Objective:To investigates the efficacy and safety of allogeneic hematopoietic stem cell transplantation(allo-HSCT)in treating older patients(≥60 years old)with hematologic malignancies.Methods:We conducted a retrospective study involving 67 patients aged 60 years and above, diagnosed with malignant hematological diseases, who received allo-HSCT at the Clinical Research Centrer for Haematologic Diseases of the First Affiliated Hospital of Soochow University between June 2015 and March 2023.We collected pre-transplant data, including the patients' age, gender, pre-transplantation disease risk stratification, disease status, and the haematopoietic cell transplantation comorbidity index(HCT-CI). We retrospectively analyzed clinical data regarding treatment-related toxicity, infections, acute and chronic graft-versus-host disease(a/cGVHD), as well as recurrent and non-recurrent deaths, to estimate the overall survival(OS)rate and event-free survival (EFS)rate.Results:Sixty-seven patients were included in the study, comprising 55 males(82.1%)and 12 females(17.9%), with a median age of 63(61, 65) years .The cohort consisted of 42 cases of acute myeloid leukaemia, 22 cases of myelodysplastic syndromes, and 3 cases of acute lymphoblastic leukaemia.The Kaplan-Meier analysis showed that the 1-year OS and EFS rates were 62.9% and 59.2%, respectively, while the 2-year OS and EFS rates were 55.3% and 51.8%, respectively.The cumulative incidence of 1-year non-relapse mortality and relapse was 25.4% and 21.2%, respectively.A total of 13 patients developed grade Ⅱ-Ⅳ aGVHD, with a 1-year cumulative incidence of 22.0%, and 7 patients developed cGVHD requiring treatment.When stratified by age group, the OS rate was higher in patients aged 60~64 years compared to those aged ≥65 years; however, this difference was not statistically significant(Log-rank χ2=0.99, P=0.317). In contrast, when stratified by disease load, the OS rate was significantly higher in the complete remission(CR)group than in the non-CR group, with a statistically significant difference(Log-rank χ2=15.04, P<0.001). When stratified by donor type, the OS rate was higher in the human leukocyte antigens (HLA) allogeneic group compared to the haploinsufficiency group; however, the difference was not statistically significant(Log-rank χ2=2.71, P=0.100). Twenty-seven patients died at an average of 125 days (range 3-1 054 days) after HSCT.The causes of death included leukemia recurrence in 9 cases (33.3%), infection in 8 cases (29.6%), GVHD in 5 cases (18.5%), poor implantation in 3 cases (11.1%), multi-organ failure in 1 case (3.7%), and cerebrovascular accident in 1 case (3.7%). The results of multifactorial analysis indicated that a pre-transplant tumor load greater than 5% was an independent risk factor for OS after transplantation ( HR=4.59, 95% CI: 2.01-10.42, P<0.001)as well as for disease recurrence ( OR=13.11, 95% CI: 1.96-87.87, P=0.008). Additionally, the occurrence of infection was identified as an independent risk factor for non-recurrent death after transplantation( OR=3.95, 95% CI: 1.13 to 13.71, P=0.031). Conclusions:For patients aged 60 years or older with hematologic malignancies, HSCT can serve as a viable treatment option, particularly for those with refractory recurrence and high cytogenetic risk, as it has the potential to significantly enhance prognosis and increase both EFS and OS rates.

Objective:To develop CNN-Dinov2, a deep learning-based automatic classification model for Gram-stained images, enabling rapid diagnosis of three prevalent Gram-negative bacilli in bloodstream infections: Escherichia coli ( E.coli), Klebsiella pneumoniae ( K.pneumoniae), and Pseudomonas aeruginosa ( P.aeruginosa). Methods:This evaluation study analyzed 1 425 Gram-stained microscopic images from patients with bloodstream infections at Houjie Hospital, in Dongguan City, collected between January 2023 and January 2024. The images, all positive for blood culture and identified as target strains, were categorized into Escherichia coli (419 images), Klebsiella pneumoniae (411 images), Pseudomonas aeruginosa (413 images), and other Gram-negative bacilli (182 images). They were randomly split into a training set (1 141 images), a validation set (141 images), and a test set (143 images) in an 8∶1∶1 ratio. A hybrid CNN-Dinov2 model was developed by integrating ResNet′s local feature extraction with Dinov2′s global pre-trained features, followed by a fully connected layer. The model was optimized by inputting the preprocessed images and adjusting parameters through loss calculation and backpropagation. AlexNet, Dinov2, and ResNet18 served as control models. The models′ classification performance was assessed using accuracy, precision, weighted F1 score, and recall rate, derived from the confusion matrix. The PR curve and AP value further evaluated each model′s classification capability across the four image categories. Results:The CNN-Dinov2 model achieved a training accuracy of 99.74%, a validation accuracy of 98.12%, and a validation loss of 0.070 6, demonstrating robust generalization without overfitting. Validation metrics revealed superior performance with an accuracy of 98.60%, precision of 98.65%, a weighted F1 score of 98.60%, and a recall rate of 98.60%, outperforming other models. The confusion matrix confirmed its strong classification capability, with the highest sum of diagonal values for identifying four types of bacteria. The macro average precision (AP) values under the precision-recall (PR) curves were all 1, indicating excellent discrimination across all categories. Overall, the CNN-Dinov2 model exhibited the best performance among the four models evaluated.Conclusion:This study successfully developed CNN-Dinov2, an automated classification model for Gram staining images. It offers valuable support for the rapid diagnosis of bloodstream infections caused by Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, demonstrating practical utility.

Bone metastasis,as a common terminal event in patients with advanced malignant tumors,significantly impacts patients'quality of life and survival prognosis,posing a major clinical challenge in the field of oncology.With the deepening understanding of tumor biology,the treatment paradigm for bone metastasis has progressively shifted from traditional palliative care to precise targeted interventions.Currently,clinical treatment strategies have demonstrated diversified development,with various therapeutic approaches-including radiotherapy,immunotherapy,bone-modifying agents,and small-molecule targeted drugs—achieving notable clinical progress.However,existing treatment regimens still face challenges such as significant interindividual variability in efficacy,frequent drug resistance,and prominent adverse effects.This article systematically reviews the latest advances in precision therapy for bone metastasis,provides an in-depth analysis of the strengths and limitations of different treatment strategies,and offers perspectives on future research directions and therapeutic prospects,aiming to provide reference for optimizing clinical practice and promoting translational research.

Bone metastasis,as a common terminal event in patients with advanced malignant tumors,significantly impacts patients'quality of life and survival prognosis,posing a major clinical challenge in the field of oncology.With the deepening understanding of tumor biology,the treatment paradigm for bone metastasis has progressively shifted from traditional palliative care to precise targeted interventions.Currently,clinical treatment strategies have demonstrated diversified development,with various therapeutic approaches-including radiotherapy,immunotherapy,bone-modifying agents,and small-molecule targeted drugs—achieving notable clinical progress.However,existing treatment regimens still face challenges such as significant interindividual variability in efficacy,frequent drug resistance,and prominent adverse effects.This article systematically reviews the latest advances in precision therapy for bone metastasis,provides an in-depth analysis of the strengths and limitations of different treatment strategies,and offers perspectives on future research directions and therapeutic prospects,aiming to provide reference for optimizing clinical practice and promoting translational research.

Objective:To investigates the efficacy and safety of allogeneic hematopoietic stem cell transplantation(allo-HSCT)in treating older patients(≥60 years old)with hematologic malignancies.Methods:We conducted a retrospective study involving 67 patients aged 60 years and above, diagnosed with malignant hematological diseases, who received allo-HSCT at the Clinical Research Centrer for Haematologic Diseases of the First Affiliated Hospital of Soochow University between June 2015 and March 2023.We collected pre-transplant data, including the patients' age, gender, pre-transplantation disease risk stratification, disease status, and the haematopoietic cell transplantation comorbidity index(HCT-CI). We retrospectively analyzed clinical data regarding treatment-related toxicity, infections, acute and chronic graft-versus-host disease(a/cGVHD), as well as recurrent and non-recurrent deaths, to estimate the overall survival(OS)rate and event-free survival (EFS)rate.Results:Sixty-seven patients were included in the study, comprising 55 males(82.1%)and 12 females(17.9%), with a median age of 63(61, 65) years .The cohort consisted of 42 cases of acute myeloid leukaemia, 22 cases of myelodysplastic syndromes, and 3 cases of acute lymphoblastic leukaemia.The Kaplan-Meier analysis showed that the 1-year OS and EFS rates were 62.9% and 59.2%, respectively, while the 2-year OS and EFS rates were 55.3% and 51.8%, respectively.The cumulative incidence of 1-year non-relapse mortality and relapse was 25.4% and 21.2%, respectively.A total of 13 patients developed grade Ⅱ-Ⅳ aGVHD, with a 1-year cumulative incidence of 22.0%, and 7 patients developed cGVHD requiring treatment.When stratified by age group, the OS rate was higher in patients aged 60~64 years compared to those aged ≥65 years; however, this difference was not statistically significant(Log-rank χ2=0.99, P=0.317). In contrast, when stratified by disease load, the OS rate was significantly higher in the complete remission(CR)group than in the non-CR group, with a statistically significant difference(Log-rank χ2=15.04, P<0.001). When stratified by donor type, the OS rate was higher in the human leukocyte antigens (HLA) allogeneic group compared to the haploinsufficiency group; however, the difference was not statistically significant(Log-rank χ2=2.71, P=0.100). Twenty-seven patients died at an average of 125 days (range 3-1 054 days) after HSCT.The causes of death included leukemia recurrence in 9 cases (33.3%), infection in 8 cases (29.6%), GVHD in 5 cases (18.5%), poor implantation in 3 cases (11.1%), multi-organ failure in 1 case (3.7%), and cerebrovascular accident in 1 case (3.7%). The results of multifactorial analysis indicated that a pre-transplant tumor load greater than 5% was an independent risk factor for OS after transplantation ( HR=4.59, 95% CI: 2.01-10.42, P<0.001)as well as for disease recurrence ( OR=13.11, 95% CI: 1.96-87.87, P=0.008). Additionally, the occurrence of infection was identified as an independent risk factor for non-recurrent death after transplantation( OR=3.95, 95% CI: 1.13 to 13.71, P=0.031). Conclusions:For patients aged 60 years or older with hematologic malignancies, HSCT can serve as a viable treatment option, particularly for those with refractory recurrence and high cytogenetic risk, as it has the potential to significantly enhance prognosis and increase both EFS and OS rates.

Objective:To develop CNN-Dinov2, a deep learning-based automatic classification model for Gram-stained images, enabling rapid diagnosis of three prevalent Gram-negative bacilli in bloodstream infections: Escherichia coli ( E.coli), Klebsiella pneumoniae ( K.pneumoniae), and Pseudomonas aeruginosa ( P.aeruginosa). Methods:This evaluation study analyzed 1 425 Gram-stained microscopic images from patients with bloodstream infections at Houjie Hospital, in Dongguan City, collected between January 2023 and January 2024. The images, all positive for blood culture and identified as target strains, were categorized into Escherichia coli (419 images), Klebsiella pneumoniae (411 images), Pseudomonas aeruginosa (413 images), and other Gram-negative bacilli (182 images). They were randomly split into a training set (1 141 images), a validation set (141 images), and a test set (143 images) in an 8∶1∶1 ratio. A hybrid CNN-Dinov2 model was developed by integrating ResNet′s local feature extraction with Dinov2′s global pre-trained features, followed by a fully connected layer. The model was optimized by inputting the preprocessed images and adjusting parameters through loss calculation and backpropagation. AlexNet, Dinov2, and ResNet18 served as control models. The models′ classification performance was assessed using accuracy, precision, weighted F1 score, and recall rate, derived from the confusion matrix. The PR curve and AP value further evaluated each model′s classification capability across the four image categories. Results:The CNN-Dinov2 model achieved a training accuracy of 99.74%, a validation accuracy of 98.12%, and a validation loss of 0.070 6, demonstrating robust generalization without overfitting. Validation metrics revealed superior performance with an accuracy of 98.60%, precision of 98.65%, a weighted F1 score of 98.60%, and a recall rate of 98.60%, outperforming other models. The confusion matrix confirmed its strong classification capability, with the highest sum of diagonal values for identifying four types of bacteria. The macro average precision (AP) values under the precision-recall (PR) curves were all 1, indicating excellent discrimination across all categories. Overall, the CNN-Dinov2 model exhibited the best performance among the four models evaluated.Conclusion:This study successfully developed CNN-Dinov2, an automated classification model for Gram staining images. It offers valuable support for the rapid diagnosis of bloodstream infections caused by Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, demonstrating practical utility.

Background: Twenty-four-hour urinary free cortisol (UFC) measurement is the initial diagnostic test for Cushing’s syndrome (CS). We compared UFC determination by both direct and extraction immunoassays using Abbott Architect, Siemens Atellica Solution, and Beckman DxI800 with liquid chromatography-tandem mass spectrometry (LC-MS/MS). In addition, we evaluated the value of 24-hr UFC measured by six methods for diagnosing CS. Methods: Residual 24-hr urine samples of 94 CS and 246 non-CS patients were collected.A laboratory-developed LC-MS/MS method was used as reference. UFC was measured by direct assays (D) using Abbott, Siemens, and Beckman platforms and by extraction assays (E) using Siemens and Beckman platforms. Method was compared using Passing–Bablok regression and Bland–Altman plot analyses. Cut-off values for the six assays and corresponding sensitivities and specificities were calculated by ROC analysis. Results: Abbott-D, Beckman-E, Siemens-E, and Siemens-D showed strong correlations with LC-MS/MS (Spearman coefficient r = 0.965, 0.922, 0.922, and 0.897, respectively), while Beckman-D showed weaker correlation (r = 0.755). All immunoassays showed proportionally positive bias. The areas under the curve were 0.975 for Abbott-D, 0.972 for LCMS/MS, 0.966 for Siemens-E, 0.948 for Siemens-D, 0.955 for Beckman-E, and 0.877 for Beckman-D. The cut-off values varied significantly (154.8–1,321.5 nmol/24 hrs). Assay sensitivity and specificity ranged from 76.1% to 93.2% and from 93.0% to 97.1%, respectively. Conclusions Commercially available immunoassays for measuring UFC show different levels of analytical consistency compared to LC-MS/MS. Abbott-D, Siemens-E, and Beckman-E have high diagnostic accuracy for CS.

The STAR tool was used to evaluate and analyze the science, transparency, and applicability of Chinese pathology guidelines and consensus published in medical journals in 2022. There were a total of 18 pathology guidelines and consensuses published in 2022, including 1 guideline and 17 consensuses. The results showed that the guideline score was 21.83 points, lower than the overall guideline average (43.4 points). Consensus ratings scored an average of 27.87 points, on par with the overall consensus level (28.3 points). Areas that scored above the overall level were "conflict of interest" and "working groups", while areas that scored below the overall level were "proposals", "funding", "evidence", "consensus approaches" and "accessibility". To sum up, the formulation of pathology guidelines and consensuses in 2022 is not standardized, and the evidence retrieval process, evidence evaluation methods and grading criteria for recommendations on clinical issues are not provided in the formulation process; the process and method for reaching consensus are not provided, the plan is lacking, and registration is not carried out. It is therefore suggested that guidelines/consensus makers in the field of pathology should attach importance to evidence-based medical evidence, strictly follow guideline formulation methods and processes, further improve the scientific, applicable and transparent guidelines/consensuses in the field, and better provide support for clinicians and patients.

Objective To investigate the mechanism by which lectin-like oxidized low density lipoprotein receptor-1(LOX-1)regulates hyperglycemic-induced myocardial fibroblast(CFs)fibrosis through the glycogen synthase kinase-3β(GSK-3β)/signal transducer and activator of transcription 3(STAT3)pathway.Methods CFs were isolated,cultured and identified.LOX-1 RNAi lentiviral vector was constructed and infected CFs.The experimental groups were as follows:Normal control(NC)group,High glucose(HG)group,LV-LOX-1,LV-Con group,Hypertonic(HPG)group.After LV-LOX-1 and LV-Con were infected with CFs,adding 25 mmol/L glucose to culture CFs for 24 h,they were denoted as HG+LV-LOX-1 group and HG+LV-Con group.Cells in HG+LV-LOX-1 group and HG+LV-Con group were treated with 10 μ mol/L SB216763 and 10 μ mol/L STATTIC for 24 h,respectively,and then they were recorded as HG+LV-LOX-1+SB216763 group,HG+LV-Con+SB216763 group,HG+LV-LOX-1+STATTIC group and HG+LV-Con+STATTIC group.CCK-8 was used to detect the activity of CFs,and the expression levels of mRAN and protein of LOX-1,collagen type I(COL-I),thioredoxin 5(TXNDC5),GSK-3β,STAT3,p-GSK-3β and p-STAT3 were detected by qRT-PCR and Western blot.Results CFs infected with LOX-1 RNAi lentiviral vector were obtained,which showed green under fluorescence microscopy.Compared with HG and HG+LV-Con groups,the mRNA expressions of LOX-1,COL-I and TXNDC5 were decreased in HG+LV-LOX-1 group(P<0.05).Compared with HG+LV-LOX-1 group,mRNA expressions of COL-I and TXNDC5 were decreased in HG+LV-LOX-1+SB216763 and HG+LV-LOX-1+STATTIC groups(P<0.05).Compared with HG and HG+LV-Con groups,p-GSK-3β protein expression was increased in HG+LV-LOX-1 group(P<0.05),while LOX-1,p-STAT3,COL-I,TXNDC5 protein expression was decreased in HG+LV-LOX-1 group(P<0.05).Compared with HG+LV-LOX-1 group,p-GSK-3β protein expression was increased in HG+LV-LOX-1+SB216763 group(P<0.05),while the protein expressions of p-STAT3,COL-I and TXNDC5 were decreased in HG+LV-LOX-1+SB216763 and HG+LV-LOX-1+STATTIC groups(P<0.05).Conclusion LOX-1,GSK-3β,STAT3,TXNDC5,and COL-I are involved in high glucose induced CFs fibrosis.LOX-1 promotes the expression of TXNDC5 and COL-I through GSK-3β/STAT3 pathway,and inhibition of LOX-1 can inhibit high glucose induced CFs fibrosis.

Objective To investigate the MRI characteristics of subventricular zone(SVZ)-associated isocitrate dehydrogenase(IDH)wild-type glioblastoma(GBM)and their correlations with Ki-67 expression and O6-methylguanine-DNA methyltransferase(MGMT)promoter methylation status.Methods A retrospective analysis was conducted on data of 78 patients with IDH wild-type GBM who underwent surgery and received pathological confirmation.Preoperative MRI contrast-enhanced T1 WI sequences were used to assess SVZ involvement,and postoperative molecular testing of tumor markers,including Ki-67 expression and MGMT methylation status,was utilized to categorize the patients accordingly.Results The SVZ involved(+)group(P＜0.001)and the MGMT(+)group(P=0.036)exhibited significantly larger tumor volumes.There were no significant differences between the groups in terms of gender,age,left/right hemispheric lateralization,or specific brain lobe distribution.There was no significant association between Ki-67 expression levels,MGMT methylation status,and SVZ involvement,respectively.Conclusion The SVZ(+)group and the MGMT(+)group demonstrates a wider range of tumor invasion.