Application of Real-Time Ultrasound Elastography Combined with Prostate Calcification in Differential Diagnosis of Prostate Cancer.

OBJECTIVE: This study aimed to explore the clinical and differential diagnostic value of real-time ultrasound elastography combined with transabdominal prostate calcification in prostate cancer (PCa). METHODS: This study retrospectively analysed the clinical pathological data of 97 patients with PCa and 105 patients with benign prostatic hyperplasia (BPH) diagnosed by postoperative pathology in our hospital from May 2020 to May 2021; Comparatively analysed the clinical data of the two groups, including the elastic strain ratio, elastic image compression index, types of prostate calcification and calcification diameter; And used logistic regression analysis to screen out the independent risk factors for identifying PCa and BPH. RESULTS: No significant difference in age, body weight, body mass index, location of calcification and calcification diameter was observed between the two groups (p > 0.05), and overt differences in elastic strain ratio, elastic image compression index, types of calcification, and testosterone were found between the PCa group and BPH group (p < 0.05). Logistic regression analysis showed that the elastic strain ratio, elastic image compression index and types of calcification were independent risk factors for identifying PCa (p < 0.05). The area under curve value of combined diagnosis under receiver operating characteristic curve was as high as 0.756 (95% CI: 0.691-0.813), with a sensitivity of 67.60% and a specificity of 76.30%. CONCLUSIONS: A certain correlation is observed amongst elastic strain ratio, elastic image compression index, types of prostate calcification and the occurrence and development of PCa. The application of real-time ultrasound elastography combined with the detection of transabdominal prostate calcification in clinical diagnosis can improve the detection rate of PCa, which has an important clinical application value.

Static-Dynamic coordinated Transformer for Tumor Longitudinal Growth Prediction.

Accurate prediction of the tumor's future imaging features can provide its complete growth evolution and more detailed clinical parameters. The existing longitudinal models tend to lose detailed growth information and make it difficult to model the complete tumor development process. In this paper, we propose the Static-Dynamic coordinated Transformer for Tumor Longitudinal Growth Prediction (SDC-Transformer). To extract the static high-level features of tumors in each period, and to further explore the dynamic growth associations and expansion trend of tumors between different periods. Aiming at the insensitivity to local pixel information of the Transformer, we propose the Local Adaptive Transformer Module to facilitate a strongly coupled status of feature images, which ensures the characterization of tumor complex growth trends. Faced with the dynamic changes brought about by tumor growth, we introduce the Dynamic Growth Estimation Module to predict the future growth trend of the tumor. As a core part of SDC-Transformer, we design the Enhanced Deformable Convolution to enrich the sampling space of tumor growth pixels. And a novel Cascade Self-Attention is performed under multi-growth imaging to obtain dynamic growth relationships between periods and use dual cascade operations to predict the tumor's future expansion trajectories and growth contours. Our SDC-Transformer is rigorously trained and tested on longitudinal tumor data composed of the National Lung Screening Trial (NLST) and collaborative Shanxi Provincial People's Hospital. The RMSE, Dice, Recall, and Specificity of the longitudinal prediction results reach 11.32, 89.31%, 90.57%, and 89.64%, respectively. This result shows that our proposed SDC-Transformer model can achieve accurate longitudinal prediction of tumors, which will help physicians to establish specific treatment plans and accurately diagnose lung cancer. The code will be released soon.

Edge Constraint and Location Mapping for Liver Tumor Segmentation from Nonenhanced Images.

As there is no contrast enhancement, the liver tumor area in nonenhanced MRI exists with blurred edges and low contrast, which greatly affects the speed and accuracy of liver tumor diagnosis. As a result, precise segmentation of liver tumor from nonenhanced MRI has become an urgent and challenging task. In this paper, we propose an edge constraint and localization mapping segmentation model (ECLMS) to accurately segment liver tumor from nonenhanced MRI. It consists of two parts: localization network and dual-branch segmentation network. We build the localization network, which generates prior coarse masks to provide position mapping for the segmentation network. This part enhances the ability of the model to localize liver tumor in nonenhanced images. We design a dual-branch segmentation network, where the main decoding branch focuses on the feature representation in the core region of the tumor and the edge decoding branch concentrates on capturing the edge information of the tumor. To improve the ability of the model for capturing detailed features, sSE blocks and dense upward connections are introduced into it. We design the bottleneck multiscale module to construct multiscale feature representations using kernels of different sizes while integrating the location mapping of tumor. The ECLMS model is evaluated on a private nonenhanced MRI dataset that comprises 215 different subjects. The model achieves the best Dice coefficient, precision, and accuracy of 90.23%, 92.25%, and 92.39%, correspondingly. The effectiveness of our model is demonstrated by experiment results, and our model reaches superior results in the segmentation task of nonenhanced liver tumor compared to existing segmentation methods.

Immunoglobulin Classification Based on FC* and GC* Features.

Immunoglobulins have a pivotal role in disease regulation. Therefore, it is vital to accurately identify immunoglobulins to develop new drugs and research related diseases. Compared with utilizing high-dimension features to identify immunoglobulins, this research aimed to examine a method to classify immunoglobulins and non-immunoglobulins using two features, FC* and GC*. Classification of 228 samples (109 immunoglobulin samples and 119 non-immunoglobulin samples) revealed that the overall accuracy was 80.7% in 10-fold cross-validation using the J48 classifier implemented in Weka software. The FC* feature identified in this study was found in the immunoglobulin subtype domain, which demonstrated that this extracted feature could represent functional and structural properties of immunoglobulins for forecasting.

Patient delay and associated factors among Chinese women with breast cancer: A cross-sectional study.

To examine the current situation of patient delay and to identify factors associated with patient delay among women with breast cancer in China.A total of 283 women, aged 23 to 83 years old and with histologically confirmed breast cancer, were investigated in this cross-sectional study. The women were recruited from seven selected hospitals in Sichuan Province, China. Face-to-face interviews using a structured questionnaire were performed.Among the 283 participants, the range of patient delay was 0.2 to 900 days with a median patient delay of 50 days. A total of 35.8% of patients waited ≥90 days to access medical treatment after symptom onset. Binary logistic regression analysis showed that the main predictors of patient delay were knowledge of breast cancer symptoms (OR = 0.716, 95%CI:0.637-0.804, P = .000), external health locus of control (OR = 1.173, 95%CI:1.087-1.266, P = .000), breast self-examination/physical examination (OR = 0.065, 95%CI: 0.007-0.590, P = .015), perceived health competence (OR = 0.873, 95%CI:0.808-0.944, P = .000), family support (OR = 0.911,95%CI:0.847-0.981, P = .013), pain stimulation (OR = 0.191, 95%CI:0.046-0.792, P = .023) and age (OR = 1.028, 95%CI:1.000-1.058, P = .049).These factors explained 41.0% of the variance.Information on the current situation and predictors of patient delay in Chinese women with breast cancer might provide meaning insights into the early diagnosis of breast cancer. The results of this study may help health professionals develop specific clinical practice strategies to reduce patient delay of initial treatment as a way to improve outcomes for women with breast cancer.

Fluorescence modulation in tribranched switchable [4]rotaxanes.

Two novel tribranched [4]rotaxanes with a 1,3,5-triphenylene core and three rotaxane arms have been designed, synthesized, and characterized by (1)H and (13)C NMR spectroscopies and HR-ESI mass spectrometry. [4]Rotaxanes 1 and 2 each possess the same three-armed skeleton. Each arm incorporates two distinguishable binding sites for a dibenzo[24]crown-8 ring, namely a dibenzylammonium site and an N-methyltriazolium site, and is terminated by a 4-morpholino-naphthalimide fluorophore as a stopper. [4]Rotaxane 1 has three di-ferrocene-functionalized dibenzo[24]crown-8 rings whereas 2 has three simple dibenzo[24]crown-8 rings interlocked with the thread component. Uniform shuttling motions of the three macrocycles in both 1 and 2 can be driven by external acid-base stimuli, which were confirmed by (1)H NMR spectroscopy. However, [4]rotaxanes 1 and 2 show distinct modes of fluorescence modulation in response to external acid-base stimuli. [4]Rotaxane 1 exhibits a remarkable fluorescence decrease in response to the addition of 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU) as a base, which can displace the ferrocene-functionalized macrocycle from the dibenzylammonium station to the N-methyltriazolium station. In contrast, the fluorescence intensity of [4]rotaxane 2 showed an enhancement with the addition of DBU. Time-resolved fluorescence measurements have been performed. The different photoinduced electron-transfer processes responsible for the fluorescence changes in the two molecular systems are discussed. Topological structures of this kind have significant potential for the design and construction of large and complex assemblies with controllable functions.

Dual-mode operation of a bistable [1]rotaxane with a fluorescence signal.

We report the operation of a ferrocene-based bistable [1]rotaxane that can work in two parallel platforms. In an "active" signal mode, the relative mechanical movement of its ring and thread in response to external acid-base-stimuli can result in a remarkable fluorescence signal output observed by the naked eye, whereas no obvious fluorescence change occurred in a "silent" signal mode after oxidation. Its fluorescence responses to the different combinations of DBU and/or Fe(ClO4)3 corresponds to an INHIBIT logic gate.

[Genetically modified industrial brewing yeast with high-glutathione and low-diacetyl production].

Recombinant plasmid pICG was constructed by replacing the internal fragment of a-acetohydroxyacid synthase (AHAS) gene (ILV2) with a copy of gamma-glutamylcysteine synthetase gene (GSH1) and copper chelatin gene (CUP1) from the industrial brewing yeast strain YSF31. YSF31 was transformed with plasmid pICG linearized by Kpn I and Pst I. A recombinant strain with high-glutathione and low-diacetyl production was selected. The results of fermentation in 100-L bioreactor showed that the lagering time of beer produced for recombinant strain T2 was shortened by 3 days and the shelf life of the beer was prolonged about 50%. It may be more acceptable for the commercial application, as it does not contain foreign DNA.