With the rapid development of artificial intelligence, computational pathology has been seamlessly integrated into the entire clinical workflow, which encompasses diagnosis, treatment, prognosis, and biomarker discovery. This integration has significantly enhanced clinical accuracy and efficiency while reducing the workload for clinicians. Traditionally, research in this field has depended on the collection and labeling of large datasets for specific tasks, followed by the development of task-specific computational pathology models. However, this approach is labor intensive and does not scale efficiently for open-set identification or rare diseases. Given the diversity of clinical tasks, training individual models from scratch to address the whole spectrum of clinical tasks in the pathology workflow is impractical, which highlights the urgent need to transition from task-specific models to foundation models (FMs). In recent years, pathological FMs have proliferated. These FMs can be classified into three categories, namely, pathology image FMs, pathology image-text FMs, and pathology image-gene FMs, each of which results in distinct functionalities and application scenarios. This review provides an overview of the latest research advancements in pathological FMs, with a particular emphasis on their applications in oncology. The key challenges and opportunities presented by pathological FMs in precision oncology are also explored.
Humans ; Precision Medicine/methods* ; Medical Oncology/methods* ; Artificial Intelligence ; Neoplasms/pathology* ; Computational Biology/methods*

Objective To systematically retrieve,evaluate and summarize the related evidences of plate-let implantation delayed management in the patients with allogeneic hematopoietic stem cell transplantation.Methods According to the"6S"model,the clinical decision systems,guidelines network,professional associa-tion websites and databases were retrieved to collect the evidences regarding the platelet implantation delayed management in the patients with allogeneic hematopoietic stem cell transplantation,the retrieval time limit was from the database establishment to May 2024.Two researchers independently conducted the quality eval-uation of the literatures,evidence extraction and evidence integration.Results A total of 17 articles were fi-nally included,including 1 guideline,2 clinical decisions,3 systematic reviews,5 expert consensus and 6 ran-domized controlled trials.A total of 24 pieces of evidences were summarized in 5 aspects,including the pre-transplantation evaluation and prevention,application of mesenchymal stem cells,thrombopoietic drugs man-agement,blood transfusion support and complication management such as bleeding.Conclusion The medical and care staffs should carry out the best evidence practice for platelet implantation delayed management in the patients with allogeneic hematopoietic stem cell transplantation by combining with the domestic clinical situa-tion to reduce the hemorrhage in multiple organ systems after transplantation and improve the survival quality.

ObjectiveTo observe the effect of gene mutation on the effectiveness of arsenic-containing Chinese herbal compound formulas in the treatment of myelodysplastic syndromes （MDS） of different traditional Chinese medicine （TCM） patterns， so as to provide the basis for the clinical application. MethodsClinical data of 442 MDS patients who were treated with arsenic-containing herbal compound formulas were retrospectively collected， including the baseline demographic and clinical characteristics of the patients. Based on the TCM four examinations， the patients were divided into the spleen-kidney deficiency group as well as the qi-yin deficiency group， and according to the results of the next-generation sequencing （NGS） test， they were divided into the group with and without gene mutation respectively. The influence of gene mutation on the clinical effectiveness of patients with different TCM patterns was analyzed， the baseline demographic and clinical characteristics of the patients with different outcomes of the two TCM patterns were compared， and multivariate Logistic regression analysis was conducted on the influencing factors of the effective rate of MDS patients with gene mutation. ResultsA total of 190 cases were included in the spleen-kidney deficiency group （119 cases with gene mutation） and 43 cases in the qi-yin deficiency group （23 cases with gene mutation）. No statistically significant differences were noted in effectiveness assessment， total effective rate， and total response rate between the spleen-kidney deficiency group and the qi-yin deficiency group （P＞0.05）. In the spleen-kidney deficiency group， the total effective rate of MDS with gene mutation was 65.55% （78/119）， which was lower than 80.28% （57/71） of MDS without gene mutation， with statistical significance （P = 0.033）， while no statistical differences in effectiveness assessment and total response rate were noted （P＞0.05）. In the qi-yin deficiency group， no statistical differences were observed in effectiveness assessment， total effective rate， and total response rate of the patients in with or without gene mutation （P＞0.05）. In the spleen-kidney deficiency group with gene mutation， the rate of complex karyotype （P = 0.031） and the mutation rate of CBL gene （P = 0.032） in the ineffective population were higher than those in the effective population， while the mutation rate of DDX41 gene in the effective population was higher than that in the ineffective population （P = 0.033）. No statistically significant differences were found in other gene mutations， age， gender distribution， number of gene mutations， bone marrow hyperplasia degree， blast cell range， reticular fiber tissue proliferation or not， and prognosis of chromosomal abnormalities between the effective and ineffective populations （P＞0.05）. In the qi-yin deficiency group with gene mutation， no statistically significant differences were found in various items between populations with different outcomes （P＞0.05）. Multivariate Logistic regression analysis showed that complex karyotype， CBL mutation， and DDX41 mutation were independently associated with the effective rate of MDS with spleen-kidney deficiency and gene mutation （P＜0.05）. DDX41 mutation was an independent protective factor in the spleen-kidney deficiency group （OR＞1）， while complex karyotype and CBL mutation were independent risk factors （OR＜1）. ConclusionThe arsenic-containing TCM compound formulas exhibited better effectiveness in MDS with spleen-kidney deficiency pattern without mutation； and in MDS with spleen-kidney deficiency pattern without complex karyotypes， CBL mutation， and with DDX41 mutations. Furthermore， DDX41 mutation was an independent protective factor in the spleen-kidney deficiency group， while complex karyotype and CBL mutation were independent risk factors. In MDS with qi-yin deficiency pattern， gene mutation-related factors showed no significant impact on the effectiveness of arsenic-containing TCM compound formulas.

Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1％of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9％)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5％)was lower than that in inpatient children(31.5％).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1％)than in inpatient children(59.4％).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14％,11.7％,47.8％in outpatients,but 24.2％,20.6％,and 52.8％in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.

Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)％.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0％vs 29.5％).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7％vs 7.8％,0.8％vs 0.1％,both P＜0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)％with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9％and 1.8％,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1％).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10％.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P＜0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.

Objective:To explore the effectiveness of nursing based on the Roy model in patients with Guillain-Barre syndrome (GBS) .Methods:Convenience sampling was used to select 55 patients with GBS at the First People's Hospital of Shangqiu between January 2020 and May 2024 as study subjects. Patients were divided into an intervention group ( n=28) and a control group ( n=27). Control group received conventional nursing, while intervention group received nursing based on Roy adaptation model. The recovery time, psychological state, and social support of the two groups of patients were compared. Results:Intervention group demonstrated shorter recovery times, lower anxiety and depression scores, and higher Social Support Rating Scale scores compared to control group, with all differences being statistically significant ( P<0.05) . Conclusions:The Roy model nursing in this study of GBS patients, effectively improves recovery outcomes, psychological state, and social support among GBS patients through comprehensive assessment, personalized nursing intervention, and ongoing evaluation.

Objective To explore the value of the Transformer model based on multi-sequence MRI to predict isocitrate dehydrogenase(IDH)mutation status in patients with glioma.Methods The multi-sequence MRI data of 500 glioma patients(103 mutation-type and 397 wild-type)were analyzed retrospectively from the publicly available dataset Cancer Imaging Archive.The prediction model was constructed through the Transformer deep learning algorithm.Area under the curve(AUC)of the receiver operating characteristic(ROC)curve was used to evaluate the predictive performance,and the five-fold crossover was used for validation of the predictive model.Results The clinical,multi-sequence MRI,and combined clinical+multi-sequence MRI models based on the Transformer deep learning algorithm could be used to predict the IDH mutation status of patients with glioma,and the combined clinical+multi-sequence MRI model had the highest diagnostic efficacy compared with the former two,with an AUC of 0.904[95％confidence interval(CI)0.875-0.928],and the sensitivity and specificity of 86.41％and 86.40％,respectively.DeLong's test showed that the difference in AUC between the combined clinical+multi-sequence MRI model and the clinical model was statistically significant(Z=3.327,P＜0.001).Conclusion The Transformer model based on multi-sequence MRI can effectively identify patients with IDH mutation-type glioma and IDH wild-type glioma.

Objective:To explore the effectiveness of nursing based on the Roy model in patients with Guillain-Barre syndrome (GBS) .Methods:Convenience sampling was used to select 55 patients with GBS at the First People's Hospital of Shangqiu between January 2020 and May 2024 as study subjects. Patients were divided into an intervention group ( n=28) and a control group ( n=27). Control group received conventional nursing, while intervention group received nursing based on Roy adaptation model. The recovery time, psychological state, and social support of the two groups of patients were compared. Results:Intervention group demonstrated shorter recovery times, lower anxiety and depression scores, and higher Social Support Rating Scale scores compared to control group, with all differences being statistically significant ( P<0.05) . Conclusions:The Roy model nursing in this study of GBS patients, effectively improves recovery outcomes, psychological state, and social support among GBS patients through comprehensive assessment, personalized nursing intervention, and ongoing evaluation.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.