Environmental damage affects many aspects of healthcare, from extreme weather events to evolving population disease. Singapore's healthcare sector has the world's second highest healthcare emissions per capita, hampering the nation's pledge to reduce emissions by 2030 and achieve net zero emissions by 2050. In this review, we provide an overview of the impact environmental damage has on healthcare, including facilities, supply chain and human health, and examine measures to address healthcare's impact on the environment. Utilising the 'R's of sustainability - rethinking, reducing/refusing, reusing/repurposing/reprocessing, repairing, recycling and research - we have summarised the opportunities and challenges across medical disciplines. Awareness and advocacy to adopt strategies at institutional and individual levels is needed to revolutionise our environmental footprint and improve healthcare sustainability. By leveraging evidence from ongoing trials and integrating sustainable practices, our healthcare system can remain resilient against environment-driven challenges and evolving healthcare demands while minimising further impacts of environmental destruction.
Humans ; Climate Change ; Delivery of Health Care ; Singapore ; Conservation of Natural Resources ; Sustainable Development ; Environment

The choice of biopsy method is critical in diagnosing prostate cancer (PCa). This retrospective cohort study compared systematic biopsy (SB) or cognitive fusion-targeted biopsy combined with SB (CB) in detecting PCa and clinically significant prostate cancer (csPCa). Data from 2572 men who underwent either SB or CB in Fudan University Shanghai Cancer Center (Shanghai, China) between January 2019 and December 2023 were analyzed. Propensity score matching (PSM) was used to balance baseline characteristics, and detection rates were compared before and after PSM. Subgroup analyses based on prostate-specific antigen (PSA) levels and Prostate Imaging-Reporting and Data System (PI-RADS) scores were performed. Primary and secondary outcomes were the detection rates of PCa and csPCa, respectively. Of 2572 men, 1778 were included in the PSM analysis. Before PSM, CB had higher detection rates for both PCa (62.9% vs 52.4%, odds ratio [OR]: 1.54, P < 0.001) and csPCa (54.9% vs 43.3%, OR: 1.60, P < 0.001) compared to SB. After PSM, CB remained superior in detecting PCa (63.1% vs 47.9%, OR: 1.86, P < 0.001) and csPCa (55.0% vs 38.2%, OR: 1.98, P < 0.001). In patients with PSA 4-12 ng ml -1 (>4 ng ml -1 and ≤12 ng ml -1 , which is also applicable to the following text), CB detected more PCa (59.8% vs 40.7%, OR: 2.17, P < 0.001) and csPCa (48.1% vs 27.7%, OR: 2.42, P < 0.001). CB also showed superior csPCa detection in those with PI-RADS 3 lesions (32.1% vs 18.0%, OR: 2.15, P = 0.038). Overall, CB significantly improves PCa and csPCa detection, especially in patients with PSA 4-12 ng ml -1 or PI-RADS 3 lesions.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Propensity Score ; Retrospective Studies ; Middle Aged ; Aged ; Image-Guided Biopsy/methods* ; Prostate-Specific Antigen/blood* ; Prostate/diagnostic imaging*

OBJECTIVE: To analyze the Epstein-Barr virus (EBV) load in different lymphocyte subsets, as well as clinical characteristics and outcomes in patients with hematologic malignancies experiencing EBV reactivation. METHODS: Peripheral blood samples from patients were collected. B, T, and NK cells were isolated sorting with magnetic beads by flow cytometry. The EBV load in each subset was quantitated by real-time quantitative polymerase chain reaction (RT-qPCR). Clinical data were colleted from electronic medical records. Survival status was followed up through outpatient visits and telephone calls. Statistical analyses were performed using SPSS 25.0. RESULTS: A total of 39 patients with hematologic malignancies were included, among whom 35 patients had undergone allogeneic hematopoietic stem cell transplantation (allo-HSCT). The median time to EBV reactivation was 4.8 months (range: 1.7-57.1 months) after allo-HSCT. EBV was detected in B, T, and NK cells in 20 patients, in B and T cells in 11 patients, and only in B cells in 4 patients. In the 35 patients, the median EBV load in B cells was 2.19×10⁴ copies/ml, significantly higher than that in T cells (4.00×10³ copies/ml, P <0.01) and NK cells (2.85×10² copies/ml, P <0.01). Rituximab (RTX) was administered for 32 patients, resulting in EBV negativity in 32 patients with a median time of 8 days (range: 2-39 days). Post-treatment analysis of 13 patients showed EBV were all negative in B, T, and NK cells. In the four non-transplant patients, the median time to EBV reactivation was 35 days (range: 1-328 days) after diagnosis of the primary disease. EBV was detected in one or two subsets of B, T, or NK cells, but not simultaneously in all three subsets. These patients received a combination chemotherapy targeting at the primary disease, with 3 patients achieving EBV negativity, and the median time to be negative was 40 days (range: 13-75 days). CONCLUSION In hematologic malignancy patients after allo-HSCT, EBV reactivation commonly involves B, T, and NK cells, with a significantly higher viral load in B cells compared to T and NK cells. Rituximab is effective for EBV clearance. In non-transplant patients, EBV reactivation is restricted to one or two lymphocyte subsets, and clearance is slower, highlighting the need for prompt anti-tumor therapy.
Humans ; Hematologic Neoplasms/virology* ; Herpesvirus 4, Human/physiology* ; Epstein-Barr Virus Infections ; Hematopoietic Stem Cell Transplantation ; Virus Activation ; Lymphocyte Subsets/virology* ; Flow Cytometry ; Killer Cells, Natural/virology* ; Male ; Female ; B-Lymphocytes/virology* ; Viral Load ; Adult ; T-Lymphocytes/virology* ; Middle Aged

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.

Objective To observe the clinical efficacy of Lingnan Traditional Vesiculating Moxibustion No.4 Recipe(mainly composed of Brassicae Junceae Semen,Euodiae Fructus,and Curcumae Radix)in the treatment of mild depressive disorder(DD),and to provide a novel approach to the treatment of mild DD population.Methods Sixty-one patients with mild DD were randomly divided into 31 cases in the trial group and 30 cases in the control group.The trial group was given medicinal vesiculation treatment with Lingnan Traditional Vesiculating Moxibustion No.4 Recipe,and the control group was given medicinal vesiculation treatment with the placebo of Lingnan Traditional Vesiculating Moxibustion No.4 Recipe.The treatment was performed twice a week and with an interval of 3-4 days between the treatment,and the course of treatment covered 6 weeks.The changes of Hamilton Depression Scale-17(HAMD-17)scores and Patient Health Questionnaire-9(PHQ-9)scores in the two groups were observed before and after the treatment.After treatment,the clinical efficacy and safety of the patients in the two groups were evaluated.Results(1)After 6 weeks of treatment,the total efficacy rate of the trial group was 77.42%(24/31),and that of the control group was 26.67%(8/30).The intergroup comparison(tested by rank sum test)showed that the efficacy of the trial group was significantly superior to that of the control group,and the difference was statistically significant(P＜0.01).(2)After treatment,the HAMD-17 scores and PHQ-9 scores of patients in the two groups were lower than those before treatment(P＜0.01),and the decrease of HAMD-17 and PHQ-9 scores in the trial group was significantly superior to that of the control group,the difference being statistically significant(P＜0.01).(3)During the trial,there were 5 cases of adverse events related to the vesiculating moxibustion treatment,and all 5 cases of adverse events occurred in the trial group,manifested as minor blisters at the acupoint application region.The 5 cases kept on participating in the trial after relevant treatment.Conclusion Lingnan Traditional Vesiculating Moxibustion No.4 Recipe can effectively relieve the clinical symptoms of patients with mild DD,and has high safety.

The detection of cancer markers is of great significance for the early diagnosis and subsequent treatment of cancer.However,the existing traditional detection methods have some limitations,especially in the early stages of cancer,thus is often difficult to detect in a timely and accurate manner.As an efficient detection technique,electrochemical sensors can meet the requirement of accurate detection of various cancer markers,provide strong support for early diagnosis of cancer,and have broad application prospects.MXene is a new two-dimensional material,which is widely used in electrochemical sensors because of its unique properties such as high electron transfer ability,high conductivity,large specific surface area,good biocompatibility and hydrophilicity and abundant surface chemical groups,etc.This paper reviewed the applications of electrochemical biosensors based on MXene composites in cancer marker detection in recent years,introduced the function of MXene in electrochemical biosensor,and discussed challenges and future development trends of MXene in the early diagnosis of cancer,aiming to provide reference for early detection of cancer.

In the study of age estimation in living individuals,a lot of data needs to be analyzed by mathematical statistics,and reasonable medical statistical methods play an important role in data design and analysis.The selection of accurate and appropriate statistical methods is one of the key factors af-fecting the quality of research results.This paper reviews the principles and applicable principles of the commonly used medical statistical methods such as descriptive statistics,difference analysis,consistency test and multivariate statistical analysis,as well as machine learning methods such as shallow learning and deep learning in the age estimation research of living individuals,and summarizes the relevance and application prospects between medical statistical methods and machine learning methods.This paper aims to provide technical guidance for the age estimation research of living individuals to obtain more scientific and accurate results.

Objective To study the effects of dual-hemispheric transcranial direct current stimulation(Dual-tDCS)on upper limb motor function in chronic-phase stroke patients to provide theoretical references for neural mechanisms-based treatment of upper limb dysfunction.Methods Totally 24 chronic-phase stroke patients with upper limb motor dysfunction were selected from some hospital and divided into an experimental group(n=13)and a control group(n=11)the random number table.The control group was treated with tDCS pseudo-stimulation combined with conventional rehabilitation,while the experimental group was given with Dual-tDCS combined with conventional rehabilitation.The patient activities were assessed before and after treatment with Fugl-Meyer assessment upper limb scale(FMA-UL)and activities of daily living(ADL)scale.The changes of primary motor cortex(M1 area)and whole brain functional connectivity(FC)were compared before and after treatment.SPSS 24.0 statistical software was used for data analysis.Results After treatment,the two groups both had the FAM-UL and ADL scores increased significantly,and the experimental group had the scores statistically higher than those of the control group,and the differences were all statistically significant(P＜0.05).In the control group,the analysis on M1 area and whole brain FC after treatment indicated the FC decreased from M1 area at the unaffected side to midoccipital gyrus at the affected side and lingual gyrus and healthy angular gyrus at the unaffected side;there were no brain areas with changed FC found(P＜0.01).In the experimental group,the FC was lowered from M1 area at the unaffected side to cerebellum and cerebellar vermis at the unaffected side,while raised to precentral gyrus at the affected side(P＜0.01);the FC ascended from M1 area at the affected side to cerebellum and middle temporal gyrus at the affected side,while declined to precentral gyrus at the unaffected side(P＜0.01).Conclusion The neuromodulatory effect of Dual-tDCS on the brain improves FC in motor and non-motor-related brain areas in chronic-phase stroke patients,and may contribute to rehabilitation of upper limb motor dysfunction in chronic-phase stroke.[Chinese Medical Equipment Journal,2024,45(2):67-73]

Purpose/Significance To investigate and analyze the current status and influencing factors of digital health literacy(DHL)of the elderly,and to provide references for relevant departments.Method/Process The eHEALS scale is used to investigate the DHL status of 419 elderly people aged 60 and above in Shanghai through convenience sampling,and the influencing factors are explored through binary logistic regression analysis.Result/Conclusion Low education,smoking,and health anxiety are risk factors,while regular physical exami-nation is protective factor.Relevant departments should focus on the elderly people with lower education,and strengthen research and edu-cation on health examinations,smoking hazards,and the alleviation of anxiety.