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Thyroid nodules are a common endocrine system disorder for which accurate ultrasound image segmentation is important for evaluation and diagnosis, as well as a critical step in computer‐aided diagnostic systems. However, the accuracy and consistency of segmentation remains a challenging task due to the presence of scattering noise, low contrast and resolution in ultrasound images. Therefore, we propose a deep learning‐based CAD (computer‐aided diagnosis) method, STU3Net in this paper, aiming at automatic segmentation of thyroid nodules. The method employs a modified Swin Transformer combined with a CNN encoder, which is capable of extracting morphological features and edge details of thyroid nodules in ultrasound images. In decoding through the features for image reconstruction, we introduce a modified three‐layer U‐Net network with cross‐layer connectivity to further enhance image reduction. This cross‐layer connectivity enhances the network's capture and representation of the contained image feature information by creating skip connections between different layers and merging the detailed information of the shallow network with the abstract information of the deeper network. Through comparison experiments with current mainstream deep learning methods on the TN3K and BUSI datasets, we validate the superiority of the STU3Net method in thyroid nodule segmentation performance. The experimental results show that STU3Net outperforms most of the mainstream models on the TN3K dataset, with Dice and IoU reaching 0.8368 and 0.7416, respectively, which are significantly better than other methods. The method demonstrates excellent performance on these datasets and provides radiologists with an effective auxiliary tool to accurately detect thyroid nodules in ultrasound images. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence technology, the digital transformation of student-oriented education becomes particularly important. How to promote real-time interaction between teachers and students in the classroom is an urgent issue which is needed to pay attention to. Based on the facial expression features of students in a classroom, this paper analyzes the changes in angles between facial expression feature points using Dlib. Additionally, this paper proposes a novel algorithm for extracting variable scale template edge trend features. The algorithm adaptively processes the template based on the edge trend features of expression feature points, and use the proposed template slope normalization algorithm to achieve multi-scale template edge trend extraction. Then, DNN are used to recognize different listening expressions. The experimental results show that the proposed algorithm has faster recognition speed and better robustness when applied to classroom expression recognition. By identifying students' class status to remind teachers to adjust their class progress, the goal of improving classroom learning effectiveness is achieved [ABSTRACT FROM AUTHOR]

Mirror‐image proteins (D‐proteins) are useful in biomedical research for purposes such as mirror‐image screening for D‐peptide drug discovery, but the chemical synthesis of many D‐proteins is often low yielding due to the poor solubility or aggregation of their constituent peptide segments. Here, we report a Lys‐C protease‐cleavable solubilizing tag and its use to synthesize difficult‐to‐obtain D‐proteins. Our tag is easily installed onto multiple amino acids such as DLys, DSer, DThr, and/or the N‐terminal amino acid of hydrophobic D‐peptides, is impervious to various reaction conditions, such as peptide synthesis, ligation, desulfurization, and transition metal‐mediated deprotection, and yet can be completely removed by Lys‐C protease under denaturing conditions to give the desired D‐protein. The efficacy and practicality of the new method were exemplified in the synthesis of two challenging D‐proteins: D‐enantiomers of programmed cell death protein 1 IgV domain and SARS‐CoV‐2 envelope protein, in high yield. This work demonstrates that the enzymatic cleavage of solubilizing tags under denaturing conditions is feasible, thus paving the way for the production of more D‐proteins. [ABSTRACT FROM AUTHOR]

D‐peptide ligands can be screened for therapeutic potency and enzymatic stability using synthetic mirror‐image proteins (D‐proteins), but efficient acquisition of these D‐proteins can be hampered by the need to accomplish their in vitro folding, which often requires the formation of correctly linked disulfide bonds. Here, we report the finding that temporary installation of natural O‐linked‐β‐N‐acetyl‐D‐glucosamine (O‐GlcNAc) groups onto selected D‐serine or D‐threonine residues of the synthetic disulfide‐bonded D‐proteins can facilitate their folding in vitro, and that the natural glycosyl groups can be completely removed from the folded D‐proteins to afford the desired chirally inverted D‐protein targets using naturally occurring O‐GlcNAcase. This approach enabled the efficient chemical syntheses of several important but difficult‐to‐fold D‐proteins incorporating disulfide bonds including the mirror‐image tumor necrosis factor alpha (D‐TNFα) homotrimer and the mirror‐image receptor‐binding domain of the Omicron spike protein (D‐RBD). Our work establishes the use of O‐GlcNAc to facilitate D‐protein synthesis and folding and proves that D‐proteins bearing O‐GlcNAc can be good substrates for naturally occurring O‐GlcNAcase. [ABSTRACT FROM AUTHOR]

Each year, 9.4 million episodes of foodborne illness occur in the United States (1). According to the Centers for Disease Control and Prevention, -95% of these infections are sporadic, nonoutbreak [...]

Membrane‐associated D‐proteins are an important class of synthetic molecules needed for D‐peptide drug discovery, but their chemical synthesis using canonical ligation methods such as native chemical ligation is often hampered by the poor solubility of their constituent peptide segments. Here, we describe a Backbone‐Installed Split Intein‐Assisted Ligation (BISIAL) method for the synthesis of these proteins, wherein the native L‐forms of the N‐ and C‐intein fragments of the unique consensus‐fast (Cfa) (i.e. L–CfaN and L–CfaC) are separately installed onto the two D‐peptide segments to be ligated via a removable backbone modification. The ligation proceeds smoothly at micromolar (μM) concentrations under strongly chaotropic conditions (8.0 M urea), and the subsequent removal of the backbone modification groups affords the desired D‐proteins without leaving any "ligation scar" on the products. The effectiveness and practicality of the BISIAL method are exemplified by the synthesis of the D‐enantiomers of the extracellular domains of T cell immunoglobulin and ITIM domain (TIGIT) and tropomyosin receptor kinase C (TrkC). The BISIAL method further expands the chemical protein synthesis ligation toolkit and provides practical access to challenging D‐protein targets. [ABSTRACT FROM AUTHOR]

Salmonella enterica causes ≅ 1 million illnesses and >350 deaths annually in the United States (1). Among >2,500 known serotypes, S. enterica serotype Enteritidis is one of the most commonly [...]

Vascular endothelial growth factor (VEGF) is a critical regulator of malignant pleural effusion (MPE) in non-small-cell lung cancer (NSCLC). Bevacizumab (BEV) and apatinib (APA) are novel VEGF blockers that inhibit lung cancer cell proliferation and the development of pleural effusion. In this study, we established Lewis lung cancer (LLC) xenograft mouse models to compare the therapeutic effect of APA and BEV in combination with cisplatin (CDDP) against MPE. The anti-tumour and anti-angiogenic effects of this combination therapy were evaluated by 18F-FDG PET/CT imaging, TUNEL assay and Immunohistochemistry. The triple drug combination significantly prolonged the overall survival of the tumour-bearing mice by reducing MPE and glucose metabolism and was more effective in lowering VEGF/soluble VEGFR-2 levels in the serum and pleural exudates compared to either of the monotherapies. Furthermore, CDDP + APA + BEV promoted in vivo apoptosis and decreased microvessel density. Mechanistically, LLC-induced MPE was inhibited by targeting the VEGF-MEK/ERK pathways. Further studies are needed to establish the synergistic therapeutic effect of these drugs in NSCLC patients with MPE. Combined treatment of MPE with apatinib, bevacizumab and cisplatin can prolong the survival time of mice, reduce the content of MPE, decrease the SUVmax of thoracic tumour tissue, down-regulate the content of VEGF and sVEGFR-2 in serum and pleural fluid, and promote the apoptosis of tumour cells. Angiogenesis and MPE formation can be inhibited by down-regulation of HIF-1α, VEGF, VEGFR-2, MEK1 and MMP-2 molecular signalling pathway proteins. [ABSTRACT FROM AUTHOR]

Skin metastasis from ovarian cancer is rare, and its prognosis is poor. Effective therapeutic strategies are currently lacking, but the combination of various treatment methods shrink the tumor and relieve symptoms. The present study reports a rare case of advanced ovarian cancer with skin metastases and intestinal wall thickening, along with a BRCA1 DNA repair associated (BRCA1) mutation. After standard first-line treatment and non-standard second-line treatment, the patient developed skin metastases. The patient's skin itching, pain and lesions were completely relieved after administering bevacizumab in combination with paclitaxel and carboplatin. After 4 months, skin metastases recurred along with anal distension during maintenance treatment with oral poly(ADP ribose) polymerase (PARP) inhibitors. The patient was treated again with bevacizumab combined with docetaxel, and the anal distension was significantly relieved. Angiogenesis therapy combined with chemotherapy is effective, but that the disease-free survival time is short, and PARP inhibitor maintenance effect is limited even in cases with a BRCA1 gene mutation. [ABSTRACT FROM AUTHOR]

Information security has become a focal topic in the information and digital age. How to realize secure transmission and the secure storage of image data is a major research focus of information security. Aiming at this hot topic, in order to improve the security of image data transmission, this paper proposes an image encryption algorithm based on improved Arnold transform and a chaotic pulse-coupled neural network. Firstly, the oscillatory reset voltage is introduced into the uncoupled impulse neural network, which makes the uncoupled impulse neural network exhibit chaotic characteristics. The chaotic sequence is generated by multiple iterations of the chaotic pulse-coupled neural network, and then the image is pre-encrypted by XOR operation with the generated chaotic sequence. Secondly, using the improved Arnold transform, the pre-encrypted image is scrambled to further improve the scrambling degree and encryption effect of the pre-encrypted image so as to obtain the final ciphertext image. Finally, the security analysis and experimental simulation of the encrypted image are carried out. The results of quantitative evaluation show that the proposed algorithm has a better encryption effect than the partial encryption algorithm. The algorithm is highly sensitive to keys and plaintexts, has a large key space, and can effectively resist differential attacks and attacks such as noise and clipping. [ABSTRACT FROM AUTHOR]