Objective To explore the correlation of MET status in patients with advanced prostatic acinar adenocarcinoma with the clinical pathological parameters and prognosis. Methods The specimen from 135 patients with advanced prostatic acinar adenocarcinoma was included. The expression of c-MET protein was detected via immunohistochemistry, and MET gene amplification was assessed by fluorescence in situ hybridization. The relationships of c-MET expression and gene amplification with clinicopathological features and prognosis were analyzed. Results The positive expression rate of c-MET was 52.60% (71/135). Compared with the c-MET expression in adjacent tissues, that in tumor tissues showed lower heterogeneous expression. Among the cases, 1.71% (2/117) exhibited MET gene polyploidy, but no gene amplification was detected. Positive c-MET expression was significantly correlated with high Gleason scores and grade groups (P=0.0073). However, no significant relationship was found between c-MET expression and progression-free survival or post-treatment t-PSA levels. Conclusion c-MET protein is expressed at a relatively low level in advanced prostatic acinar adenocarcinoma, suggesting that c-MET may not be a viable target for ADC drug development in prostatic acinar adenocarcinoma.

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

HDAC7, a member of class IIa HDACs, plays a pivotal regulatory role in tumor, immune, fibrosis, and angiogenesis, rendering it a potential therapeutic target. Nevertheless, due to the high similarity in the enzyme active sites of class IIa HDACs, inhibitors encounter challenges in discerning differences among them. Furthermore, the substitution of key residue in the active pocket of class IIa HDACs renders them pseudo-enzymes, leading to a limited impact of enzymatic inhibitors on their function. In this study, proteolysis targeting chimera (PROTAC) technology was employed to develop HDAC7 drugs. We developed an exceedingly selective HDAC7 PROTAC degrader B14 which showcased superior inhibitory effects on cell proliferation compared to TMP269 in various diffuse large B cell lymphoma (DLBCL) and acute myeloid leukemia (AML) cells. Subsequent investigations unveiled that B14 disrupts BCL6 forming a transcriptional inhibition complex by degrading HDAC7, thereby exerting proliferative inhibition in DLBCL. Our study broadened the understanding of the non-enzymatic functions of HDAC7 and underscored the importance of HDAC7 in the treatment of hematologic malignancies, particularly in DLBCL and AML.

Abstract Prenatal stress is a common, systemic, nonspecific stress response that occurs during pregnancy. The gut microbiota, which is known as the “second genome” of the human body, interacts with all major systems of the body. Changes in the gut microbiota can impact the development and health of infants and young children. Advances in research technology have allowed us to uncover the relationship between prenatal stress and imbalances in offspring intestinal microbiota, as well as the development of multiple systemic diseases. However, the exact mechanisms through which prenatal stress disrupts the gut microbiota of offspring remain incompletely understood. This review summarizes the existing research on diseases caused by prenatal stress disrupting the offspring intestinal flora, and seeks future research directions to expand the understanding of the pathogenesis of infant diseases.

Abstract Asthma is a well-characterized heterogeneous disease marked by airway remodeling and chronic airway inflammation. Clinically, the treatment of asthma primarily relies on hormonal drugs. However, the long-term use of these medications can lead to significant side effects. Mitophagy is a biological process that selectively transports damaged mitochondria to lysosomes for degradation. Recent research has revealed the crosstalk between mitophagy and asthma. Accordingly, taking mitophagy as an entry point, summarizing the key molecular mechanisms and regulators of mitophagy in asthma will facilitate the development of novel intervention targets and strategies for asthmatic treatment.

Objective To investigate the osteogenic properties of a methacrylated gelatin(GelMA)/bone marrow mesenchymal stem cells(BMSCs)composite hydrogel applied to the skull defect area of rats and to provide an experi-mental basis for the development of bone regeneration biomaterials.Methods This study was approved by the Animal Ethics Committee of Nanjing University.A novel photocurable composite biohydrogel was developed by constructing photoinitiators[lthium phenyl(2,4,6-trimethylbenzoyl)phosphinate,LAP],GelMA,and BMSCs.The surface morphology and elemental composition of the gel were examined using scanning electron microscopy(SEM)and energy-dispersive X-ray spectroscopy(EDX).The compressive strength of the gel was evaluated using an electronic universal testing ma-chine.After in vitro culture for 1,2,and 5 days,the proliferation of the BMSCs in the hydrogels was assessed using a CCK-8 assay,and their survival and morphology were examined through confocal microscopy.A 5 mm critical bone de-ficiency model was generated in a rat skull.The group receiving composite hydrogel treatment was referred to as the Gel-MA/BMSCs group,whereas the untreated group served as the control group.At the 4th and 8th weeks,micro-CT scans were taken to measure the bone defect area and new bone index,while at the 8th week,skull samples from the defect ar-ea were subjected to H&E staining,van Gieson staining,and Goldner staining to evaluate the quality of bone regenera-tion and new bone formation.Results SEM observed that the solidified GelMA showed a 3D spongy gel network with uniform morphology,the porosity of GelMA was 73.41％and the pore size of GelMA was(28.75±7.13)μm.EDX results showed that C and O were evenly distributed in the network macroporous structure of hydrogel.The hydrogel compres-sion strength was 152 kPa.On the 5th day of GelMA/BMSCs culture,the cellular morphology transitioned from oval to spindle shaped under microscopic observation,accompanied by a significant increase in cell proliferation(159.4％,as determined by the CCK-8 assay).At 4 weeks after surgery,a 3D reconstructed micro-CT image revealed a minimal re-duction in bone defect size within the control group and abundant new bone formation in the GelMA/BMSCs group.At 8 weeks after surgery,no significant changes were observed in the control group's bone defect area,with only limited evi-dence of new bone growth;however,substantial healing of skull defects was evident in the GelMA/BMSCs group.Quan-titative analysis at both the 4-and 8-week examinations indicated significant improvements in the new bone volume(BV),new bone volume/total bone volume(BV/TV),bone surface(BS),and bone surface/total bone volume(BS/TV)in the GelMA/BMSCs group compared to those in the control group(P＜0.05).Histological staining showed continuous and dense formation of bone tissue within the defects in the GelMA/BMSCs group and only sporadic formation of new bone,primarily consisting of fibrous connective tissue,at the defect edge in the control group.Conclusion Photocur-ing hydrogel-based stem cell therapy exhibits favorable biosafety profiles and has potential for clinical application by inducing new bone formation and promoting maturation within rat skull defects.

Highly sensitive multiple detection and accurate identification of gases are of great importance in the fields of public safety,environmental protection,health diagnosis and industrial production.However,the traditional means of gas detection have many shortcomings such as low sensitivity,long time-consuming,bulky equipment,cumbersome processes and expensive costs.In recent years,Raman spectroscopy has become a hotspot in the field of gas detection because of its fast,sensitive and non-destructive characteristics,and has been more and more closely combined with artificial intelligence.This paper reviews the progress of Raman spectroscopy in gas detection in recent years,including conventional Raman spectroscopy and enhanced Raman spectroscopy,and also introduces the integration of artificial intelligence algorithms in gas Raman detection technology,and discusses the future development of gas Raman detection.

Objective To propose a method for classifying small bowel capsule endoscopy images by combining the Swin Transformer network with an improved Adapt-RandAugment data augmentation approach,aiming to enhance the accuracy and efficiency of small bowel lesion classification and recognition.Methods An Adapt-RandAugment data augmentation approach was formulated based on the RandAugment data enhancement sub-strategy and the principles of no feature loss and no distortion when enhancing small bowel capsule endoscopy images.In the publicly available Kvasir-Capsule dataset of small bowel capsule endoscopic images,the Adapt-RandAugment data augmentation approach was trained based on the Swin Transformer network,and the convolutional neural networks ResNet152 and DenseNet161 were used as the benchmarks to validate the combined Swin Transformer network and Adapt-RandAugment data augmentation approach for small bowel capsule endoscopy image classification.Results The proposed algorithm gained advantages over ResNet152 and DenseNet161 networks in the indicators,which had the macro average precision(MAC-PRE),macro average recall(MAC-REC),macro average F1 score(MAC-Fi-S)being 0.383 2,0.314 8 and 0.290 5 respectively,the micro average precision(MIC-PRE),micro average recall(MIC-REC)and micro average F1 score(MIC-Fi-S)all being 0.755 3,and the Matthews correlation coe-fficient(MCC)being 0.452 3.Conclusion The proposed small bowel capsule endoscopy image classification method based on Swin Transformer network and Adapt-RandAugment data augmentation approach behaves well in classified recognition efficiency and accuracy.[Chinese Medical Equipment Journal,2024,45(6):9-16]

The working principle of TMC BC ROBO 6 intelligent blood collection system was described in brief.The causes of three faults during daily operation of the system were analyzed,and the countermeasures were put forward accordingly.References were provided for clinical engineers to treat similar faults.[Chinese Medical Equipment Journal,2024,45(6):113-116]