Objective:To establish a model based on the characteristics of breast cancer ultrasound images through deep learning methods to predict the risk of axillary lymph node metastasis（ALNM）in patients with breast cancer（maximum diameter ≤2.5 cm）before surgery.Methods:A total of 419 patients（3 433 breast tumor ultrasound images）with breast cancer（maximum diameter ≤2.5 cm）who underwent axillary lymph node dissection at Beijing Tiantan Hospital，Capital Medical University from January 2019 to December 2024 were retrospectively included. According to the pathological results of axillary lymph nodes，they were divided into 220 cases in the ALNM occurrence group（positive group）and 199 cases in the non-ALNM occurrence group（negative group）. The breast cancer ultrasound images of the two groups of cases were randomly classified into the training set（2 404 images），the validation set（687 images）and the test set（342 images）according to a ratio of 7∶2∶1. YOLOv8 was used as the basic model of You Only Look Once（YOLO）and optimized. The optimized model was applied to locate and capture the potential ultrasound features of breast cancer cases in the training set. A prediction model was constructed based on the captured ultrasound features. The model was adjusted and optimized through the validation set，and then matched with the case images in the test set. The confusion classification matrix graph and the curve graph for measuring the model performance were used to evaluate the model prediction performance and interpret the model，and the efficacy of this model in identifying breast cancer patients at risk of ALNM was analyzed.Results:There were statistically significant differences between the positive and negative groups in terms of the pathological maximum diameter of breast tumors，pathological T staging，the differentiation degree，the presence of distant metastasis，the maximum diameter measured by ultrasound，the quadrant of breast tumor occurrence，the Breast Imaging - Reporting and Data System（BI-RADS）classification of breast tumors，and the presence of abnormal ultrasound features of lymph node（all P<0.05）. The established deep learning model could automatically perform bounding box localization for the breast cancer of patients.The breast tumors in the positive group had potential ultrasound features that could be captured by the model compared with those in the negative group. The mean average precision（mAP）50 was 0.883，mAP 50-95 was 0.636，PR-AUC was 0.884 5，strict PR-AUC was 0.636 4，the sensitivity was 90.5%，and the specificity was 91.2%，and it had a good predictive efficacy. Conclusions:This prediction model based on the ultrasound characteristics of breast cancer through deep learning can effectively predict breast cancer（maximum diameter ≤ 2.5 cm）with the risk of ALNM，providing an effective basis for the clinical management of axillary lymph nodes in breast cancer patients.

In recent years,there has been an increase in the prevalence and incidence of acute myocardial infarction.Despite advances in diagnostic and therapeutic technologies related to the disease,challenges remain in the management of the disease after patients are discharged from the hospital.Home-based cardiac rehabilitation has been demonstrated to be an effective means of improving the prognosis of the disease.The utilization of digital health technology has the potential to enhance patient compliance and quality of life in the context of home-based cardiac rehabilitation for those who have experienced an acute myocardial infarction.This article reviews the forms of intervention,specific applications and effects of digital health technologies in home-based cardiac rehabilitation,It analyses the existing problems and puts forward nursing countermeasures.The aim is to further help nursing staff to guide the practice of home cardiac rehabilitation for patients with acute myocardial infarction.

In recent years,there has been an increase in the prevalence and incidence of acute myocardial infarction.Despite advances in diagnostic and therapeutic technologies related to the disease,challenges remain in the management of the disease after patients are discharged from the hospital.Home-based cardiac rehabilitation has been demonstrated to be an effective means of improving the prognosis of the disease.The utilization of digital health technology has the potential to enhance patient compliance and quality of life in the context of home-based cardiac rehabilitation for those who have experienced an acute myocardial infarction.This article reviews the forms of intervention,specific applications and effects of digital health technologies in home-based cardiac rehabilitation,It analyses the existing problems and puts forward nursing countermeasures.The aim is to further help nursing staff to guide the practice of home cardiac rehabilitation for patients with acute myocardial infarction.

Objective:To establish a model based on the characteristics of breast cancer ultrasound images through deep learning methods to predict the risk of axillary lymph node metastasis（ALNM）in patients with breast cancer（maximum diameter ≤2.5 cm）before surgery.Methods:A total of 419 patients（3 433 breast tumor ultrasound images）with breast cancer（maximum diameter ≤2.5 cm）who underwent axillary lymph node dissection at Beijing Tiantan Hospital，Capital Medical University from January 2019 to December 2024 were retrospectively included. According to the pathological results of axillary lymph nodes，they were divided into 220 cases in the ALNM occurrence group（positive group）and 199 cases in the non-ALNM occurrence group（negative group）. The breast cancer ultrasound images of the two groups of cases were randomly classified into the training set（2 404 images），the validation set（687 images）and the test set（342 images）according to a ratio of 7∶2∶1. YOLOv8 was used as the basic model of You Only Look Once（YOLO）and optimized. The optimized model was applied to locate and capture the potential ultrasound features of breast cancer cases in the training set. A prediction model was constructed based on the captured ultrasound features. The model was adjusted and optimized through the validation set，and then matched with the case images in the test set. The confusion classification matrix graph and the curve graph for measuring the model performance were used to evaluate the model prediction performance and interpret the model，and the efficacy of this model in identifying breast cancer patients at risk of ALNM was analyzed.Results:There were statistically significant differences between the positive and negative groups in terms of the pathological maximum diameter of breast tumors，pathological T staging，the differentiation degree，the presence of distant metastasis，the maximum diameter measured by ultrasound，the quadrant of breast tumor occurrence，the Breast Imaging - Reporting and Data System（BI-RADS）classification of breast tumors，and the presence of abnormal ultrasound features of lymph node（all P<0.05）. The established deep learning model could automatically perform bounding box localization for the breast cancer of patients.The breast tumors in the positive group had potential ultrasound features that could be captured by the model compared with those in the negative group. The mean average precision（mAP）50 was 0.883，mAP 50-95 was 0.636，PR-AUC was 0.884 5，strict PR-AUC was 0.636 4，the sensitivity was 90.5%，and the specificity was 91.2%，and it had a good predictive efficacy. Conclusions:This prediction model based on the ultrasound characteristics of breast cancer through deep learning can effectively predict breast cancer（maximum diameter ≤ 2.5 cm）with the risk of ALNM，providing an effective basis for the clinical management of axillary lymph nodes in breast cancer patients.

ObjectiveTo discriminate the age of Arisaema Cum Bile， the combination of headspace solid-phase microextraction （HS-SPME） with gas chromatography-mass spectrometry （GC-MS） was applied to explore the differences of volatile components of unfermented， 1-year fermented， 2-year fermented， and 3-year fermented Arisaema Cum Bile. MethodSamples with different fermentation durations were collected and HS-SPME-GC-MS technology was employed to detect the volatile components of each sample. The relative contents of detected volatile components were processed and analyzed by chemometrics methods such as principal component analysis （PCA）， hierarchical cluster analysis （HCA）， and partial least squares discriminant analysis （PLS-DA）. ResultThe results showed that 145 volatile components were identified. Among these volatile components， the relative contents of heterocyclic， alcohols， aldehydes and aromatics were high. PCA， HCA， and PLS-DA can effectively separate Arisaema Cum Bile with four different ages. Based on variable importance in projection （VIP） value > 1， 73 markers of differential volatile components were identified. The content of 2，6，11-trimethyldodecane and m-xylene in unfermented samples was the highest， and the content difference between them and those in fermented samples was significant （P<0.05）. 2，3-butanediol was detected only in 1-year samples， octane was detected only in 2-year samples， and ethyl heptanoate was detected only in 3-year samples. These components can be used as odor markers for Arisaema Cum Bile with different fermentation years. ConclusionThe identification method of volatile components of Arisaema Cum Bile was established by HS-SPME-GC-MS technology， which can realize the rapid identification of unfermented， 1-year fermented， 2-year fermented， and 3-year fermented samples， and provide a scientific basis for the standardization of processing technology and quality standards of Arisaema Cum Bile.

BACKGROUND:Compared with traditional two-dimensional culture,three-dimensional microtissue culture can show greater advantages.However,more favorable cultivation methods in three-dimensional culture still need to be further explored. OBJECTIVE:To evaluate the cell behavior of microtissue and its ability to promote cartilage formation under two three-dimensional culture methods. METHODS:Cartilage-derived microcarriers were prepared by chemical decellularization and tissue crushing.DNA quantification and nuclear staining were used to verify the success of decellularization,and histological staining was used to observe the matrix retention before and after decellularization.The microcarriers were characterized by scanning electron microscopy and CCK-8 assay.Cartilage-derived microtissues were constructed by combining cartilage-derived microcarriers with human adipose mesenchymal stem cells through three-dimensional static culture and three-dimensional dynamic culture methods.The cell viability and chondrogenic ability of the two groups of microtissues were detected by scanning electron microscopy,live and dead staining,and RT-qPCR. RESULTS AND CONCLUSION:(1)Cartilage-derived microcarriers were successfully prepared.Compared with before decellularization,the DNA content significantly decreased after decellularization(P<0.001).Scanning electron microscope observation showed that the surface of the microcarrier was surrounded by collagen,maintaining the characteristics of the natural extracellular matrix of cartilage cells.CCK-8 assay indicated that microcarriers had no cytotoxicity and could promote cell proliferation.(2)Scanning electron microscopy and live and dead staining results showed that compared with the three-dimensional static group,the three-dimensional dynamic group had a more extended morphology of microtissue cells,and extensive connections between cells and cells,between cells and matrix,and between matrix.(3)The results of RT-qPCR showed that the expressions of SOX9,proteoglycan,and type Ⅱ collagen in microtissues of both groups were increased at 7 or 14 days.The relative expression levels of each gene in the three-dimensional dynamic group were significantly higher than those in the three-dimensional static group at 14 days(P<0.05).At 21 days,the three-dimensional static group had significantly higher gene expression compared with the three-diomensional dynamic group(P<0.001).(4)The results showed that compared with three-dimensional static culture microtissue,three-dimensional dynamic culture microtissue could achieve higher expression of chondrogen-related genes in a shorter time,showing better cell viability and chondrogenic ability.

Objective:To study the in vitro construction of functional and self-renewing cartilage organoids based on cartilage acellular extracellular matrix (ECM) microcarriers.Methods:Fresh porcine articular cartilage was taken. The merely crushed cartilage particles were set as natural cartilage group and ECM microcarriers of appropriate particle size, which were prepared by the acellular method of combining physical centrifugation and chemical extraction, were set as microcarrier group. Cartilage organoids were constructed by loading human umbilical cord mesenchymal stem cells (hUCMSCs) and human chondrocytes (hCho) with a ratio of 3∶1 with microcarriers through a rotating bioreactor. The organoids with different induction times were divided into 0-, 7-, 14-, and 21-day induction groups. The cell residues of the microcarrier group and natural cartilage group were evaluated by 4′, 6-diaminidine 2-phenylindole (DAPI) fluorescence staining and DNA quantitative analysis. The retention of microcarrier components was observed by Safranin O and toluidine blue stainnings, and the collagen and glycosaminoglycan (GAGs) levels in the microcarrier group and the natural cartilage group were determined by colorimetric method and dimethyl-methylene blue (DMMB) method. The microcarriers were further characterized by scanning electron microscopy and energy dispersive spectroscopy. The hUCMSCs cultured with Dulbecco′s Modified Eagle′s Medium (DMEM) supplemented with fetal bovine serum (FBS) in a volume fraction of 10% was used as the control group and the hUCMSCs cultured with the microcarrier extract was used as the experimental group. Subgroups of hUCMSCs cultured at 3 time points: 1, 3 and 5 days were set up in the two groups separately. Cell Counting Kit 8 (CCK-8) was used to detect the biocompatibility of the two groups. The cellular activity of the organoids of the 0-, 7-, 14-, and 21-day induction groups was detected by live/dead staining and the self-renewal ability of the cartilage organoids of the 14-day induced group was identified by Ki67 fluorescence staining. The organoids of the 7-, 14-, and 21-day induction groups were detected by RT-PCR in terms of the expression levels of chondrogenesis-related marker aggrecan (ACAN), type II collagen (COL2A1), SRY-related high mobility group-box gene-9 (SOX9), cartilage hypertrophy-and mineralization-related marker type I collagen (COL1A1), Runt-related transcription factor-2 (RUNX2), and osteocalcin (OCN). Colorimetric and DMMB assays were performed to determine the ability of organoids in the 0-, 7-, 14-, and 21-day induction groups to secrete collagen and GAGs.Results:The results of DAPI fluorescent staining showed that the natural cartilage group had a large number of nuclei while the microcarrier group hardly had any nuclei. The DNA content of the microcarrier group was (7.8±1.8)ng/mg, which was significantly lower than that of the natural cartilage group [(526.7±14.7)ng/mg] ( P<0.01). Saffranin O and toluidine blue staining showed that the microcarrier was dark- and uniform-colored and it kept a lot of cartilage ECM components. The collagen and GAGs contents of the microcarrier group were (252.9±1.4)μg/mg and (173.4±0.8)μg/mg, which were significantly lower than those of the natural cartilage group [(311.9±2.2)μg/mg and (241.3±0.7)μg/mg] ( P<0.01). Scanning electron microscopy showed that the surface of the microcarriers had uneven and interleaved collagen fiber network. The results of energy spectrum analysis showed that elements C, O and N were evenly distributed in the microcarriers, indicating that the composition of the microcarrier was uniform. The microcarrier had good biocompatibility and there was no statistical significance in the results of CCK-8 test between the control group and the experimental group after 1 and 3 days of culture ( P>0.05). After 5 days of culture, the A value of the experimental group was 0.53±0.02, which was better than that of the control group (0.44±0.03) ( P<0.05). In the 0-, 7-, 14-, and 21-day induction groups, hUCMSCs and hCho were attached to the surface of the microcarriers, with good cellular activity, and the live/death rates were (70.6±1.1)%, (80.5±0.6)%, (94.5±0.9)%, and (90.8±0.5)% respectively ( P<0.01). There were a large number of Ki67 positive cells in cartilage organoids. RT-PCR showed that the expression levels of ACAN, COL2A1, SOX9, COL1A1, RUNX2 and OCN were 1.00±0.09, 1.00±0.24, 1.00±0.18, 1.00±0.03, 1.00±0.06 and 1.00±0.13 respectively in the 7-day induction group; 4.16±0.28, 5.09±1.25, 5.65±1.05, 0.47±0.01, 1.68±0.02 and 0.21±0.06 respectively in the 14-day induction group; 13.42±0.92, 3.07±0.21, 1.84±1.08, 2.72±0.17, 2.91±0.18 and 3.32±1.20 respectively in the 21-day induction group. Compared with the 7-day induction group, the expression levels of ACAN, COL2A1, SOX9 and RUNX2 in the 14-day group were increased ( P<0.05), but COL1A1 expression level was decreased ( P<0.05), with no significant difference in OCN expression level ( P>0.05). Compared with the 7-day induction group, the expression levels of ACAN, COL1A1 and RUNX2 in the 21-day induction group were significantly increased ( P<0.01), with no significant differences in the expression levels of COL2A1, SOX9 and OCN ( P>0.05). Compared with the 14-day induction group, the expression levels of ACAN, COL1A1, RUNX2 and OCN in the 21-day group were increased ( P<0.05 or 0.01), with no significant difference in the expression level of COL2A1 ( P>0.05), but the expression level of SOX9 was decreased ( P<0.05). The contents of collagen in 0-, 7-, 14-and 21-day induction groups were (219.15±0.48)μg/mg, (264.07±1.58)μg/mg, (270.83±0.84)μg/mg and (280.01±0.48)μg/mg respectively. The GAGs contents were (171.18±1.09)μg/mg, (184.06±1.37)μg/mg, (241.08±0.84)μg/mg and (201.14±0.17)μg/mg respectively. Compared with the 0-day induction group, the contents of collagen and GAGs in 7-, 14-, and 21-day induction groups were significantly increased ( P<0.01), among which the content of collagen was the lowest in 7-day induction group ( P<0.01) but the highest in the 21-day induced group ( P<0.01); the content of GAGs was the lowest in the 7-day induced group ( P<0.01) but the highest in the 14-day induction group ( P<0.01). Conclusions:The microcarriers prepared by combining physical and chemical methods are decellularized successfully, with more matrix retention, uniform composition and on cytotoxicity. By loading microcarriers with hUCMSCs and hCho, cartilage organoids are successfully constructed in vitro, which are characterized by good cell activity, self-renewal ability, strong expression of genes related to chondrogenesis and secretion of collagen and GAGs. The cartilage organoids constructed at 14 days of induction have the best chondrogenic activity.

Frailty and trauma are closely related, and together affect the health outcomes of elderly trauma patients. However, insufficient attention has been paid to the frailty of elderly trauma patients in China. This paper reviews the relationship between frailty and trauma, assessment tools and management of frailty in elderly trauma patients, in order to provide a new perspective of nursing care for elderly trauma patients in China and to provide references for carrying out research on frailty in elderly trauma patients.

Objective:To design a set of assessment tool for the effectiveness of internal performance management in public hospitals, so as to provide reference for optimization hospital internal systems and multi-institutional comparison.Methods:From September 2022 to April 2023, literature review and expert group discussion were used to initially construct an index system for evaluating the effectiveness of performance management in public hospitals, based on the " structure-process-outcome" model. Index quantitative scoring rules and standardized staff questionnaire for supporting use were developed by drawing on the World Management Survey Hospital Edition and Chinese Hospital Management Survey. Two rounds of Delphi consultation were made to rate the importance and measurement feasibility of each index. The analytic hierarchy process was used to determine the relative importance of the finalized indexes. Results:The effective recovery rate of expert consultation questionnaire was 100%, and the authority coefficient was 0.882. The index system consisted of 3 first-level indexes (structure, process, and result), 9 second-level indexes, and 27 third-level indexes. The weights of structure, process and result were 0.307, 0.406 and 0.287, respectively. The second-level indexes with the highest weight were internal effectiveness, informationization, and performance tracking and evaluation, with values of 0.180, 0.156 and 0.115, respectively. The third-level indexes with the highest weight were the construction level of performance management information integration platform, the incentive degree of hospital performance management system to employees, and the scope of performance tracking and evaluation, with values of 0.156, 0.075 and 0.073. The third-level index quantitative scoring rules covered the management activity points that were easy to collect via investigation. Among them, the feasibility of 22 scoring rules were recognized by all the 15 experts, 5 rules were recognized by 14 experts, and 2 rules were recognized by 13 experts. A standardized survey questionnaire covering 25 questions was established based on four third-level indexes: the level of understanding, recognition, satisfaction, and motivation of employees towards the hospital performance management system. The importance scores of each question ranged from 7.43 to 8.71.Conclusions:This study developed a comprehensive suite of assessment instruments, including an index system, a set of quantitative scoring rules, and a standardized staff questionnaire, which could provide reference for hospitals to upgrade their internal performance management levels.

The tumors of central nervous system refer to a group of benign and malignant diseases originating from tissues or structures within the central nervous system. Common tumors of central nervous system are sporadic, but a few have familial onset. Compared with sporadic brain tumors, the clinical symptoms, diagnostic ideas and follow-up review plans of familial brain tumors are more complicated. The multidisciplinary diagnosis and treatment (MDT) mode usually refers to a treatment mode in which a case involving multiple organs and systems is discussed, and the best treatment plan is formulated for the patient based on the comprehensive opinions of various disciplines. Because familial brain tumors often involve multiple organs, multiple disciplines and multiple systems, and their low incidence leads to less clinical experience for neurosurgeons, the MDT model is more conducive to efficient diagnosis, treatment and management of familial brain tumors. This review elaborates on the neurosurgeon-led MDT model, and introduces the latest research on the epidemiology, genetic characteristics, clinical manifestations, diagnostic ideas and multidisciplinary management of familial brain tumors.