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Ultrasound is a critical non-invasive test for preoperative diagnosis of ovarian cancer. Deep learning is making advances in image-recognition tasks; therefore, we aimed to develop a deep convolutional neural network (DCNN) model that automates evaluation of ultrasound images and to facilitate a more accurate diagnosis of ovarian cancer than existing methods.In this retrospective, multicentre, diagnostic study, we collected pelvic ultrasound images from ten hospitals across China between September 2003, and May 2019. We included consecutive adult patients (aged ≥18 years) with adnexal lesions in ultrasonography and healthy controls and excluded duplicated cases and patients without adnexa or pathological diagnosis. For DCNN model development, patients were assigned to the training dataset (34 488 images of 3755 patients with ovarian cancer, 541 442 images of 101 777 controls). For model validation, patients were assigned to the internal validation dataset (3031 images of 266 patients with ovarian cancer, 5385 images of 602 with benign adnexal lesions), external validation datasets 1 (486 images of 67 with ovarian cancer, 933 images of 268 with benign adnexal lesions), and 2 (1253 images of 166 with ovarian cancer, 5257 images of 723 benign adnexal lesions). Using these datasets, we assessed the diagnostic value of DCNN, compared DCNN with 35 radiologists, and explored whether DCNN could augment the diagnostic accuracy of six radiologists. Pathological diagnosis was the reference standard.For DCNN to detect ovarian cancer, AUC was 0·911 (95% CI 0·886-0·936) in the internal dataset, 0·870 (95% CI 0·822-0·918) in external validation dataset 1, and 0·831 (95% CI 0·793-0·869) in external validation dataset 2. The DCNN model was more accurate than radiologists at detecting ovarian cancer in the internal dataset (88·8% vs 85·7%) and external validation dataset 1 (86·9% vs 81·1%). Accuracy and sensitivity of diagnosis increased more after DCNN-assisted diagnosis than assessment by radiologists alone (87·6% [85·0-90·2] vs 78·3% [72·1-84·5], p0·0001; 82·7% [78·5-86·9] vs 70·4% [59·1-81·7], p0·0001). The average accuracy of DCNN-assisted evaluations for six radiologists reached 0·876 and were significantly augmented when they were DCNN-assisted (p0·05).The performance of DCNN-enabled ultrasound exceeded the average diagnostic level of radiologists matched the level of expert ultrasound image readers, and augmented radiologists' accuracy. However, these observations warrant further investigations in prospective studies or randomised clinical trials.National Key Basic Research Program of China, National Sci-Tech Support Projects, and National Natural Science Foundation of China.

Background Oxidative stress and inflammation play important roles in the neuronal injury caused by intracerebral hemorrhage (ICH). Uric acid (UA), an important natural antioxidant, might reduce the neuronal injury caused by ICH. Delineating the relationship between UA and ICH will enhance our understanding of antioxidative mechanisms in recovery from ICH. Methods We conducted a retrospective study of 325 patients with acute supratentorial ICH to investigate the relationship between serum UA levels and hematoma volumes and prognosis. A hematoma volume of ≥30 mL was defined as a large hematoma. An unfavorable outcome was defined as a modified Rankin scale score of 4–6 on day 30. Results The serum UA level was significantly lower in the patients with a large hematoma volume (median, 306 μmol/L; 25th to 75th percentile, 243–411 μmol/L) than in those with a small hematoma volume (median, 357 μmol/L; 25th to 75th percentile, 271–442 μmol/L; P = 0.012). Similarly, the unfavorable outcome group had had lower serum UA levels (median, 309 vs. 363 μmol/L; P = 0.009) compared with the favorable outcome group. The results of the multivariate logistic analysis indicated that a lower serum UA level was associated with a larger hematoma volume (odds ratio, 0.996; P = 0.006) and an unfavorable outcome (odds ratio, 0.997; P = 0.030). Conclusions The results from the present study have indicated that in patients with acute supratentorial ICH, a low serum UA level might indicate that the patient has a large hematoma volume and might be a risk factor for a poor day 30 functional prognosis.

Ataxia–telangiectasia mutated (ATM) is a key DNA damage signaling kinase that is mutated in humans with ataxia–telangiectasia (A-T) syndrome. This syndrome is characterized by neurodegeneration, immune abnormality, cancer predisposition, and premature aging. To better understand the function of ATM in vivo, we engineered a viable zebrafish model with a mutated atm gene. Zebrafish atm loss-of-function mutants show characteristic features of A-T-like motor disturbance, including coordination disorders, immunodeficiency, and tumorigenesis. The immunological disorder of atm homozygote fish is linked to the developmental blockade of hematopoiesis, which occurs at the adulthood stage and results in a decrease in infection defense but, with little effect on wound healing. Malignant neoplasms found in atm mutant fish were mainly nerve sheath tumors and myeloid leukemia, which rarely occur in A-T patients or Atm−/− mice. These results underscore the importance of atm during immune cell development. This zebrafish A-T model opens up a pathway to an improved understanding of the molecular basis of tumorigenesis in A-T and the cellular role of atm.

Cystatin C (CysC) has been found to be associated with hemorrhagic and ischemic stroke in many studies. However, the association between CysC level and the risk of delayed cerebral ischemia after endovascular treatment of aneurysmal subarachnoid hemorrhage has been reported rarely. Our study was proposed to explore this association. Consecutive patients from June 2015 to February 2021 in this single-center retrospective study were selected. Univariate and multivariate analyses were used to identify potential prognostic risk factors for delayed cerebral ischemia, and the stability of the association was demonstrated by several statistical methods, such as subgroup analysis, interaction testing, generalized linear models, and propensity score matching. A total of 424 patients were included in the analysis. Cystatin C was independently associated with delayed cerebral ischemia. The independent effects of CysC on delayed cerebral ischemia were shown in generalized linear models with a logit link, and the results were relatively stable in crude, partial, and full models with ORs (95% CIs) for delayed cerebral ischemia. Subgroup analysis showed no significant subgroup differences in the effect of CysC on delayed cerebral ischemia. There was also no interaction effect between CysC and other confounders. Patients in the high CysC group had a higher risk of delayed cerebral ischemia than those in the low CysC group before and after propensity score matching. CysC level could be an independent predictor for the risk of delayed cerebral ischemia after endovascular treatment of aneurysmal subarachnoid hemorrhage.

Ataxia-telangiectasia mutated (

International audience; Zebrafish is broadly used as a model organism in gene loss-of-function studies in vivo, but its employment in vitro is greatly limited by the lack of efficient gene knockdown approaches in zebrafish cell lines such as ZF4. In this article, we attempted to induce silencing of telomere associated genes in ZF4 by applying the frequently-used siRNA transfection technology and a novel moiety-linked morpholino (vivo-MO). By proceeding with integrated optimization of siRNAs transfection and vivo-MOs treatment, we compared five transfection reagents and vivo-MOs simultaneously to evaluate the efficiency of terfa silencing in ZF4. 48 h after siRNAs transfection, Lipofectamine™ 3000 and X-tremeGENE™ HP leaded to knockdown in 35% and 43% of terfa transcription, respectively, while vivo-MO-terfa modulated 58% down-expression of zfTRF2 in contrast to vivo-MO-ctrl 72 h after treatment. Further siRNAs transfection targeting telomere associated genes by X-tremeGENE™ HP showed silencing in 40-68% of these genes without significant cytotoxicity and off-target effect. Our results confirmed the feasibility of gene loss-of-function studies in a zebrafish cell line, offered a systematic optimizing strategy to employ gene silencing experiments, and presented Lipofectamine™ 3000, X-tremeGENE™ HP and vivo-morpholinos as candidate gene silencing approaches for zebrafish in vitro gene loss-of-function studies. Successfully knockdown of shelterin genes further opened a new field for telomeric study in zebrafish.

The expanding population and rapid urbanisation, in particular in the Global South, are leading to global challenges on resource supply stress and rising waste generation. A transformation to resource-circular systems and sustainable recovery of carbon-containing and nutrient-rich waste offers a way to tackle such challenges. Eco-industrial parks have the potential to capture symbioses across individual waste producers, leading to more effective waste-recovery schemes. With whole-system design, economically attractive approaches can be achieved, reducing the nvironmental impacts while increasing the recovery of high-value resources. In this paper, an optimisation framework is developed to enable such design, allowing for wide ranging treatment options to be considered capturing both technological and fnancial detail. As well as technology selection, the framework also accounts for spatial aspects, with the design of suitable transport networks playing a key role. A range of scenarios are investigated using the network, highlighting the multi-faceted nature of the problem. The need to incorporate the impact of resource recovery at the design stage is shown to be of particular importance., Comment: 31 pages, 13 figures

Wastewater treatment plants (WWTPs) are designed to eliminate pollutants and alleviate environmental pollution resulting from human activities. However, the construction and operation of WWTPs consume resources, emit greenhouse gases (GHGs) and produce residual sludge, thus require further optimization. WWTPs are complex to control and optimize because of high non-linearity and variation. This study used a novel technique, multi-agent deep reinforcement learning (MADRL), to simultaneously optimize dissolved oxygen (DO) and chemical dosage in a WWTP. The reward function was specially designed from life cycle perspective to achieve sustainable optimization. Five scenarios were considered: baseline, three different effluent quality and cost-oriented scenarios. The result shows that optimization based on LCA has lower environmental impacts compared to baseline scenario, as cost, energy consumption and greenhouse gas emissions reduce to 0.890 CNY/m3-ww, 0.530 kWh/m3-ww, 2.491 kg CO2-eq/m3-ww respectively. The cost-oriented control strategy exhibits comparable overall performance to the LCA-driven strategy since it sacrifices environmental benefits but has lower cost as 0.873 CNY/m3-ww. It is worth mentioning that the retrofitting of WWTPs based on resources should be implemented with the consideration of impact transfer. Specifically, LCA-SW scenario decreases 10 kg PO4-eq in eutrophication potential compared to the baseline within 10 days, while significantly increases other indicators. The major contributors of each indicator are identified for future study and improvement. Last, the authors discussed that novel dynamic control strategies required advanced sensors or a large amount of data, so the selection of control strategies should also consider economic and ecological conditions. In a nutshell, there are still limitations of this work and future studies are required.

To explore the necessity and feasibility of early anti-depressive therapies in acute stroke patients, we conducted a meta-analysis of currently available randomized control studies (RCTs). Literature search in six databases was done with keywords of cerebrovascular accident, depression and prevention. Only RCTs that met the inclusion criteria were enrolled for further analysis. Twelve eligible studies were included in this meta-analysis. Prophylactic anti-depressive therapies following acute stroke were shown to reduce the incidence of depression in the patients (RR = =0.33, 95% CI: 0.25 to 0.43, p 0.001), improve symptoms of depression (WMD: 5.73, 95% CI: 4.18 to 7.29, p 0.001), improve motor function (WMD: 12.56, 95%CI: 9.07 to 16.04, p 0.001) and neurological function (WMD: 1.13, 95%CI: 0.57 to 1.69, p 0.001). However, anti-depressive therapies showed no effects on mortality (RR = 1.63, 95%CI: 0.55 to 4.85, p = 0.377) and adverse events incidence (RR = 0.93, 95%CI: 0.53 to 1.64, p = 0.806). Anti-depressive therapies following acute stroke is effective thus deserves to be advocated.

Wastewater treatment plants (WWTPs) play an important role within the urban water cycle in preventing the natural water environment and human health from being negatively affected by human activities. However, wastewater treatment processes such as the discharge of effluent and indirect emissions resulting from energy or chemical production, also negatively affect the environment. Footprints have been used to track human influence on the environment through different areas of concern and have been applied in assessing the sustainability of WWTPs. A comprehensive review of footprint assessment for evaluating the wastewater treatment process in WWTPs was investigated in this article. The review showed that the carbon footprint and the water footprint were the two of the most popular footprints for evaluating the sustainability of WWTPs, and other footprint (such as nitrogen and phosphorus footprints) assessment applications were also introduced to assess the eutrophication of water bodies. To promote the application of footprint assessment on WWTP, this article regulated the study goals, frameworks, system boundary, data treatment methods, resultant interpretation process. The pros and cons of footprint assessments were discussed and investigated in detail, several suggestions were come up with for the improvement of footprint assessments. The analyzation of footprint assessments under different WWTPs revealed that wastewater treatment technologies and scales significantly impacted the footprints. Moreover, the research hotspots identified by way of a keyword network diagram showed that researchers tended to propose new indicators and models for the grey water footprint and the carbon footprint respectively, and water-carbon-energy nexus was a promising direction for future studies. Finally, two possible application scenarios, element tracing through modified footprints and management improvement through mathematical optimization, were proposed to optimize the operation strategies of WWTPs. Overall, footprint assessment research for WWTPs is still at the initial stage and needs further exploration and improvement, e.g. introducing new tools, exploring system variation under various scenarios, combining other footprints, and implementing the nexus assessment.

As an essential dynamic evolving mechanism, triangle behavior can be observed ubiquitously in the real world. Combining transfer mechanism with weighted dynamic, in this paper, we propose a new community model and deduce the strength distribution. Consistent with the theoretical results, numerical simulations show decent right-skewed scale-free characters of strength distribution. Moreover, we calculate some important coefficients to analyze the correlations of nodes and demonstrate the disassortative property of this model. Finally, the process of epidemic spreading with different weighted transmission rate is introduced on the weighted community network, and the results indicate that the triangle behavior has a significant influence on the dynamic of the epidemic spreading. Composed with the models proposed already, our model is supposed to be closer to the realistic network and imitate the real system more accurately and exactly.

Tensile stress occurs in the vicinity of upper surface of the specimen in the severe plastic deformation zone, which increases the cracking and fracture tendency of the specimen and impedes the further ECAP processing. In this paper, the conventional ECAP die (Ψ = 16° and Φ = 90°) was modified to eliminate the tensile stress and enhance the compressive stress in the severe plastic deformation zone, therefore reducing the cracking and fracture tendency of the specimen. Finite element analysis demonstrated that the stress state changes from tensile to strongly compressive when using the modified die. A modified die was made and employed to extrude the commercially pure aluminum to verify its effectiveness experimentally. The billet was successfully extruded for 20 passes without obvious surface defects with the modified die, compared to 13–14 passes at most for the conventional die. Consequently, much more fine and uniform microstructure was obtained with the average grain size of 200–300 nm, while the average grain size is ∼500 nm in the case of using the conventional die.

This paper analyzed the statistical data that collected by four air quality monitoring stations in Longyan city, Fujian Province, which indicate that the percentage of sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ) and respirable particulate matter (PM 10 ) in atmosphere. The annual average concentrations of the three pollutants are calculated. Then the fuzzy evaluation method is applied to evaluate the air quality of Longyan city. The result indicates that the air quality of Longyan city is improving better year by year. Its air quality meets the national air quality standards for grade II in most times. Respirable particulate matter (PM 10 ) is the key pollutant that influences the evaluation result of Longyan's air quality. According to the result, many countermeasures to improve the air quality of Longyan city are presented.