AIM: To detect the distribution and expression of vascular endothelial growth factor(VEGF)in radiation retinopathy(RR)through fluorescence targeted imaging.METHODS:Covalent binding of fluorescein FITC with VEGF antibody ranibizumab to prepare targeted fluorescent imaging probe ranibizumab-FITC. SD rats were randomly divided into three groups based on the principle of weight balance: a normal control group(Con group), a low-dose radiation group(10 Gy group), and a high-dose radiation group(30 Gy group). Medical linear accelerators and lead blocks were used to locally irradiate the rat eyeballs for modeling. Western blot and qRT-PCR were used to detect the expression levels of VEGF-A in each group and to screen for appropriate modeling dose. The inverted fluorescence microscope and the confocal microscope were used to observe the distribution of VEGF and imaging probes in the retinas of control and RR model group rats, and to verify the effectiveness of targeted probes.RESULTS:The expression level of VEGF-A in the retina of rats in the high-dose radiation group(30 Gy group)was higher than that in the normal control group(Con group). In early RR, VEGF expression was observed to be associated with microaneurysms and abnormal microvessels in the retina. VEGF accumulation was observed at the site of capillary wall damage. When retinal capillary endothelial damage occurred, targeted probes gathered on the outer surface of the vessel wall.CONCLUSION:The expression level of VEGF in the retina of RR model rats is elevated, and fluorescent targeted molecular imaging probes can detect the spatial distribution of VEGF at the microvascular lesions in the retina of RR rats.

This paper proposes a two-stage method integrating visual foundation models （VFM） and diffusion models. The segment anything model （SAM） as VFM is combined with the SegRefiner diffusion model to construct the SAM-SegRefiner framework for automated segmentation of edema， inflammation， and thrombus regions in histopathological images of hemorrhoidal tissue， providing a reproducible technical tool for the objective quantification of pathological morphology and its application in traditional Chinese medicine （TCM） syndrome research. Trained and validated on multi-center retrospective data， the SAM-SegRefiner model achieved an average pixel accuracy of 95.32% and a mean intersection over union （mIoU） of 66.81% on an independent test set， significantly outperfor-ming comparative models such as U-Net， MixU-Net， and SAM-Med2D， and also demonstrating robust cross-center generalization capability. Furthermore， by correlating the quantitatively segmented results from the model with the patients' TCM syndrome types， the potential associations between pathomorphological features and TCM syndrome differentiation have been explored. The analysis revealed no statistically significant differences in the degree of inflammatory infiltration and thrombus formation among different syndrome types， suggesting a complex relationship between local pathological changes and systemic syndrome manifestations.

The gut microbiota is regarded as the "eighth organ" of the human body and plays a critical regulatory role in the occurrence and progression of various diseases. Ulcerative colitis （UC） is a chronic inflammatory bowel disease with a complex etiology and a tendency toward recurrent episodes. In recent years， studies have shown that gut microbiota dysbiosis plays a key role in its pathological processes. Meanwhile， an increasing number of studies have demonstrated that imbalances in the gut microbiota and abnormalities in its metabolites are closely associated with the development of atrial fibrillation （AF）. Although UC and AF belong to diseases of the digestive system and cardiovascular system， respectively， both exhibit systemic inflammatory characteristics and are often accompanied by gut microbiota dysregulation and abnormal metabolic products. However， systematic investigations into the mechanisms by which gut microbiota-derived metabolites act in these two diseases remain limited. Based on this， the present study adopts literature review and theoretical analysis methods， taking the "gut microbiota-gut-heart" axis as the entry point， to systematically summarize the signaling networks of three key classes of metabolites， i.e.， short-chain fatty acids （SCFAs）， bile acids （BAs）， and trimethylamine N-oxide （TMAO）， in the comorbidity mechanism of UC and AF. The findings indicate that these metabolites may activate key inflammatory pathways， such as NF-κB and NLRP3， thereby synergistically mediating intestinal barrier dysfunction and systemic inflammation and constructing a potential comorbidity network. On this basis， potential intervention strategies for the treatment of UC-AF comorbidity， including probiotic intervention and fecal microbiota transplantation， are further discussed. This study aims to provide new theoretical evidence and research perspectives for prevention and treatment strategies of cross-system diseases.

BACKGROUND:Gradient artificial bone repair scaffolds can mimic unique anatomical features in musculoskeletal tissues,showing great potential for repairing injured musculoskeletal tissues. OBJECTIVE:To review the latest research advances in gradient artificial bone repair scaffolds for tissue engineering in the musculoskeletal system and describe their advantages and fabrication strategies. METHODS:The first author of the article searched the Web of Science and PubMed databases for articles published from 2000 to 2023 with search terms"gradient,bone regeneration,scaffold".Finally,76 papers were analyzed and summarized after the screening. RESULTS AND CONCLUSION:(1)As an important means of efficient and high-quality repair of skeletal system tissues,gradient artificial bone repair scaffolds are currently designed bionically for the natural gradient characteristics of bone tissue,bone-cartilage,and tendon-bone tissue.These scaffolds can mimic the extracellular matrix of native tissues to a certain extent in terms of structure and composition,thus promoting cell adhesion,migration,proliferation,differentiation,and regenerative recovery of damaged tissues to their native state.(2)Advanced manufacturing technology provides more possibilities for gradient artificial bone repair scaffold preparation:Gradient electrospun fiber scaffolds constructed by spatially differentiated fiber arrangement and loading of biologically active substances have been developed;gradient 3D printed scaffolds fabricated by layered stacking,graded porosity,and bio-3D printing technology;gradient hydrogel scaffolds fabricated by in-situ layered injections,simple layer-by-layer stacking,and freeze-drying method;and in addition,there are also scaffolds made by other modalities or multi-method coupling.These scaffolds have demonstrated good biocompatibility in vitro experiments,were able to accelerate tissue regeneration in small animal tests,and were observed to have significantly improved histological structure.(3)The currently developed gradient artificial bone repair scaffolds have problems such as mismatch of gradient scales,unclear material-tissue interactions,and side effects caused by degradation products,which need to be further optimized by combining the strengths of related disciplines and clinical needs in the future.

Objective:To compare the efficacy of body posture combined with pharmacotherapy and pharmacotherapy alone in the treatment of chronic subdural hematoma(CSDH).Methods:Firstly, retrospective case series study was conducted. Thirty cases of CSDH that had received body posture combined with pharmacotherapy at Department of Neurosurgery, Huashan Hospital Affiliated to Fudan University from December 2016 to October 2020 were studied retrospectively. Twenty-seven patients were male, and 3 patients were female. The age of patients ( M(IQR)) was 66(16) years (range:28 to 84). Nineteen patients had unilateral hematoma, and 11 patients had bilateral hematoma. All patients received pharmacotherapy and body posture therapy that was to raise their lower limbs 20 to 30 cm with leg lift pad and get abdominal compressed with customized abdominal belt in supine position. Patients were required to maintain the body posture as much as possible, with the maximum to 16 to 18 hours per day. Patients with unilateral hematoma should tilt the head to the affected side and avoid tilting it to the opposite side. For patients with bilateral hematoma, there was no need for head lateralization. Patient were treated with oral dexamethasone and atorvastatin simultaneously. The preliminary efficacy of body posture combined with pharmacotherapy was determined by hematoma improvement rate which was analyzed by Clopper-Pearson method. Then, the multi-center, prospective, randomized controlled trial had carried out in 9 medical centers from August 2020 to November 2021. The stratified block randomization method was adopted. Patients were randomized in a ratio of 1∶1 to either receive pharmacotherapy alone(the control group) or body posture combined with pharmacotherapy(the experiment group) for 3 months and followed up for 6 months. Effective treatment was defined as complete absorption of hematoma, or the hematoma volume decreased by more than 10 ml and Markwalder grading scale score had improved by more than 1 point compared to the baseline. The efficacy rate and surgery conversion rate at 3 months and recurrence at 6 months were observed. Comparison between groups was performed with paired sample t test, Mann-Whitney U test, χ2 test, corrected χ2 test, or Fisher exact probability method. Logistic regression was used to compare the effective rate and operation rate between the two groups. Results:In the respective study, 30 patients completed follow-up 13 to 353 days after treatment. At the last follow-up, the incidence of almost complete absorption or significantly absorption of hematoma (hematoma volume was significantly reduced accompanied by symptom improvement) was 93.3%. The 95% CI for the incidence that analyzed by the Clopper-Pearson method was 77.9% to 99.2%. One hundred and six patients were enrolled in the multicenter study. Fifty-five patients underwent body posture combined with pharmacotherapy. The age was 74(17) years (range:26 to 92). Thirty-nine patients were males and 16 were females. Fifty-one patients underwent pharmacotherapy alone. The age was 69(12) years (range:48 to 84). Thirty-seven patients were males and 14 were females. The length of body posture recorded in diary card was (15.7±2.3) hours(range:7.6 to 19.3 hours). The efficacy rate in the body posture combined with pharmacotherapy group and pharmacotherapy alone group were 83.6% (46/55) and 56.9% (29/51), respectively at 3 months. The result of the logistic regression analysis showed that the efficacy of body posture combined with pharmacotherapy group was better than that of pharmacotherapy alone group ( OR=3.88,95% CI:1.57 to 9.58, P=0.003). Surgery rate in the body posture combined with pharmacotherapy group and pharmacotherapy alone group were 5.5% (3/55) and 21.6% (11/51) respectively. The result of Logistic regression showed that the pharmacotherapy alone group was more likely to be converted to surgery ( OR=0.21,95% CI:0.05 to 0.80, P=0.023). At the 6 months, no recurrence of cases was found in the body posture combined with pharmacotherapy group. However, the recurrence rate of pharmacotherapy alone group was 6.3% (3/48), there was no significant difference between the two groups ( P>0.05). Conclusion:The effect of body posture combined with pharmacotherapy for chronic subdural hematoma is better than that of pharmacotherapy alone.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective·To evaluate the clearance and pharmacokinetics/pharmacodynamics(PK/PD)of antibiotics from the perspective of protein binding rates in critically ill patients undergoing intermittent hemodialysis(IHD),in order to explore the association between protein binding rate and dialysis clearance of antibiotics,and to provide theoretical basis for developing antibiotic dosing regimens during hemodialysis.Methods·Nineteen patients undergone low-flux hemodialysis and received antibiotic therapy at the Department of Nephrology,Shanghai Ninth People's Hospital,Shanghai Jiao Tong University School of Medicine,were enrolled and divided into the meropenem group(n=7),the vancomycin group(n=5)and the ceftriaxone group(n=7)according to the type of antibiotics.A liquid chromatography with tandem mass spectrometry(LC-MS/MS)method was established to detect meropenem,vancomycin,and ceftriaxone in human plasma/serum and dialysate.A two-compartment pharmacokinetic model was established using MATLAB.Instantaneous and total dialysis clearance rates were calculated,and PK/PD parameters were analyzed.Results·No significant differences were found in the clinical characteristics of subjects among the three groups.The dialysis clearance rates were as follows:meropenem group(5.14?5.97 L/h)>vancomycin group(2.87?3.77 L/h)>ceftriaxone group(1.21?1.90 L/h),with statistically significant differences(P<0.001).All three antibiotics showed good fit in the two-compartment pharmacokinetic model with a dialysate chamber(fval%<2),and the calculated PK/PD parameters were consistent with previous literature.For meropenem,the fraction of time that the free drug concentration remained above the minimal inhibitory concentration(%fT>MIC)values were 95.2%,60.8%and 32.4%at minimal inhibitory concentration(MIC)values of 2,8 and 16 μg/mL,respectively.For ceftriaxone(free concentration),the%fT>MIC values were all above 45.0%at MICs of 0.25,4 and 16 μg/mL.For vancomycin,only 14.0%of the trough concentrations reached the target range of 15?20 mg/L.Conclusion·The three antibiotics are well described by the two-compartment model.The plasma protein binding rate has a significant effect on the dialysis clearance of antibiotics in low-flux IHD,with higher protein binding associated with lower clearance.The regimens of meropenem(0.5 g/d)and ceftriaxone(2.0 g/d)are generally effective among patients undergoing low-flux IHD,while the vancomycin regimen with a loading dose of 1.0 g and a maintenance dose of 0.5 g/2 d carries a risk of treatment failure.

Objective:To explore the causal association between insulin-like growth factor-1(IGF-1)and colorectal cancer(CRC)based on two sample Mendelian randomization(MR)analysis.Methods:A bidirectional two sample MR analysis was conducted based on publicly aggregated data from the IEU OpenGWAS project.The inverse variance weighted(IVW)method was used as the main analysis model to assess the causal relationship between IGF-1 and CRC.Additional analyses were performed using weighted median(WM),MR-Egger regression,weighted mode estimator(WME),and simple mode(SM)methods.Sensitivity analysis was performed to assess the robustness of the results.Results:A total of 386 single nucleotide polymorphisms(SNPs)were selected as instrumental variables(IVs)with IGF-1 as the exposure factor.The MR analysis results revealed a positive causal association between IGF-1 and the risk of CRC[odds ratio(OR)=1.178,95％confidence interval(CI):1.092-1.272)](P＜0.001),and the association remained significant after adjusting for height[OR(95％CI)=1.214(1.111,1.327)](P＜0.001).Cochran's Q-test showed heterogeneity among the IVs(P＜0.05),while the horizontal pleiotropy of IV was not detected by the MR-Egger regression(P＞0.05).The leave-one-out analysis showed that the MR results were robust.Reverse MR analysis indicated no reverse causal relationship between IGF-1 and CRC[OR(95％CI):1.017(0.997,1.037)](P=0.103).Conclusion:There is a causal relationship between IGF-1 level and CRC,and elevated IGF-1 level could be a risk factor for CRC.

Objective To investigate the diagnostic value of our regression model based on quantitative parameters of dual-energy CT and clinical features for stages T2 and T3 colorectal cancer.Methods A cross-section study was performed on 91 patients with colorectal cancer confirmed by postoperative pathology in our hospital from January 2022 to November 2023.All of them underwent dual-energy CT examination.According to the pathological T staging criteria of Chinese Colorectal Cancer Diagnosis and Treatment Standard(2020 Edition),they were divided into T2 group(n=43)and T3 group(n=48).Univariate analysis was used to compare the differences in quantitative CT parameters and clinical features between the 2 groups,and the obtained significant variables were employed to construct diagnosis models by univariate or multivariate logistic regression analysis.The area under receiver operating characteristic curve(AUC)of the CT parametric model and the model combined with clinical features was compared to evaluate the efficacy of diagnosing T2 and T3 stages.Results Univariate analysis showed that carcinoembryonic antigen(CEA),N stage,tumor location,tumor longest diameter(LD),CT value of virtual noncontrast(CT-VNC),fat fraction,electron density(Rho)and dual energy index(DEI)were significantly different between the T2 and T3 groups(P＜0.05).Multivariate logistic regression analysis found that N stage,tumor location,LD,fat fraction and DEI were independent risk factors for the diagnosis of stage T3.The AUC value of the model of above CT parameters in diagnosing stage T3 colorectal cancer was 0.671(95％CI:0.558～0.783),and the AUC value of the combined model of above CT parameters and clinical features was 0.886(95％CI:0.815～0.957),and statistical difference was observed in the AUC value between the combined model and the CT parametric model(P＜0.01).Conclusion The regression model constructed with dual-energy CT quantitative parameters combined with clinical features has high value in the preoperative diagnosis of stages T2 and T3 colorectal cancer before surgery.

With the increasing demand for dynamic,real-time and rapid qualitative analysis of chemical composition in areas such as emergency response and space exploration,chip-scale mass spectrometers have attracted significant attention.These devices are expected to drive the integration of mass spectrometry with micro/nano-fabrication and intelligent sensing technologies,fostering profound innovation and breakthroughs in analytical chemistry.As an excellent mass analyzer,the ion trap exhibits numerous advantages,and its miniaturization creates favorable conditions for the high-density integration of miniature mass spectrometers.However,the reduction in ion storage capacity may compromise its sensitivity and dynamic range,rendering the study of ion unidirectional ejection in highly miniaturized ion traps of significant practical importance.In this work,a research was conducted on achieving efficient ion unidirectional ejection while maintaining high mass resolution in the extremely miniature hyperbolic linear ion trap(M-HLIT)with a field radius of 1 mm,and an electric field compensation method was proposed,which combined asymmetric electrode stretching and unbalanced RF voltage to achieve high-precision optimization of the electric field composition.Simulations showed that in an ideal structure,this method achieved 100％unidirectional ejection efficiency with the mass resolution of 518,significantly outperforming traditional asymmetric structure method(365)and unbalanced voltage method(321).Following the introduction of ion ejection slots,further optimization through bidirectional stretching and electrical parameters improved the resolution to 790 while maintaining a unidirectional ejection efficiency of 93％.This method eliminated the requirement for additional excitation voltage,offering an ideal solution for the miniature mass analyzer with high detection performance of chip-level mass spectrometers.