Metagenomic next-generation sequencing, as an unbiased detection technology, demonstrates higher diagnostic efficacy than traditional methods. Gut microorganisms are important flora for safeguarding health and have become a hot research topic. Modeling and analyzing the genomic data of intestinal flora using machine learning is very important in disease prediction and diagnosis. This paper briefly introduces the characteristics of metagenomic next-generation sequencing, key algorithms and evaluation indexes of machine learning, outlines the main steps of combining machine learning with metagenomic next-generation sequencing, and summarizes the application of the combination of machine learning and metagenomic next-generation sequencing technology in the study of intestinal flora, which will provide a more accurate method for diagnosis and prediction of the related diseases, and give more ideas for the future research and clinical practice.

Knowledge graphs have been more popular in the medical industry in recent years due to the development of big data analysis technologies.Information reflecting a range of physiological markers of patients is gathered in laboratory medicine,which forms an essential basis for clinical decision-making.Knowledge graphs could uncover the hidden value in inspection and consequently furnish accurate inspection data.Knowledge graphs are currently used in laboratory medicine to forecast possible adverse drug responses,help with diagnosis,integrate historical trends of patient laboratory inspections,and identify correlations across detection projects.The interaction between inspection items,auxiliary diagnosis,and medication guidance are three angles from which the use of knowledge graphs in laboratory medicine is analyzed and evaluated.Further support the intelligent construction of clinical laboratory diagnosis,it is also suggested that the development of test medical knowledge graphs extend in the direction of semantic search,decision support,and intelligent question answer.

Knowledge graphs have been more popular in the medical industry in recent years due to the development of big data analysis technologies.Information reflecting a range of physiological markers of patients is gathered in laboratory medicine,which forms an essential basis for clinical decision-making.Knowledge graphs could uncover the hidden value in inspection and consequently furnish accurate inspection data.Knowledge graphs are currently used in laboratory medicine to forecast possible adverse drug responses,help with diagnosis,integrate historical trends of patient laboratory inspections,and identify correlations across detection projects.The interaction between inspection items,auxiliary diagnosis,and medication guidance are three angles from which the use of knowledge graphs in laboratory medicine is analyzed and evaluated.Further support the intelligent construction of clinical laboratory diagnosis,it is also suggested that the development of test medical knowledge graphs extend in the direction of semantic search,decision support,and intelligent question answer.

Metagenomic next-generation sequencing, as an unbiased detection technology, demonstrates higher diagnostic efficacy than traditional methods. Gut microorganisms are important flora for safeguarding health and have become a hot research topic. Modeling and analyzing the genomic data of intestinal flora using machine learning is very important in disease prediction and diagnosis. This paper briefly introduces the characteristics of metagenomic next-generation sequencing, key algorithms and evaluation indexes of machine learning, outlines the main steps of combining machine learning with metagenomic next-generation sequencing, and summarizes the application of the combination of machine learning and metagenomic next-generation sequencing technology in the study of intestinal flora, which will provide a more accurate method for diagnosis and prediction of the related diseases, and give more ideas for the future research and clinical practice.

ObjectiveTo observe the effect and mechanism of curcumin on cognitive function in the mouse model of low oxygen-induced chronic nerve injury. MethodEighty male C57BL/6 mice were randomized into eight groups： control， low-， medium-， and high-dose （100， 200， and 300 mg·kg^-1， respectively） curcumin， model， model + low-dose curcumin， model + medium-dose curcumin， and model + high-dose curcumin groups （n=10）. The mouse model of low oxygen-induced nerve injury was prepared by continuous stimulation with simulated oxygen concentration at Lhasa altitude （13% O₂ at about 3 700 m） for 14 days. After the completion of modeling， mice in the six curcumin groups were administrated with curcumin at corresponding doses by gavage， while those in the control group and the model group were administrated with the same amount of normal saline once a day for one week. After that， open field， novel object recognition， and Morris water maze tests were carried out to reveal the behavioral changes of mice. The morphological changes of the hippocampus were observed by hematoxylin-eosin staining. The mRNA levels of interleukin （IL）-6 and tumor necrosis factor （TNF）-α in the hippocampus and peripheral blood of mice were determined by real-time PCR. The activation of microglia in the hippocampus was observed by Iba-1 staining. The protein levels of brain-derived neurotrophic factor （BDNF） and cAMP-response element-binding protein （CREB） in the hippocampus were determined by Western blot. ResultCompared with the control group， the model group showed decreased new object recognition rate （P<0.01）， extended time to find the platform （P<0.01）， and reduced platform crossings （P<0.05）， which proved that the cognitive function of mice was impaired. Compared with model group， the model + medium-dose curcumin group showed increased new object recognition rate， shortened time to find the platform， and increased platform crossings （P<0.05，P<0.01）. Moreover， the application of curcumin repaired the abnormal morphological and structural changes in the hippocampus， reduced the inflammatory cytokine levels and activation of microglia， and upregulated the expression of CREB and BDNF （P<0.05）. ConclusionCurcumin demonstrates a therapeutic effect on low oxygen-induced cognitive decline， which provide a potential cure for treating chronic brain injury induced by high-altitude low oxygen in clinical practice.

Objective To study the effect of MT-1207 on blood glucose,blood lipids and atherosclerosis in mice.Methods The apolipoprotein E knockout(ApoE-/-)mice were fed with normal feed,drug feed containing losartan and drug feed containing MT-1207 at a dosage of 30 mg/kg.The body weight,blood glucose and blood lipids were detected,and the plaque area of atherosclerotic was evaluated.8-week-old male C57 mice were fed a high fat diet and given intragastric administration of MT-1207 and losartan at a dose of 30 mg/kg per day.The body weight,blood glucose and lipids levels were also examined to further evaluate the effects of MT-1207 on blood glucose and lipids levels.Results ApoE-/-mice treated with MT-1207 and losartan gained weight faster.There was no significant improvement in blood glucose and lipid levels,and no significant change in atherosclerotic plaque area.MT-1207 and losartan had no significant improvement effect on blood glucose and blood lipids of C57 mice.Conclusion MT-1207 and losartan couldn't improve the levels of blood glucose,blood lipids and atherosclerosis,and couldn't aggravate atherosclerosis.

Osteosarcoma is a common primary malignant bone tumor in adolescents and children,characterized by a high recurrence rate and metastasis,making its treatment extremely challenging.Traditional treatment modalities,including surgery,radiation therapy,and chemotherapy,can alleviate symptoms to some extent,but improving long-term survival rates remains a pressing issue.With the continuous development of immunotherapy,breakthroughs have been made in the research of tumor immune microenvironment and the application of immunotherapy in recent years,providing new perspectives and strategies for osteosarcoma treatment.Currently,immunotherapy strategies include tumor vaccines,targeted cytokines,immune checkpoint inhibition,adoptive cell therapy,combination therapy,etc.,significantly enhancing patient immune responses from the aspects of boosting immunity,overcoming immune tolerance,and preventing immune evasion,thereby effectively improving the patients'survival rates and prognosis.This review aims to systematically introduce the immune microenvironment of osteosarcoma and discuss the latest advances in immunotherapy in clinical translational research of osteosarcoma.By deeply understanding the immune characteristics of osteosarcoma and corresponding treatment methods,it is hopeful to provide more effective strategies for personalized treatment,contributing to the improvement of the patients' survival rates and prognosis.

Objective:To investigate the status quo and influencing factors of knowledge,attitude and behavior of hospice care among medical staff in medical and nursing institutions in Liaoning Province,so as to provide a theoretical reference for further proposing the promotion strategy of hospice care services in medical and nursing institutions in Liaoning Province.Methods:The knowledge,attitude and behavior questionnaire of hospice care designed by Pan Qini et al.was used to investigate the knowledge,attitude and behavior status quo of 153 medical staff in the medical and nursing institutions in Liaoning Province by convenient sampling method.Multiple linear regression analysis was used to analyze the influencing factors of knowledge,attitude and behavior of hospice care among medical staff.Results:The total score of knowledge,attitude and behavior of hospice care of medical staff in medical and nursing institutions was(78.93±15.45),the score of knowledge dimension was(0.42±1.58),the score of attitude dimension was(33.67±8.10),and the score of behavior dimension was(44.84±10.25).There were differences in the scores of knowledge,attitude and behavior in the different nature of medical and nursing institutions,whether they had religious beliefs,the experience of caring for seriously ill relatives,the number of end-stage patients treated/cared for in the past year,the satisfaction with the intensity of work,the support of family members for hospice care,the emotional impact of engaging in hospice care,whether they were willing to stay and continue to engage in hospice care.Whether they had religious beliefs and the number of end-stage patients treated/cared for in the past year were the main influencing factors of the knowledge,attitude and behavior level of hospice care among medical staff(P＜0.05).Conclusions:The knowledge,attitude and behavior of hospice care among medical staff in medical and nursing institutions in Liaoning Province are at a medium level,and the levels of knowledge,attitude,and behavior need to be further improved.The management personnel of medical and nursing institutions should actively supervise and urge the development of targeted professional training,and strengthen the concept of hospice care of medical staff,so as to comprehensively improve the service level of hospice care of medical staff.

Tumor metastasis is responsible for most mortality in cancer patients, and remains a challenge in clinical cancer treatment. Platelets can be recruited and activated by tumor cells, then adhere to circulating tumor cells (CTCs) and assist tumor cells extravasate in distant organs. Therefore, nanoparticles specially hitchhiking on activated platelets are considered to have excellent targeting ability for primary tumor, CTCs and metastasis in distant organs. However, the activated tumor-homing platelets will release transforming growth factor-β (TGF-β), which promotes tumor metastasis and forms immunosuppressive microenvironment. Therefore, a multitalent strategy is needed to balance the accurate tumor tracking and alleviate the immunosuppressive signals. In this study, a fucoidan-functionalized micelle (FD/DOX) was constructed, which could efficiently adhere to activated platelets through P-selectin. Compared with the micelle without P-selectin targeting effect, FD/DOX had increased distribution in both tumor tissue and metastasis niche, and exhibited excellent anti-tumor and anti-metastasis efficacy on 4T1 spontaneous metastasis model. In addition, due to the contribution of fucoidan, FD/DOX treatment was confirmed to inhibit the expression of TGF-β, thereby stimulating anti-tumor immune response and reversing the immunosuppressive microenvironment. The fucoidan-functionalized activated platelets-hitchhiking micelle was promising for the metastatic cancer treatment.

【Objective】 This paper screened the factors that may influence the spatial differentiation of Neutrophil-to-lymphocyte ratio （NLR） reference values in healthy adults in China and explored the trend of NLR reference values in China. 【Methods】 For this research， we collected the NLR of 162 681 healthy adults from 62 cities in China. Spearman regression analysis was used to analyze the correlation between NLR and 25 geography secondary indexes. We extracted 9 indexes with significant correlation， built a random forest （RF） model， and predicted the country’s urban healthy adults’ NLR reference value. By using the disjunctive Kriging method， we obtained the geographical distribution of NLR reference value of healthy adults in China. 【Results】 The reference value of NLR of healthy adults in China was significantly correlated with the 9 secondary indexes， namely， altitude， sunshine duration， annual average temperature， annual average relative humidity， annual temperature range， annual average wind speed， content of organic matter in topsoil， cation exchange capacity in topsoil （clay）， and total amount of CaSO4 in soil. The geographical distribution of NLR values of healthy adults in China showed a trend of being higher in Southeast China and lower in Northwest China， higher in coastal areas and lower in inland areas. 【Conclusion】 This study lays a foundation for further research on the mechanism of different influencing factors on the reference value of NLR index. A random forest model composed of significant influencing factors has been established to provide the basis for formulating reference criteria for the prognostic factors of the novel coronavirus using NLR reference values in different regions.