Predictive Value of Serum microRNA-29b-3p in Recurrence of Atrial Fibrillation After Radiofrequency Catheter Ablation.

Objective: Atrial fibrillation (AF) is a common arrhythmia. This study explored serum miR-29b-3p expression in AF patients and its value in predicting AF recurrence after radiofrequency catheter ablation (RFCA). Methods: Totally 100 AF patients who underwent RFCA were enrolled, with 100 individuals without AF as controls. Serum miR-29b-3p expression in participants was determined using RT-qPCR. The correlation between miR-29b-3p and atrial fibrosis markers (FGF-21/FGF-23) was assessed by Pearson analysis. The diagnostic efficacy of serum miR-29b-3p and FGF-21/FGF-23 in predicting AF recurrence after RFCA was analyzed by the receiver operating characteristic (ROC) curves. The Kaplan-Meier method was adopted to evaluate the effect of miR-29b-3p expression on the incidence of AF recurrence after RFCA. The independent risk factors for AF recurrence after RFCA were analyzed by logistic regression analysis. Results: Serum miR-29b-3p was poorly expressed in AF patients. After RFCA, AF patients showed elevated serum miR-29b-3p expression. Serum miR-29b-3p expression in AF patients negatively correlated with serum FGF-21 and FGF-23 concentrations. The cut-off values of serum miR-29b-3p, FGF-21, and FGF-23 in identifying AF recurrence were 0.860 (sensitivity: 100.00%, specificity: 39.71%), 222.2 pg/mL (sensitivity: 96.88%, specificity: 32.35%) and 216.3 ng/mL (sensitivity: 53.13%, specificity: 70.59%), respectively. Patients with low miR-29b-3p expression had a significantly higher incidence of AF recurrence than patients with high miR-29b-3p expression. Serum miR-29b-3p expression was one of the independent risk factors for AF recurrence after RFCA. Conclusion: Low miR-29b-3p expression in AF patients has certain predictive values and is one of the independent risk factors for AF recurrence after RFCA.

A new intestinal supplement 'Synbiotics' therapeutically regulates gut microbiota and activates PPARs pathway to inhibit Alzheimer's disease progression in mouse models.

We aimed to investigate the role of Synbiotic preparations on the interaction of gut microbiota with AD development. APP/PS1 mice were randomized into APP/PS1 and Synbiotics groups, and C57BL/6J mice were used as wild type (WT) control group. The mice in the Synbiotics group and the APP/PS1 group were given Synbiotics and xylo-oligosaccharides for 3 months, respectively. The mice in the WT group were given the same amount of normal saline. Cognitive function was measured. Positron emission computed tomography/magnetic resonance imaging (PET/MRI) was used to detect fasting blood glucose level. Immunohistochemical assay, ELISA, western blot and qRT-PCR were carried out to detect inflammatory factors. DNA extraction of fecal sample was performed to carry out sequencing. Bioinformatics analysis, metabolites sample preparation and Liquid Chromatograph Mass Spectrometer (LC/MS) analysis were also performed. Synbiotics treatment can significantly ameliorate learning and memory competence by inhibiting Aß protein deposition. Different bacteria in the intestine were significantly improved and changes in gut microbiota can affect the intestinal metabolism to affect multiple potential pathways after Synbiotics treatment. Synbiotics treatment can activate peroxisome proliferator activated receptor (PPARs) signaling pathway and significantly reduce neuroinflammation in APP/PS1 mice brains. Synbiotics treatment can effectively reduce neuro-inflammatory response through the regulation of intestinal microflora to delay AD development.

Optimization of a Ge2Sb2Te5-Based Electrically Tunable Phase-Change Thermal Emitter for Dynamic Thermal Camouflage.

Controlling infrared thermal radiations can significantly improve the environmental adaptability of targets and has attracted increasing attention in the field of thermal camouflage. Thermal emitters based on Ge2Sb2Te5 (GST) can flexibly change their radiation energy by controlling the reversible phase transition of GST, which possesses fast switching speed and low power consumption. However, the feasibility of the dynamic regulation of GST emitters lacks experimental and simulation verification. In this paper, we propose an electrically tunable thermal emitter consisting of a metal-insulator-metal plasmonic metasurface based on GST. Both optical and thermal simulations are conducted to optimize the structural parameters of the GST emitter. The results indicate that this emitter possesses large emissivity tunability, wide incident angle, polarization insensitivity, phase-transition feasibility, and dynamic thermal camouflage capability. Therefore, this work proposes a reliable optimization method to design viable GST-based thermal emitters. Moreover, it provides theoretical support for the practical application of phase-change materials in dynamic infrared thermal camouflage technology.

SEM Electron-Beam-Induced Ultrathin Carbon Deposition Layer on Cu Substrate: Improved Dry Oxidation Protection Performance than CVD Single Layer Graphene.

An amorphous carbon deposition layer (CDL) with nanoscale thickness induced by scanning electron microscope (SEM) electron beam is studied as a carbon-based protective layer on copper (Cu). CDL is prepared by inducing the deposition of pollutants or hydrocarbons in the cavity of SEM through electron beam irradiation (EBI). Wrinkles and cracks will not form and the interfacial spacing of CDL/Cu is smaller than Graphene/Cu (Gr/Cu). The thickness and coverage of the interfacial oxide layer of CDL/Cu are all smaller than that of the Gr/Cu after the same oxidation conditions. Characterization of Raman mapping also demonstrates that CDL shows better oxidation inhibition effects than graphene. The structure of CDL is determined to be C = C and C = O, CH3 - and C-O can be loaded vertically on CDL. Density functional theory (DFT) is employed for demonstrating the smaller interfacial gap of CDL/Cu, less wrinkles and cracks and larger adsorbing energy of water/oxygen compared with Gr/Cu. Molecular dynamic (MD) simulation also indicates that the diffusion of water or oxygen into CDL/Cu is more difficult and the oxidation of Cu covered by CDL is well suppressed. This work provides a new approach for the study of carbon-based antioxidant materials on Cu.

Analyzing the value of delayed 18 F-FDG PET/CT images in diagnosing small colorectal cancer liver metastases in patients with hypothyroidism based on diagnostic accuracy and image standardized uptake value.

PURPOSE: The objective of this study was to investigate the value of delayed 18F fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) images in patients with small colorectal cancer liver metastases (CRLMs) with hypothyroidism. METHOD: We performed a retrospective analysis of 66 small-CRLM patients with hypothyroidism and 66 small-CRLM patients with euthyroidism, all of whom underwent dual-time-point 18 F-FDG PET/CT imaging. First, the diagnostic accuracy of PET/CT early imaging and PET/CT delayed imaging on lesions was analyzed. Next, the correlation of metabolic parameters between PET/CT early imaging and PET/CT delayed imaging was analyzed according to the grouping of all lesions. Finally, PET/CT parameters were analyzed for correlation with thyroid hormones. RESULTS: The diagnostic accuracy of delayed imaging in small-CRLM patients with hypothyroidism is not as good as that in small-CRLM patients with euthyroidism; PET/CT metabolic parameters are also unfavorable for the diagnosis of small-CRLM. For small-CRLM patients with hypothyroidism, the greater the thyroid-stimulating hormone level, the greater the uptake of 18 F-FDG in normal liver tissue, and the smaller the ratio of tumor lesion uptake to normal liver tissue uptake. CONCLUSION: PET/CT-delayed imaging has better performance than early imaging in small-CRLM patients with euthyroidism. However, the more severe the hypothyroidism, the worse the diagnostic delayed imaging performance. The scan time can be extended appropriately to optimize the imaging efficacy.

DeepSF-4mC: A deep learning model for predicting DNA cytosine 4mC methylation sites leveraging sequence features.

N4-methylcytosine (4mC) is a DNA modification involving the addition of a methyl group to the fourth nitrogen atom of the cytosine base. This modification may influence gene regulation, providing potential insights into gene control mechanisms. Traditional laboratory methods for detecting 4mC DNA methylation have limitations, but the rise of artificial intelligence has introduced efficient computational strategies for 4mC site prediction. Despite this progress, challenges persist in terms of model performance and interpretability. To tackle these challenges, we propose DeepSF-4mC, a deep learning model specifically designed for predicting DNA cytosine 4mC methylation sites by leveraging sequence features. Our approach incorporates multiple encoding techniques to enhance prediction accuracy, increase model stability, and reduce the computational resources needed. Leveraging transfer learning, we harness existing models to enhance performance through learned representations or fine-tuning. Ensemble learning techniques combine predictions from multiple models, boosting robustness and accuracy. This research contributes to DNA methylation analysis and lays the groundwork for understanding 4mC's multifaceted role in biological processes. The web server for DeepSF-4mC is accessible at: http://deepsf-4mc.top/and the original code can be found at: https://github.com/754131799/DeepSF-4mC.

High-Safety Electrolytes with an Anion-Rich Solvation Structure Tuned by Difluorinated Cations for High-Voltage Lithium Metal Batteries.

As next-generation energy storage devices, lithium metal batteries (LMBs) must offer high safety, high-voltage resistance, and a long life span. Electrolyte engineering is a facile strategy to tailor the interfacial chemistry of LMBs. In particular, the solvation structure and derived solid electrolyte interphase (SEI) are crucial for a satisfactory battery performance. Herein, a novel middle-concentrated ionic liquid electrolyte (MCILE) with an anion-rich solvation structure tuned by difluorinated cations is demonstrated to achieve ultrahigh safety, high-voltage stability, and excellent ternary-cathode compatibility. Novel gem-difluorinated cations first synthesized for prestoring fluorine on positively charged species, not only preferentially adsorb in the inner-Helmholtz layers, but also participate in regulating the Li+ solvation structure, resulting in a robust interphase. Moreover, these weak interactions in the Li+ solvation structure including anion-solvent and ionic liquid (IL) cation-solvent pairs are first revealed, which are beneficial for promoting an anion-dominated solvation structure and the desolvation process. Benefiting from the unique anion-rich solvation structure, a stable hetero-SEI structure is obtained. The designed MCILE exhibits compatibility with Li metal anode and the high-voltage ternary cathode at high temperatures (60 °C). This work provides a new approach for regulating the solvation structure and electrode interphase chemistry of LMBs via difluorinated IL cations.

Epidemiology, site-specific characteristics and survival of carcinosarcoma: a retrospective study based on SEER database.

OBJECTIVES: Carcinosarcoma (CS) is a rare and biphasic malignancy characterised by a highly invasive biological nature and poor prognosis. This study explored the epidemiology, site-specific characteristics and survival outcome of CS. DESIGN: We conducted a retrospective study in the Surveillance, Epidemiology and End Results (SEER) database (1975-2018) for primary CS. SETTING AND PARTICIPANTS: SEER database includes publicly available information from regional and state cancer registries in the US centres. A total of 5042 CS patients were identified. We selected the top five anatomic CS (uterus, double adnexa, lung, bladder and breast) patients for further analysis. PRIMARY OUTCOME MEASURES: Incidence was estimated by geographical region, age, sex, race, stage and primary site. Trends were calculated using joinpoint regression. The cancer-specific survival (CSS) rate and initial treatment were summarised. RESULTS: Nearly 80% of CS occurred in the uterus and double adnexa, followed by lung, bladder and breast. The elderly and black population presented the highest age-adjusted rate of CS. The rates of distant metastasis in CS progressively increased from 1989 to 2018. Atlanta was the area with the highest incidence at 0.7 per 100 000. Pulmonary and bladder CS more frequently occurred in men and were diagnosed with regional stage. Distant metastasis was mostly found in ovary/fallopian tube CS. Radiotherapy was more commonly applied in uterine CS, while adnexa CS cases were more likely to receive chemotherapy. Multiple treatments were more used in breast CS. Pulmonary CS seemed to suffer worse CSS (median: 9.92 months), for which radiotherapy might not provide survival benefits (HR 0.60, 95% CI 0.42 to 0.86). Compared with the common histological types in each site, CS had the shortest survival. CONCLUSIONS: CS has unique clinical features in each primary site. Substantial prognosis variances exist based on tumour locations. The aggressive course is the common feature in CS at all sites.

Analysis of independent risk factors for aneurysm rupture based on carotid tortuosity index and morphological parameters of single intracranial aneurysms in anterior circulation.

PURPOSE: Our study focused on the risk factors associated with anterior circulation intracranial aneurysm (IA) rupture by examining the carotid artery (CA) tortuosity index (TI) and anterior circulation IA morphological parameters. METHOD: This study conducted a retrospective analysis of clinical and imaging data from 163 patients with anterior circulation IA diagnosed by head and neck computed tomography angiography (CTA). The patients were categorized into two groups: the ruptured group (57 cases) and the unruptured group (106 cases). CA was categorized based on its location into three segments: the extracranial segment of the internal carotid artery (EICA) TI, the angle of the internal carotid artery (ICA) and the common carotid artery (CCA) TI. Measure the morphological parameters of all IA: IA length neck (L), IA height (H), aneurysm diameter width (D), the ratio of L to the mean diameter of the IA-bearing artery (SR), the ratio of H to D (AR), the angle of flow inflow (FA) and IA angle (AA). The study conducted five types of analysis to determine the risk factors for anterior circulation IA rupture. The first was an univariate analysis of the risk factors. The second was an analysis of the correlation between CA TI and IA morphological parameters. The third used multivariate logistic stepwise regression analysis to analyse independent risk factors for IA rupture. The fourth was to plot ROC curves to build a predictive model for IA rupture and calculate diagnostic thresholds. Finally, a data set from another hospital (78 cases) was used as a validation set to validate the multivariate model. RESULT: Univariate analysis revealed that there were statistically significant differences (P < 0.05) in gender, EICA TI, location of IA and IA morphological parameters (FA, H, AR, L, SR), which acted as risk factors for anterior circulation IA rupture. The results of Spearman correlation analysis indicate that CCA TI is significantly correlated with SR, H and L (P < 0.05), while EICA TI is significantly correlated with FA and L (P < 0.05). The results of multivariate logistic analysis showed that FA (OR = 1.072, 95%CI = 1.04-1.10, P < 0.001), SR (OR = 4.949, 95%CI = 1.96-12.53, P = 0.001), EICA TI (OR = 1.037, 95%CI = 1.01-1.07, P = 0.003) were independent risk factors for IA rupture. The ROC curve plotting results suggest that the area under the curve (AUC) of FA is 0.860 with a diagnostic threshold of 110.1°; the AUC of SR is 0.786 with a diagnostic threshold of 1.67; the AUC of EICA TI is 0.723 with a diagnostic threshold of 28.845; the AUC of the three combined is 0.903 with a threshold of 0.480. The combined factor diagnostic model is validated according to the validation set, and the results show that the AUC (0.866) of the validation set is not much different from the AUC (0.903) of the multivariate model, and the multivariate model has a better diagnostic effect. CONCLUSION: In clinical practice, it is important to consider the evaluation of aneurysm rupture in combination with imaging, as FA, SR and ECIA TI are independent risk factors for IA rupture in the anterior circulation. Unlike the IA morphological parameters, EICA TI is an often overlooked extracranial parameter, but is equally important in its power to predict IA rupture. When the EICA TI exceeds 28.845, the IA has the possibility of rupture. Finally, multivariate diagnostic model are of interest when considering rupture of the anterior circulation IA.

Clinical value of 125I radioactive seed implantation in the treatment of lymph node metastasis of 131I refractory differentiated thyroid cancer.

PURPOSE: To evaluate the clinical value of 1251 seed implantation in the treatment of lymph node metastasis of 111 cases of refractory differentiated thyroid cancer (RAIR-DTC). METHODS AND MATERIALS: From January 2015 to June 2016, 42 patients with RAIR-DTC with lymph node metastasis (14 males and 28 females, median age 49 years) were analyzed retrospectively. After CT-guided 1251 seed implantation, CT was reexamined 2,4,6 months after operation, and the changes of metastatic lymph node size, serum thyroglobulin (Tg) level and complications were compared before or after treatment. Paired-Samples T Test, Methods repetitive measure analysis of variance, Spearman correlation coefficient analysis were used to analyze the data. RESULTS: Among the 42 patients, 2 had complete remission (4.76%), 9 had partial remission (21.43%), 29 had no change (69.05%), and 2 had disease progression (4.76%), with an overall effective rate of 95.24% (40/42). The diameter of lymph node metastasis was (1.39 ± 0.75) cm after treatment and (1.99 ± 0.38) cm before treatment; the diameter of lymph node metastasis was significantly reduced after treatment compared with that before metastasis (t = 5.557, P< 0.01); the serum Tg at 2, 4 and 6 months after treatment were (53.34 ± 14.05) ug/L, (33.17 + 7.61)ug/L and (25.93 ± 10.91)ug/L, respectively, compared with (57.72 ± 15.23)ug/L before treatment, and the differences between serum Tg after treatment and before treatment were all statistically significant (F = 23.612,P<0.05). Except for the diameter of lymph node metastasis (χ2 = 4.524, P<0.05), the patients' age, gender, metastasis site and the number of implanted particles per lesion were not influential factors in the efficacy (χ2 = 0.569-15.884, rs = 0.277, all P>0.05). CONCLUSION: 125I RSIT can significantly alleviate the clinical symptoms of RAIR-DTC patients with LNM, and the LNM lesions size has relevance for the treatment effect. The clinical follow-up time of serum Tg level can be extended to 6 months or even longer.

Artificial intelligence-based diagnosis of Alzheimer's disease with brain MRI images.

Alzheimer's disease, a primary neurodegenerative condition, predominantly impacts the elderly and pre-elderly population. This progressive neurological disorder is characterized by an array of symptoms including memory loss, cognitive decline, and various physiological and psychological disturbances, significantly compromising the quality of life of patients and their caregivers. Recent advancements in Magnetic Resonance Imaging (MRI) technology have catalyzed research in AI-enhanced diagnostics for Alzheimer's disease, fostering optimism for early detection and timely interventions. This progress has paved the way for the development of sophisticated algorithms and models adept at analyzing complex brain imaging data, thereby augmenting diagnostic accuracy and efficiency. This advancement fuels optimism regarding the transformative potential of AI-driven diagnostics in revolutionizing Alzheimer's disease management, with the prospect of facilitating more effective treatment strategies and improved patient outcomes. The objective of this review is to provide a comprehensive overview of recent developments in deep learning methodologies applied to brain MRI images for the classification of various stages of Alzheimer's disease, with a particular emphasis on early diagnosis. Furthermore, this review underscores the limitations of current research, discussing potential challenges and future research directions in this dynamic field.

Tubeimuside I improves the efficacy of a therapeutic Fusobacterium nucleatum dendritic cell-based vaccine against colorectal cancer.

Introduction: Fusobacterium nucleatum (F. nucleatum) infection has been confirmed to be associated with the development, chemoresistance, and immune evasion of colorectal cancer (CRC). The complex relationship between the microorganism, host cells, and the immune system throughout all stages of CRC progression, which makes the development of new therapeutic methods difficult. Methods: We developed a new dendritic cell (DC) vaccine to investigate the antitumor efficacy of CRC immunotherapy strategies. By mediating a specific mode of interaction between the bacteria, tumor, and host, we found a new plant-derived adjuvant, tubeimuside I (TBI), which simultaneously improved the DC vaccine efficacy and inhibited the F. nucleatum infection. Encapsulating TBI in a nanoemulsion greatly improved the drug efficacy and reduced the drug dosage and administration times. Results: The nanoemulsion encapsulated TBI DC vaccine exhibited an excellent antibacterial and antitumor effect and improved the survival rate of CRC mice by inhibiting tumor development and progression. Discussion: In this study, we provide a effective strategy for developing a DC-based vaccine against CRC and underlies the importance of further understanding the mechanism of CRC processes caused by F. nucleatum.

Metabolic Anomaly Appearance Aware U-Net for Automatic Lymphoma Segmentation in Whole-Body PET/CT Scans.

Positron emission tomography-computed tomography (PET/CT) is an essential imaging instrument for lymphoma diagnosis and prognosis. PET/CT image based automatic lymphoma segmentation is increasingly used in the clinical community. U-Net-like deep learning methods have been widely used for PET/CT in this task. However, their performance is limited by the lack of sufficient annotated data, due to the existence of tumor heterogeneity. To address this issue, we propose an unsupervised image generation scheme to improve the performance of another independent supervised U-Net for lymphoma segmentation by capturing metabolic anomaly appearance (MAA). Firstly, we propose an anatomical-metabolic consistency generative adversarial network (AMC-GAN) as an auxiliary branch of U-Net. Specifically, AMC-GAN learns normal anatomical and metabolic information representations using co-aligned whole-body PET/CT scans. In the generator of AMC-GAN, we propose a complementary attention block to enhance the feature representation of low-intensity areas. Then, the trained AMC-GAN is used to reconstruct the corresponding pseudo-normal PET scans to capture MAAs. Finally, combined with the original PET/CT images, MAAs are used as the prior information for improving the performance of lymphoma segmentation. Experiments are conducted on a clinical dataset containing 191 normal subjects and 53 patients with lymphomas. The results demonstrate that the anatomical-metabolic consistency representations obtained from unlabeled paired PET/CT scans can be helpful for more accurate lymphoma segmentation, which suggest the potential of our approach to support physician diagnosis in practical clinical applications.

LaCOme: Learning the latent convolutional patterns among transcriptomic features to improve classifications.

OMIC is a novel approach that analyses entire genetic or molecular profiles in humans and other organisms. It involves identifying and quantifying biological molecules that contribute to a species' structure, function, and dynamics. Finding the secrets of OMIC is like deciphering the biochemical code, but building data-driven models to mine the hidden phenotypic trait information has been a research hotspot. Transcriptome analysis is a popular biological technology for characterizing living systems' overall health, including cells and tissues. Individual transcript expression levels are known to be correlated with those of other transcripts. Nevertheless, most computational studies do not fully exploit these inter-feature correlations. Differential expression analyses, for example, assume that the expression levels of the transcripts are independent. Thus, we propose extracting these inter-feature correlations using the convolutional neural network (CNN) and transforming the transcriptomic features into a new space of convolutional transcriptomic (LaCOme) features. On most transcriptomic datasets in use, a series of comprehensive experiments have demonstrated that engineered LaCOme features outperform the original transcriptomic features in classification performances. Based on experimental results, OMIC data from biological samples could be further enriched using CNN to enhance computational analysis results. Also, feature rough screening can be used to extract valuable information from OMIC, regardless of the algorithm used to select features. It may always be better to create a novel feature than to keep the original. Furthermore, we investigated the feasibility of the feature construction method through cross-validation and independent verification, hoping to develop a more efficient and effective method.

3D-FVS: construction and application of three-dimensional fundus vascular structure model based on single image features.

BACKGROUND: Fundus microvasculature may be visually observed by ophthalmoscope and has been widely used in clinical practice. Due to the limitations of available equipment and technology, most studies only utilized the two-dimensional planar features of the fundus microvasculature. METHODS: This study proposed a novel method for establishing the three-dimensional fundus vascular structure model and generating hemodynamic characteristics based on a single image. Firstly, the fundus vascular are segmented through our proposed network framework. Then, the length and width of vascular segments and the relationship among the adjacent segments are collected to construct the three-dimensional vascular structure model. Finally, the hemodynamic model is generated based on the vascular structure model, and highly correlated hemodynamic features are selected to diagnose the ophthalmic diseases. RESULTS: In fundus vascular segmentation, the proposed network framework obtained 98.63% and 97.52% on Area Under Curve (AUC) and accuracy respectively. In diagnosis, the high correlation features extracted based on the proposed method achieved 95% on accuracy. CONCLUSIONS: This study demonstrated that hemodynamic features filtered by relevance were essential for diagnosing retinal diseases. Additionally, the method proposed also outperformed the existing models on the levels of retina vessel segmentation. In conclusion, the proposed method may represent a novel way to diagnose retinal related diseases, which can analysis two-dimensional fundus pictures by extracting heterogeneous three-dimensional features.

Clinical efficacy analysis of radioactive 125I particle implantation for the treatment of pelvic local recurrence of cervical cancer after radiotherapy.

Purpose: To explore the efficacy of CT-guided iodine-125 (125I) radioactive particle implantation for the treatment of pelvic local recurrence of cervical cancer after radiotherapy. Material and methods: To analyze clinical data of 46 patients with pelvic local recurrence of cervical cancer after radiotherapy, who underwent 125I particle implantation, post-operative follow-up using Kaplan-Meier method to calculate the rate of local control, and observation of complications. Univariate and multi-factorial analyses were performed with log-rank test and Cox regression statistical method to observe changes in serum SCC-Ag and CEA levels. Results: A total of 57 lesions in 46 patients had a short-term local control rate of 87.72% (50/57) and effective rate of 68.42% (39/57). As of the end of follow-up, the median local progression-free survival time of 46 patients was 12.2 (range, 3.5-32) months, the median overall survival time was 16.3 (range, 3.5-40) months, with 1-year and 2-year OS of 63.04% and 41.30%. Univariate and multi-factorial analyses suggested that local recurrent mass size and recurrence site were the main factors affecting survival. Loco-regional progression-free survival (LPFS) time was 15.5 and 11.25 months in cases with recurrent mass diameter < 3 cm and ≥ 3 cm, respectively (χ2 = 10.83, p = 0.001 < 0.05). In patients with pelvic wall recurrence and central recurrence, the time to LPFS was 15.80 and 10.00 months, respectively (χ2 = 8.833, p = 0.0030 < 0.05). Tumor markers serum SCC-Ag and CEA decreased to different degrees after treatment, and the difference was statistically significant. The median LPFS in the SCC-Ag ≤ 3.5 ng/ml group was significantly higher than that in the SCC-Ag > 3.5 ng/ml group (χ2 = 4.241, p = 0.036 < 0.05). No serious post-operative complications were observed. Conclusions: CT-guided 125I seed implantation has significant short-term efficacy in the treatment of pelvic local recurrence of cervical cancer after radiotherapy. It can improve the effective rate in patients with initial clinical stage II, especially in those with locally recurrent masses < 3 cm and in those with a recurrence in the pelvic wall.

Percutaneous transhepatic cholangial drainage combined with intra-tumoral iodine-125 seeds implantation and chemotherapy for locally progressive pancreatic head cancer with obstructive jaundice.

Purpose: To investigate the clinical efficacy of percutaneous transhepatic cholangial drainage (PTCD) combined with intra-tumoral iodine-125 (125I) particle implantation and chemotherapy in the treatment of locally advanced pancreatic head cancer (LAPHC) with obstructive jaundice. Material and methods: Twenty-one patients with LAPHC with obstructive jaundice were selected, and routine examination before surgery to determine location of obstruction and degree of bile duct dilatation was performed. All 21 patients underwent PTCD first, and usual examinations, including liver and kidney function, were re-examined after operation. When the liver function recovered significantly, patients were treated with seed implantation and systemic chemotherapy after surgery. Clinical efficacy and complications of 21 patients were observed, and changes in survival time and serum level of tumor markers were analyzed. Results: After combined treatment, there were 3 cases of complete response (CR), 12 cases of partial response (PR), 3 cases of stable disease (SD), and 3 cases of progressive disease (PD) in 21 patients. The overall effective rate was 71.43%, and the local control rate was 85.71%. The pain relief was statistically significant one month after treatment, compared with that before treatment (VAS scores: 6.76 ±2.25 vs. 3.25 ±1.92, p < 0.001), and the rate of pain relief was 71.43% (15/21). In all patients, jaundice, abdominal pain, and abdominal distension improved to different degrees after surgery, and the skin pruritus disappeared. Bilirubin and transaminase improved to varying degrees 3 days, 1 week, and 4 weeks after treatment (p < 0.05). Cancer antigen 199 (CA-199), carcinoembryonic antigen (CEA), and cancer antigen 125 (CA-125) after combination therapy, achieved statistically significant differences (t = 9.525, 10.378, 3.262, respectively, p < 0.05). The overall survival time of 21 patients was 11.6 months, ranging from 3.9 to 22.6 months. Conclusions: For LAPHC patients with obstructive jaundice, PTCD combined with particle implantation and chemotherapy is clinically effective in improving the quality of life and prolonging survival.

FunSwin: A deep learning method to analysis diabetic retinopathy grade and macular edema risk based on fundus images.

Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are forms of degenerative retinal disorders that may result in vision impairment or even permanent blindness. Early detection of these conditions is essential to maintaining a patient's quality of life. The fundus photography technique is non-invasive, safe, and rapid way of assessing the function of the retina. It is widely used as a diagnostic tool for patients who suffer from fundus-related diseases. Using fundus images to analyze these two diseases is a challenging exercise, since there are rarely obvious features in the images during the incipient stages of the disease. In order to deal with these issues, we have proposed a deep learning method called FunSwin. The Swin Transformer constitutes the main framework for this method. Additionally, due to the characteristics of medical images, such as their small number and relatively fixed structure, transfer learning strategy that are able to increase the low-level characteristics of the model as well as data enhancement strategy to balance the data are integrated. Experiments have demonstrated that the proposed method outperforms other state-of-the-art approaches in both binary and multiclass classification tasks on the benchmark dataset.

Primary Adrenal Sarcomatoid Carcinoma Detected by 18F-FDG PET/CT.

ABSTRACT: Adrenal sarcomatoid carcinoma is extremely rare. A 53-year-old man was admitted to our hospital due to pain in the upper right abdomen for 1 month. Abdominal CT revealed a huge mass in the right adrenal gland, and a malignancy was suspected. 18F-FDG PET/CT showed a mass in the right adrenal gland with intense FDG uptake. Finally, postoperative pathology confirmed the diagnosis of adrenal sarcomatoid carcinoma.

Antimicrobial limonoids from the seeds of Cipadessa cinerascensa.

Phytochemical investigation on the 90% EtOH extract of the seeds of Cipadessa cinerascensa led to the isolation of three new limonoids, cinerascenoids A-C (1-3). Structural elucidation of all the compounds were performed by spectral methods such as 1 D and 2 D (1H-1H COSY, HMQC, and HMBC) NMR spectroscopy. All the limonoids were in vitro evaluated for their antimicrobial activities against six pathogenic microorganisms. Limonoids 1 and 2 exhibited some activities against three Gram negative bacteria with MIC values less than 60 µg/ml.