMSSMS is divided into three parts: (1) miniature skin spectrum measurement device (MSSMD), (2) DNN model, and (3) mobile app. The MSSMD was developed with innovative low-cost MSSC, 3D printing, and a simple LED light source. The DNN model is designed to enhance measurement accuracy. Finally, the mobile app is used to control and show the measurement results. The developed app also includes a variety of skin-spectrum-related applications, such as erythema index and melanin index (EI/MI) measurement, Fitzpatrick skin-type classification, Pantone SkinTone classification, sun-exposure estimation, and body-fat measurement. In order to verify the feasibility of LMSSMS, we used the standard instrumentation device as a reference. The results show that the accuracy of the LMSSMS can reach 94.7%, which also confirms that this development idea has much potential for further development.

Connected-SegNets: A Deep Learning Model for Breast Tumor Segmentation from X-ray Images.

Inspired by Connected-UNets, this study proposes a deep learning model, called Connected-SegNets, for breast tumor segmentation from X-ray images. In the proposed model, two SegNet architectures are connected with skip connections between their layers. Moreover, the cross-entropy loss function of the original SegNet has been replaced by the intersection over union (IoU) loss function in order to make the proposed model more robust against noise during the training process. As part of data preprocessing, a histogram equalization technique, called contrast limit adapt histogram equalization (CLAHE), is applied to all datasets to enhance the compressed regions and smooth the distribution of the pixels. Additionally, two image augmentation methods, namely rotation and flipping, are used to increase the amount of training data and to prevent overfitting. The proposed model has been evaluated on two publicly available datasets, specifically INbreast and the curated breast imaging subset of digital database for screening mammography (CBIS-DDSM). The proposed model has also been evaluated using a private dataset obtained from Cheng Hsin General Hospital in Taiwan. The experimental results show that the proposed Connected-SegNets model outperforms the state-of-the-art methods in terms of Dice score and IoU score. The proposed Connected-SegNets produces a maximum Dice score of 96.34% on the INbreast dataset, 92.86% on the CBIS-DDSM dataset, and 92.25% on the private dataset. Furthermore, the experimental results show that the proposed model achieves the highest IoU score of 91.21%, 87.34%, and 83.71% on INbreast, CBIS-DDSM, and the private dataset, respectively.

Revisiting the multisite phosphorylation that produces the M-phase supershift of key mitotic regulators.

The term M-phase supershift denotes the phosphorylation-dependent substantial increase in the apparent molecular weight of numerous proteins of varied biological functions during M-phase induction. Although the M-phase supershift of multiple key mitotic regulators has been attributed to the multisite phosphorylation catalyzed by the Cdk1/cyclin B/Cks complex, this view is challenged by multiple lines of paradoxical observations. To solve this problem, we reconstituted the M-phase supershift of Xenopus Cdc25C, Myt1, Wee1A, APC3, and Greatwall in Xenopus egg extracts and characterized the supershift-producing phosphorylations. Our results demonstrate that their M-phase supershifts are each due to simultaneous phosphorylation of a considerable portion of S/T/Y residues in a long intrinsically disordered region that is enriched in both S/T residues and S/TP motifs. Although the major mitotic kinases in Xenopus egg extracts, Cdk1, MAPK, Plx1, and RSK2, are able to phosphorylate the five mitotic regulators, they are neither sufficient nor required to produce the M-phase supershift. Accordingly, inhibition of the four major mitotic kinase activities in Xenopus oocytes did not inhibit the M-phase supershift in okadaic acid-induced oocyte maturation. These findings indicate that the M-phase supershift is produced by a previously unrecognized category of mitotic phosphorylation that likely plays important roles in M-phase induction.

Open Reduction of Displaced Radial Neck Fractures in Children by Internal Fixation Techniques: Comparison of Percutaneous Kirschner Wiring and Elastic Stable Intramedullary Nailing.

Background: Although most paediatric radial neck fractures can be treated with closed reduction, some severely displaced fractures require open reduction. The purpose of this study is to compare the effects of ESIN and KW fixation in open reduction of radial neck fracture in children. Methods: Twenty-four patients with mean age of 8.5 years were included. Four of the patients had a Judet type III fracture and 20 had a Judet type IV fracture. Ten patients who underwent percutaneous KW fixation were assigned to group A, while 14 patients who underwent ESIN fixation were assigned to group B. Variables of interest included age, sex, fracture type, associated lesions, surgical time, fracture reduction, cost, follow-up, healing time, X-rays, clinical outcomes, and complications. Results: There were no significant between-group differences in sex, age, additional injuries, fracture type, and quality of reduction. Costs were significantly lower in Group A. Fracture healing was achieved in 23 of 24 patients (10/10 in group A and 13/14 in group B). In a postoperative elbow function assessment based on the Steele and Graham classification, 80% of patients in group A had a score of excellent or good, compared to 78.6% of patients in group B. Two cases of nail shifting and joint protrusion were observed in group B, one of which also presented with nonunion during follow-up. Conclusions: Both KW and ESIN may achieve good clinical outcomes, but KW is associated with lower costs, easier implant removal (without the need for a secondary surgery), and lower iatrogenic complications.