A Transfer Learning Approach for Malignant Prostate Lesion Detection on Multiparametric MRI

Purpose: In prostate focal therapy, it is important to accurately localize malignant lesions in order to increase biological effect of the tumor region while achieving a reduction in dose to noncancerous tissue. In this work, we proposed a transfer learning–based deep learning approach, for classification of prostate lesions in multiparametric magnetic resonance imaging images. Methods: Magnetic resonance imaging images were preprocessed to remove bias artifact and normalize the data. Two state-of-the-art deep convolutional neural network models, InceptionV3 and VGG-16, were pretrained on ImageNet data set and retuned on the multiparametric magnetic resonance imaging data set. As lesion appearances differ by the prostate zone that it resides in, separate models were trained. Ensembling was performed on each prostate zone to improve area under the curve. In addition, the predictions from lesions on each prostate zone were scaled separately to increase the area under the curve for all lesions combined. Results: The models were tuned to produce the highest area under the curve on validation data set. When it was applied to the unseen test data set, the transferred InceptionV3 model achieved an area under the curve of 0.81 and the transferred VGG-16 model achieved an area under the curve of 0.83. This was the third best score among the 72 methods from 33 participating groups in ProstateX competition. Conclusion: The transfer learning approach is a promising method for prostate cancer detection on multiparametric magnetic resonance imaging images. Features learned from ImageNet data set can be useful for medical images

The current status of mercury repair technology in the environment

In recent years, due to the pollution of heavy metals in the environment, it has brought a serious crisis to my country's ecological balance, especially the pollution of heavy metal mercury (Hg), so the repair of mercury in the environment is crucial. At present, there are many technologies for repairing mercury in the environment. The main repair techniques include physical repair technology and chemical repair technology. However, there are many problems in these two repair methods, such as high repair costs, and it is easy to cause secondary pollution. Microbial repair method is a method of repairing the environment. It can not only adsorb and fix heavy metal mercury, and does not bring pollution to the environment. Therefore, using microorganisms to remove mercury in the environment is by far the most promising environmental repair technology

Exploiting wireless received signal strength indicators to detect evil-twin attacks in smart homes

Evil-twin is becoming a common attack in Smart Home environments where an attacker can set up a fake AP to compromise the security of the connected devices. To identify the fake APs, The current approaches of detecting Evil-twin attacks all rely on information such as SSIDs, the MAC address of the genuine AP or network traffic patterns. However, such information can be faked by the attacker, often leading to low detection rates and weak protection. This paper presents a novel evil-twin attack detection method based on the received signal strength indicator (RSSI). Our key insight is that the location of the genuine AP rarely moves in a home environment and as a result the RSSI of the genuine AP is relatively stable. Our approach considers the RSSI as a fingerprint of APs and uses the fingerprint of the genuine AP to identify fake ones. We provide two schemes to detect a fake AP in two different scenarios where the genuine AP can be located at either a single or multiple locations in the property, by exploiting the multipath effect of the WIFI signal. As a departure from prior work, our approach does not rely on any professional measurement devices. Experimental results show that our approach can successfully detect 90% of the fake APs, at the cost of an one-off, modest connection delay

Terazosin Analogs Targeting Pgk1 as Neuroprotective Agents: Design, Synthesis, and Evaluation

Nitrogen-containing heterocyclic compounds have shown promising therapeutic effects in a variety of inflammatory and neurodegenerative diseases. Recently, terazosin (TZ), a heterocyclic compound with a quinazoline core, was found to combine with phosphoglycerol kinase 1 (Pgk1) and protect neurons by enhancing Pgk1 activity and promoting glycolysis, thereby slowing, or preventing the neurodegeneration of PD. These findings indicated that terazosin analogs have bright prospects for the development of PD therapeutics. In this study, a series of terazosin analogs were designed and synthesized for neuroprotective effects by targeting Pgk1. Among them, compound 12b was obtained with the best Pgk1 agonistic activity and neuroprotective activity. Further study indicates that it can increase intracellular ATP content and reduce ROS levels by stimulating the activity of Pgk1, thereby playing a role in protecting nerve cells. In conclusion, this study provides a new strategy and reference for the development of neuroprotective drugs

Comparative studies on flavor substances of leaves and pericarps of Zanthoxylum bungeanum Maxim. at different harvest periods

Purpose: To study the transformation of the aroma components and pungent constituents of Zanthoxylum bungeanum Maxim. (ZBM) leaves and pericarps at different periods, and to provide a basis for selecting an appropriate harvest time for the pericarps and leaves.Methods: Quantitative analysis of the pungent components of ZBM leaves and pericarps was performed by high performance liquid chromatography (HPLC) while their aroma constituents were analyzed by headspace solid phase micro-extraction combined with gas chromatography-mass spectrometry (HS-SPME-GC-MS).Results: HPLC analysis revealed that hydroxy-α-sanshool was the predominant pungent component in both the leaves and pericarps of different parts of ZBM at different harvest periods, followed by hydroxy- γ-sanshool and hydroxy-β-sanshool. During the growth of ZBM, the contents of pungent substances in the leaves declined gradually, while pungent substances in the pericarps increased. The results of HSSPME- GC-MS analysis showed that linalyl acetate, linalool and limonene were the major aroma components of the leaves and pericarps of ZBM at different harvest periods. During the growth of ZBM, the contents of monoterpenes in the leaves decreased gradually, whereas monoterpenes in the pericarps increased.Conclusion: These results suggest that the pungent and aroma components produced in ZBM at early developmental stages are stored in the leaves, and are gradually transferred to the pericarps at the final developmental stages. Thus, the leaves of ZBM can be used as a new source of food and medicine.Keywords: Zanthoxylum bungeanum Maxim., Pericarp, Pungent components, Aroma component

Value of machine learning model based on MRI radiomics in predicting histological grade of cervical squamous cell carcinoma

Objective To explore the predictive value of different machine learning models based on MRI radiomics combined with clinical features for histological grade of cervical squamous cell carcinoma. Methods Clinical data of 150 patients with cervical squamous cell carcinoma confirmed by pathological biopsy were retrospectively analyzed. They were randomly divided into the training set and validation set at a ratio of 4∶1. Features were extracted from the regions of interest of T2WI fat suppression sequence （FS-T2WI） and enhanced T1WI （delayed phase）. After dimensionality reduction and feature selection， logistic regression （LR）， support vector machine （SVM）， naïve Bayes （NB）， random forest （RF）， Light Gradient Boosting Machine （LightGBM）， K-nearest neighbor （KNN） were used to construct a radiomics model for predicting the histological grade of cervical squamous cell carcinoma. The area under the receiver operating characteristic （ROC） curve （AUC） was used to evaluate the predictive performance of the six models. Univariate and multivariate logistic regression analyses were performed to predict the independent risk factors， and a combined model of clinical and radiomics was established. The differences of each model were compared by AUC， and the clinical value of the model was evaluated by decision curve （DCA）. Results In the radiomics model， the LightGBM model had the largest AUC （0.910 in the training set， and 0.839 in the validation set）. The AUC of clinical features combined with LightGBM model was the largest （0.935 in the training set， and 0.888 in the validation set）， which was higher than those of clinical model （0.762 in the training set， and 0.710 in the validation set） and LightGBM radiomics model. Conclusions The LightGBM model has a high predictive value in the radiomics model. The combined model has the optimal DCA effect and the highest clinical net benefit. The combined prediction model combining radiomics and clinical features has good predictive value for cervical squamous cell carcinoma with low differentiation， providing a non-invasive and efficient method for clinical decision-making

Microvesicles secreted by macrophages shuttle invasion-potentiating microRNAs into breast cancer cells

<p>Abstract</p> <p>Background</p> <p>Tumor-associated macrophages (TAMs) are alternatively activated cells induced by interleukin-4 (IL-4)-releasing CD4⁺T cells. TAMs promote breast cancer invasion and metastasis; however, the mechanisms underlying these interactions between macrophages and tumor cells that lead to cancer metastasis remain elusive. Previous studies have found microRNAs (miRNAs) circulating in the peripheral blood and have identified microvesicles, or exosomes, as mediators of cell-cell communication. Therefore, one alternative mechanism for the promotion of breast cancer cell invasion by TAMs may be through macrophage-secreted exosomes, which would deliver invasion-potentiating miRNAs to breast cancer cells.</p> <p>Results</p> <p>We utilized a co-culture system with IL-4-activated macrophages and breast cancer cells to verify that miRNAs are transported from macrophages to breast cancer cells. The shuttling of fluorescently-labeled exogenous miRNAs from IL-4-activated macrophages to co-cultivated breast cancer cells without direct cell-cell contact was observed. miR-223, a miRNA specific for IL-4-activated macrophages, was detected within the exosomes released by macrophages and was significantly elevated in the co-cultivated SKBR3 and MDA-MB-231 cells. The invasiveness of the co-cultivated breast cancer cells decreased when the IL-4-activated macrophages were treated with a miR-223 antisense oligonucleotide (ASO) that would inhibit miR-223 expression. Furthermore, results from a functional assay revealed that miR-223 promoted the invasion of breast cancer cells via the Mef2c-β-catenin pathway.</p> <p>Conclusions</p> <p>We conclude that macrophages regulate the invasiveness of breast cancer cells through exosome-mediated delivery of oncogenic miRNAs. Our data provide insight into the mechanisms underlying the metastasis-promoting interactions between macrophages and breast cancer cells.</p

Characterization and potential of periosteum-derived cells: an overview

As a thin fibrous layer covering the bone surface, the periosteum plays a significant role in bone physiology during growth, development and remodeling. Over the past several decades, the periosteum has received considerable scientific attention as a source of mesenchymal stem cells (MSCs). Periosteum-derived cells (PDCs) have emerged as a promising strategy for tissue engineering due to their chondrogenic, osteogenic and adipogenic differentiation capacities. Starting from the history of PDCs, the present review provides an overview of their characterization and the procedures used for their isolation. This study also summarizes the chondrogenic, osteogenic, and adipogenic abilities of PDCs, serving as a reference about their potential therapeutic applications in various clinical scenarios, with particular emphasis on the comparison with other common sources of MSCs. As techniques continue to develop, a comprehensive analysis of the characterization and regulation of PDCs can be conducted, further demonstrating their role in tissue engineering. PDCs present promising potentials in terms of their osteogenic, chondrogenic, and adipogenic capacities. Further studies should focus on exploring their utility under multiple clinical scenarios to confirm their comparative benefit over other commonly used sources of MSCs

Discovery of Shiga Toxin-Producing Escherichia coli (STEC)-Specific Bacteriophages From Non-fecal Composts Using Genomic Characterization

Composting is a complex biodegradable process that converts organic materials into nutrients to facilitate crop yields, and, if well managed, can render bactericidal effects. Majority of research focused on detection of enteric pathogens, such as Shiga toxin-producing Escherichia coli (STEC) in fecal composts. Recently, attention has been emphasized on bacteriophages, such as STEC-specific bacteriophages, associated with STEC from the fecal-contaminated environment because they are able to sustain adverse environmental condition during composting process. However, little is known regarding the isolation of STEC-specific bacteriophages in non-fecal composts. Thus, the objectives were to isolate and genomically characterize STEC-specific bacteriophages, and to evaluate its association with STEC in non-fecal composts. For bacteriophage isolation, the samples were enriched with non-pathogenic E. coli (3 strains) and STEC (14 strains), respectively. After purification, host range, plaque size, and phage morphology were examined. Furthermore, bacteriophage genomes were subjected to whole-genome sequencing using Illumina MiSeq and genomic analyses. Isolation of top six non-O157 and O157 STEC utilizing culture methods combined with PCR-based confirmation was also conducted. The results showed that various STEC-specific bacteriophages, including vB_EcoM-Ro111lw, vB_EcoM-Ro121lw, vB_EcoS-Ro145lw, and vB_EcoM-Ro157lw, with different but complementary host ranges were isolated. Genomic analysis showed the genome sizes varied from 42kb to 149kb, and most bacteriophages were unclassified at the genus level, except vB_EcoM-Ro111lw as FelixO1-like viruses. Prokka predicted less than 25% of the ORFs coded for known functions, including those essential for DNA replication, bacteriophage structure, and host cell lysis. Moreover, none of the bacteriophages harbored lysogenic genes or virulence genes, such as stx or eae. Additionally, the presence of these lytic bacteriophages was likely attributed to zero isolation of STEC and could also contribute to additional antimicrobial effects in composts, if the composting process was insufficient. Current findings indicate that various STEC-specific bacteriophages were found in the non-fecal composts. In addition, the genomic characterization provides in-depth information to complement the deficiency of biological features regarding lytic cycle of the new bacteriophages. Most importantly, these bacteriophages have great potential to control various serogroups of STEC