OBJECTIVE: To investigate the role of MK2 inhibitor MMI-0100 on inflammatory response after allogeneic hematopoietic stem cell transplantation (allo-HSCT) and related mechanisms. METHODS: An allo-HSCT mouse model was established. Recipient rats were randomly divided into BMT+NaCl group and BMT+MMI-0100 group, and were injected with NaCl and MMI-0100 every day after transplantation, respectively. Samples of the two groups were collected on d 7 and 14, femur paraffin sections were stained with HE, and pathological changes in the bone marrow cavity were observed under the light microscope. The gene and protein expression levels of pro-inflammatory cytokines IL-1β and IL-18 were detected by qPCR and Western blot. Macrophage typing was detected by flow cytometry. The expression levels of NLRP3 and Caspase-1 were detected by Western blot. RESULTS: Inflammatory cell infiltration in the bone marrow cavity was significantly reduced in the BMT+MMI-0100 group. Western blot results showed that the protein expression levels of IL-1β and IL-18 in the BMT+MMI-0100 group were decreased compared to the BMT+NaCl group on day 7 and day 14 (all P <0.01). The qPCR results showed that compared to the BMT+NaCl group, the IL-18 gene expression levels in the BMT+MMI-0100 group were significantly reduced on day 7 and day 14 (both P <0.01). In the BMT+MMI-0100 group, the expression level of IL-1β gene decreased on day 7 (P <0.05), but increased and was higher than that in the BMT+NaCl group on day 14 (P <0.05). Flow cytometry results showed that the expression of M1 macrophages and M1/M2 ratio decreased in the BMT+MMI-0100 group compared to BMT+NaCl group (all P <0.05). Western blot results showed that the protein expression levels of NLRP3 and Caspase-1 in the BMT+MMI-0100 group were lower than those in the BMT+NaCl group (all P <0.05). CONCLUSION MMI-0100 can ameliorate bone marrow inflammatory injury after allo-HSCT and may act by reducing NLRP3 expression to promote M2 polarization.
Animals ; Interleukin-1beta/metabolism* ; Rats ; Interleukin-18/metabolism* ; Hematopoietic Stem Cell Transplantation/adverse effects* ; Mice ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Inflammation ; Bone Marrow/pathology* ; Protein Serine-Threonine Kinases/metabolism* ; Intracellular Signaling Peptides and Proteins/antagonists & inhibitors* ; Caspase 1/metabolism* ; Macrophages ; Transplantation, Homologous

OBJECTIVE: To evaluate the effect and safety of Chinese medicine (CM) Fuzheng Huazhuo Decoction (FHD) in treating patients with coronavirus disease 2019 (COVID-19) who persistently tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: This retrospective cohort study was conducted at Shanghai New International Expo Center shelter hospital in China between April 1 and May 30, 2022. Patients diagnosed as COVID-19 with persistently positive SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) test results for ⩾8 days after diagnosis were enrolled. Patients in the control group received conventional Western medicine (WM) treatment, while those in the FHD group received conventional WM plus FHD for at least 3 days. The primary outcome was viral clearance time. Secondary outcomes included negative conversion rate within 14 days, length of hospital stay, cycle threshold (Ct) values of the open reading frame 1ab (ORF1ab) and nucleocapsid protein (N) genes, and incidence of new-onset symptoms during hospitalization. Adverse events (AEs) that occurred during the study period were recorded. RESULTS: A total of 1,765 eligible patients were enrolled in this study (546 in the FHD group and 1,219 in the control group). Compared with the control group, patients receiving FHD treatment showed shorter viral clearance time for nucleic acids [hazard ratio (HR): 1.500, 95% confidence interval (CI): 1.353-1.664, P<0.001] and hospital stays (HR: 1.371, 95% CI: 1.238-1.519, P<0.001), and a higher negative conversion rate within 14 days (96.2% vs. 82.6%, P<0.001). The incidence of new-onset symptoms was 59.5% in the FHD group, similar to 57.8% in the control group (P>0.05). The Ct values of ORF1ab and N genes increased more rapidly over time in the FHD group than those in the control group post-randomization (ORF1ab gene: β =0.436±0.053, P<0.001; N gene: β =0.415 ±0.053, P<0.001). The incidence of AEs in the FHD group was lower than that in the control group (24.2% vs. 35.4%, P<0.001). No serious AEs were observed. CONCLUSION FHD was effective and safe for patients with persistently positive SARS-CoV-2 PCR tests. (Registration No. ChiCTR2200063956).
Humans ; Drugs, Chinese Herbal/adverse effects* ; Retrospective Studies ; Male ; Female ; Middle Aged ; COVID-19 Drug Treatment ; SARS-CoV-2/drug effects* ; COVID-19/virology* ; Adult ; Aged ; Treatment Outcome

Objective To explore the trajectory of psychological symptom clusters in pregnant women with assisted reproductive technology(ART),and analyze the influencing factors of each trajectory subgroups,in order to provide a theoretical basis for the management of psychological health during pregnancy in pregnant women with ART.Methods A total of 205 pregnant women who had conceived using ART were sampled from the obstetrics clinic of a tertiary hospital in Nanjing from August 2023 to April 2024 using a convenient sampling method.The baseline data were assessed by general information questionnaire,Symptom Checklist-90,Distress Disclosure Index and Positive Psychological Capital Questionnaire at 10-14 weeks gestation,and the follow-up information was assessed by Symptom Checklist-90 at 22-26 weeks of gestation and 34-38 weeks of gestation.Exploratory factor analysis was used to extract symptom clusters;the latent class growth mixture model was used to identify the track categories;the multiple logistic regression analysis was used to analyze the influencing factors of the track.Results 180 cases were finally included.By exploratory factor analysis,5,4 and 5 factors were extracted at 3 time points respectively.Trajectories of psychological symptom clusters in pregnant women with ART is divided into 3 potential classes:low level-slow relieving group(28.89％),high level-significant increasing group(6.11％),medium level-slow increasing group(65.00％).Logistic regression analyses showed that duration of infertility,number of ART,literacy,pain self-expression and positive psychological capital were influential factors in the potential categories of psychological symptom clusters in pregnant women conceived with ART(all P＜0.05).Conclusion The trajectory of psychological symptom clusters in pregnant women with ART was divided into 3 potential classes.Medical workers could develop corresponding interventions based on the influencing factors and implement comprehensive and efficient symptom management.

Objective:To explore the clinical features of Brucellar myelitis and diagnosis and treatment of secondary neuromyelitis optica spectrum disorder (NMOSD), and enhance the awareness of clinicians about this disease.Methods:A retrospective study was performed; 13 patients with Brucellar myelitis admitted to Department of Neurology, Inner Mongolia Autonomous Region People's Hospital from January 2020 to December 2024 were chosen. Clinical data were collected, and MRI images and serological changes during the infection period were observed. Serum and cerebrospinal fluid demyelinating antibody markers and cerebrospinal fluid oligoclonal bands (OCBs) in the suspected secondary inflammatory demyelinating diseases of the central nervous system patients were detected. All patients received standard antibiotic treatment and/or individualized immunotherapy depending on disease severity. The patients were followed up for 24 (12, 42) months. At the last follow-up, the neurological outcomes were evaluated using modified Rankin scale (mRS, scores of 0-2: good prognosis; scores of 3-6: poor prognosis).Results:(1) Among the 13 patients, 12 had motor disorder, 9 had bladder/bowel dysfunction, 7 had sensory abnormality, and 4 had other symptoms such as dizziness, behavioral changes, or unsteady gait. (2) MRI results showed that 8 patients had spinal cord abnormalities, including 2 with long-segment intramedullary high signal at T2-weighted image and 6 with short-segment local intramedullary high signal at T2-weighted image. Enhanced MRI was performed in 11 patients, with 2 showing lesion enhancement, 3 showing meningeal enhancement, and 6 showing no enhancement. (3) Four patients had elevated cerebrospinal fluid pressure (>180 mmH 2O); 9 patients had elevated cerebrospinal fluid protein level (>0.45 g/L). Brucella-specific DNA was detected in the cerebrospinal fluid of 6 patients. One patient was positive for OCB type II. One patient was positive for aquaporin 4 antibody (AQP4-IgG) in both serum and cerebrospinal fluid, and one patient was double positive for myelin oligodendrocyte glycoprotein antibody (MOG-IgG) and AQP4-IgG in serum. (4) All 13 patients received standard antibiotic treatment; 12 patients received immunotherapy. (5) Among the 4 patients with poor prognosis, 3 died and the remaining 9 had a good prognosis. The mRS score decreasing from 4 (3, 4) at admission to 2 (2, 3) at the last follow-up, showing an overall improvement in neurological function. (6) Among the 13 patients, 2 were diagnosed as having Brucellar myelitis secondary NMOSD. On the basis of antibiotic treatment, one AQP4-IgG positive patient was treated with high-dose glucocorticoids only and later died; one MOG-IgG and AQP4-IgG double positive patient was treated with intravenous immunoglobulin combined with high-dose glucocorticoids and sequential rituximab, with mRS score decreasing from 5 at admission to 2 at the last follow-up and good neurological function recovery. Conclusions:The clinical manifestations of Brucellar myelitis are diverse and overlap with the clinical features of NMOSD. For patients with suspected Brucellar myelitis secondary NMOSD, combination of immunosuppressant (such as rituximab) with antibiotics may be an effective individualized treatment.

AIM: To examine how three distinct central positioning techniques for anterior capsulotomy-pupil center, limbus center, and lens apex-affect intraocular lens(IOL)placement and visual quality following femtosecond laser-assisted cataract surgery(FLACS).METHODS: A total of 36 patients(72 eyes)with age-related cataracts who underwent FLACS and ZCB00 aspherical IOL implantation at Aier Eye Hospital Medical Center, Anhui Medical University between January and December 2023 were included in this prospective study. Patients were divided into three groups based on the central positioning mode for anterior capsulotomy: pupil center, limbus center, and lens apex center groups. IOL alignment and displacement were evaluated using the Casia2 device, and the postoperative visual quality was assessed.RESULTS: At 1 d postoperatively, the IOL tilt for the pupil, limbus, and apex groups were 3.96°±1.51°, 4.63°±1.87°, and 3.90°±2.24°, respectively(F=1.07, P=0.35); IOL decentration values were 0.21±0.10 mm, 0.23±0.16 mm, and 0.21±0.12 mm, respectively(F=0.14, P=0.87); total higher-order aberrations were 0.32±0.40 μm, 0.56±0.61 μm, and 0.53±0.60 μm, respectively(F=1.38, P=0.26); and coma aberrations values were 0.13±0.10 μm, 0.16±0.15 μm, and 0.14±0.15 μm, respectively(F=0.3, P=0.74). All results obtained postoperative day 1 did not differ significantly. At 3 mo postoperatively, IOL tilt values were 5.42°±2.00°, 3.96°±1.44°, and 3.20°±1.19°, respectively(F=12.40, P<0.001); IOL decentration values were 0.33±0.07 mm, 0.23±0.11 mm, and 0.21±0.11 mm, respectively(F=4.99, P=0.008); total higher-order aberrations were 0.67±0.29 μm, 0.44±0.37 μm, and 0.42±0.19 μm, respectively(F=5.50, P=0.006); and coma aberrations values were 0.21±0.12 μm, 0.19±0.12 μm, and 0.12±0.11 μm, respectively(F=3.87, P=0.03). All results obtained 3 mo postoperatively were statistically significant.CONCLUSION: Using the lens apex as the central positioning mode for anterior capsulotomy in FLACS improves postoperative IOL stability and reduces postoperative IOL tilt and decentration. If the lens apex cannot be determined intraoperatively, the limbus center-positioning mode is recommended.

BACKGROUND: Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation and joint destruction. Iguratimod (IGU) is a novel conventional synthetic disease-modifying antirheumatic drugs (csDMARD) with good efficacy and safety for the treatment of active RA in China and Japan. However, the long-term effects of IGU on the progression of bone destruction or radiographic progression in patients with active RA remain unknown. We aimed to investigate the efficacy and safety of iguratimod (IGU), a combination of methotrexate (MTX) and IGU, and IGU in patients with active rheumatoid arthritis (RA) who were naïve to MTX. METHODS: This multicenter, double-blind, randomized, non-inferiority clinical trial was conducted at 28 centers for over 52 weeks in China. In total, 911 patients were randomized (1:1:1) to receive MTX monotherapy (10-15 mg weekly, n = 293), IGU monotherapy (25 mg twice daily, n = 297), or IGU + MTX (10-15 mg weekly for MTX and 25 mg twice daily for IGU, n = 305) for 52 weeks. The patients' clinical characteristics, Simplified Disease Activity Index (SDAI), Clinical Disease Activity Index (CDAI), disease activity score in 28 joints-C-reactive protein (DAS28-CRP) level, and disease activity score in 28 joints-erythrocyte sedimentation rate (DAS28-ESR) were assessed at baseline. The primary endpoints were the proportion of patients with ≥20% improvement according to the American College of Rheumatology (ACR20) response and changes in the van der Heijde-modified total Sharp score (vdH-mTSS) at week 52. RESULTS: The proportions of patients achieving an ACR20 response at week 52 were 77.44%, 77.05 %, and 65.87% for IGU monotherapy, IGU + MTX, and MTX monotherapy, respectively. The non-inferiority of IGU monotherapy to MTX monotherapy was established with the ACR20 (11.57%; 95% confidence interval [CI], 4.35-18.79%; P <0.001) and vdH-mTSS (-0.37; 95% CI, -1.22-0.47; P = 0.022). IGU monotherapy was also superior to MTX monotherapy in terms of ACR20 ( P = 0.002) but not the vdH-mTSS. The superiority of IGU + MTX over MTX monotherapy was confirmed in terms of the ACR20 (11.18%; 95% CI, 3.99-18.37%; P = 0.003), but not in the vdH-mTSS (-0.68; 95% CI, -1.46-0.11; P = 0.091). However, the difference in the incidence rates of adverse events was not statistically significant. CONCLUSIONS: IGU monotherapy/IGU + MTX showed a more favorable clinical response than did MTX monotherapy. IGU may have some clinical benefits over MTX in terms of radiographic progression, implying that IGU may be considered as an initial therapeutic option for patients with active RA. TRIAL REGISTRATION https://classic.clinicaltrials.gov/ , NCT01548001.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Antirheumatic Agents/therapeutic use* ; Arthritis, Rheumatoid/drug therapy* ; Chromones/adverse effects* ; Double-Blind Method ; Drug Therapy, Combination ; Methotrexate/adverse effects* ; Treatment Outcome ; Sulfonamides

The aim of this study was to identify the Salmonella strains isolated from an outbreak of foodborne illness in a seafood buffet restaurant and analyze their pathogenic characteristics.Epidemiological data,fecal samples from patients and chefs,and food/environmental samples from the restaurant were analyzed.Research methods included bacterial culture,serotyping,quadruple fluo-rescence PCR identification,whole-genome sequencing and antibiotic susceptibility testing.The results showed that 4 S.Java strains(serotype 1,4,12∶b∶1,2;ST42)were isolated from two outbreak cases and two sporadic cases.All isolates exhibited similar genomic features,harboring 9 virulence islands and 98 virulence genes.Antimicrobial resistance profiling revealed streptomycin monoresis-tance,mediated by aac(6′)-Iy and aac(6′)-Iaa genes.In conclusion,this event was the first reported outbreak of foodborne illness caused by S.Java in China,indicating that S.Java may be prevalent in the surveyed district.The catering industry should optimize food handling and processing procedures and enhance the surveillance of high risk pathogens.Meanwhile,further studies should ad-dress differential diagnosis and pathogenic mechanism differences between S.Java and S.paratyphi B,which will facilitate evidence-based monitoring in China.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.