BACKGROUND: Several studies have demonstrated the occurrence of secondary tumors as a rare but significant complication of chimeric antigen receptor T (CAR-T) cell therapy, underscoring the need for a detailed investigation. Given the limited variety of secondary tumor types reported to date, a comprehensive characterization of the various secondary tumors arising after CAR-T therapy is essential to understand the associated risks and to define the role of the immune microenvironment in malignant transformation. This study aims to characterize the immune microenvironment of a newly identified secondary tumor post-CAR-T therapy, to clarify its pathogenesis and potential therapeutic targets. METHODS: In this study, the bone marrow (BM) samples were collected by aspiration from the primary and secondary tumors before and after CD19 CAR-T treatment. The CD45 + BM cells were enriched with human CD45 microbeads. The CD45 + cells were then sent for 10× genomics single-cell RNA sequencing (scRNA-seq) to identify cell populations. The Cell Ranger pipeline and CellChat were used for detailed analysis. RESULTS: In this study, a rare type of secondary chronic myelomonocytic leukemia (CMML) were reported in a patient with diffuse large B-cell lymphoma (DLBCL) who had previously received CD19 CAR-T therapy. The scRNA-seq analysis revealed increased inflammatory cytokines, chemokines, and an immunosuppressive state of monocytes/macrophages, which may impair cytotoxic activity in both T and natural killer (NK) cells in secondary CMML before treatment. In contrast, their cytotoxicity was restored in secondary CMML after treatment. CONCLUSIONS This finding delineates a previously unrecognized type of secondary tumor, CMML, after CAR-T therapy and provide a framework for defining the immune microenvironment of secondary tumor occurrence after CAR-T therapy. In addition, the results provide a rationale for targeting macrophages to improve treatment strategies for CMML treatment.
Humans ; Lymphoma, Large B-Cell, Diffuse/therapy* ; Tumor Microenvironment/genetics* ; Antigens, CD19/metabolism* ; Leukemia, Myelomonocytic, Chronic/genetics* ; Immunotherapy, Adoptive/adverse effects* ; Male ; Single-Cell Analysis/methods* ; Female ; Sequence Analysis, RNA/methods* ; Receptors, Chimeric Antigen ; Middle Aged

Methods: This study enrolled 40 patients with AIS, 20 patients with congenital scoliosis (CS), and 20 patients with spinal degenerative disease (SDD). All patients underwent open posterior surgery in our hospital, and a paravertebral muscle (multifidus muscle) biopsy was performed intraoperatively. This study included many indexes that describe muscle, especially dystrophin staining. The above pathological results were compared among the AIS, CS, and SDD groups. The correlation between the Cobb angle and Nash–Moe classification and the above pathological results was analyzed in patients with AIS. Results: Significant reductions in the dystrophin staining of dystrophin-1 (p<0.001), dystrophin-2 (p<0.001), and dystrophin-3 (p<0.001) were observed in the AIS group than in the CS and SDD groups. The higher the Nash–Moe classification in the AIS group, the more significant the loss of dystrophin-2 (p=0.042) in the convex paraspinal muscles. Additionally, a significantly positive correlation was observed between the reductions of dystrophin-2 on the concave side of the AIS group and Cobb angle (p=0.011). Conclusions Dystrophin protein deficiency in the paraspinal muscles plays a crucial role in AIS formation and progression. The severity of scoliosis in patients with AIS is correlated with the extent of dystrophin loss in the paravertebral muscles. Therefore, dystrophin dysfunction may be relevant to AIS occurrence and development.

Methods: This study enrolled 40 patients with AIS, 20 patients with congenital scoliosis (CS), and 20 patients with spinal degenerative disease (SDD). All patients underwent open posterior surgery in our hospital, and a paravertebral muscle (multifidus muscle) biopsy was performed intraoperatively. This study included many indexes that describe muscle, especially dystrophin staining. The above pathological results were compared among the AIS, CS, and SDD groups. The correlation between the Cobb angle and Nash–Moe classification and the above pathological results was analyzed in patients with AIS. Results: Significant reductions in the dystrophin staining of dystrophin-1 (p<0.001), dystrophin-2 (p<0.001), and dystrophin-3 (p<0.001) were observed in the AIS group than in the CS and SDD groups. The higher the Nash–Moe classification in the AIS group, the more significant the loss of dystrophin-2 (p=0.042) in the convex paraspinal muscles. Additionally, a significantly positive correlation was observed between the reductions of dystrophin-2 on the concave side of the AIS group and Cobb angle (p=0.011). Conclusions Dystrophin protein deficiency in the paraspinal muscles plays a crucial role in AIS formation and progression. The severity of scoliosis in patients with AIS is correlated with the extent of dystrophin loss in the paravertebral muscles. Therefore, dystrophin dysfunction may be relevant to AIS occurrence and development.

Methods: This study enrolled 40 patients with AIS, 20 patients with congenital scoliosis (CS), and 20 patients with spinal degenerative disease (SDD). All patients underwent open posterior surgery in our hospital, and a paravertebral muscle (multifidus muscle) biopsy was performed intraoperatively. This study included many indexes that describe muscle, especially dystrophin staining. The above pathological results were compared among the AIS, CS, and SDD groups. The correlation between the Cobb angle and Nash–Moe classification and the above pathological results was analyzed in patients with AIS. Results: Significant reductions in the dystrophin staining of dystrophin-1 (p<0.001), dystrophin-2 (p<0.001), and dystrophin-3 (p<0.001) were observed in the AIS group than in the CS and SDD groups. The higher the Nash–Moe classification in the AIS group, the more significant the loss of dystrophin-2 (p=0.042) in the convex paraspinal muscles. Additionally, a significantly positive correlation was observed between the reductions of dystrophin-2 on the concave side of the AIS group and Cobb angle (p=0.011). Conclusions Dystrophin protein deficiency in the paraspinal muscles plays a crucial role in AIS formation and progression. The severity of scoliosis in patients with AIS is correlated with the extent of dystrophin loss in the paravertebral muscles. Therefore, dystrophin dysfunction may be relevant to AIS occurrence and development.

Osteoporosis is a globally prevalent metabolic bone disease,with bone homeostasis imbalance being its key pathogenic mechanism.Over the years,studies on the relationship between ambient temperature and bone health have shown heterogeneous results due to different conditions.Epidemiological studies indicate that the incidence of osteoporotic fractures varies geographically and climatically.People in cold regions experience earlier bone loss,and high-latitude cold areas are high-risk zones for hip fractures.Osteoporosis is more prevalent in North China that in South China.Additionally,the early stage of the disease is insidious,highlighting the need for early prevention and treatment across the entire population.Mechanistically,low temperatures affect acral bone development,reduce bone blood circulation,cause degradation of bone microstructure,and increase osteocyte apoptosis,thereby promoting bone resorption and reducing bone mass.This review aims to provide data and new lines of thought for the early precise prevention and effective clinical treatment of osteoporosis in cold regions.

Objective To explore the effect of cognitive behavioral therapy(CBT)on improving anxiety,depression,sleep,and fatigue in patients with post-intensive care syndrome(PICS).Methods Sixty PICS patients transferred from the department of respiratory intensive care unit(RICU)of Puyang Oilfield General Hospital from September 2022 to February 2023 were selected as the study subjects.Patients were divided into a control group and an intervention group using a random number table method,with 30 cases in each group.The control group only received routine health education,while the intervention group received CBT on the basis of routine health education.After 3 months of intervention,the changes in hospital anxiety and depression scale(HADS),Pittsburgh sleep quality index(PSQI),and fatigue assessment scale(FAS)before and after intervention were observed in both groups of patients.Results There was no statistically significant difference in anxiety,depression,PSQI,and FAS scores between the two groups of patients before intervention.The scores gradually decreased over time and reached the lowest level at 3 months after intervention.After intervention,the above scores in the intervention group were significantly lower than those in the control group(anxiety score:5.06±1.76 vs.9.33±1.42,depression score:6.93±1.64 vs.7.63±1.61,PSQI score:5.27±1.37 vs.8.43±2.56,FAS score:5.67±0.47 vs.9.97±0.21,all P<0.05).Conclusion Implementing CBT for PICS patients can alleviate anxiety and depression,improve their sleep quality and fatigue symptoms,thereby enhancing their quality of life.

Objective To construct a prediction model for the progression of knee osteoarthritis(KOA)based on ultrasound score,magnetic resonance imaging(MRI)score,and serum levels of transforming growth factor-β1(TGF-β1)and cathepsin D(Cat D).Methods Clinical data from 270 patients with KOA in Hengshui People's hospital from December 2022 to June 2024 were retrospec-tively analyzed.The patients were randomly divided into a modeling set(n=189)and validation set(n=81)at a ratio of 7∶3.The patients in the modeling set were categorized into mild-to-moderate and severe groups based on the degree of disease progression.Mul-tivariate logistic regression analysis was used to identify factors influencing KOA progression,and a prediction model was constructed using R software.Results Multivariate logistic regression analysis showed that body mass index,knee injury history,ultrasound score,WORMS score,TGF-β1,and Cat D were significant predictors of KOA progression(P＜0.05).A nomogram-based prediction model was developed using these variables.The areas under the curve(AUC)of the nomograms for predicting disease progression in the modeling and validation sets were 0.889 and 0.860,respectively.The calibration curves showed that the predicted probability was in good agreement with the actual probability.Conclusion The prediction model developed in this study is effective in identifying patients at high-risk of KOA progression and may servce as a valuable tool for clinical assessment and decision making.

Objective To construct a prediction model for the progression of knee osteoarthritis(KOA)based on ultrasound score,magnetic resonance imaging(MRI)score,and serum levels of transforming growth factor-β1(TGF-β1)and cathepsin D(Cat D).Methods Clinical data from 270 patients with KOA in Hengshui People's hospital from December 2022 to June 2024 were retrospec-tively analyzed.The patients were randomly divided into a modeling set(n=189)and validation set(n=81)at a ratio of 7∶3.The patients in the modeling set were categorized into mild-to-moderate and severe groups based on the degree of disease progression.Mul-tivariate logistic regression analysis was used to identify factors influencing KOA progression,and a prediction model was constructed using R software.Results Multivariate logistic regression analysis showed that body mass index,knee injury history,ultrasound score,WORMS score,TGF-β1,and Cat D were significant predictors of KOA progression(P＜0.05).A nomogram-based prediction model was developed using these variables.The areas under the curve(AUC)of the nomograms for predicting disease progression in the modeling and validation sets were 0.889 and 0.860,respectively.The calibration curves showed that the predicted probability was in good agreement with the actual probability.Conclusion The prediction model developed in this study is effective in identifying patients at high-risk of KOA progression and may servce as a valuable tool for clinical assessment and decision making.

Objective To explore the effect of cognitive behavioral therapy(CBT)on improving anxiety,depression,sleep,and fatigue in patients with post-intensive care syndrome(PICS).Methods Sixty PICS patients transferred from the department of respiratory intensive care unit(RICU)of Puyang Oilfield General Hospital from September 2022 to February 2023 were selected as the study subjects.Patients were divided into a control group and an intervention group using a random number table method,with 30 cases in each group.The control group only received routine health education,while the intervention group received CBT on the basis of routine health education.After 3 months of intervention,the changes in hospital anxiety and depression scale(HADS),Pittsburgh sleep quality index(PSQI),and fatigue assessment scale(FAS)before and after intervention were observed in both groups of patients.Results There was no statistically significant difference in anxiety,depression,PSQI,and FAS scores between the two groups of patients before intervention.The scores gradually decreased over time and reached the lowest level at 3 months after intervention.After intervention,the above scores in the intervention group were significantly lower than those in the control group(anxiety score:5.06±1.76 vs.9.33±1.42,depression score:6.93±1.64 vs.7.63±1.61,PSQI score:5.27±1.37 vs.8.43±2.56,FAS score:5.67±0.47 vs.9.97±0.21,all P<0.05).Conclusion Implementing CBT for PICS patients can alleviate anxiety and depression,improve their sleep quality and fatigue symptoms,thereby enhancing their quality of life.

Anxiety disorders are characterized by high prevalence and recurrence rate.Selective serotonin reuptake inhibitors(SSRIs)and cognitive behavioral therapy(CBT)are recommended as first-line treatments for anxiety disorders,while some patients do not response to either of these treatments.Therefore,exploring the neurobiological mechanisms associated with treatment response and valuable prognostic marker is of great value in guiding clinical decision making.Previous studies have reported an altered electroencephalogram(EEG)pattern in patients with anxiety disorders after treatment,and revealed a correlation between baseline EEG and treatment response,suggesting that EEG is of great value in predicting the treatment response in anxiety disorders.The purpose of this article is to delineate findings from a systematic review of the literature investigating the EEG signal in prognostic prediction and exploration of neurobiological mechanisms,so as to provide electrophysiological evidence for individualized treatment of anxiety disorders.Results of this review show that patients responding more strongly to negative emotional stimuli before treatment are more likely to benefit from SSRIs and CBT.After the CBT,no statistical difference is found in the amplitude of error-related negativity(ERN)and P1 component between pre-and post-procedure measurements,suggesting that CBT may not reduce anxiety symptoms by improving attention bias and behavioral monitoring.EEG indicators related to emotion perception under negative emotional stimuli at baseline,such as late positive potential(LPP),may be promising markers for predicting response to treatment in anxiety disorders.