Purpose To investigate the changes in quadriceps femoris microcirculatory perfusion level after low-load blood flow restriction training and its relationship with muscle strength.Materials and Methods Twenty-five healthy subjects were prospectively recruited in the First Affiliated Hospital of Kunming Medical University from September to November 2022.A 200 mmHg pressure cuff was applied at the root of the left thigh for blood flow restriction,and the subjects completed regular knee extension training within 4 weeks.Before the first training session and within 24 hours after the last training session,all subjects underwent scanning with the 3.0T MRI intravoxel incoherent motion sequence and the multi-echo steady-state acquisition three-dimentional imaging sequence.After image post-processing,the quadriceps femoris cross-sectional area,perfusion fraction and pseudo-diffusion coefficient were obtained,and the peak torque was measured using an isokinetic dynamometer.The MRI and muscle strength test parameters before and after training were compared,and correlation analyses were performed between the change of peak torque and the change of perfusion fraction,cross-sectional area,and pseudo-diffusion coefficient respectively.Results After low-load blood flow restriction training,the cross-sectional area of the left quadriceps femoris in subjects increased(t=-4.515,P<0.05).Among its components,the cross-sectional area of the left rectus femoris,vastus intermedius and vastus lateralis all increased(t=-3.302,-2.877,-3.207,all P<0.05).The perfusion fraction value of the left quadriceps femoris increased(t=-5.447,P<0.05);the perfusion fraction values of the left rectus femoris,vastus intermedius,vastus lateralis and vastus medialis all increased(t=-5.723,-4.621,-3.767,-4.682,all P<0.05);the muscle strength of the left quadriceps femoris increased(t=-3.983,P<0.05).There was a highly positive correlation between change of perfusion fraction and peak torque of the left quadriceps femoris in subjects(r=0.708,P<0.05).Conclusion After low-load blood flow restriction training,the changes in quadriceps femoris muscle microperfusion quantified by intravoxel incoherent motion are related to muscle strength,which is helpful for formulating rehabilitation training strategies for young patients.

Purpose To investigate the changes in quadriceps femoris microcirculatory perfusion level after low-load blood flow restriction training and its relationship with muscle strength.Materials and Methods Twenty-five healthy subjects were prospectively recruited in the First Affiliated Hospital of Kunming Medical University from September to November 2022.A 200 mmHg pressure cuff was applied at the root of the left thigh for blood flow restriction,and the subjects completed regular knee extension training within 4 weeks.Before the first training session and within 24 hours after the last training session,all subjects underwent scanning with the 3.0T MRI intravoxel incoherent motion sequence and the multi-echo steady-state acquisition three-dimentional imaging sequence.After image post-processing,the quadriceps femoris cross-sectional area,perfusion fraction and pseudo-diffusion coefficient were obtained,and the peak torque was measured using an isokinetic dynamometer.The MRI and muscle strength test parameters before and after training were compared,and correlation analyses were performed between the change of peak torque and the change of perfusion fraction,cross-sectional area,and pseudo-diffusion coefficient respectively.Results After low-load blood flow restriction training,the cross-sectional area of the left quadriceps femoris in subjects increased(t=-4.515,P<0.05).Among its components,the cross-sectional area of the left rectus femoris,vastus intermedius and vastus lateralis all increased(t=-3.302,-2.877,-3.207,all P<0.05).The perfusion fraction value of the left quadriceps femoris increased(t=-5.447,P<0.05);the perfusion fraction values of the left rectus femoris,vastus intermedius,vastus lateralis and vastus medialis all increased(t=-5.723,-4.621,-3.767,-4.682,all P<0.05);the muscle strength of the left quadriceps femoris increased(t=-3.983,P<0.05).There was a highly positive correlation between change of perfusion fraction and peak torque of the left quadriceps femoris in subjects(r=0.708,P<0.05).Conclusion After low-load blood flow restriction training,the changes in quadriceps femoris muscle microperfusion quantified by intravoxel incoherent motion are related to muscle strength,which is helpful for formulating rehabilitation training strategies for young patients.

Objective:To establish a serum detection method of surface-enhanced Raman spectroscopy (SERS) combining with machine learning for early screening of colorectal cancer (CRC).Methods:Serum samples were collected from 150 CRC patients diagnosed at Jiangdu People′s Hospital, Affiliated to Yangzhou University, and also from 37 healthy subjects. Gold nanohexapod (AuNHs) arrays were prepared using an oil-water interface self-assembly method. A 5 μl serum sample was applied onto the AuNHs array. Scatheless and rapid detection for serum were performed using a Renishaw inVia Raman spectrometer at room temperature with a laser wavelength of 785 nm, exposure time of 10 s, and power of 5 mW. The raw SERS spectra were preprocessed using Savitzky-Golay smoothing, AsLS baseline correction, and Min-Max normalization with Origin 2019 software. Furthermore, the principal component analysis (PCA)-support vector machine (SVM) model was constructed using Python′s scikit-learn library. Leave-One-Out Cross-Validation (LOOCV) was used to evaluate the model′s accuracy, sensitivity, specificity, and area under the curve (AUC).Results:The AuNHs arrays exhibited uniform morphology. The relative standard deviation (RSD) of the SERS intensity at 1 080 cm -1 was 5.69%, and the RSD of the SERS intensity at 1 340 cm -1 was 6.20%. The limit of detection (LOD) of the AuNHs array was 9.42×10 -12 mol/L. The PCA-SVM model achieved an accuracy of 90.91% (170/187), sensitivity of 96.79% (181/187), specificity of 99.47% (186/187), and an AUC of 0.98. The most significant characteristic peaks distinguishing different CRC stages were at 747, 940, 1 000, 1 447, and 1 612 cm -1. Conclusion:The serum detection method based on SERS combined with machine learning can accurately screen CRC with higher accuracy, sensitivity, and specificity, demonstrating potential clinical application value.

Objective:To investigate the uptake patterns of 18F-fluorodeoxy glucose ( 18F-FDG) in the endometrium using positron emission tomography (PET) imaging and to differentiate these from stage IA endometrial cancer. Methods:From September 2022 to April 2024, a prospective inclusion of 354 women without gynecological diseases and no hormone usage who underwent 18F-FDG PET-CT examinations at the affiliated hospital of Qingdao University were set as the physiological group, while a group containing 42 cases of Stage IA endometrial carcinoma was also set. The physiological group was divided into five groups based on the menstrual cycle: menstrual period, proliferative phase, ovulatory phase, secretory phase, and menopausal phase. The images were analyzed using visual and quantitative measurements; quantitative analysis indicators were standardized uptake value maximum (SUVmax) and the region of interest/liver ratio (R/L value). Receiver operating characteristic (ROCs) curve was used to determine the optimal cutoff values for SUVmax and R/L value. A clinical model was established using binary logistic regression, and ROC curves were drawn to evaluate the predictive performance of the model. Results:The uptake of 18F-FDG in the endometrium exhibited cyclical variations throughout different physiological phases, with higher uptakes observed during the menstrual and ovulation phases (SUVmax values of 6.66±3.26 and 3.89±1.21, respectively), which are significantly higher than those in the proliferative phase [median SUVmax of 2.54 (2.02, 3.47)], secretory phase (SUVmax of 2.55±0.86), and menopausal phase [SUVmax median of 2.04 (1.69, 2.29)]. During the menstrual and ovulation phases, the radiotracer accumulation patterns were triangular in 105 cases, oval in 32 cases, and round-like in 2 cases. All 42 cases of endometrial cancer showed 18F-FDG uptake, with radiotracer accumulation patterns being round-like in 17 cases, oval in 10 cases, triangular in 9 cases, and irregular in 6 cases. There were statistically significant differences in the shapes of radiotracer concentration between the menstrual, ovulatory periods, and endometrial carcinoma (both P＜0.001). The SUVmax and R/L values in menstrual period and ovulatory period were significantly lower than that in endometrial carcinoma group ( P＜0.001). During the menstrual phase, the optimal cutoff values for SUVmax and R/L in distinguishing between endometrial and endometrial cancer were 12.59 and 3.81, respectively, with corresponding AUCs of 0.885 and 0.842. After incorporating endometrial uptake morphology into the model, the AUCs was improved to 0.969 and 0.948, respectively. During the ovulatory phase, the optimal cutoff values for SUVmax and R/L were 5.96 and 2.85, respectively, with AUCs of 0.984 and 0.968. After integrating endometrial uptake morphology into the model, the AUCs were increased to 0.999 and 0.998, respectively. Conclusions:The 18F-FDG PET imaging of the endometrium shows higher uptake during the menstrual and ovulatory periods, primarily triangular in shape; endometrial carcinoma uptake is significantly higher than the physiological uptake during the menstrual and ovulatory periods, mainly in circular, oval, and irregular shapes. When SUVmax≥5.96, R/L≥2.85, combined with the physiological cycle of the subjects and the morphological characteristics of the radiotracer concentration, it is possible to effectively differentiate between physiological uptake and Stage IA endometrial carcinoma.

Objective:To establish a serum detection method of surface-enhanced Raman spectroscopy (SERS) combining with machine learning for early screening of colorectal cancer (CRC).Methods:Serum samples were collected from 150 CRC patients diagnosed at Jiangdu People′s Hospital, Affiliated to Yangzhou University, and also from 37 healthy subjects. Gold nanohexapod (AuNHs) arrays were prepared using an oil-water interface self-assembly method. A 5 μl serum sample was applied onto the AuNHs array. Scatheless and rapid detection for serum were performed using a Renishaw inVia Raman spectrometer at room temperature with a laser wavelength of 785 nm, exposure time of 10 s, and power of 5 mW. The raw SERS spectra were preprocessed using Savitzky-Golay smoothing, AsLS baseline correction, and Min-Max normalization with Origin 2019 software. Furthermore, the principal component analysis (PCA)-support vector machine (SVM) model was constructed using Python′s scikit-learn library. Leave-One-Out Cross-Validation (LOOCV) was used to evaluate the model′s accuracy, sensitivity, specificity, and area under the curve (AUC).Results:The AuNHs arrays exhibited uniform morphology. The relative standard deviation (RSD) of the SERS intensity at 1 080 cm -1 was 5.69%, and the RSD of the SERS intensity at 1 340 cm -1 was 6.20%. The limit of detection (LOD) of the AuNHs array was 9.42×10 -12 mol/L. The PCA-SVM model achieved an accuracy of 90.91% (170/187), sensitivity of 96.79% (181/187), specificity of 99.47% (186/187), and an AUC of 0.98. The most significant characteristic peaks distinguishing different CRC stages were at 747, 940, 1 000, 1 447, and 1 612 cm -1. Conclusion:The serum detection method based on SERS combined with machine learning can accurately screen CRC with higher accuracy, sensitivity, and specificity, demonstrating potential clinical application value.

Objective:To investigate the uptake patterns of 18F-fluorodeoxy glucose ( 18F-FDG) in the endometrium using positron emission tomography (PET) imaging and to differentiate these from stage IA endometrial cancer. Methods:From September 2022 to April 2024, a prospective inclusion of 354 women without gynecological diseases and no hormone usage who underwent 18F-FDG PET-CT examinations at the affiliated hospital of Qingdao University were set as the physiological group, while a group containing 42 cases of Stage IA endometrial carcinoma was also set. The physiological group was divided into five groups based on the menstrual cycle: menstrual period, proliferative phase, ovulatory phase, secretory phase, and menopausal phase. The images were analyzed using visual and quantitative measurements; quantitative analysis indicators were standardized uptake value maximum (SUVmax) and the region of interest/liver ratio (R/L value). Receiver operating characteristic (ROCs) curve was used to determine the optimal cutoff values for SUVmax and R/L value. A clinical model was established using binary logistic regression, and ROC curves were drawn to evaluate the predictive performance of the model. Results:The uptake of 18F-FDG in the endometrium exhibited cyclical variations throughout different physiological phases, with higher uptakes observed during the menstrual and ovulation phases (SUVmax values of 6.66±3.26 and 3.89±1.21, respectively), which are significantly higher than those in the proliferative phase [median SUVmax of 2.54 (2.02, 3.47)], secretory phase (SUVmax of 2.55±0.86), and menopausal phase [SUVmax median of 2.04 (1.69, 2.29)]. During the menstrual and ovulation phases, the radiotracer accumulation patterns were triangular in 105 cases, oval in 32 cases, and round-like in 2 cases. All 42 cases of endometrial cancer showed 18F-FDG uptake, with radiotracer accumulation patterns being round-like in 17 cases, oval in 10 cases, triangular in 9 cases, and irregular in 6 cases. There were statistically significant differences in the shapes of radiotracer concentration between the menstrual, ovulatory periods, and endometrial carcinoma (both P＜0.001). The SUVmax and R/L values in menstrual period and ovulatory period were significantly lower than that in endometrial carcinoma group ( P＜0.001). During the menstrual phase, the optimal cutoff values for SUVmax and R/L in distinguishing between endometrial and endometrial cancer were 12.59 and 3.81, respectively, with corresponding AUCs of 0.885 and 0.842. After incorporating endometrial uptake morphology into the model, the AUCs was improved to 0.969 and 0.948, respectively. During the ovulatory phase, the optimal cutoff values for SUVmax and R/L were 5.96 and 2.85, respectively, with AUCs of 0.984 and 0.968. After integrating endometrial uptake morphology into the model, the AUCs were increased to 0.999 and 0.998, respectively. Conclusions:The 18F-FDG PET imaging of the endometrium shows higher uptake during the menstrual and ovulatory periods, primarily triangular in shape; endometrial carcinoma uptake is significantly higher than the physiological uptake during the menstrual and ovulatory periods, mainly in circular, oval, and irregular shapes. When SUVmax≥5.96, R/L≥2.85, combined with the physiological cycle of the subjects and the morphological characteristics of the radiotracer concentration, it is possible to effectively differentiate between physiological uptake and Stage IA endometrial carcinoma.

In recent years, the recurrence rate of stroke has gradually increased, and recurrent stroke is usually more disabling and lethal than first-ever stroke. More than half of stroke patients in China have sleep disorders, which may increase the risk of stroke recurrence and death, but are often overlooked in reality. This article mainly discusses the relationship between stroke-related sleep disorders, stroke recurrence, and mortality risk, possible mechanisms, treatment methods, and therapeutic effects.

Objective:To investigate the value of 18F-FDG PET/CT imaging signs and metabolic parameters in predicting tumor spread through air spaces (STAS) of stage Ⅰ lung adenocarcinoma. Methods:From January 2019 to December 2021, clinical, imaging and metabolic parameters of 381 patients (126 males, 255 females, age (61.2±9.2) years) with stage Ⅰ lung adenocarcinoma were retrospectively analyzed in the Affiliated Hospital of Qingdao University. According to the postoperative pathological results, patients were divided into STAS positive group and STAS negative group. According to the operation time, patients were divided into training set ( n=254) and verification set ( n=127). χ2 test or Mann-Whitney U test was used to compare the differences of different parameters between patients with STAS positive and negative, and binary logistic regression analysis was used to select the predictors of STAS status. The prediction model was established, and ROC curve was used to evaluate the predictive efficacy. Results:There were 49(19.3%, 49/254) patients with STAS positive and 205(80.7%, 205/254) patients with STAS negative in the training set, while those were 35(27.6%, 35/127) and 92(72.4%, 92/127) in the verification set. In the training set, the differences of age ( z=-2.30, P=0.021), type of lesions ( χ2=6.81, P=0.009), spiculation ( χ2=12.64, P<0.001), bronchus truncation ( χ2=6.98, P=0.008), ground glass ribbon sign ( χ2=26.93, P<0.001) and SUV max ( z=-4.62, P<0.001) between the two groups were statistically significant. Multivariate logistic regression analysis showed that age (odds ratio ( OR)=1.048, 95% CI: 1.004-1.094, P=0.032), ground glass ribbon sign ( OR=3.857, 95% CI: 1.693-8.788, P=0.001) and SUV max ( OR=1.133, 95% CI: 1.001-1.282, P=0.049) were independent predictors of STAS status in stage Ⅰ lung adenocarcinoma patients. The logistic regression model was P=1/(1+ e - x), x=-5.292+ 0.480×age (year)+ 1.493×ground glass ribbon sign+ 0.170×SUV max. The AUCs of the model in the training set and verification set were 0.770 and 0.801, with the sensitivity of 81.6%(40/49) and 82.9%(29/35), and the specificity of 69.8%(143/205) and 65.2%(60/92), respectively. Conclusion:Age, ground glass ribbon sign and SUV max have good predictive effects on the occurrence of STAS in stage Ⅰ lung adenocarcinoma.

Obstructive sleep apnea (OSA) is a sleep disorder characterized by recurrent upper respiratory tract obstruction, sleep fragmentation, and hypoxia during sleep. This disease often leads to cognitive, emotional, and memory related neurological damage, and its mechanism is closely associated with the disruption of the blood-brain barrier (BBB). This article mainly discusses the relationship between BBB damage caused by OSA and vascular cognitive impairment (VCI), as well as the role of early prevention, intervention, and repairing BBB on reducing VCI.

Post-stroke cognitive impairment (PSCI) refers to a clinical syndrome that occurs after a stroke and meets the diagnostic criteria for cognitive impairment, lasting for more than 6 months, and seriously affecting the daily life of patients. The complement system has been confirmed to be associated with PSCI. This article reviews the correlation between complement system and PSCI, as well as the possibility of complement system as an intervention target for PSCI.