Enhanced acrylic gauge with five eccentric circles for optimizing CT angiography spatial resolution via Taguchi's methodology.

BACKGROUND: Cerebral examination via CTA is always the first choice for patients with unexpected brain injury or different types of brain lesions to detect ruptured hemangiomas, vascular infarcts, or other brain tissue lesions. OBJECTIVE: This study innovated the acrylic gauge with five eccentric circles for computed tomography angiography (CTA) analysis to optimize the spatial resolution via Taguchi's methodology. METHODS: The customized gauge was revised from the V-shaped slit gauge and transferred into five eccentric circles' slit gauge. The gauge was assembled with another six acrylic layers to simulate the human head. Taguchi's L18 orthogonal array was adopted to optimize the spatial resolution of CTA imaging quality. In doing so, six essential factors of CTA are kVp, mAs, spiral rotation pitch, FOV, rotation time of the CT and reconstruction filter, and each factor has either two or three levels to organize into eighteen combinations to simulate the full factor combination of 486 (21 × 35 = 486) times according to Taguchi's recommendation. Three well-trained radiologists ranked the gauge's 18 CTA scanned imaging qualities according to contrast, sharpness, and spatial resolution and derived the unique fish-bone-plot of six factors for further analysis. The optimal factor combination of CTA was proven by follow-up verification and ANOVA to obtain this study's dominant or minor factor. RESULTS: The optimal factor combination of CTA was A2 (120 kVp), B3 (200 mAs), C1 (Pitch 0.6), D2 (FOV 220 mm2), E1 (rotation time 0.33 s), and F3 (Brain sharp, UC). Furthermore, deriving a quantified MDD (minimum detectable difference) to imply the spatial resolution of CTA, a semiauto profile analysis program run in MATLAB and OriginPro was recommended to evaluate the MDD and to suppress the manual error in calculation. Eventually, the derived MDDs of the conventional and optimal factor combinations of CTA were 2.35 and 2.26 mm, respectively, in this study. CONCLUSION: Taguchi's methodology was found applicable for quantifying the CTA imaging quality in practical applications.

Artificial intelligence algorithms for predicting post-operative ileus after laparoscopic surgery.

Objective: By constructing a predictive model using machine learning and deep learning technologies, we aim to understand the risk factors for postoperative intestinal obstruction in laparoscopic colorectal cancer patients, and establish an effective artificial intelligence-based predictive model to guide individualized prevention and treatment, thus improving patient outcomes. Methods: We constructed a model of the artificial intelligence algorithm in Python. Subjects were randomly assigned to either a training set for variable identification and model construction, or a test set for testing model performance, at a ratio of 7:3. The model was trained with ten algorithms. We used the AUC values of the ROC curves, as well as accuracy, precision, recall rate and F1 scores. Results: The results of feature engineering composited with the GBDT algorithm showed that opioid use, anesthesia duration, and body weight were the top three factors in the development of POI. We used ten machine learning and deep learning algorithms to validate the model, and the results were as follows: the three algorithms with best accuracy were XGB (0.807), Decision Tree (0.807) and Neural DecisionTree (0.807); the two algorithms with best precision were XGB (0.500) and Decision Tree (0.500); the two algorithms with best recall rate were adab (0.243) and Decision Tree (0.135); the two algorithms with highest F1 score were adab (0.290) and Decision Tree (0.213); and the three algorithms with best AUC were Gradient Boosting (0.678), XGB (0.638) and LinearSVC (0.633). Conclusion: This study shows that XGB and Decision Tree are the two best algorithms for predicting the risk of developing ileus after laparoscopic colon cancer surgery. It provides new insight and approaches to the field of postoperative intestinal obstruction in colorectal cancer through the application of machine learning techniques, thereby improving our understanding of the disease and offering strong support for clinical decision-making.

A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm.

We constructed an early prediction model for postoperative pulmonary complications after thoracoscopic surgery using machine learning and deep learning algorithms. The artificial intelligence prediction models were built in Python, primarily using artificial intelligencealgorithms including both machine learning and deep learning algorithms. Correlation analysis showed that postoperative pulmonary complications were positively correlated with age and surgery duration, and negatively correlated with serum albumin. Using the light gradient boosting machine(LGBM) algorithm, weighted feature engineering revealed that single lung ventilation duration, history of smoking, surgery duration, ASA score, and blood glucose were the main factors associated with postoperative pulmonary complications. Results of artificial intelligence algorithms for predicting pulmonary complications after thoracoscopy in the test group: In terms of accuracy, the two best algorithms were Logistic Regression (0.831) and light gradient boosting machine(0.827); in terms of precision, the two best algorithms were Gradient Boosting (0.75) and light gradient boosting machine (0.742); in terms of recall, the three best algorithms were gaussian naive bayes (0.581), Logistic Regression (0.532), and pruning Bayesian neural network (0.516); in terms of F1 score, the two best algorithms were LogisticRegression (0.589) and pruning Bayesian neural network (0.566); and in terms of Area Under Curve(AUC), the two best algorithms were light gradient boosting machine(0.873) and pruning Bayesian neural network (0.869). The results of this study suggest that pruning Bayesian neural network (PBNN) can be used to assess the possibility of pulmonary complications after thoracoscopy, and to identify high-risk groups prior to surgery.

Delineating effects of angiopoietin-2 inhibition on vascular permeability and inflammation in models of retinal neovascularization and ischemia/reperfusion.

Introduction: Clinical trials demonstrated that co-targeting angiopoietin-2 (Ang-2) and vascular endothelial growth factor (VEGF-A) with faricimab controls anatomic outcomes and maintains vision improvements, with strong durability, through 2 years in patients with neovascular age-related macular degeneration and diabetic macular edema. The mechanism(s) underlying these findings is incompletely understood and the specific role that Ang-2 inhibition plays requires further investigation. Methods: We examined the effects of single and dual Ang-2/VEGF-A inhibition in diseased vasculatures of JR5558 mice with spontaneous choroidal neovascularization (CNV) and in mice with retinal ischemia/reperfusion (I/R) injuries. Results: In JR5558 mice, Ang-2, VEGF-A, and dual Ang-2/VEGF-A inhibition reduced CNV area after 1 week; only dual Ang-2/VEGF-A inhibition decreased neovascular leakage. Only Ang-2 and dual Ang-2/VEGF-A inhibition maintained reductions after 5 weeks. Dual Ang-2/VEGF-A inhibition reduced macrophage/microglia accumulation around lesions after 1 week. Both Ang-2 and dual Ang-2/VEGF-A inhibition reduced macrophage/microglia accumulation around lesions after 5 weeks. In the retinal I/R injury model, dual Ang-2/VEGF-A inhibition was statistically significantly more effective than Ang-2 or VEGF-A inhibition alone in preventing retinal vascular leakage and neurodegeneration. Discussion: These data highlight the role of Ang-2 in dual Ang-2/VEGF-A inhibition and indicate that dual inhibition has complementary anti-inflammatory and neuroprotective effects, suggesting a mechanism for the durability and efficacy of faricimab in clinical trials.

Predicting early postoperative PONV using multiple machine-learning- and deep-learning-algorithms.

OBJECTIVE: PONV reduces patient satisfaction and increases hospital costs as patients remain in the hospital for longer durations. In this study, we build a preliminary artificial intelligence algorithm model to predict early PONV in patients. METHODS: We use R for statistical analysis and Python for the machine learning prediction model. RESULTS: Average characteristic engineering results showed that haloperidol, sex, age, history of smoking, and history of PONV were the first 5 contributing factors in the occurrence of early PONV. Test group results for artificial intelligence prediction of early PONV: in terms of accuracy, the four best algorithms were CNNRNN (0.872), Decision Tree (0.868), SVC (0.866) and adab (0.865); in terms of precision, the three best algorithms were CNNRNN (1.000), adab (0.400) and adab (0.868); in terms of AUC, the top three algorithms were Logistic Regression (0.732), SVC (0.731) and adab (0.722). Finally, we built a website to predict early PONV online using the Streamlit app on the following website: ( https://zhouchengmao-streamlit-app-lsvc-ad-st-app-lsvc-adab-ponv-m9ynsb.streamlit.app/ ). CONCLUSION: Artificial intelligence algorithms can predict early PONV, whereas logistic regression, SVC and adab were the top three artificial intelligence algorithms in overall performance. Haloperidol, sex, age, smoking history, and PONV history were the first 5 contributing factors associated with early PONV.

Linarin Ameliorates Diabetic Liver Injury by Alleviating Oxidative Stress and Inflammation through the Inhibition of AKR1B1.

AIMS: The study aims to find a new functional additive for diabetic liver injury. BACKGROUND: It is well-established that type 2 diabetes mellitus (T2DM) is a metabolic disease with multiple complications and places a significant health and economic burden on modern society. Linarin is a natural flavonoid isolated from Asteraceae and Lamiaceae, which has beneficial effects in preventing and treating metabolic diseases such as nonalcoholic steatohepatitis and diabetes. OBJECTIVE: We aimed to investigate the pharmacological effect and underlying mechanism of linarin on T2DM-associated liver injury in vivo and in vitro. METHODS: Using a high-glucose and high-palmitic acid-induced hepatocyte injury model and a type 2 diabetic rat model. Following linarin treatment, serum biochemical parameters, liver histology, and lipid profiles of rats were examined. Oxidative stress index and inflammatory response were detected in vivo and in vitro. The expression level of AKR1B1 in rat liver tissues and in vitro cells was detected by western blot and by real-time fluorescent quantitative PCR. RESULTS: The present study found that linarin could prevent oxidative stress and inflammation. In high-fat-fed diabetic rats, linarin administration (15, 30, and 60 mg/kg/day) reduced hepatic lipid accumulation, oxidative stress, and inflammation. Linarin (20 µM) significantly alleviated oxidative stress, inflammation, and apoptosis induced by high glucose combined with palmitic acid in LX-2 cells. Western blotting and overexpression experiments showed that these effects were related to AKR1B1 inhibition in vivo and in vitro. CONCLUSION: This study indicated that linarin could protect against liver injury in T2DM by alleviating oxidative stress and inflammation mediated by AKR1B1 and may be a promising additive for diabetic liver injury therapy.

Differentiation of Bone Metastasis in Elderly Patients With Lung Adenocarcinoma Using Multiple Machine Learning Algorithms.

OBJECTIVE: We tested the performance of general machine learning and joint machine learning algorithms in the classification of bone metastasis, in patients with lung adenocarcinoma. METHODS: We used R version 3.5.3 for statistical analysis of the general information, and Python to construct machine learning models. RESULTS: We first used the average classifiers of the 4 machine learning algorithms to rank the features and the results showed that race, sex, whether they had surgery and marriage were the first 4 factors affecting bone metastasis. Machine learning results in the training group: for area under the curve (AUC), except for RF and LR, the AUC values of all machine learning classifiers were greater than .8, but the joint algorithm did not improve the AUC for any single machine learning algorithm. Among the results related to accuracy and precision, the accuracy of other machine learning classifiers except the RF algorithm was higher than 70%, and only the precision of the LGBM algorithm was higher than 70%. Machine learning results in the test group: Similarly, for areas under the curve (AUC), except RF and LR, the AUC values for all machine learning classifiers were greater than .8, but the joint algorithm did not improve the AUC value for any single machine learning algorithm. For accuracy, except for the RF algorithm, the accuracy of other machine learning classifiers was higher than 70%. The highest precision for the LGBM algorithm was .675. CONCLUSION: The results of this concept verification study show that machine learning algorithm classifiers can distinguish the bone metastasis of patients with lung cancer. This will provide a new research idea for the future use of non-invasive technology to identify bone metastasis in lungcancer. However, more prospective multicenter cohort studies are needed.

Predicting postoperative gastric cancer prognosis based on inflammatory factors and machine learning technology.

OBJECTIVE: There is a strong association between gastric cancer and inflammatory factors. Many studies have shown that machine learning can predict cancer patients' prognosis. However, there has been no study on predicting gastric cancer death based on machine learning using related inflammatory factor variables. METHODS: Six machine learning algorithms are applied to predict total gastric cancer death after surgery. RESULTS: The Gradient Boosting Machine (GBM) algorithm factors accounting for the prognosis weight outcome show that the three most important factors are neutrophil-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR) and age. The total postoperative death model showed that among patients with gastric cancer from the predictive test group: The highest accuracy was LR (0.759), followed by the GBM algorithm (0.733). For the six algorithms, the AUC values, from high to low, were LR, GBM, GBDT, forest, Tr and Xgbc. Among the six algorithms, Logistic had the highest precision (precision = 0.736), followed by the GBM algorithm (precision = 0.660). Among the six algorithms, GBM had the highest recall rate (recall = 0.667). CONCLUSION: Postoperative mortality from gastric cancer can be predicted based on machine learning.

A long duration of intraoperative hypotension is associated with postoperative delirium occurrence following thoracic and orthopedic surgery in elderly.

BACKGROUND: Postoperative delirium (POD) is a common surgical complication associated with increased morbidity and mortality in elderly. Although the underlying mechanisms remain elusive, perioperative risk factors were reported to be closely related to its development. This study was designed to investigate the association between the duration of intraoperative hypotension and POD incidence following thoracic and orthopedic surgery in elderly. METHOD: The perioperative data from 605 elderly undergoing thoracic and orthopedic surgery from January 2021 to July 2022 were analyzed. The primary exposure was a cumulative duration of mean arterial pressure (MAP) ≤ 65 mmHg. The primary end-point was the POD incidence assessed with confusion assessment method (CAM) or CAM-ICU for three days after surgery. Restricted cubic spline (RCS) was conducted to examine the continuous relationship between the duration of intraoperative hypotension and POD incidence adjusted with patients' demographics and surgery related factors. Then the duration of intraoperative hypotension was categorized into three groups: no hypotension, short (< 5 mins) or long duration (≥ 5 mins) of hypotension for further analysis. RESULT: The incidence of POD was 14.7% (89 cases out of 605) within three days after surgery. The duration of hypotension presented a non-linear and "inverted L-shaped" effect on POD development. Compared to no hypotension, long duration (adjusted OR 3.93; 95% CI: 2.07-7.45; P < 0.001) rather than short duration of MAP ≤65 mmHg (adjusted OR 1.18; 95% CI: 0.56-2.50; P = 0.671) was closely related to the POD incidence. CONCLUSION: Intraoperative hypotension (MAP ≤65 mmHg) for ≥5 mins was associated with an increased incidence of POD after thoracic and orthopedic surgery in elderly.

Enriched binocular experience followed by sleep optimally restores binocular visual cortical responses in a mouse model of amblyopia.

Studies of primary visual cortex have furthered our understanding of amblyopia, long-lasting visual impairment caused by imbalanced input from the two eyes during childhood, which is commonly treated by patching the dominant eye. However, the relative impacts of monocular vs. binocular visual experiences on recovery from amblyopia are unclear. Moreover, while sleep promotes visual cortex plasticity following loss of input from one eye, its role in recovering binocular visual function is unknown. Using monocular deprivation in juvenile male mice to model amblyopia, we compared recovery of cortical neurons' visual responses after identical-duration, identical-quality binocular or monocular visual experiences. We demonstrate that binocular experience is quantitatively superior in restoring binocular responses in visual cortex neurons. However, this recovery was seen only in freely-sleeping mice; post-experience sleep deprivation prevented functional recovery. Thus, both binocular visual experience and subsequent sleep help to optimally renormalize bV1 responses in a mouse model of amblyopia.

Cellular mechanisms underlying extraordinary sulfide tolerance in a crustacean holobiont from hydrothermal vents.

The shallow-water hydrothermal vent system of Kueishan Island has been described as one of the world's most acidic and sulfide-rich marine habitats. The only recorded metazoan species living in the direct vicinity of the vents is Xenograpsus testudinatus, a brachyuran crab endemic to marine sulfide-rich vent systems. Despite the toxicity of hydrogen sulfide, X. testudinatus occupies an ecological niche in a sulfide-rich habitat, with the underlying detoxification mechanism remaining unknown. Using laboratory and field-based experiments, we characterized the gills of X. testudinatus that are the major site of sulfide detoxification. Here sulfide is oxidized to thiosulfate or bound to hypotaurine to generate the less toxic thiotaurine. Biochemical and molecular analyses demonstrated that the accumulation of thiosulfate and hypotaurine is mediated by the sodium-independent sulfate anion transporter (SLC26A11) and taurine transporter (Taut), which are expressed in gill epithelia. Histological and metagenomic analyses of gill tissues demonstrated a distinct bacterial signature dominated by Epsilonproteobacteria. Our results suggest that thiotaurine synthesized in gills is used by sulfide-oxidizing endo-symbiotic bacteria, creating an effective sulfide-buffering system. This work identified physiological mechanisms involving host-microbe interactions that support life of a metazoan in one of the most extreme environments on our planet.

Construction of a Competitive Endogenous RNA Network Related to Exosomes in Diabetic Retinopathy.

BACKGROUND: The competing endogenous RNA (ceRNA) network plays an important role in the occurrence and development of a variety of diseases. This study aimed to construct a ceRNA network related to exosomes in diabetic retinopathy (DR). METHODS: We explored the Gene Expression Omnibus (GEO) database and then analyzed the RNAs of samples to obtain differentially expressed lncRNAs (DELs), miRNAs (DEMs) and mRNAs (DEGs) alongside the progress of DR. Next, Gene Set Enrichment Analysis (GSEA) analysis of DEGs, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of up-DEGs were performed. In addition, a ceRNA network related to exosomes in DR was constructed on the base of DELs, DEMs and DEGs. Finally, the function of the ceRNA network was explored by GO and KEGG enrichment analysis. RESULTS: Through our analysis, 267 DELs (93 up and 174 down), 114 DEMs (64 up and 50 down) and 2368 DEGs (1252 up and 1116 down) were screened. The GSEA analysis results show that these genes were mainly related to cytokine-cytokine receptor interaction, hippo signaling pathway and JAK-STAT signaling pathway. The GO and KEGG results show that these up-DEGs were mainly enriched in viral gene expression, components of ribosomes, mineral absorption, Wntprotein binding, and TGF-ß signaling pathway. Besides, a ceRNA network, including 15 lncRNAs (e.g., C1orf145, FGF14-IT1, and PRNT), 3 miRNAs (miR-10a-5p, miR-1297 and miR-507) and 11 mRNAs (NCOR2, CHAC1 and LIX1L, etc.) was constructed. Those 5 lncRNAs were up-regulated, 1 miRNA was down-regulated and 5 mRNAs were up-regulated in DR, while 10 lncRNAs were downregulated, 2 miRNAs were up-regulated and 6 mRNAs were down-regulated in DR. CONCLUSION: The novel ceRNA network that we constructed will provide new insights into the underlying molecular mechanisms of exosomes in DR.

Study on Fatigue Performance of Pulsed Tungsten Inert Gas Welding Joint of Duplex Stainless Steel Thin Tube.

To solve the shortage of austenite phase precipitation caused by nitrogen loss in the welding process of UNS S2205 duplex stainless steel (DSS), shielding gas nitriding was investigated by adding different N2 contents in Ar shielding gas during the welding process. A good thin-walled pipe butt joint was formed using the pulsed tungsten inert gas (P-TIG) welding method with Ar-N2 shielding gas. High cycle fatigue tests of the weld joints were conducted to study the effect of shielding gas nitriding on the fatigue properties. Fatigue tests at three stress levels of 225 MPa, 270 MPa, and 360 MPa were carried out on the weld joints with different N2 contents, and the fatigue samples were all fractured in the high temperature heat-affected zone (H-HAZ). Within the current process parameters, the fatigue life of the 4 vol.% N2 welded joints was optimal. Fatigue striations appeared in the fatigue crack propagation zone, and the transient fracture zone was similar to the tensile fracture. Under the low-stress level, the area of the crack propagation zone under 4 vol.% N2 was the highest, the tear ridges all expanded around the crack source area, and the fatigue crack propagation zone presented a radial distribution. The proliferation and expansion of dislocations were mainly carried out in the austenite grains, and the dislocation density of the fatigue specimens under 4 vol.% N2 was smaller than that of the Ar specimens. Shielding gas nitriding effectively improved the balance of the two-phase ratio and the hardness of austenite phase, optimized the internal slip system, inhibited the proliferation of dislocations in the austenite phase, and improved the fatigue life of weld joints.

Exploration of the policy structure of China s school sexuality education based on text analysis / 中国学校卫生

Objective@#To explore the structural status of school sexuality education policies in China, so as to provide a reference to optimize their effectiveness and development.@*Methods@#A total of 45 policy documents closely related to school sexuality education, released at the national level, as samples in order to construct an analytic framework of policy objectives/instruments by analyzing their textual content.@*Results@#In terms of policy objectives, school sexuality education policies focused on educational methods guidance (32.76%), and tend to underestimate the evaluation of educational effects (5.17%) and the protection of teachers and students rights and interests (5.17%), while failed to consider the creation of educational environments (0). In regards to policy tools, school sexuality education policies often used command line tools (59.45%) and capacity building tools ( 29.71% ), while the use of system change tools (2.70%) and incentive tools was lacking (0). In respect to the adaptability of policy objectives/tools, school sexuality education policies focused on using command based tools to guide educational methods ( 68.42% ), educational process management (54.55%), student literacy improvement (38.46%), and educational resource development ( 37.50% ). However, system change tools and incentive tools were scarcely used to achieve policy goals in education effectiveness evaluation, to protect teacher student rights and interests, and to improve student literacy and comprehensive social governance.@*Conclusions@#There is some deviations in the positioning of policy objectives, the selection of policy tools, and the interaction and adaptation between the two in school sex education policies, and further improvement is needed.

Identification of Novel Artemisinin Hybrids Induce Apoptosis and Ferroptosis in MCF-7 Cells.

A series of novel 1,3,4-oxadiazole-artemisinin hybrids have been designed and synthesized. An MTT assay revealed that most of tested hybrids showed more enhanced anti-proliferative activities than artemisinin, among which A8 had the superior potency with IC50 values ranging from 4.07 µM to 9.71 µM against five tested cancer cell lines. Cell colony formation assays showed that A8 could inhibit significantly more cell proliferation than artemisinin and 5-fluorouracil. Further mechanism studies reveal that A8 induces apoptosis and ferroptosis in MCF-7 cells in a dose-dependent manner, and CYPs inhibition assays reveal that A8 has a moderate inhibitory effect on CYP1A2 and CYP3A4 in the human body at 10 µM. The present work indicates that hybrid A8 may merit further investigation as a potential therapeutic agent.

Predicting difficult airway intubation in thyroid surgery using multiple machine learning and deep learning algorithms.

Background: In this paper, we examine whether machine learning and deep learning can be used to predict difficult airway intubation in patients undergoing thyroid surgery. Methods: We used 10 machine learning and deep learning algorithms to establish a corresponding model through a training group, and then verify the results in a test group. We used R for the statistical analysis and constructed the machine learning prediction model in Python. Results: The top 5 weighting factors for difficult airways identified by the average algorithm in machine learning were age, sex, weight, height, and BMI. In the training group, the AUC values and accuracy and the Gradient Boosting precision were 0.932, 0.929, and 100%, respectively. As for the modeled effects of predicting difficult airways in test groups, among the models constructed by the 10 algorithms, the three algorithms with the highest AUC values were Gradient Boosting, CNN, and LGBM, with values of 0.848, 0.836, and 0.812, respectively; In addition, among the algorithms, Gradient Boosting had the highest accuracy with a value of 0.913; Additionally, among the algorithms, the Gradient Boosting algorithm had the highest precision with a value of 100%. Conclusion: According to our results, Gradient Boosting performed best overall, with an AUC >0.8, an accuracy >90%, and a precision of 100%. Besides, the top 5 weighting factors identified by the average algorithm in machine learning for difficult airways were age, sex, weight, height, and BMI.

Structure and function of the retina of low-density lipoprotein receptor-related protein 5 (Lrp5)-deficient rats.

Loss-of-function mutations in the Wnt co-receptor, low-density lipoprotein receptor-related protein 5 (LRP5), result in familial exudative vitreoretinopathy (FEVR), osteoporosis-pseudoglioma syndrome (OPPG), and Norrie disease. CRISPR/Cas9 gene editing was used to produce rat strains deficient in Lrp5. The purpose of this study was to validate this rat model for studies of hypovascular, exudative retinopathies. The retinal vasculature of wildtype and Lrp5 knockout rats was stained with Giffonia simplifolia isolectin B4 and imaged by fluorescence microscopy. Effects on retinal structure were investigated by histology. The integrity of the blood-retina barrier was analyzed by measurement of permeability to Evans blue dye and staining for claudin-5. Retinas were imaged by fundus photography and SD-OCT, and electroretinograms were recorded. Lrp5 gene deletion led to sparse superficial retinal capillaries and loss of the deep and intermediate plexuses. Autofluorescent exudates were observed and are correlated with increased Evans blue permeability and absence of claudin-5 expression in superficial vessels. OCT images show pathology similar to OCT of humans with FEVR, and retinal thickness is reduced by 50% compared to wild-type rats. Histology and OCT reveal that photoreceptor and outer plexiform layers are absent. The retina failed to demonstrate an ERG response. CRISPR/Cas9 gene-editing produced a predictable rat Lrp5 knockout model with extensive defects in the retinal vascular and neural structure and function. This rat model should be useful for studies of exudative retinal vascular diseases involving the Wnt and norrin pathways.

The Evolutionary Trend and Genomic Features of an Emerging Lineage of Elizabethkingia anophelis Strains in Taiwan.

The incidence of Elizabethkingia anophelis bacteremia increased significantly in a tertiary hospital, Changhua Christian Hospital (CCH) since 2013. The infection density was 1.3 and 8.1 cases per 100,000 patient-days between 2005 and 2012 and 2013 and 2020, respectively (P < 0.05). During an outbreak investigation, a specific lineage of E. anophelis strains was identified by the pulsed-field gel electrophoresis analysis. To evaluate the evolution of the specific E. anophelis lineage, whole-genome sequencing was performed, and unique genomic features (GRs) were determined by comparative genomic analysis. The specific E. anophelis lineage was novel compared to worldwide strains ever reported by cg-MLST phylogenic and whole-genome comparative analysis. Multiplex PCR using primers designed from unique GRs were performed for prevalence screening among isolates from the CCH and nationwide isolates from the Taiwan surveillance of Antimicrobial Resistance (TSAR) Program. The proportion of the specific E. anophelis lineage increased from 7.9% (3/38) during 2005-2012 to 89.2% (223/250) during 2013-2020 (P < 0.05). Although E. anophelis usually confers resistance to multiple antibiotics with limited therapeutic options, the E. anophelis strains in the specific lineage had higher ciprofloxacin resistance (100% [226/226] versus 27.4% [17/62], P < 0.05) and was associated with a higher 14-day mortality rates (33.2% [37/226] versus 16.1% [10/62], P < 0.05) than other strains at CCH. A similarly increasing trend was also found in the national TSAR program during 2002-2018 (p for trend <0.05). We concluded that a novel lineage of E. anophelis strains has emerged dominantly in Taiwan. The genomic features are important for further investigations of epidemiology, resistance, virulence, and appropriate treatment. IMPORTANCE Elizabethkingia anophelis is an emerging multidrug resistant pathogen caused several global outbreaks recently. E. anophelis was frequently misidentified as E. meningoseptica in the past by conventional culture methods; therefore, the prevalence was often underestimated. Through revised identification, an increasing trend of E. anophelis infection was noted in a tertiary hospital and a dominant lineage of strains was recognized by genotyping. To our best knowledge, the dominant lineage of E. anophelis is novel in comparison to other worldwide strains by whole-genome comparative analysis and several unique genomic regions were found. The whole-genome sequencing data also demonstrated multiple putative virulence factors and genes associated with multidrug resistance. In our study, we identified a specially evolved E. anophelis in Taiwan with increasing nationwide dominance. This study will assist in further epidemiology surveillance and developing corresponsive infection control policies to restrain it potential of global dissemination.

Quadratus Lumborum Block Spares Postoperative Opioid Usage but Does Not appear to Prevent the Development of Chronic Pain After Gastrointestinal Surgery.

BACKGROUND: Regional anesthesia has been used to reduce acute postsurgical pain and to  prevent chronic pain. The best technique, however, remains controversial. OBJECTIVES: The aim of this study was to assess the short- and long-term postoperative analgesic efficacy of ultrasound-guided quadratus lumborum block (QLB) in open gastrointestinal surgery. STUDY DESIGN: A randomized, double-blinded, controlled trial. SETTING: Operating room; postoperative recovery room and ward. METHODS: One hundred eighteen patients underwent elective gastrointestinal surgery randomly assigned into 2 groups (QLB group or control group). Before anesthetic induction, QLB was performed bilaterally under ultrasound guidance using 20 mL of 0.375% ropivacaine or saline solution at each abdominal wall. The primary outcome was cumulative oxycodone consumption within 24 h after surgery. The secondary outcomes were acute pain intensity, incidence of chronic pain, and incidence of postoperative nausea or vomiting (PONV), dizziness, and pruritus. RESULTS: The cumulative oxycodone consumption was significantly lower in the QLB group during the first 6, 6-24, 24, and 48 h postoperatively when compared to the control group. At rest or during coughing, the numeric rating scale scores were significantly lower at 1, 3, 6, and 12 h postoperatively in the QLB group compared to the control group. There were no significant differences between the 2 groups regarding the incidence of chronic postoperative pain at 3 or 6 months after surgery. Significant differences were found in the incidence of PONV between the two groups, but other complications, such as dizziness and pruritus, did not differ significantly. LIMITATIONS: We did not confirm the QLB effectiveness with sensory level testing after local anesthetic injection. Cumulative oxycodone consumption could have been affected by the patients' use of oxycodone for nonsurgical pain. CONCLUSIONS: Ultrasound-guided QLB provided superior short-term analgesia and reduced oxycodone consumption and the incidence of PONV after gastrointestinal surgery. However, the incidence of chronic pain was not significantly affected by this anesthetic technique.

Recent progress on betulinic acid and its derivatives as antitumor agents: a mini review.

Natural products are one of the important sources for the discovery of new drugs. Betulinic acid (BA), a pentacyclic triterpenoid widely distributed in the plant kingdom, exhibits powerful biological effects, including antitumor activity against various types of cancer cells. A considerable number of BA derivatives have been designed and prepared to remove their disadvantages, such as poor water solubility and low bioavailability. This review summarizes the current studies of the structural diversity of antitumor BA derivatives within the last five years, which provides prospects for further research on the structural modification of betulinic acid.