Optical coherence tomography choroidal enhancement using generative deep learning.

Spectral-domain optical coherence tomography (SDOCT) is the gold standard of imaging the eye in clinics. Penetration depth with such devices is, however, limited and visualization of the choroid, which is essential for diagnosing chorioretinal disease, remains limited. Whereas swept-source OCT (SSOCT) devices allow for visualization of the choroid these instruments are expensive and availability in praxis is limited. We present an artificial intelligence (AI)-based solution to enhance the visualization of the choroid in OCT scans and allow for quantitative measurements of choroidal metrics using generative deep learning (DL). Synthetically enhanced SDOCT B-scans with improved choroidal visibility were generated, leveraging matching images to learn deep anatomical features during the training. Using a single-center tertiary eye care institution cohort comprising a total of 362 SDOCT-SSOCT paired subjects, we trained our model with 150,784 images from 410 healthy, 192 glaucoma, and 133 diabetic retinopathy eyes. An independent external test dataset of 37,376 images from 146 eyes was deployed to assess the authenticity and quality of the synthetically enhanced SDOCT images. Experts' ability to differentiate real versus synthetic images was poor (47.5% accuracy). Measurements of choroidal thickness, area, volume, and vascularity index, from the reference SSOCT and synthetically enhanced SDOCT, showed high Pearson's correlations of 0.97 [95% CI: 0.96-0.98], 0.97 [0.95-0.98], 0.95 [0.92-0.98], and 0.87 [0.83-0.91], with intra-class correlation values of 0.99 [0.98-0.99], 0.98 [0.98-0.99], and 0.95 [0.96-0.98], 0.93 [0.91-0.95], respectively. Thus, our DL generative model successfully generated realistic enhanced SDOCT data that is indistinguishable from SSOCT images providing improved visualization of the choroid. This technology enabled accurate measurements of choroidal metrics previously limited by the imaging depth constraints of SDOCT. The findings open new possibilities for utilizing affordable SDOCT devices in studying the choroid in both healthy and pathological conditions.

Petersen's hernia after gastric cancer surgery: Unravelling clinical characteristics and optimal management approaches.

INTRODUCTION: Petersen's hernia is a rare and serious complication that can occur after radical gastrectomy and digestive tract reconstruction for gastric cancer. This article summarises the symptoms, diagnosis and treatment of Petersen's hernia after surgery for gastric cancer. PATIENTS AND METHODS: A retrospective analysis was conducted on 11 male patients who were diagnosed with Petersen's hernia and underwent surgical treatment at our hospital from January 2020 to December 2022. Their clinical manifestations, perioperative conditions and follow-up after treatment were collected. RESULTS: The median age was 58.5 years (range: 45-73), and the median time since gastrectomy was 24 months (range: 4-125). Open distal gastrectomy (45.5%) and open total gastrectomy (27.3%) were the most common procedures. Roux-en-Y (81.8%) was the predominant anastomosis method. All patients underwent emergency surgery within a median time of 30 h (range: 4-45). Intestine necrosis occurred in 36.4% of cases, with a perioperative death rate of 27.3%. CONCLUSION: Petersen's hernia after gastric cancer surgery can quickly lead to necrotising intestinal obstruction and poor prognosis. Enhanced abdominal computed tomography should be performed as soon as possible, and early exploratory laparotomy should be done to avoid intestinal necrosis. Routine closure of the mesenteric defect after gastric cancer resection can prevent the occurrence of Petersen's hernia. This article highlights the need for increased awareness and preventive measures to minimise the occurrence of Petersen's hernia in gastric cancer patients. It emphasises the importance of early detection and appropriate management strategies for improved patient outcomes.

Modulating the default mode network: Antidepressant efficacy of transcutaneous electrical cranial-auricular acupoints stimulation targeting the insula.

BACKGROUND: Transcutaneous electrical cranial-auricular acupoint stimulation (TECAS) is a novel non-invasive therapy for major depressive disorder (MDD) that stimulates acupoints innervated by the trigeminal and auricular vagus nerves. However, there are few neuroimaging studies involving the TECAS for the treatment of MDD. Therefore, this study aimed to investigate the treatment response and neurological effects of TECAS using resting-state functional magnetic resonance imaging (rs-fMRI). METHOD: A total of 34 patients with mild-to-moderate MDD and 34 demographically matched healthy controls (HCs) were recruited. After an eight-week treatment the primary outcome was clinical response, defined as a baseline-to-endpoint ≥ 50 % reduction in the 17-item Hamilton Depression Rating Scale (HAMD-17). The low-frequency fluctuations (ALFF) method were used to investigate the brain abnormalities of MDD patients and HCs, and altered brain networks were analyzed between pre- and post-treatment using seed-based functional connectivity (FC) analysis. RESULTS: We found no significant differences in terms of gender, age, and years of education between the two groups. After treatment, the response rate was 58.82 %. Compared to HCs, MDD patients showed lower ALFF values in the left insula(t = -4.298,P < 0.005), the insula-based FC revealed in the right middle frontal gyrus (MFG)/ right superior frontal gyrus, orbital part (ORBsupmed) (t = -5.29,P < 0.005) and the right anterior cingulate gyrus (ACC)were decreased (t = -6.08,P < 0.005). Furthermore, Compared to pre-treatment, abnormal FC values in the ACC /orbital superior frontal gyrus (SFG) (t = 3.42,P < 0.005) and left superior frontal gyrus (SFG)/ supplement motor area (SMA) were enhanced (t = 3.34,P < 0.005). CONCLUSION: TECAS exhibits antidepressant efficacy, particularly influencing the insula-based functional connections within the Default Mode Network (DMN) related to emotion processing in individuals with MDD.

Identification and expression analysis of TCP family members in tobacco (Nicotiana tabacum L.) / 生物工程学报

TCP family as plant specific transcription factor, plays an important role in different aspects of plant development. In order to screen TCP family members in tobacco, the homologous sequences of tobacco and Arabidopsis TCP family were identified by genome-wide homologous alignment. The physicochemical properties, phylogenetic relationships and cis-acting elements were analyzed by bioinformatics. The homologous genes of AtTCP3/AtTCP4 were screened, and RT-qPCR was used to detect the changes of gene expression upon 20% PEG6000 treatment. The results show that tobacco contains 63 TCP family members. Their amino acid sequence length ranged from 89 aa to 596 aa, and their protein hydropathicity grand average of hydropathicity (GRAVY) ranged from -1.147 to 0.125. The isoelectric point (pI) ranges from 4.42 to 9.94, the number of introns is 0 to 3, and the subcellular location is all located in the nucleus. The results of conserved domain and phylogenetic relationship analysis showed that the tobacco TCP family can be divided into PCF, CIN and CYC/TB1 subfamilies, and each subfamily has a stable sequence. The results of cis-acting elements in gene promoter region showed that TCP family genes contain low docile acting elements (LTR) and a variety of stress and metabolic regulation related elements (MYB, MYC). Analysis of gene expression patterns showed that AtTCP3/AtTCP4 homologous genes (NtTCP6, NtTCP28, NtTCP30, NtTCP33, NtTCP42, NtTCP57, NtTCP63) accounted for 20% PEG6000 treatment significantly up-regulated/down-regulated expression, and NtTCP30 and NtTCP57 genes were selected as candidate genes in response to drought. The results of this study analyzed the TCP family in the tobacco genome and provided candidate genes for the study of drought-resistance gene function and variety breeding in tobacco.

Recent advances in small-molecule inhibitors targeting influenza virus RNA-dependent RNA polymerase / 药学学报

Influenza virus causes serious threat to human life and health. Due to the inherent high variability of influenza virus, clinically resistant mutant strains of currently approved anti-influenza virus drugs have emerged. Therefore, it is urgent to develop antiviral drugs with new targets or mechanisms of action. RNA-dependent RNA polymerase is directly responsible for viral RNA transcription and replication, and plays key roles in the viral life cycle, which is considered an important target of anti-influenza drug design. From the point of view of medicinal chemistry, this review summarizes current advances in diverse small-molecule inhibitors targeting influenza virus RNA-dependent RNA polymerase, hoping to provide valuable reference for development of novel antiviral drugs.

Recent advances in drug screening methods of SARS-CoV-2 spike protein / 药学学报

The pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a serious impact on global public health and the economy. SARS-CoV-2 infiltrates host cells via its surface spike protein, which binds to angiotensin-converting enzyme 2 on the host cell membrane. As a result, small molecules targeting spike protein have emerged as a hotspot in anti-SARS-CoV-2 drug research. Activity screening is an important step in seeking small molecule drugs. Therefore, this article aims to review the biological activity evaluation methods of small molecule inhibitors targeting SARS-CoV-2 spike protein, with the goal of laying the foundation for the discovery of new anti-SARS-CoV-2 drugs.

Research progress of anti-gout small molecules targeting the NLRP3 inflammasome / 药学学报

Currently, clinically used drugs for the treatment of gout inflammation, such as colchicine, nonsteroidal anti-inflammatory drugs, and glucocorticoids, can only relieve the pain of joint inflammation and have severe hepatorenal toxicity and multiple organ adverse reactions. The NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome is a key complex that induces the onset of gout inflammation and has become a crucial target in the development of anti-gout drugs. This article reviews the research progress of anti-gout small molecules targeting the NLRP3 inflammasome and their bioactivity evaluation methods in the past five years, in order to provide information for the development of specific drugs for the treatment of gout inflammation.

Advances in peripheral defocus and myopia prevention and control / 国际眼科杂志(Guoji Yanke Zazhi)

The global prevalence of myopia is increasing year by year, leading to many ocular health issues and social problems. In recent years, it has been confirmed that peripheral defocus is closely related to the occurrence and development of myopia. Alteration of the state of peripheral defocus can significantly influence the progression of myopia and emmetropization, but the exact mechanisms are still unclear. At present, there is no method that can completely control myopia. Nowadays, the main controlling methods, including orthokeratology lens, peripheral defocus lens and multi-focal soft lens, have been confirmed to be closely related to peripheral defocus. In this paper, we will review and summarize the development and effect of these peripheral defocus relating control methods. In addition, the researches on the related mechanisms of peripheral retinal defocus and myopia prevention and control at home and abroad are reviewed, as well as the potential mechanisms of peripheral defocus, with a view to further improving the controlling effects of existing methods, developing new prevention and control methods and reducing the incidence and progression of myopia.

Compound Dahuang Baiji Spray Improves Acute Radiodermatitis by Down-Regulating the Expression of ALOX5.

Acute radiodermatitis is a type of skin injury caused by tumor radiotherapy. Compound Dahuang Baiji spray (CDBS) is a traditional Chinese medicine spray made from Dahuang and Baiji decoction. In the present study, we aimed to investigate the effects and mechanisms of CDBS on radiation dermatitis. We analyzed the main components of CDBS using High Performance Liquid Chromatography (HPLC). Through network pharmacology prediction, the target of Dahuang and Baiji was identified as arachidonate 5-lipoxygenase (ALOX5), associated with inflammation. Therefore, we constructed radiodermatitis rat models and treated them with CDBS for 14 d. Skin samples were collected from the rats' injured skin tissues, and pathological changes, oxidative stress indicators, inflammatory cytokines, and ALOX5 expression were detected using techniques such as HE staining, blood parameters analysis, ELISA, Real-time qPCR, and Western blot. The characteristic appearances of radiodermatitis were observed in different rat groups which indicated that the skin injury score in the model group was at grade II and was at grade I in the CDBS group. In addition, the HE results showed that CDBS reduced the necrosis of collagen fibers and inflammatory cell infiltration in the dermis of the radiodermatitis rats. Moreover, compared to the model group, CDBS significantly decreased leukocytes, lymphocytes, and neutrophils in the blood, as well as levels of IL-2, LTB4, 5-LO, NO, and ALOX5 expression in rat blood. Our findings suggest the therapeutic effect of CDBS on radiodermatitis by downregulating ALOX5 to inhibit inflammation, potentially serving as a radiodermatitis therapy.

Predicting glaucoma progression using deep learning framework guided by generative algorithm.

Glaucoma is a slowly progressing optic neuropathy that may eventually lead to blindness. To help patients receive customized treatment, predicting how quickly the disease will progress is important. Structural assessment using optical coherence tomography (OCT) can be used to visualize glaucomatous optic nerve and retinal damage, while functional visual field (VF) tests can be used to measure the extent of vision loss. However, VF testing is patient-dependent and highly inconsistent, making it difficult to track glaucoma progression. In this work, we developed a multimodal deep learning model comprising a convolutional neural network (CNN) and a long short-term memory (LSTM) network, for glaucoma progression prediction. We used OCT images, VF values, demographic and clinical data of 86 glaucoma patients with five visits over 12 months. The proposed method was used to predict VF changes 12 months after the first visit by combining past multimodal inputs with synthesized future images generated using generative adversarial network (GAN). The patients were classified into two classes based on their VF mean deviation (MD) decline: slow progressors (< 3 dB) and fast progressors (> 3 dB). We showed that our generative model-based novel approach can achieve the best AUC of 0.83 for predicting the progression 6 months earlier. Further, the use of synthetic future images enabled the model to accurately predict the vision loss even earlier (9 months earlier) with an AUC of 0.81, compared to using only structural (AUC = 0.68) or only functional measures (AUC = 0.72). This study provides valuable insights into the potential of using synthetic follow-up OCT images for early detection of glaucoma progression.

Based on the multi-scale information sharing network of fine-grained attention for agricultural pest detection.

It is of great significance to identify the pest species accurately and control it effectively to reduce the loss of agricultural products. The research results of this project will provide theoretical basis for preventing and controlling the spread of pests and reducing the loss of agricultural products, and have important practical significance for improving the quality of agricultural products and increasing the output of agricultural products. At the same time, it provides a kind of effective prevention and control measures for farmers, so as to ensure the safety and health of crops. Because of the slow speed and high cost of manual identification, it is necessary to establish a set of automatic pest identification system. The traditional image-based insect classifier is mainly realized by machine vision technology, but because of its high complexity, the classification efficiency is low and it is difficult to meet the needs of applications. Therefore, it is necessary to develop a new automatic insect recognition system to improve the accuracy of insect classification. There are many species and forms of insects, and the field living environment is complex. The morphological similarity between species is high, which brings difficulties to the classification of insects. In recent years, with the rapid development of deep learning technology, using artificial neural network to classify pests is an important method to establish a fast and accurate classification model. In this work, we propose a novel convolutional neural network-based model (MSSN), which includes attention mechanism, feature pyramid, and fine-grained model. The model has good scalability, can better capture the semantic information in the image, and achieve more accurate classification. We evaluated our approach on a common data set: large-scale pest data set, PlantVillage benchmark data set, and evaluated model performance using a variety of evaluation indicators, namely, macro mean accuracy (MPre), macro mean recall rate (MRec), macro mean F1-score (MF1), Accuracy (Acc) and geometric mean (GM). Experimental results show that the proposed algorithm has better performance and universality ability than the existing algorithm. For example, on the data set, the maximum accuracy we obtained was 86.35%, which exceeded the corresponding technical level. The ablation experiment was conducted on the experiment itself, and the comprehensive evaluation of the complete MSSN(scale 1+2+3) was the best in various performance indexes, demonstrating the feasibility of the innovative method in this paper.

Zhenxin Anshen formula ameliorates atopic der-matitis-like skin dysfunction in mice and regulation of transient receptor potential vanilloid 1 and transient receptor potential ankyrin 1 in Neural pathways.

OBJECTIVE: To investigate the efficacy of Zhenxin Anshen formula (, ZXAS) on atopic dermatitis (AD) by transient receptor potential vanilloid 1 (TRPV1) and transient receptor potential ankyrin 1 (TRPA1) signalling pathway in mice and . METHODS: AD-like lesions were induced by 1-chloro-2,4-dinitrobenzene (DNCB) to the shaved dorsal skin of BALB/c mice. BALB/c mice were divided into five groups: normal control, model control, cetirizine, low-, medium-, and high-dose of ZXAS. After ZXAS in-tervention, the skin lesions and blood samples were collected for hematoxylin and eosin-stained and measuring the concentrations of inflammatory cytokines. Immun-oglobulin E (IgE), interleukin (IL)-4, IL-5, IL-13, and thymic stromal lymphopoietin (TSLP) were de-tected by Enzyme-linked immunosorbent assay (ELISA). The spinal cords were collected for measuring the expression of gastrin-releasing peptide receptor (GRPR), TRPV1, and TRPA1 by using immunohistochemistry, western blotting, and quantitative real-time polymerase chain reaction (qRT-PCR) analyses. In addition, 3-(4,5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide (MTT) assay, flow cytometry, ELISA, and Western blotting were conducted for analysis of primary dorsal root ganglia (DRG) neurons . RESULTS: ZXAS treatment improved DNCB-induced AD-like lesions through reducing dermatitis score, number of scratching and epidermal thickness, accompanied by the de-creased IgE and Th2 inflammatory cytokines. ZXAS also supressed the mRNA and protein expression of GRPR, TRPV1, and TRPA1 in the spinal cord. The medicated sera of ZXAS decreased capsaicin-induced Ca influx and downregulated the expression of TRPV1, TRPA1, and phospholipase C in DRG neurons. CONCLUSIONS: The therapeutic effect of ZXAS on AD may be related to the regulation of TRPV1 and TRPA1 and inhibition of Ca2+ signals in neurons.

Inflammation-responsive drug delivery nanosystems for treatment of bacterial-induced sepsis.

Sepsis, a complication of dysregulated host immune systemic response to an infection, is life threatening and causes multiple organ injuries. Sepsis is recognized by WHO as a big contributor to global morbidity and mortality. The heterogeneity in sepsis pathophysiology, antimicrobial resistance threat, the slowdown in the development of antimicrobials, and limitations of conventional dosage forms jeopardize the treatment of sepsis. Drug delivery nanosystems are promising tools to overcome some of these challenges. Among the drug delivery nanosystems, inflammation-responsive nanosystems have attracted considerable interest in sepsis treatment due to their ability to respond to specific stimuli in the sepsis microenvironment to release their payload in a precise, targeted, controlled, and rapid manner compared to non-responsive nanosystems. These nanosystems posit superior therapeutic potential to enhance sepsis treatment. This review critically evaluates the recent advances in the design of drug delivery nanosystems that are inflammation responsive and their potential in enhancing sepsis treatment. The sepsis microenvironment's unique features, such as acidic pH, upregulated receptors, overexpressed enzymes, and enhanced oxidative stress, that form the basis for their design have been adequately discussed. These inflammation-responsive nanosystems have been organized into five classes namely: Receptor-targeted nanosystems, pH-responsive nanosystems, redox-responsive nanosystems, enzyme-responsive nanosystems, and multi-responsive nanosystems. Studies under each class have been thematically grouped and discussed with an emphasis on the polymers used in their design, nanocarriers, key characterization, loaded actives, and key findings on drug release and therapeutic efficacy. Further, this information is concisely summarized into tables and supplemented by inserted figures. Additionally, this review adeptly points out the strengths and limitations of the studies and identifies research avenues that need to be explored. Finally, the challenges and future perspectives on these nanosystems have been thoughtfully highlighted.

The 'double­track sign': A novel CT finding suggestive of the diagnosis of T1a gastric cancer.

Effective identification of T1a stage cancer is crucial for planning endoscopic resection for early gastric cancers. The present study aimed to determine the diagnostic value of the double-track sign in patients with T1a gastric cancer using computed tomography (CT) imaging. A total of 152 patients diagnosed with pathologically proven T1a gastric cancer at The First Affiliated Hospital of Zhengzhou University (Zhengzhou, China) between July 2011 and August 2021 were retrospectively reviewed. The control group consisted of 2,926 patients with gastritis. Clinical data, including patient characteristics and preoperative CT imaging findings with gastric morphological features, were reviewed and analyzed. Out of 51 patients with T1a gastric cancer finally included, 31 (60.8%) exhibited local double-track enhancement changes of the stomach, referred to as the 'double-track sign', on CT images. In addition, four patients (7.8%) had well-enhanced mucosal thickening of the gastric wall. Of the 2,926 control subjects, none had any double-track sign and six patients (0.2%) had local gastric wall thickening with abnormally strengthened enhancement. In conclusion, a double-track sign on CT images is beneficial in the diagnostic differentiation of T1a gastric cancer.

Preoperative prediction of vessel invasion in locally advanced gastric cancer based on computed tomography radiomics and machine learning.

Vessel invasion (VI) is an important factor affecting the prognosis of gastric cancer (GC), and the accurate determination of preoperative VI for locally advanced GC is of great clinical significance. Traditional methods for the evaluation of VI require postoperative pathological examination. Noninvasive preoperative evaluation of VI is therefore crucial to determine the best treatment strategy. To determine the value of preoperative prediction of gastric VI based on portal venous phase computed tomography (CT) radiomic features and machine-learning models, a retrospective analysis of 296 patients with locally advanced GC confirmed through pathological examination was performed. They were divided into two groups, VI+ (n=213) and VI- (n=83), based on pathological results. Using pyradiomics to extract two-dimensional radiomic features of the portal venous stage of locally advanced GC, data were divided into training (n=207) and validation sets (n=89), with a ratio of 7:3, and three feature selection methods were cascaded and merged. Finally, least absolute shrinkage and selection operator (LASSO) regression was used for feature screening to obtain the optimal feature subset. Four current representative machine-learning algorithms were used to construct the prediction model, the receiver operating characteristic curve was constructed to evaluate the predictive performance of the model, and the area under the curve (AUC), accuracy, sensitivity, and specificity were calculated. The differentiation degree, and the Lauren's and CA199 classifications were independent risk factors for locally advanced GC VI. Pyradiomics extracted 864 quantitative features of portal vein images of locally advanced GC. After filtering out low variance features using R, 236 features remained. Next, 18 features were screened using the LASSO algorithm. Extreme gradient boosting (XGBoost), logistic regression, Gaussian naive Bayes, and support vector machine models were constructed based on the 18 best features screened out of the portal venous CT images of advanced GC and three independent risk factors of GC VI in clinical features predicted the training set AUC values of 0.914, 0.897, 0.880, and 0.814, respectively. The predicted validation set AUC values were 0.870, 0.877, 0.859, and 0.773, respectively. The DeLong test results indicated no statistically significant difference in AUC values between the XGBoost and logistic regression models in the training and validation sets. The four machine-learning models showed high predictive performance. The logistic regression model had the highest AUC value in the validation set (0.877), and the accuracy and F1 score were 77 and 87.6%, respectively. CT radiomic features and machine-learning models based on the portal venous phase can be used as a noninvasive imaging method for the preoperative prediction of VI in locally advanced GC. The logistic regression model exhibited the highest diagnostic performance.

Precision shaping of elastic stable intramedullary nail for the treatment of metaphyseal diaphysis junction fracture of the distal radius in children: a preliminary report in two centers.

BACKGROUND: This study introduces a novel retrograde precision shaping elastic stable intramedullary nailing (ESIN-RPS) technique and reports clinical outcomes in pediatric distal radius metaphyseal diaphysis junction (DRMDJ) fracture. METHODS: Data about DRMDJs were collected from February 1, 2020, to April 31, 2022 at two hospitals, retrospectively. All patients were treated with closed reduction and ESIN-RPS fixation. The operation time, blood loss, fluoroscopy times, alignment, and residual angulation on X-ray were recorded. At the last follow-up, the function of wrist and forearm rotation were evaluated. RESULTS: Totally, 23 patients were recruited. The mean time of follow-up was 11 months and the minimum was 6 months. The mean operation time was 52 min, and the mean fluoroscopies pulses were 6 times. The postoperative anterioposterior (AP) alignment was 93 ± 4% and the lateral alignment was 95 ± 3%. The postoperative AP angulation was (4 ± 1)°, and the lateral angulation was (3 ± 1)°. At the last follow-up, the evaluation of the Gartland and Werley demerit criteria of wrist revealed 22 excellent cases and 1 good case. The forearm rotation and thumb dorsiflexion functions were not limited. CONCLUSION: The ESIN-RPS is a novel, safe, and effective method for the treatment of pediatric DRMDJ fracture.

Risk factors analysis and prediction model construction of submucosal deep infiltration of early colorectal tumor / 中华肿瘤杂志

Objective: To investigate the risk factors for the development of deep infiltration in early colorectal tumors (ECT) and to construct a prediction model to predict the development of deep infiltration in patients with ECT. Methods: The clinicopathological data of ECT patients who underwent endoscopic treatment or surgical treatment at the Cancer Hospital, Chinese Academy of Medical Sciences from August 2010 to December 2020 were retrospectively analyzed. The independent risk factors were analyzed by multifactorial regression analysis, and the prediction models were constructed and validated by nomogram. Results: Among the 717 ECT patients, 590 patients were divided in the within superficial infiltration 1 (SM1) group (infiltration depth within SM1) and 127 patients in the exceeding SM1 group (infiltration depth more than SM1). There were no statistically significant differences in gender, age, and lesion location between the two groups (P>0.05). The statistically significant differences were observed in tumor morphological staging, preoperative endoscopic assessment performance, vascular tumor emboli and nerve infiltration, and degree of tumor differentiation (P<0.05). Multivariate regression analysis showed that only erosion or rupture (OR=4.028, 95% CI: 1.468, 11.050, P=0.007), localized depression (OR=3.105, 95% CI: 1.584, 6.088, P=0.001), infiltrative JNET staging (OR=5.622, 95% CI: 3.029, 10.434, P<0.001), and infiltrative Pit pattern (OR=2.722, 95% CI: 1.347, 5.702, P=0.006) were independent risk factors for the development of deep submucosal infiltration in ECT. Nomogram was constructed with the included independent risk factors, and the nomogram was well distinguished and calibrated in predicting the occurrence of deep submucosal infiltration in ECT, with a C-index and area under the curve of 0.920 (95% CI: 0.811, 0.929). Conclusion: The nomogram prediction model constructed based on only erosion or rupture, local depression, infiltrative JNET typing, and infiltrative Pit pattern has a good predictive efficacy in the occurrence of deep submucosal infiltration in ECT.

Risk factors for residual cancer or lymph node metastasis after endoscopic noncurable resection of early colorectal cancer / 中华肿瘤杂志

Objective: Risk factors related to residual cancer or lymph node metastasis after endoscopic non-curative resection of early colorectal cancer were analyzed to predict the risk of residual cancer or lymph node metastasis, optimize the indications of radical surgical surgery, and avoid excessive additional surgical operations. Methods: Clinical data of 81 patients who received endoscopic treatment for early colorectal cancer in the Department of Endoscopy, Cancer Hospital, Chinese Academy of Medical Sciences from 2009 to 2019 and received additional radical surgical surgery after endoscopic resection with pathological indication of non-curative resection were collected to analyze the relationship between various factors and the risk of residual cancer or lymph node metastasis after endoscopic resection. Results: Of the 81 patients, 17 (21.0%) were positive for residual cancer or lymph node metastasis, while 64 (79.0%) were negative. Among 17 patients with residual cancer or positive lymph node metastasis, 3 patients had only residual cancer (2 patients with positive vertical cutting edge). 11 patients had only lymph node metastasis, and 3 patients had both residual cancer and lymph node metastasis. Lesion location, poorly differentiated cancer, depth of submucosal invasion ≥2 000 μm, venous invasion were associated with residual cancer or lymph node metastasis after endoscopic (P<0.05). Logistic multivariate regression analysis showed that poorly differentiated cancer (OR=5.513, 95% CI: 1.423, 21.352, P=0.013) was an independent risk factor for residual cancer or lymph node metastasis after endoscopic non-curative resection of early colorectal cancer. Conclusions: For early colorectal cancer after endoscopic non-curable resection, residual cancer or lymph node metastasis is associated with poorly differentiated cancer, depth of submucosal invasion ≥2 000 μm, venous invasion and the lesions are located in the descending colon, transverse colon, ascending colon and cecum with the postoperative mucosal pathology result. For early colorectal cancer, poorly differentiated cancer is an independent risk factor for residual cancer or lymph node metastasis after endoscopic non-curative resection, which is suggested that radical surgery should be added after endoscopic treatment.

Efficacy of Chinese Herbal Medicines on Pregnancy Outcomes in Patients with Endometriosis in Long-Term Management: A Multicenter Retrospective Cohort Study / 中国结合医学杂志

OBJECTIVE@#To analyze the factors related to pregnancy of endometriosis and whether Chinese herbal medicines (CHMs) can improve pregnancy outcomes in patients with endometriosis in long-term management.@*METHODS@#This multicenter cohort study retrospectively analyzed the clinical data of endometriosis patients with fertility needs from January 2019 to November 2019. A total of 252 patients with endometriosis from 5 level-III Grade A hospitals in Beijing were included in this study. Univariate and multivariate logistic regression analysis were performed for the relevant factors. The propensity score matching (PSM) function of SPSS software was used to match the CHMs group with the non-CHMs group. The pregnancy rate and live birth rate were analyzed.@*RESULTS@#The results of univariate analysis showed that age, disease course, presence of infertility, presence of adenomyosis, time after surgery or use of gonadotropin-releasing hormone agonist (GnRH-a), use of CHMs and follow-up time were influencing factors of pregnancy in endometriosis patients (P<0.05). The results of multivariate analysis showed that age, presence of adenomyosis, time after surgery or use of GnRH-a, use of CHMs and follow-up time were independent factors affecting pregnancy in endometriosis patients, among which, age ⩾35 years old, presence of adenomyosis and follow-up time >6 months were independent risk factors (OR=0.445, 0.348, 0.140, respectively, P<0.05), time after surgery or use of GnRH-a ⩽6 months and use of CHMs were independent protective factors (OR=3.839, 3.842, respectively, P<0.05). After PSM, 99 pairs of two groups were matched successfully. The pregnancy rate of the CHMs group was higher than that of the non-CHMs group [55.56% (55/99) vs. 36.36% (36/99), P<0.05]. The live birth rate of the CHMs group was higher than that of the non-CHMs group [49.49% (49/99) vs. 35.35% (35/99), P<0.05].@*CONCLUSION@#CHMs can effectively improve clinical pregnancy rate and live birth rate of patients with endometriosis in the chronic disease management.

Analysis of CNNM2 gene variant in a child with Hypomagnesemia, seizures, and mental retardation syndrome / 中华医学遗传学杂志

OBJECTIVE@#To explore the genetic etiology of a child with Hypomagnesemia, epilepsy and mental retardation syndrome (HSMR).@*METHODS@#A child who was admitted to the Children's Hospital of Shandong University on July 9, 2021 due to repeated convulsions for 2 months was selected as the study subject. Clinical data of the child was collected. Peripheral blood samples of the child and his pedigree members were collected for the extraction of genomic DNA. Whole exome sequencing was carried out, and candidate variant was verified by Sanger sequencing and bioinformatic analysis.@*RESULTS@#The child, a 1-year-and-7-month-old male, had presented with epilepsy and global developmental delay. Serological testing revealed that he has low serum magnesium. Genetic testing showed that the child has harbored a heterozygous c.1448delT (p.Val483GlyfsTer29) variant of the CNNM2 gene, which was de novo in origin. The variant has caused substitution of the Valine at position 483 by Glycine and formation of a termination codon after 29 amino acids at downstream. As predicted by Swiss-Model online software, the variant may alter the protein structure, resulting in a truncation. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the c.1448delT (p.Val483GlyfsTer29) was predicted as a pathogenic variant (PVS1+PS2+PM2_Supporting+PP4).@*CONCLUSION@#The heterozygous c.1448delT variant of the CNNM2 gene probably underlay the HSMR in this child. Above finding has enriched the phenotype-genotype spectrum of the CNNM2 gene.