ObjectiveTo establish a tumor prognostic risk assessment model related to target genes of the miR-34 family. MethodsTarget genes of the miR-34 family were screened， and the scores of miR-34 target genes were assessed in 16 tumor types. Univariate Cox regression analysis was used to identify the tumor type with the strongest correlation between miR-34 target gene scores and overall survival （OS）. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed to elucidate the functional roles and signaling pathways of miR-34 target genes. A prognostic risk model based on the miR-34 target genes was constructed using univariate Cox and LASSO regression analyses. Quantitative real-time PCR （qPCR） and dual-luciferase reporter assays were conducted to validate whether the target genes bind to miR-34 and measure their RNA expression levels in the relevant tumors. Additionally， the risk score was integrated with other clinical indicators to develop a nomogram prediction model for patient survival. ResultsA total of 65 target genes of the miR-34 family were screened. The cancer type exhibiting stronger correlation between the target gene scores and OS was lung adenocarcinoma （P = 0.003， HR= 5.150）. Furthermore， miR-34 target genes were predominantly enriched in oxidative stress pathways and various tumor-related processes. Three genes， LDHA， GALNT7， and SATB2， were identified as core components of the prognostic analysis model for lung adenocarcinoma. Additionally， the constructed nomogram model demonstrated robust predictive performance. ConclusionThe risk model and prognosis model of lung adenocarcinoma constructed based on the key target genes of miR-34 have good predictive performance.

OBJECTIVE To explore the improvement effect and potential mechanism of modified Yanghe decoction on bone destruction in rats with breast cancer bone metastasis based on the receptor-interacting serine/threonine-protein kinase 1 （RIPK1）/RIPK3 pathway. METHODS The rat model of breast cancer bone metastasis was established by injecting a suspension of breast cancer cells into the bone marrow cavity. The rats with successful modeling were randomly divided into a model group （intragastric administration of equal volume of normal saline）， modified Yanghe decoction low-， medium-， and high-dose groups （intragastric administration of corresponding decoction at 1.30， 2.60 and 5.20 g/kg， calculated by the dosage of crude drug）， high-dose modified Yanghe decoction+si-RIPK1 group （intragastric administration of corresponding decoction at 5.20 g/kg， calculated by the dosage of crude drug； simultaneous injection of small interfering RNA for RIPK1 via the tail vein）， and high-dose modified Yanghe decoction+si-NC group （intragastric administration of corresponding decoction at 5.20 g/kg， calculated by the dosage of crude drug； simultaneous injection of small interfering RNA for negative control via the tail vein）， with 12 rats in each group. Another 12 healthy rats were selected as the control group and were given the same volume of normal saline intragastrically， once a day， for 14 consecutive days. Body weight was measured before administration and at the end of the last administration. The mechanical pain threshold and thermal pain threshold were measured， and the bone destruction， pathological changes and osteoclast formation of the tibia were observed. The positive expression of receptor activator of nuclear factor-κB （RANK） and receptor activator of nuclear factor-κB ligand （RANKL） in the tibial tissue， as well as the phosphorylation levels of RIPK1， RIPK3 and mixed lineage kinase domain-like protein （MLKL） were detected. RESULTS Compared with the control group， the tumor cells of tibia tissues in rats of the model group showed significant proliferation and diffuse infiltration into the bone marrow cavity. Extensive areas of tumor necrosis of cells， severe bone destruction， thinning of the bone cortex， and damage to the bone trabeculae were observed. The body weight （before administration and at the end of the last administration）， mechanical pain threshold， thermal pain threshold， and the phosphorylation levels of RIPK1， RIPK3 and MLKL were decreased significantly； the tumor volume， the proportion of bone destruction area， the number of osteoclasts， and the positive expressions of RANK and RANKL were increased/up-regulated significantly （P＜0.05）. Compared with the model group， the above pathological changes in the tibial tissues of rats in modified Yanghe decoction low-， medium- and high-dose groups were all alleviated， and all quantitative indicators showed dose-dependent improvement （P＜0.05）. After silencing RIPK1， the aforementioned beneficial effects of high-dose modified Yanghe decoction were significantly weakened （P＜0.05）.CONCLUSIONSModified Yanghe decoction can alleviate bone destruction in rats with breast cancer bone metastasis. The above effect is related to the activation of the RIPK1/RIPK3 pathway.

Objective: To determine the causative agent, clinical manifestations and risk factors for infection during a September 2023 outbreak of acute haemorrhagic conjunctivitis (AHC) in Pak Touch village, Ratanakiri province, Cambodia. Methods: A retrospective case-control study was conducted. Cases were age-matched to controls (1:1), who were randomly selected from the village population. Twenty-one conjunctival samples were analysed using real-time reverse transcription–polymerase chain reaction (RT–PCR). RNA sequencing was additionally performed to identify the causative agent of the outbreak. Logistic regression models were used to identify significant risk factors. Results: A total of 73 cases and 73 controls were included in the analysis. Cases had a median age of 20 years (range: 1–70, mean and standard deviation: 27.7 ± 20.0), and 46.6% (34/73) were male. The overall attack rate was 12.3% (73 cases/594 residents). Clinical presentations included conjunctival hyperaemia (100%), subconjunctival haemorrhage (82.2%, 60), pain and discharge (64.4%, 47 each), eyelid swelling (57.5%, 42) and tearing (54.8%, 40). RT–PCR identified enterovirus in 52.4% (11/21) of conjunctival swabs, with RNA sequencing confirming the coxsackievirus A24 variant as the causative agent in five swabs. Statistical analysis identified significant risk factors, including physical contact with patients with acute haemorrhagic conjunctivitis (adjusted odds ratio [aOR]: 4.42, 95% confidence interval [CI]: 1.90–10.10), frequent eye rubbing (aOR: 4.56, 95% CI: 2.00–10.37) and poor hand hygiene (aOR: 3.70, 95% CI: 1.64–8.43). Discussion: The outbreak of acute haemorrhagic conjunctivitis in Pak Touch village was primarily caused by coxsackievirus A24. Significant risk factors included physical contact with infected individuals, frequent eye rubbing and poor hand hygiene. Effective hygiene measures are crucial to prevent the spread of AHC.

Optical brain-computer interface (OBCI) represents an emerging class of neural interaction technologies that use “light” as an information carrier to enable the acquisition, decoding, and modulation of neural signals. Compared with conventional electrical brain-computer interface (BCI), OBCI demonstrates distinct advantages in spatial resolution, cell-type specificity, and the capacity for simultaneous multiparametric monitoring. Driven by rapid advances in functional near-infrared spectroscopy, optical neuroimaging, and optogenetics, optical approaches have progressively extended across the full “read, decode, write” continuum of neural activity, providing a novel technological framework for the development of high-precision closed-loop brain-computer systems. This review systematically summarizes the principal technological strategies and recent advances in OBCI, and further discusses the key challenges encountered during clinical translation, as well as future development direction.

BACKGROUND

Early-stage endometrial cancer often presents with favorable survival rates, but high-risk factors, including TP53 mutations and high-grade serous pathology, can lead to recurrence and poor prognosis. The standard primary treatment for endometrial cancer is surgical staging, and lymph node metastases significantly impact adjuvant therapy decisions. The subgroup of p53-abnormal (p53abn) indicates the worst prognosis and potential benefits from adjuvant chemotherapy. Molecular classification, while recommended, faces practical challenges due to resource constraints.

OBJECTIVES

The study aimed to assess the incidence of p53 abnormal expression in clinical stage 1 endometrial cancer cases that underwent surgery at a government tertiary hospital, and assess its relationship with clinicopathologic factors and pelvic and paraaortic lymph node metastasis (LNM).

METHODS

A cross-sectional retrospective analysis was conducted on clinical early-stage endometrial cancer cases that underwent surgical primary treatment between January 2018 and December 2022. Patient records were reviewed to gather demographics, surgical information, and pathological evaluations. Preoperative clinical staging was determined through imaging, and surgical staging involved comprehensive lymphadenectomy. Immunohistochemistry studies for p53 were carried out on formalin-fixed paraffin-embedded tissue samples.

RESULTS

A total of 233 endometrial cancer cases were included. The mean age at diagnosis was 53.7 years. Common comorbidities included hypertension (47.2%) and dyslipidemia (20.6%). Most cases were endometrioid histology (82.8%) and low-grade tumors (85.8%). Tumor grade (p=0.010), myometrial invasion (pCONCLUSION

Tumor grade, myometrial invasion, and LVSI were all significantly associated with lymph node involvement. While p53 immunohistochemical stains show promise in predicting metastasis and has been associated with tumor aggressiveness, this should still be correlated with clinicopathological parameters to carry out a more accurate risk stratification of early-stage patients.

Therapeutics ; Survival Rate ; Risk Factors ; Recurrence ; Prognosis ; Pathology ; Endometrial Neoplasms ; Immunohistochemistry ; Tumor Suppressor Protein P53 ; Lymph Node Excision ; Risk Assessment

BACKGROUND

Early-stage endometrial cancer often presents with favorable survival rates, but high-risk factors, including TP53 mutations and high-grade serous pathology, can lead to recurrence and poor prognosis. The standard primary treatment for endometrial cancer is surgical staging, and lymph node metastases significantly impact adjuvant therapy decisions. The subgroup of p53-abnormal (p53abn) indicates the worst prognosis and potential benefits from adjuvant chemotherapy. Molecular classification, while recommended, faces practical challenges due to resource constraints.

OBJECTIVES

The study aimed to assess the incidence of p53 abnormal expression in clinical stage 1 endometrial cancer cases that underwent surgery at a government tertiary hospital, and assess its relationship with clinicopathologic factors and pelvic and paraaortic lymph node metastasis (LNM).

METHODS

A cross-sectional retrospective analysis was conducted on clinical early-stage endometrial cancer cases that underwent surgical primary treatment between January 2018 and December 2022. Patient records were reviewed to gather demographics, surgical information, and pathological evaluations. Preoperative clinical staging was determined through imaging, and surgical staging involved comprehensive lymphadenectomy. Immunohistochemistry studies for p53 were carried out on formalin-fixed paraffin-embedded tissue samples.

RESULTS

A total of 233 endometrial cancer cases were included. The mean age at diagnosis was 53.7 years. Common comorbidities included hypertension (47.2%) and dyslipidemia (20.6%). Most cases were endometrioid histology (82.8%) and low-grade tumors (85.8%). Tumor grade (p=0.010), myometrial invasion (pCONCLUSION

Tumor grade, myometrial invasion, and LVSI were all significantly associated with lymph node involvement. While p53 immunohistochemical stains show promise in predicting metastasis and has been associated with tumor aggressiveness, this should still be correlated with clinicopathological parameters to carry out a more accurate risk stratification of early-stage patients.

Therapeutics ; Survival Rate ; Risk Factors ; Recurrence ; Prognosis ; Pathology ; Endometrial Neoplasms ; Immunohistochemistry ; Tumor Suppressor Protein P53 ; Lymph Node Excision ; Risk Assessment

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

ObjectiveTo establish consensus on Chinese Herbal Medicine (CHM) for rheumatoid arthritis (RA) among 21 Singaporean experts, this study addressed the lack of CHM clinical practice guidelines (CPGs) in Singapore. Despite advancements in RA therapies, the disease's progressive nature and high costs of novel treatments worsen disparities in management and outcomes. The initiative aimed to bridge this gap by developing expert-backed recommendations for CHM use in RA care.MethodsThe group of experts conducted two rounds of Delphi surveys containing 29 items identified from a literature review. Consensus was defined as ≥75% of votes in dichotomized ratings on a five-point ordinal scale for recognition. Items that did not reach consensus were discussed in a focus group with four selected experts.ResultsNineteen experts completed both rounds of Delphi surveys. A consensus was reached for 27 items, which encompassed Chinese medicine rationale, pattern differentiation, management, CHM prescription, and co-effectiveness with pharmacological therapy. Collective expert opinions were formed for the two remaining items. All items received a recognition score 3.5.ConclusionsThe consensus derived from this study provides a foundation for CHM CPGs for RA in Singapore. However, the findings are limited by the demographic composition of the experts and the representativeness of the patient pool.

Objective To compare the early clinical efficacy and safety of transapical transcatheter aortic valve implantation (TA-TAVI) with surgical aortic valve replacement (SAVR) in patients with severe aortic stenosis (AS). Methods A retrospective study was conducted on patients with severe AS admitted to the Department of Cardiovascular Surgery, The First Affiliated Hospital of University of Science and Technology of China from January 2020 to March 2024. According to the surgical method, patients were divided into a SAVR group and a TA-TAVI group, and the clinical data of the two groups were compared. Results A total of 71 patients were included, with 45 in the SAVR group, including 33 males and 12 females, aged 16-75 (60.89±10.88) years; 26 in the TA-TAVI group, including 15 males and 11 females, aged 61-83 (72.85±5.53) years. The results showed that postoperative aortic valve transvalvular flow velocity [(2.31±0.38) m/s vs. (2.60±0.50) m/s, P=0.019] and transvalvular pressure gradient [(21.09±6.03) mm Hg vs. (28.20±10.79) mm Hg, P=0.001] in the TA-TAVI group were lower than those in the SAVR group. In terms of left ventricular end-diastolic diameter, both preoperative [(56.73±7.74) mm vs. (52.36±7.00) mm, P=0.017] and postoperative [(52.61±7.18) mm vs. (48.04±4.78) mm, P=0.010] values in the TA-TAVI group were larger than those in the SAVR group. In terms of left ventricular ejection fraction, the preoperative value in the TA-TAVI group was lower than that in the SAVR group (58.00%±13.84% vs. 64.87%±7.63%, P=0.026), but there was no statistical difference between the two groups after surgery (P=0.670). The operation time and drainage volume on the first day after surgery in the TA-TAVI group were shorter or lower than those in the SAVR group (P<0.05). There was no statistical difference between the two groups in the postoperative hospital stay, ICU stay, or postoperative mechanical ventilation time (P>0.05). In addition, no serious complications occurred in patients after SAVR, while perivalvular leakage (2 patients), third-degree atrioventricular block (1 patient), and death (3 patients) occurred in the TA-TAVI group. Conclusion For elderly patients with severe AS and poor cardiac function, TA-TAVI technology has minimal surgical trauma, high safety and effectiveness, and is a safe and effective treatment option besides traditional surgical operations.