Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

OBJECTIVE: To investigate effectiveness of arthroscopic superior capsular reconstruction using a "sandwich" patch combined with platelet-rich plasma (PRP) injection in treating massive irreparable rotator cuff tears. METHODS: A clinical data of 15 patients (15 sides) with massive irreparable rotator cuff tears, who were admitted between September 2020 and March 2023 and met the selective criteria, was retrospectively analyzed. There were 8 males and 7 females with an average age of 62.1 years (range, 40-80 years). The rotator cuff tears were caused by trauma in 7 cases and other reasons in 8 cases. The disease duration ranged from 5 to 25 months, with an average of 17.7 months. According to the Hamada grading, the rotator cuff tears were rated as grade 1 in 2 cases, grade 2 in 8 cases, and grade 3 in 5 cases. All patients were underwent superior capsular reconstruction using the "sandwich" patches (autologous fascia lata+polypropylene patch+autologous fascia lata) combined with PRP injection on patches. The pre- and post-operative active range of motion (ROM) of the shoulder joint, American Shoulder and Elbow Surgeons (ASES) score, Constant-Murley score, University of California, Los Angeles Shoulder Rating Scale (UCLA) score, and visual analogue scale (VAS) score were recorded. The subacromial space was measured on the imaging and rotator cuff integrity was assessed based on Sugaya grading. RESULTS: All incisions healed by first intention after operation without any complications such as infection. All patients were followed up 12-18 months (mean, 14.4 months). At last follow-up, the active ROMs of flexion, abduction, external rotation, internal rotation of the shoulder joint, subacromial space, ASES score, Constant-Murley score, and UCLA score increased, and VAS score decreased, showing significant differences when compared with preoperative values ( P<0.05). There was no significant difference in the Sugaya grading between last follow-up and immediately after operation ( P>0.05). CONCLUSION For massive irreparable rotator cuff tears, arthroscopic superior capsular reconstruction using the "sandwich" patches combined with PRP injection can restore stability of the shoulder joint, relieve pain, promote rotator cuff healing, and achieve good short-term effectiveness.
Humans ; Platelet-Rich Plasma ; Female ; Male ; Middle Aged ; Aged ; Rotator Cuff Injuries/therapy* ; Arthroscopy/methods* ; Adult ; Retrospective Studies ; Aged, 80 and over ; Treatment Outcome ; Plastic Surgery Procedures/methods* ; Rotator Cuff/surgery* ; Range of Motion, Articular ; Shoulder Joint/surgery*

OBJECTIVE: To establish and validate a novel diabetic retinopathy (DR) risk-prediction model using a whole-exome sequencing (WES)-based machine learning (ML) method. METHODS: WES was performed to identify potential single nucleotide polymorphism (SNP) or mutation sites in a DR pedigree comprising 10 members. A prediction model was established and validated in a cohort of 420 type 2 diabetic patients based on both genetic and demographic features. The contribution of each feature was assessed using Shapley Additive explanation analysis. The efficacies of the models with and without SNP were compared. RESULTS: WES revealed that seven SNPs/mutations ( rs116911833 in TRIM7, 1997T>C in LRBA, 1643T>C in PRMT10, rs117858678 in C9orf152, rs201922794 in CLDN25, rs146694895 in SH3GLB2, and rs201407189 in FANCC) were associated with DR. Notably, the model including rs146694895 and rs201407189 achieved better performance in predicting DR (accuracy: 80.2%; sensitivity: 83.3%; specificity: 76.7%; area under the receiver operating characteristic curve [AUC]: 80.0%) than the model without these SNPs (accuracy: 79.4%; sensitivity: 80.3%; specificity: 78.3%; AUC: 79.3%). CONCLUSION Novel SNP sites associated with DR were identified in the DR pedigree. Inclusion of rs146694895 and rs201407189 significantly enhanced the performance of the ML-based DR prediction model.
Diabetic Retinopathy/diagnosis* ; Humans ; Machine Learning ; Male ; Female ; Polymorphism, Single Nucleotide ; Middle Aged ; Exome Sequencing ; Aged ; Adult ; Pedigree ; Diabetes Mellitus, Type 2/complications* ; Genetic Predisposition to Disease ; Mutation

Objective To explore whether creatine therapy regulates neuronal ferroptosis by inhibiting the activation of STAT1 signaling pathway associated with suppressor of cytokine signaling 1(SOCS1)in Alzheimer's disease.Methods Immunohistochemical staining and counting of positive results using paraffin sections of human brain frontal lobes were employed to determine the trend of changes in the target proteins.Further validation was performed by immunofluorescence and Western blotting.STAT1 phosphorylation was inhibited by creatine injection using eleven FAD4T mice and by cerebellar medullary pool puncture,and the expression of target proteins was examined by immunohistochemistry and immunofluorescence after postmortem sampling.Results Compared with the age controls,interferon-γ(IFN-γ),an activating cytokine of the STAT1 signaling pathway,and SOCS1,a negative regulator of STAT1 activation,were both significantly up-regulated,STAT1 phosphorylation was enhanced,and the ferroptosis markers ferritin light chain(FTL)and cystine/glutamate transporter(xCT)increased markedly in the cortex of AD human brains;Creatine treatment of FAD4T mice resulted in a reduction of both IFN-γ and SOCS1,and a significant decrease in the ferroptosis markers FTL and xCT(SLC7A11).Conclusion Creatine ameliorates neuronal ferroptosis in AD model mice by reducing neuronal STAT1-SOCS1 signalling activation.

The application of artificial intelligence(AI)in medical diagnosis and treatment is becoming increasingly widespread,providing doctors and patients with more high-quality,efficient and personalized medical services.However,it also raised a series of ethical issues such as data security,algorithm transparency,responsibility definition,fairness and justice,doctor-patient relationships,and other aspects.Based on the combing of existing research results,this paper analyzed the research status of medical ethics in the application of AI in diagnosis and treatment,as well as expected that future medical ethics research can further explore the ethical issues of AI technology in medical treatment in greater depth,thus ensuring the rational application of AI in the medical field and maximizing the protection of patients'rights and interests.

Objective To investigate the effect of paeoniflorin on aerobic glycolysis of macrophages induced by resiquimod.Methods THP-1 cells were treated with phorbol ester(PM A)to differentiate into macrophages.The cells were divided into control group,model group and low,medium,high dose experimental group.The cells in the control group were cultured normally;in the model group,2 μg·mL-1 resiquimod was used to stimulate macrophages for 24 h to induce aerobic glycolysis.The low,medium and high dose experimental groups were treated with 1,10 and 100 μmol·L-1 paeoniflorin for 24 h on the basis of the model group.Cell activity was detected by cell counting kit-8(CCK-8)method.Lactate and glucose determination kit were used to detect lactate secretion and glucose consumption of cells in each group.The protein and mRNA expression levels of(PKM2)and(LDHA)were detected by Western blot and real-time fluorescence quantitative polynucleotide chain reaction(q-PCR)respectively.Immunofluorescence method was used to compare the fluorescence intensity of PKM2 in each group.Results After 24 h stimulation of THP-1 cells with 2 μg·mL-1 resiquimod,the glucose contents in cell culture supernatants of control group,model group and low,medium and high dose experimental groups were(14.70±0.44),(9.83±0.43),(10.68±0.29),(11.79±0.33)and(13.63±0.74)mmol·L-1;the lactate secreted by cells were(6.17±0.48),(11.94±0.55),(9.08±0.55),(7.79±0.66)and(6.50±0.55)mmol·L-1;the protein expression levels of PKM2 in cells were 1.00±0.00,1.33±0.18,1.02±0.17,0.74±0.17 and 0.73±0.18;the protein expression levels of LDHA were 1.00±0.00,1.20±0.09,0.90±0.14,0.76±0.12 and 0.78±0.17;the PKM2 mRNA levels were 1.00±0.09,2.11±0.23,1.98±0.31,1.38±0.25 and 0.93±0.32;the LDHA mRNA levels were 1.00±0.13,1.85±0.25,1.44±0.21,0.91±0.24 and 0.96±0.14;the average fluorescence intensities of PKM2 were 136.41±33.63,217.94±5.33,210.27±1.03,204.14±3.27 and 186.79±14.03.Compared with control group,the above indicators in model group showed statistically significant differences(P＜0.05,P＜0.01);compared with model group,the differences in the above indicators in medium and high dose experimental group were all statistically significant(P＜0.05,P＜0.01).Conclusion Paeoniflorin can inhibit the aerobic glycolysis of macrophages induced by resiquimod.