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.

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.

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.

Efficacy of Human-Recombinant Epidermal Growth Factor Combined with Povidone-Iodine for Pressure Ulcers and Its Influence on Inflammatory Cytokines.

Purpose: To determine the clinical efficacy of recombinant human epidermal growth factor (rh-EGF) combined with povidone-iodine (PVI) on patients with pressure ulcers (PUs). Methods: One hundred and five PU patients treated between January 2018 and January 2021 were enrolled and retrospectively analyzed. Of them, 50 patients who received conventional treatment were assigned to the control group (Con group), while 55 patients treated with rh-EGF combined with PVI were assigned to the observation group (Obs group). The two groups were compared in clinical efficacy, PU alleviation (total area reduction rate, total depth reduction rate, and total volume reduction rate), healing time, pain degree (Visual Analog Scale [VAS] score), inflammatory indexes (interleukin-8 [IL-8], tumor necrosis factor-α [TNF-α], and hypersensitive C reactive protein [hs-CRP]), and hydroxyproline content in the wound. Results: The Obs group yielded a higher total effective rate than the Con group (P < 0.05). The Obs group also experienced statistically shorter healing time and milder pain, with better PU alleviation and lower levels of inflammation indexes compared with the Con group (all P < 0.05). In addition, a higher hydroxyproline content in the wound was found in the Obs group. Conclusions: All in all, rh-EGF combined with PVI has a definite curative effect on patients with PUs. It can promote PU alleviation and hydroxyproline secretion in the wound and inhibit pain and inflammatory reactions, which is worthy of clinical promotion.

Double-Constraint Inpainting Model of a Single-Depth Image.

In real applications, obtained depth images are incomplete; therefore, depth image inpainting is studied here. A novel model that is characterised by both a low-rank structure and nonlocal self-similarity is proposed. As a double constraint, the low-rank structure and nonlocal self-similarity can fully exploit the features of single-depth images to complete the inpainting task. First, according to the characteristics of pixel values, we divide the image into blocks, and similar block groups and three-dimensional arrangements are then formed. Then, the variable splitting technique is applied to effectively divide the inpainting problem into the sub-problems of the low-rank constraint and nonlocal self-similarity constraint. Finally, different strategies are used to solve different sub-problems, resulting in greater reliability. Experiments show that the proposed algorithm attains state-of-the-art performance.

The protective effects of distal ischemic treatment on apoptosis and mitochondrial permeability in the hippocampus after cardiopulmonary resuscitation.

Apoptosis and mitochondrial dysfunction are the main cause of neurological injury after cardiopulmonary resuscitation (CPR). However, the effects of distal ischemic treatments on ischemia induced apoptosis are rarely studied, and the mechanism by which mitochondrial dysfunction contributes to CPR still unclear. A rat model of distal ischemia was established by clipping the right femoral artery. Rats were divided into blank, model, pre distal ischemic treatment, per-treatment, and post-treatment groups. Neurological deficit score was scored to evaluate neurologic function after cardiopulmonary resuscitation for 72 hr. We employed TUNEL and flow cytometry to measure the rate of apoptosis of hippocampal neurons, the integrity of mitochondrial membrane and the degree of mitochondrial permeability transition pore (mPTP) opening. The rate of apoptosis rate of hippocampal CA1 neurons in the pre-treatment and post-treatment groups were significantly lower than that of the model group. Moreover, the integrity of the mitochondrial membrane in the pre-treatment and post-treatment groups was higher than that in the model and per- treatment groups. Furthermore, the degree of mPTP opening was lower in the pre-treatment and post-treatment groups than the untreated and per-treatment groups. Taken together, our results show that ischemic preconditioning and post processing can maintain the integrity of mitochondria, perhaps by inhibiting the opening of mPTP, and reducing apoptosis of hippocampal neurons by regulating expression of apoptosis related proteins after CPR, to improve neurological function. This study highlights a novel target pathway for treatment of CPR.

A high-mobility group box 1 that binds to DNA, enhances pro-inflammatory activity, and acts as an anti-infection molecule in black rockfish, Sebastes schlegelii.

High-mobility group box (HMGB) 1 is a chromosomal protein that plays critical roles in DNA transcription, replication and repair. In addition, HMGB1 functions as a pro-inflammatory molecule in many vertebrates and invertebrates. In teleosts, very limited studies of HMGB1 have been reported. In this study, we identified a HMGB1 homologue (SsHMGB1) from black rockfish (Sebastes schlegelii) and analyzed its structure, expression and biological function. The open reading frame of SsHMGB1 is 621 bp, with a 5'-untranslated region (UTR) of 62 bp and a 3'-UTR of 645 bp. SsHMGB1 contains two typical HMG boxes and an acidic C-terminal tail. The deduced amino acid sequence of SsHMGB1 shares the highest overall identity (89.4%) with the HMGB1 of Anoplopoma fimbria. The expression of SsHMGB1 occurred in multiple tissues and was highest in the brain. Moreover, the mRNA level of SsHMGB1 in head kidney (HK) macrophages could be induced by Listonella anguillarum in a time-dependent manner. Recombinant SsHMGB1 purified from Escherichia coli (i) bound DNA fragments in a dose-dependent manner; and (ii) induced the expression of cytokines in HK macrophages, including a significant increase in TNF-α activity and enhanced mRNA level of TNF13B and IL-1 ß, which are known to be involved in antibacterial defense; moreover, (iii) significantly improved the macrophage bactericidal activity together with reduced pathogen dissemination and replication of bacteria in fish kidney. These results indicated that SsHMGB1 is a novel HMGB1 that possesses apparent immunoregulatory properties and is likely to be involved in fighting bacterial infection.

A correspondence finding method based on space conversion in 3D shape measurement using fringe projection.

Phase correlation is an effective method used for 3D shape measurement. It has a defect in the step of finding corresponding points. This work analyses the complexity of phase maps and the problems caused by it in real applications, proposes a correspondence finding method based on space conversion. Applying space conversion, two sets of phase maps from two cameras are integrated to a unique phase space. Accordingly, searching corresponding point between two images can be carried out in the same image coordinate system of the projector. As a supplementary, two algorithms are given for CC method and VR method. Experimental results show that proposed algorithms are successful and effective.

Prognostic value of systemic immune-inflammation index/albumin ratio for immunotherapy-treated patients receiving opioids.

OBJECTIVE: This study evaluated the effect of the systemic immune-inflammation index/albumin ratio (SII/ALB) on the prognosis of immunotherapy-treated patients receiving opioids. METHODS: A retrospective analysis was conducted of 185 immunotherapy-treated patients who received opioids at Xuzhou Central Hospital from 01/09/2021 to 01/09/2023. The results of related clinical data were collected during the week before the cancer patients received immunotherapy. The SII/ALB cut-off value was determined, and the relationship between the SII/ALB and clinical pathological parameters was analyzed using the chi-square test. The effect of the SII/ALB on progression-free survival (PFS) was examined using Kaplan-Meier curves and the Cox proportional hazard model. RESULT: The SII/ALB cut-off value was 20.86, and patients were divided into low (SII/ALB ≤ 20.86) and high (SII/ALB > 20.86) SII/ALB groups. Adverse reactions (hazard ratio [HR] = 0.108; 95% confidence interval [CI]: 0.061-0.192, P < 0.001) and the SII/ALB (HR = 0.093; 95% CI: 0.057-0.151, P < 0.001) were independent prognostic factors for PFS. Compared with the high SII/ALB group, the low SII/ALB group had longer PFS after opioid treatment (12.2 vs. 5.2 months, P < 0.001). CONCLUSION: The SII/ALB is a potentially important prognostic parameter in immunotherapy-treated patients receiving opioids.

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.

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.

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.

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.

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.

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.

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.

Flexible error-reduction method for shape measurement by temporal phase unwrapping: phase averaging method.

Temporal phase unwrapping is an important method for shape measurement in structured light projection. Its measurement errors mainly come from both the camera noise and nonlinearity. Analysis found that least-squares fitting cannot completely eliminate nonlinear errors, though it can significantly reduce the random errors. To further reduce the measurement errors of current temporal phase unwrapping algorithms, in this paper, we proposed a phase averaging method (PAM) in which an additional fringe sequence at the highest fringe density is employed in the process of data processing and the phase offset of each set of the four frames is carefully chosen according to the period of the phase nonlinear errors, based on fast classical temporal phase unwrapping algorithms. This method can decrease both the random errors and the systematic errors with statistical averaging. In addition, the length of the additional fringe sequence can be changed flexibly according to the precision of the measurement. Theoretical analysis and simulation experiment results showed the validity of the proposed method.

Anxiolytic-like effects of compound zhi zhu xiang in rats.

The purpose of this study was to determine whether compound zhi zhu xiang (CZZX) exerts anxiolytic-like effects in rats. The animals were orally administered CZZX (0.75, 1.5, and 3 g/kg daily) for 10 days and tested in the elevated plus maze (EPM), Vogel conflict test (VCT), and open field. Repeated treatment with CZZX (3 g/kg/day, p.o.) significantly increased the percentage of both entries into and time spent on the open arms of the EPM compared with saline controls. In the VCT, repeated treatment with CZZX (1.5 and 3 g/kg/day, p.o.) significantly increased the number of punished licks. The drug did not change the total entries into the open arms of the EPM or interfere with water consumption or nociceptive threshold, discarding potential confounding factors in the two tests. In the open field, locomotion was not reduced, discarding the possible sedative effect of CZZX. In the binding assay, the binding of [(3)H] Ro 15-1788 (flumazenil) to the benzodiazepine binding site in washed crude synaptosomal membranes from rat cerebral cortex was affected by CZZX. These data indicate an anxiolytic-like profile of action for CZZX without sedative side effects, and this activity may be mediated by benzodiazepine binding site modulation at γ-aminobutyric acid-A receptors.

A model for community health service development in depressed rural areas in China.

BACKGROUND: To introduce a model of community health service organization (as implemented in urban areas) to less developed rural areas in China and evaluate the impact of this model on health care utilization. METHODS: The intervention involved developing leadership at county level, training rural health practitioners, providing clinical management guidelines and standards, encouraging clinic improvements and providing access to subsidies for public health work. We chose 7 townships and 49 administrative villages in Chongyi County as the intervention sites; 3 townships and 9 administrative villages in Luxi County as the comparison sites. Officers from county health bureaus and postgraduates from School of Public Health, Nanchang University visited each township hospital and village clinic in field together and made observations and interviewed clinic staff. RESULTS: There was little change in health facilities or workforce in the two areas. However, there was an increase in the use of public health services at township and village level in the intervention sites in Chongyi. In these, the proportion of clinics which had developed a child health (under the age of 3) management system, maternal postpartum visit and chronic disease management increased from 53%, 51% and 47% to 78%, 73%, and 71% respectively. There was no significant change in the comparison sites. CONCLUSIONS: The trial demonstrated that it was feasible to implement a model of community health service delivery that was adapted to depressed rural areas because it required little organizational change, additional funding or personnel. The model had a positive impact on the provision of public health programs, a finding which has implications for efforts to improve access to primary health care in rural China.