The focus of green analytical chemistry (GAC) is to minimize the negative impacts of analytical procedures on human safety, human health, and the environment. Several factors, such as the reagents used, sample collection, sample processing, instruments, energy consumed, and the quantities of hazardous materials and waste generated during analytical procedures, need to be considered in the evaluation of the greenness of analytical assays. In this study, we propose a greenness evaluation metric for analytical methods (GEMAM). The new greenness metric is simple, flexible, and comprehensive. The evaluation criteria are based on both the 12 principles of GAC (SIGNIFICANCE) and the 10 factors of sample preparation, and the results are presented on a 0-10 scale. The GEMAM calculation process is easy to perform, and its results are easy to interpret. The output of GEMAM is a pictogram that can provide both qualitative and quantitative information based on color and number.

The focus of green analytical chemistry(GAC)is to minimize the negative impacts of analytical pro-cedures on human safety,human health,and the environment.Several factors,such as the reagents used,sample collection,sample processing,instruments,energy consumed,and the quantities of hazardous materials and waste generated during analytical procedures,need to be considered in the evaluation of the greenness of analytical assays.In this study,we propose a greenness evaluation metric for analytical methods(GEMAM).The new greenness metric is simple,flexible,and comprehensive.The evaluation criteria are based on both the 12 principles of GAC(SIGNIFICANCE)and the 10 factors of sample prep-aration,and the results are presented on a 0-10 scale.The GEMAM calculation process is easy to perform,and its results are easy to interpret.The output of GEMAM is a pictogram that can provide both qualitative and quantitative information based on color and number.

Psychiatric comorbidity is common in symptom-based diagnoses like autism spectrum disorder (ASD), attention/deficit hyper-activity disorder (ADHD), and obsessive-compulsive disorder (OCD). However, these co-occurring symptoms mediated by shared and/or distinct neural mechanisms are difficult to profile at the individual level. Capitalizing on unsupervised machine learning with a hierarchical Bayesian framework, we derived latent disease factors from resting-state functional connectivity data in a hybrid cohort of ASD and ADHD and delineated individual associations with dimensional symptoms based on canonical correlation analysis. Models based on the same factors generalized to previously unseen individuals in a subclinical cohort and one local OCD database with a subset of patients undergoing neurosurgical intervention. Four factors, identified as variably co-expressed in each patient, were significantly correlated with distinct symptom domains (r = -0.26-0.53, P < 0.05): behavioral regulation (Factor-1), communication (Factor-2), anxiety (Factor-3), adaptive behaviors (Factor-4). Moreover, we demonstrated Factor-1 expressed in patients with OCD and Factor-3 expressed in participants with anxiety, at the degree to which factor expression was significantly predictive of individual symptom scores (r = 0.18-0.5, P < 0.01). Importantly, peri-intervention changes in Factor-1 of OCD were associated with variable treatment outcomes (r = 0.39, P < 0.05). Our results indicate that these data-derived latent disease factors quantify individual factor expression to inform dimensional symptom and treatment outcomes across cohorts, which may promote quantitative psychiatric diagnosis and personalized intervention.
Humans ; Male ; Female ; Attention Deficit Disorder with Hyperactivity ; Obsessive-Compulsive Disorder ; Adult ; Autism Spectrum Disorder ; Bayes Theorem ; Adolescent ; Young Adult ; Magnetic Resonance Imaging ; Middle Aged ; Child ; Brain/metabolism* ; Cohort Studies ; Comorbidity

Green analytical chemistry (GAC) focuses on mitigating the adverse effects of analytical activities on human safety, human health, and environment. In addition to the 12 principles of GAC, proper GAC tools should be developed and employed to assess the greenness of different analytical assays. The 15 widely used GAC metrics, i.e., national environmental methods index (NEMI), advanced NEMI, assessment of green profile (AGP), chloroform-oriented toxicity estimation scale (ChlorTox Scale), Analytical Eco-Scale, Green Certificate Modified Eco-Scale, analytical method greenness score (AMGS), green analytical procedure index (GAPI), ComplexGAPI, red-green-blue (RGB) additive color model, RGB 12 algorithm, analytical greenness calculator (AGREE), AGREE preparation (AGREEprep), HEXAGON, and blue applicability grade index (BAGI), are selected as the typical tools. This article comprehensively presents and elucidates the principles, characteristics, merits, and demerits of 15 widely used GAC tools. This review is helpful for researchers to use the current GAC metrics to assess the environmental sustainability of analytical assays.

Objective To construct and apply an intelligent follow-up information system for patients with cancer pain,providing references for improving the efficiency of hospital follow-up and promoting pain management of patients at home.Methods The intelligent discharge follow-up system for patients with cancer pain includes 2 platforms,namely a patient self-report platform and an administrator operation platform.The administrator operation platform consists of 5 modules,namely the workbench module,the follow-up plan module,the follow-up results module,the health education module and the data statistics module.In January 2022,the system was officially put into clinical application.The use of the system was analyzed,and patients'completion rate,medication compliance,incidence of moderate and severe pain and satisfaction with pain control were compared before(from January 2020 to December 2021)and after(from January 2022 to November 2023)the application of the system.Results At present,this system has been applied in 95 cancer-related wards of our hospital.From January 2022 to November 2023,the number of people who should be followed up was 4 248,and the number of people who actually completed the follow-up was 4 127;the rate of follow-up completion was 97.2%;the rate of timely completion of the follow-up was 94.9%;the rate of automatic follow-up by the system was 40.1%;the rate of patient abnormality report was 31.9%;the rate of timely treatment of patient abnormality report was 89.1%.After the application of the system,the completion rate of pain follow-up was increased,and the difference was statistically significant(P<0.001).After the application of the system,the medication compliance rate of patients with cancer pain increased from 86.9%to 91.0%;the incidence of moderate and severe pain decreased from 6.8%to 5.2%;the satisfaction with pain control increased from 81.0%to 83.5%(P<0.05).Conclusion The intelligent discharge follow-up system for patients with cancer pain can effectively improve the discharge follow-up efficiency and promote the management of patients with cancer pain at home.

To summarize the nursing experience of a patient with multiple enterostomies after segmental small bowel resection for acute mesenteric vein embolism.Nursing points:early identification of necrosis of retained intestinal tubes and improvement of early warning care;active improvement of tissue perfusion for retained indeterminate necrotic intestinal tubes;relay enteral nutritional support for 4 stomas based on the collaborative care model;implementation of combined dressing changes for surgical incisions and stomas,control of incisional infections and peristoma dermatitis;attention to the psychological aspects of the patients and their families and provision of psychological support.The patient successfully underwent stoma retraction on the 42nd day after surgery,and no obvious short bowel syndrome occurred in the postoperative period.

To summarize the nursing experience of a patient with median arcuate ligament compression syndrome.Nursing points:to implement effective measures to relieve local compression and improve gastrointestinal symptoms;to establish a monitoring and evaluation plan focusing on abdominal pain to prevent serious adverse vascular events;to implement pre-rehabilitation care with psychological and nutritional support to reduce surgical risks;to actively provide postoperative gastroparesis care and discharge follow-up care.The patient was discharged from the hospital 22 days after surgery and was followed up for 6 months.His weight increased and his quality of life was high.

Green analytical chemistry(GAC)focuses on mitigating the adverse effects of analytical activities on human safety,human health,and environment.In addition to the 12 principles of GAC,proper GAC tools should be developed and employed to assess the greenness of different analytical assays.The 15 widely used GAC metrics,i.e.,national environmental methods index(NEMI),advanced NEMI,assessment of green profile(AGP),chloroform-oriented toxicity estimation scale(ChlorTox Scale),Analytical Eco-Scale,Green Certificate Modified Eco-Scale,analytical method greenness score(AMGS),green analytical pro-cedure index(GAPI),ComplexGAPI,red-green-blue(RGB)additive color model,RGB 12 algorithm,analytical greenness calculator(AGREE),AGREE preparation(AGREEprep),HEXAGON,and blue appli-cability grade index(BAGI),are selected as the typical tools.This article comprehensively presents and elucidates the principles,characteristics,merits,and demerits of 15 widely used GAC tools.This review is helpful for researchers to use the current GAC metrics to assess the environmental sustainability of analytical assays.

This paper provided a comprehensive review of the concept, current situation and influencing factors of survivors returning to work after hematopoietic stem cell transplantation, both in domestic and international contexts. The research analyzed and elaborates on four aspects of individual factors, disease-related factors, occupational factors, and social support, in order to provide references for constructing an intervention program for the return to work of hematopoietic stem cell transplantation survivors based on the cultural background in China.

BACKGROUND:Inflammation,oxidative stress and bacterial infection are the main causes of delayed wound healing in diabetes.In recent years,various inorganic nanomaterials have been widely used in the treatment of skin wound healing due to their antibacterial activities,but their effects on anti-oxidation and anti-inflammation are limited. OBJECTIVE:To investigate the effect of Prussian blue nanoparticles on the wound repair of diabetes in terms of antioxidant,anti-inflammatory and photothermal antibacterial activities. METHODS:Prussian blue nanoparticles were prepared and characterized.(1)In vitro:The biocompatibility of Prussian blue nanoparticles with different concentrations was detected by MTT assay.The cytoprotective effect of Prussian blue nanoparticles and the intracellular reactive oxidative species level were examined under the condition of hydrogen peroxide.The ability of Prussian blue nanoparticles to decompose hydrogen peroxide and superoxide anion radicals was tested;the effect of Prussian blue nanoparticles on lipopolysaccharide-induced macrophage inflammation was investigated.The photothermal antibacterial activity of Prussian blue nanoparticles was detected by the plate colony counting method.(2)In vivo:ICR mice were intraperitoneally injected with streptozotocin to establish a diabetes mouse model.After the model was successfully established,a 6 mm wound was created on the back with a hole punch.There were the control group(no treatment),the Prussian blue group and the Prussian blue with light group.The wound healing and histomorphological changes were observed. RESULTS AND CONCLUSION:(1)In vitro:Prussian blue nanoparticles in 25-200 μg/mL were non-toxic to cells.Prussian blue nanoparticles had the extremely strong antioxidant capacity and mitigated the intracellular reactive oxidative species at a high oxidative stress environment,resulting in a pronounced cytoprotective effect.The Prussian blue nanoparticles not only exhibited hydrogen peroxide degradation activity but also showed strong superoxide scavenging ability.Prussian blue nanoparticles also displayed significant anti-inflammatory activity and extremely strong antibacterial ability after light irradiation.(2)In vivo:After 14 days,the wound sizes of the Prussian blue group and Prussian blue with light group were significantly reduced,and the healing speed of Prussian blue with light group was the fastest.Hematoxylin-eosin and Masson staining showed a lot of granulation tissue formation and collagen deposition in the Prussian blue group and the Prussian blue with light group,of which the Prussian blue with light group was the most.Immunofluorescence staining displayed that,compared with the control group,the expressions of α-SMA and CD31 were increased significantly in Prussian blue group and Prussian blue with light group(P<0.05),but F4/80 expression was decreased significantly in Prussian blue group and Prussian blue with light group(P<0.05),indicating more obvious improvement in the Prussian blue with light group.(3)These results showed that Prussian blue nanoparticles could promote the skin wound healing of the diabetes mouse model by exerting anti-inflammatory,antioxidant and antibacterial effects.