The Transcription Factor Zfp335 Promotes Differentiation and Survival of Effector Th1 Cells by Directly Regulating Lmna Expression.

Ag-specific effector CD4+ T cells play a crucial role in defending against exogenous pathogens. However, the mechanisms governing the differentiation and function of IFN-γ-producing effector CD4+ Th1 cells in immune responses remain largely unknown. In this study, we elucidated the pivotal role of zinc finger protein 335 (Zfp335) in regulating effector Th1 cell differentiation and survival during acute bacterial infection. Mice with Zfp335 knockout in OT-II cells exhibited impaired Ag-specific CD4+ T cell expansion accompanied by a significant reduction in resistance to Listeria infection. Furthermore, Zfp335 deficiency restricted the effector CD4+ Th1 cell population and compromised their survival upon Listeria challenge. The expression of T-bet and IFN-γ was accordingly decreased in Zfp335-deficient Th1 cells. Mechanistically, Zfp335 directly bound to the promoter region of the Lmna gene and regulated its expression. Overexpression of Lmna was able to rescue the survival and function of Zfp335-deficient effector Th1 cells. Therefore, our study provides novel insights into the mechanisms governing effector Th1 cell differentiation and survival during acute infection.

Legumain-Triggered Macrocyclization of Radiofluorinated Tracer for Enhanced PET Imaging.

Enhancing the accumulation and retention of small-molecule probes in tumors is an important way to achieve accurate cancer diagnosis and therapy. Enzyme-stimulated macrocyclization of small molecules possesses great potential for enhanced positron emission tomography (PET) imaging of tumors. Herein, we reported an 18F-labeled radiotracer [18F]AlF-RSM for legumain detection in vivo. The tracer was prepared by a one-step aluminum-fluoride-restrained complexing agent ([18F]AlF-RESCA) method with high radiochemical yield (RCY) (88.35 ± 3.93%) and radiochemical purity (RCP) (>95%). More notably, the tracer can be transformed into a hydrophobic macrocyclic molecule under the joint action of legumain and reductant. Simultaneously, the tracer could target legumain-positive tumors and enhance accumulation and retention in tumors, resulting in the amplification of PET imaging signals. The enhancement of radioactivity enables PET imaging of legumain activity with high specificity. We envision that, by combining this highly efficient 18F-labeled strategy with our intramolecular macrocyclization reaction, a range of radiofluorinated tracers can be designed for tumor PET imaging and early cancer diagnosis in the future.

The comparative study of two new Schiff bases derived from 5-(thiophene-2-yl)isoxazole as "Off-On-Off" fluorescence sensors for the sequential detection of Ga3+ and Fe3+ ions.

Two new Schiff bases, TIC ((E)-N'-(2-hydroxybenzylidene)-5-(thiophene-2-yl)isoxazole-3-carbohydrazide) and TIE ((E)-N'-(3-ethoxy-2-hydroxybenzylidene)-5-(thiophene-2-yl)isoxazole-3-carbohydrazide), have been designed and synthesized as chemosensors for distinct recognition of Ga3+ and Fe3+ ions. TIE demonstrated a prominent "turn on" response characterized by clear distinguished fluorescence when coordination with Ga3+ ions in the DMSO/H2O buffer solution. In comparison, TIC also showed "turn on" response of blue fluorescence which was more selective and sensitive than that of TIE due to the steric hindrance of ethoxy group of TIE. The newly formed complexes TIC-Ga3+ and TIE-Ga3+ may act as selective "turn-off" fluorescent probes towards Fe3+ ions. Limits of detection of TIC and TIE towards Ga3+ ions were 7.8809 × 10-9 M and 2.6277 × 10-8 M, respectively. Limits of detection of TIC-Ga3+ and TIE-Ga3+ towards Fe3+ ions were 8.6562 × 10-9 M and 3.3764 × 10-7 M, respectively. The molar ratio of the complex between the sensor and Ga3+ or Fe3+ ions were all 1:2 determined through Job's Plot, mass spectrometry, and theoretical calculations. Both sensors were utilized for the determination of target ions in environment water samples, and the portable paper sensors for detecting Ga3+ ions have been successfully developed.

Near-infrared fluorescence-assisted superficial inguinal lymph-node excision for low-risk penile cancer.

OBJECTIVE: Identification of superficial inguinal lymph nodes during low-risk penile cancer surgery using near-infrared (NIR) fluorescence to improve the accuracy of lymph-node dissection and reduce the incidence of missed micrometastases and complications. METHODS: Thirty-two cases were selected, which were under the criteria of < T1, and no lymph-node metastasis was found with magnetic resonance imaging (MRI) detection. Two groups were randomly divided based on the fluorescence technique, the indocyanine green (ICG) group and the non-ICG group. In the ICG group, the ICG preparation was subcutaneously injected into the edge of the penile tumor 10 min before surgery, and the near-infrared fluorescence imager was used for observation. After the lymph nodes were visualized, the superficial inguinal lymph nodes were removed first, and then, the penis surgery was performed. The non-ICG group underwent superficial inguinal lymph-node dissection and penile surgery. RESULTS: Among the 16 patients in the ICG group, we obtained 11 lymph-node specimens using grayscale values of images (4.13 ± 0.72 vs. 3.00 ± 0.82 P = 0.003) along with shorter postoperative healing time (7.31 ± 1.08 vs. 8.88 ± 2.43 P = 0.025), and less lymphatic leakage (0 vs. 5 P = 0.04) than the 16 patients in the non-ICG group. Out of 11, 3 lymph nodes that are excised were further grouped into fluorescent and non-fluorescent regions (G1/G2) and found to be metastasized. CONCLUSION: Near-infrared fluorescence-assisted superficial inguinal lymph-node dissection in penile carcinoma is accurate and effective, and could reduce surgical complications.

Hemodynamic property incorporated brain tumor segmentation by deep learning and density-based analysis of dynamic susceptibility contrast-enhanced magnetic resonance imaging (MRI).

Background: Magnetic resonance imaging (MRI) is a primary non-invasive imaging modality for tumor segmentation, leveraging its exceptional soft tissue contrast and high resolution. Current segmentation methods typically focus on structural MRI, such as T1-weighted post-contrast-enhanced or fluid-attenuated inversion recovery (FLAIR) sequences. However, these methods overlook the blood perfusion and hemodynamic properties of tumors, readily derived from dynamic susceptibility contrast (DSC) enhanced MRI. This study introduces a novel hybrid method combining density-based analysis of hemodynamic properties in time-dependent perfusion imaging with deep learning spatial segmentation techniques to enhance tumor segmentation. Methods: First, a U-Net convolutional neural network (CNN) is employed on structural images to delineate a region of interest (ROI). Subsequently, Hierarchical Density-Based Scans (HDBScan) are employed within the ROI to augment segmentation by exploring intratumoral hemodynamic heterogeneity through the investigation of tumor time course profiles unveiled in DSC MRI. Results: The approach was tested and evaluated using a cohort of 513 patients from the open-source University of Pennsylvania glioblastoma database (UPENN-GBM) dataset, achieving a 74.83% Intersection over Union (IoU) score when compared to structural-only segmentation. The algorithm also exhibited increased precision and localized predictions of heightened segmentation boundary complexity, resulting in a 146.92% increase in contour complexity (ICC) compared to the reference standard provided by the UPENN-GBM dataset. Importantly, segmenting tumors with the developed new approach uncovered a negative correlation of the tumor volume with the scores in the Karnofsky Performance Scale (KPS) clinically used for assessing the functional status of patients (-0.309), which is not observed with the prevailing segmentation standard. Conclusions: This work demonstrated that including hemodynamic properties of tissues from DSC MRI can improve existing structural or morphological feature-based tumor segmentation techniques with additional information on tumor biology and physiology. This approach can also be applied to other clinical indications that use perfusion MRI for diagnosis or treatment monitoring.

Full-dose whole-body PET synthesis from low-dose PET using high-efficiency denoising diffusion probabilistic model: PET consistency model.

PURPOSE: Positron Emission Tomography (PET) has been a commonly used imaging modality in broad clinical applications. One of the most important tradeoffs in PET imaging is between image quality and radiation dose: high image quality comes with high radiation exposure. Improving image quality is desirable for all clinical applications while minimizing radiation exposure is needed to reduce risk to patients. METHODS: We introduce PET Consistency Model (PET-CM), an efficient diffusion-based method for generating high-quality full-dose PET images from low-dose PET images. It employs a two-step process, adding Gaussian noise to full-dose PET images in the forward diffusion, and then denoising them using a PET Shifted-window Vision Transformer (PET-VIT) network in the reverse diffusion. The PET-VIT network learns a consistency function that enables direct denoising of Gaussian noise into clean full-dose PET images. PET-CM achieves state-of-the-art image quality while requiring significantly less computation time than other methods. Evaluation with normalized mean absolute error (NMAE), peak signal-to-noise ratio (PSNR), multi-scale structure similarity index (SSIM), normalized cross-correlation (NCC), and clinical evaluation including Human Ranking Score (HRS) and Standardized Uptake Value (SUV) Error analysis shows its superiority in synthesizing full-dose PET images from low-dose inputs. RESULTS: In experiments comparing eighth-dose to full-dose images, PET-CM demonstrated impressive performance with NMAE of 1.278 ± 0.122%, PSNR of 33.783 ± 0.824 dB, SSIM of 0.964 ± 0.009, NCC of 0.968 ± 0.011, HRS of 4.543, and SUV Error of 0.255 ± 0.318%, with an average generation time of 62 s per patient. This is a significant improvement compared to the state-of-the-art diffusion-based model with PET-CM reaching this result 12× faster. Similarly, in the quarter-dose to full-dose image experiments, PET-CM delivered competitive outcomes, achieving an NMAE of 0.973 ± 0.066%, PSNR of 36.172 ± 0.801 dB, SSIM of 0.984 ± 0.004, NCC of 0.990 ± 0.005, HRS of 4.428, and SUV Error of 0.151 ± 0.192% using the same generation process, which underlining its high quantitative and clinical precision in both denoising scenario. CONCLUSIONS: We propose PET-CM, the first efficient diffusion-model-based method, for estimating full-dose PET images from low-dose images. PET-CM provides comparable quality to the state-of-the-art diffusion model with higher efficiency. By utilizing this approach, it becomes possible to maintain high-quality PET images suitable for clinical use while mitigating the risks associated with radiation. The code is availble at https://github.com/shaoyanpan/Full-dose-Whole-body-PET-Synthesis-from-Low-dose-PET-Using-Consistency-Model.

Automatic Detection of Scalp High-Frequency Oscillations Based on Deep Learning.

Scalp high-frequency oscillations (sHFOs) are a promising non-invasive biomarker of epilepsy. However, the visual marking of sHFOs is a time-consuming and subjective process, existing automatic detectors based on single-dimensional analysis have difficulty with accurately eliminating artifacts and thus do not provide sufficient reliability to meet clinical needs. Therefore, we propose a high-performance sHFOs detector based on a deep learning algorithm. An initial detection module was designed to extract candidate high-frequency oscillations. Then, one-dimensional (1D) and two-dimensional (2D) deep learning models were designed, respectively. Finally, the weighted voting method is used to combine the outputs of the two model. In experiments, the precision, recall, specificity and F1-score were 83.44%, 83.60%, 96.61% and 83.42%, respectively, on average and the kappa coefficient was 80.02%. In addition, the proposed detector showed a stable performance on multi-centre datasets. Our sHFOs detector demonstrated high robustness and generalisation ability, which indicates its potential applicability as a clinical assistance tool. The proposed sHFOs detector achieves an accurate and robust method via deep learning algorithm.

Take CT, get PET free: AI-powered breakthrough in lung cancer diagnosis and prognosis.

PET scans provide additional clinical value but are costly and not universally accessible. Salehjahromi et al.1 developed an AI-based pipeline to synthesize PET images from diagnostic CT scans, demonstrating its potential clinical utility across various clinical tasks for lung cancer.

A near-infrared fluorescence probe with large Stokes shift for selectively monitoring nitroreductase in living cells and mouse tumor models.

Hypoxia is commonly regarded as a typical feature of solid tumors, which originates from the insufficient supply of oxygen. Herein, the development of an efficient method for assessing hypoxia levels in tumors is strongly desirable. Nitroreductase (NTR) is an overexpressed reductase in the solid tumors, has been served as a potential biomarker to evaluate the degrees of hypoxia. In this work, we elaborately synthesized a new near-infrared (NIR) fluorescence probe (MR) to monitor NTR activity for assessment of hypoxia levels in living cells and in tumors. Upon exposure of NTR, the nitro-unit of MR could be selectively reduced to amino-moiety with the help of nicotinamide adenine dinucleotide. Moreover, the obtained fluorophore emitted a prominent NIR fluorescence, because it possessed a classical "push-pull" structure. The MR displayed several distinguished characters toward NTR, including intense NIR fluorescent signals, large Stokes shift, high selectivity and low limit of detection (46 ng/mL). Furthermore, cellular confocal fluorescence imaging results validated that the MR had potential of detecting NTR levels in hypoxic cells. Significantly, using the MR, the elevated of NTR levels were successfully visualized in the tumor-bearing mouse models. Therefore, this detecting platform based on this probe may be tactfully constructed for monitoring the variations of NTR and estimating the degrees of hypoxia in tumors.

High-resolution 3T to 7T ADC map synthesis with a hybrid CNN-transformer model.

BACKGROUND: 7 Tesla (7T) apparent diffusion coefficient (ADC) maps derived from diffusion-weighted imaging (DWI) demonstrate improved image quality and spatial resolution over 3 Tesla (3T) ADC maps. However, 7T magnetic resonance imaging (MRI) currently suffers from limited clinical unavailability, higher cost, and increased susceptibility to artifacts. PURPOSE: To address these issues, we propose a hybrid CNN-transformer model to synthesize high-resolution 7T ADC maps from multimodal 3T MRI. METHODS: The Vision CNN-Transformer (VCT), composed of both Vision Transformer (ViT) blocks and convolutional layers, is proposed to produce high-resolution synthetic 7T ADC maps from 3T ADC maps and 3T T1-weighted (T1w) MRI. ViT blocks enabled global image context while convolutional layers efficiently captured fine detail. The VCT model was validated on the publicly available Human Connectome Project Young Adult dataset, comprising 3T T1w, 3T DWI, and 7T DWI brain scans. The Diffusion Imaging in Python library was used to compute ADC maps from the DWI scans. A total of 171 patient cases were randomly divided into 130 training cases, 20 validation cases, and 21 test cases. The synthetic ADC maps were evaluated by comparing their similarity to the ground truth volumes with the following metrics: peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and mean squared error (MSE). In addition, RESULTS: The results are as follows: PSNR: 27.0 ± 0.9 dB, SSIM: 0.945 ± 0.010, and MSE: 2.0E-3 ± 0.4E-3. Both qualitative and quantitative results demonstrate that VCT performs favorably against other state-of-the-art methods. We have introduced various efficiency improvements, including the implementation of flash attention and training on 176×208 resolution images. These enhancements have resulted in the reduction of parameters and training time per epoch by 50% in comparison to ResViT. Specifically, the training time per epoch has been shortened from 7.67 min to 3.86 min. CONCLUSION: We propose a novel method to predict high-resolution 7T ADC maps from low-resolution 3T ADC maps and T1w MRI. Our predicted images demonstrate better spatial resolution and contrast compared to 3T MRI and prediction results made by ResViT and pix2pix. These high-quality synthetic 7T MR images could be beneficial for disease diagnosis and intervention, producing higher resolution and conformal contours, and as an intermediate step in generating synthetic CT for radiation therapy, especially when 7T MRI scanners are unavailable.

Achieving robust synthetic tolerance in industrial E. coli through negative auto-regulation of a DsrA-Hfq module.

In industrial fermentation processes, microorganisms often encounter acid stress, which significantly impact their productivity. This study focused on the acid-resistant module composed of small RNA (sRNA) DsrA and the sRNA chaperone Hfq. Our previous study had shown that this module improved the cell growth of Escherichia coli MG1655 at low pH, but failed to obtain this desired phenotype in industrial strains. Here, we performed a quantitative analysis of DsrA-Hfq module to determine the optimal expression mode. We then assessed the potential of the CymR-based negative auto-regulation (NAR) circuit for industrial application, under different media, strains and pH levels. Growth assay at pH 4.5 revealed that NAR-05D04H circuit was the best acid-resistant circuit to improve the cell growth of E. coli MG1655. This circuit was robust and worked well in the industrial lysine-producing strain E. coli SCEcL3 at a starting pH of 6.8 and without pH control, resulting in a 250 % increase in lysine titer and comparable biomass in shaking flask fermentation compared to the parent strain. This study showed the practical application of NAR circuit in regulating DsrA-Hfq module, effectively and robustly improving the acid tolerance of industrial strains, which provides a new approach for breeding industrial strains with tolerance phenotype.

GTPBP8 modulates mitochondrial fission through a Drp1-dependent process.

Mitochondrial fission is a tightly regulated process involving multiple proteins and cell signaling. Despite extensive studies on mitochondrial fission factors, our understanding of the regulatory mechanisms remains limited. This study shows the critical role of a mitochondrial GTPase, GTPBP8, in orchestrating mitochondrial fission. Depletion of GTPBP8 resulted in drastic elongation and interconnectedness of mitochondria. Conversely, overexpression of GTPBP8 shifted mitochondrial morphology from tubular to fragmented. Notably, the induced mitochondrial fragmentation from GTPBP8 overexpression was inhibited in cells either depleted of the mitochondrial fission protein Drp1 or carrying mutated forms of Drp1. Importantly, downregulation of GTPBP8 caused an increase in oxidative stress, modulating cell signaling involved in the heightened phosphorylation of Drp1 at Ser637. This phosphorylation hindered the recruitment of Drp1 to mitochondria, leading to mitochondrial fission defects. On the other hand, GTPBP8 overexpression triggered enhanced recruitment and assembly of Drp1 to mitochondria. In summary, our study illuminates the cellular function of GTPBP8 as a pivotal modulator of the mitochondrial division apparatus, inherently reliant on its influence on Drp1.

Intracorporeal versus extracorporeal anastomosis in laparoscopic right hemicolectomy for overweight colon cancer patients: a case-control study.

INTRODUCTION: Either extracorporeal anastomosis (EA) or intracorporeal anastomosis (IA) could be selected for digestive reconstruction in laparoscopic right hemicolectomy (LRH). However, whether LRH with IA is feasible and beneficial for overweight right-side colon cancer (RCC) is unclear. This study aims to investigate the feasibility and advantage of IA in LRH for overweight RCC. METHODS: Forty-eight consecutive overweight RCC patients undergoing LRH with IA were matched with 48 consecutive cases undergoing LRH with EA. Both clinical and surgical data were collected and analyzed. RESULTS: The incidence of postoperative complications was 20.8% (10/48) in the EA group and 14.6% (7/48) in the IA group respectively, with no statistical difference. Compared to the EA group, patients in the IA group revealed faster gas (40.2 + 7.8 h vs. 45.6 + 7.9 h, P = 0.001) and stool discharge (4.0 + 1.2 d vs. 4.5 + 1.1 d, P = 0.040), shorter assisted incision (5.3 + 1.3 cm vs. 7.5 + 1.2 cm, P = 0.000), and less analgesic used (3.3 + 1.3 d vs. 4.0 + 1.3 d, P = 0.012). There were no significant differences in operation time, blood loss, or postoperative hospital stays. In the IA group, the first one third of cases presented longer operation time (228.4 + 29.3 min) compared to the middle (191.0 + 35.0 min, P = 0.003) and the last one third of patients (182.2 + 20.7 min, P = 0.000). CONCLUSION: LRH with IA is feasible and safe for overweight RCC, with faster bowel function recovery and less pain. Accumulation of certain cases of LRH with IA will facilitate surgical procedures and reduce operation time.

Advancing medical imaging with language models: featuring a spotlight on ChatGPT.

This review paper aims to serve as a comprehensive guide and instructional resource for researchers seeking to effectively implement language models in medical imaging research. First, we presented the fundamental principles and evolution of language models, dedicating particular attention to large language models. We then reviewed the current literature on how language models are being used to improve medical imaging, emphasizing a range of applications such as image captioning, report generation, report classification, findings extraction, visual question response systems, interpretable diagnosis and so on. Notably, the capabilities of ChatGPT were spotlighted for researchers to explore its further applications. Furthermore, we covered the advantageous impacts of accurate and efficient language models in medical imaging analysis, such as the enhancement of clinical workflow efficiency, reduction of diagnostic errors, and assistance of clinicians in providing timely and accurate diagnoses. Overall, our goal is to have better integration of language models with medical imaging, thereby inspiring new ideas and innovations. It is our aspiration that this review can serve as a useful resource for researchers in this field, stimulating continued investigative and innovative pursuits of the application of language models in medical imaging.

Evaluation of Laparoscopic Colorectal Resection Among Elderly Individuals With Colorectal Malignancy: A Single-center Retrospective Analysis.

OBJECTIVE: The purpose of the current study was to statistically clarify the precise risk age in elderly patients undergoing colorectal surgery and to evaluate the safety and efficacy of laparoscopic colorectal resection in these patients. METHODS: Patients' clinical variables were extracted from the database of the Gastrointestinal Surgery Centre, Third Affiliated Hospital of Sun Yat-sen University, from 2015 to 2019. Logistic regression was conducted to identify independent risk factors of postoperative complications and ORs for each age. Curves of odds ratios (ORs) and CIs for each age were fitted by using a locally weighted scatterplot smoother, and a structural breakpoint was determined by the Chow test to identify a precise cutoff risk age for elderly patients. Comparison and subgroup analysis were conducted between surgical approach groups using the Student ttest and χ2 analysis. RESULTS: Locally weighted scatterplot smoother OR analysis manifested that patients aged 69 years old or older suffered a higher possibility of postoperative complications and should be defined as high-risk age. Comparison according to the high-risk age revealed laparoscopic colorectal surgery is better than laparotomic surgery for elderly individuals in terms of hospital stay (9.46 ± 5.96 vs 15.01 ± 6.34, P< 0.05), the incidence of intensive care unit transfer (4 vs 20, P< 0.05), and incidence of surgical site infection (15 vs 20, P< 0.05). Patients who underwent laparotomic surgery had a greater prevalence of Clavien-Dindo II/III complications (P< 0.05). These findings remained stable even after propensity matching. Furthermore, such superiority was proved especially significant for patients who underwent left-side colorectal resection. In addition, overall survival was improved in the laparoscopic surgery group, whereas no differences were observed in disease-free survival. CONCLUSION: In our study population, age 69 or older was a cutoff point age suggests a higher possibility of postoperative morbidity after colorectal surgery. Laparoscopic colorectal resection should be regarded as a superior therapeutic choice for these elderly individuals, especially for left-side colorectal surgeries.

A molecular view of single-atom catalysis toward carbon dioxide conversion.

Carbon dioxide (CO2) conversion has attracted much interest recently owing to its importance in both scientific research and practical applications, but still faces a bottleneck in selectivity control and mechanism understanding owing to diversified active sites. Single-atom catalysts (SACs) featuring isolated and well-defined active centers are proved to not only exhibit unparalleled performances in various processes of CO2 conversion but also provide excellent research paradigms by circumventing the heterogeneity of active sites. Herein, we will not only critically review recent progress on the application of SACs in chemical CO2 conversion based on previous comprehension of general thermodynamics and kinetics, but also try to offer a multi-level understanding of SACs from a molecular point of view in terms of the central atom, coordination environment, support effect and synergy with other active centers. Meanwhile, crucial scientific issues of research methods will be also identified and highlighted, followed by a future outlook that is expected to present potential aspects of further developments.

Analysis of clinical data of different endometrial pathological types in perimenopausal women with abnormal uterine bleeding.

Objective: Early detection and diagnosis are important for improving the therapeutic effect and quality of life in patients with endometrial cancer (EC). This study aimed to analyze the clinical data of different endometrial pathological types in perimenopausal women with abnormal uterine bleeding (AUB) in order to provide evidence for the prevention and early diagnosis of EC. Methods: A total of 462 perimenopausal women with AUB were enrolled in this prospective observational study. Endometrial biopsy was performed in patients with suspected endometrial lesions. According to the pathological examination results, the patients were divided into endometrial polyp group (EP) (n = 71), endometrial hyperplasia without atypia group (EH) (n = 59), atypical endometrial hyperplasia (AEH) (n = 36), and EC group (n = 27). The history risk factors and ultrasonic imaging characteristics of endometrium among the four groups were compared. Results: Twenty-seven women were diagnosed with EC (5.84%). The prevalence rate of AEH and EC in the group of 51- to 55-year-old women was significantly higher than that in the groups of 40- to 45-year-old women and of 46- to 50-year-old women (P < 0.05). The age, body mass index, and history of diabetes gradually increased with the development of endometrial pathological types. In addition, the correlation index of endometrial blood flow increased gradually, and the proportion of uneven endometrial echo, unclear endometrial-myometrial junction (EMJ), and ovarian cyst also increased gradually. However, no statistically significant difference was found when comparing endometrial thickness (ET) and endometrial volume (EV) among endometrial pathological groups (P > 0.05). The ET, EV, endometrial vascularization index, endometrial flow index, and vascularization flow index in the ovarian cyst group were significantly higher (P < 0.05), and the proportion of uneven endometrium echo and unclear EMJ were significantly higher compared with that in the non-ovarian cyst group (P < 0.05). Conclusions: The most common cause of perimenopausal women with AUB was benign endometrial lesions. However, women aged 51-55 years old with endometrial high risk factors and ovarian cyst should be alert to AEH and EC. Endometrial biopsy needs to be performed to determine endometrial malignancy in necessity.

Causal relationship between gestational diabetes and preeclampsia: A bidirectional mendelian randomization analysis.

AIMS: The study aimed to explore the potential causal link between gestational diabetes mellitus (GDM) and preeclampsia (PE) using a bidirectional mendelian randomization (MR) analysis. MATERIALS: We conducted a bidirectional MR analysis to investigate the causal relationship between GDM and PE. Data from public genome-wide association studies (GWAS) for GDM and PE were obtained from the FinnGen consortium. Various MR methods were employed, including inverse-variance weighted (IVW), MR-Egger, and sensitivity analyses. Additionally, a knowledge-based approach identified genes underlying this potential connection. RESULTS: The IVW method revealed a lack of significant association between GDM and PE (OR: 1.04, 95 % CI: 0.96-1.14; p = 0.275). Conversely, IVW analysis indicated a causal connection from PE to GDM (OR: 1.14, 95 % CI: 1.06-1.23; p < 0.001). Molecular pathway analysis identified 20 key genes, including ASAP2, central to the PE-GDM relationship. Tissue enrichment analysis showed pertinent gene expression in significant tissues. Moreover, lower ASAP2 expression was detected in PE patients' placentas. CONCLUSIONS: Our bidirectional MR analysis offers evidence supporting a causal link between PE and GDM, elucidating their interconnected pathogenesis. Genetic and knowledge-based insights facilitate a deeper comprehension of these complex pregnancy complications.

Quantifying carboxymethyl lysine and carboxyethyl lysine in human plasma: clinical insights into aging research using liquid chromatography-tandem mass spectrometry.

OBJECTIVE: The objective of this study was to establish a methodology for determining carboxymethyl lysine (CML) and carboxyethyl lysine (CEL) concentrations in human plasma using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The test results were also used for clinical aging research. METHODS: Human plasma samples were incubated with aqueous perfluorovaleric acid (NFPA), succeeded by precipitation utilizing trichloroacetic acid, hydrolysis facilitated by hydrochloric acid, nitrogen drying, and ultimate re-dissolution utilizing NFPA, followed by filtration. Cotinine-D3 was added as an internal standard. The separation was performed on an Agela Venusil ASB C18 column (50 mm × 4.6 mm, 5 µm) with a 5 mmol/L NFPA and acetonitrile/water of 60:40 (v/v) containing 0.15% formic acid. The multiple reaction monitoring mode was used for detecting CML, CEL, and cotinine-D3, with ion pairs m/z 205.2 > 84.1 (for quantitative) and m/z 205.2 > m/z 130.0 for CML, m/z 219.1 > 84.1 (for quantitative) and m/z 219.1 > m/z 130.1 for CEL, and m/z 180.1 > 80.1 for cotinine-D3, respectively. RESULTS: The separation of CML and CEL was accomplished within a total analysis time of 6 minutes. The retention times of CML, CEL, and cotinine-D3 were 3.43 minutes, 3.46 minutes, and 4.50 minutes, respectively. The assay exhibited linearity in the concentration range of 0.025-1.500 µmol/L, with a lower limit of quantification of 0.025 µmol/L for both compounds. The relative standard deviations of intra-day and inter-day were both below 9%, and the relative errors were both within the range of ±4%. The average recoveries were 94.24% for CML and 97.89% for CEL. CONCLUSION: The results indicate that the developed methodology is fast, highly sensitive, highly specific, reproducible, and suitable for the rapid detection of CML and CEL in clinical human plasma samples. The outcomes of the clinical research project on aging underscored the important indicative significance of these two indicators for research on human aging.

Alterations in HCN1 expression and distribution during epileptogenesis in rats.

BACKGROUND: The hyperpolarization-activated cyclic nucleotide-gated cation channel (HCN1) is predominantly located in key regions associated with epilepsy, such as the neocortex and hippocampus. Under normal physiological conditions, HCN1 plays a crucial role in the excitatory and inhibitory regulation of neuronal networks. In temporal lobe epilepsy, the expression of HCN1 is decreased in the hippocampi of both animal models and patients. However, whether HCN1 expression changes during epileptogenesis preceding spontaneous seizures remains unclear. OBJECTIVE: The aim of this study was to determine whether the expression of HCN1 is altered during the epileptic prodromal phase, thereby providing evidence for its role in epileptogenesis. METHODS: We utilized a cobalt wire-induced rat epilepsy model to observe changes in HCN1 during epileptogenesis and epilepsy. Additionally, we also compared HCN1 alterations in epileptogenic tissues between cobalt wire- and pilocarpine-induced epilepsy rat models. Long-term video EEG recordings were used to confirm seizures development. Transcriptional changes, translation, and distribution of HCN1 were assessed using high-throughput transcriptome sequencing, total protein extraction, membrane and cytoplasmic protein fractionation, western blotting, immunohistochemistry, and immunofluorescence techniques. RESULTS: In the cobalt wire-induced rat epilepsy model during the epileptogenesis phase, total HCN1 mRNA and protein levels were downregulated. Specifically, the membrane expression of HCN1 was decreased, whereas cytoplasmic HCN1 expression showed no significant change. The distribution of HCN1 in the distal dendrites of neurons decreased. During the epilepsy period, similar HCN1 alterations were observed in the neocortex of rats with cobalt wire-induced epilepsy and hippocampus of rats with lithium pilocarpine-induced epilepsy, including downregulation of mRNA levels, decreased total protein expression, decreased membrane expression, and decreased distal dendrite expression. CONCLUSIONS: Alterations in HCN1 expression and distribution are involved in epileptogenesis beyond their association with seizure occurrence. Similarities in HCN1 alterations observed in epileptogenesis-related tissues from different models suggest a shared pathophysiological pathway in epileptogenesis involving HCN1 dysregulation. Therefore, the upregulation of HCN1 expression in neurons, maintenance of the HCN1 membrane, and distal dendrite distribution in neurons may represent promising disease-modifying strategies in epilepsy.