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Protein aggregation causes alpha-synuclein (α-syn) to change from its original physiological role to a pathological state, which is a potential pathogenic mechanism in Parkinson’s disease (PD). Chi...

Determination of 1p/19q co-deletion status is important for the classification, prognostication, and personalized therapy in diffuse lower-grade gliomas (LGG). We developed and validated a deep learning imaging signature (DLIS) from preoperative magnetic resonance imaging (MRI) for predicting the 1p/19q status in patients with LGG. The DLIS was constructed on a training dataset (n = 330) and validated on both an internal validation dataset (n = 123) and a public TCIA dataset (n = 102). The receiver operating characteristic (ROC) analysis and precision recall curves (PRC) were used to measure the classification performance. The area under ROC curves (AUC) of the DLIS was 0.999 for training dataset, 0.986 for validation dataset, and 0.983 for testing dataset. The F1-score of the prediction model was 0.992 for training dataset, 0.940 for validation dataset, and 0.925 for testing dataset. Our data suggests that DLIS could be used to predict the 1p/19q status from preoperative imaging in patients with LGG. The imaging-based deep learning has the potential to be a noninvasive tool predictive of molecular markers in adult diffuse gliomas. The authors developed a deep learning model predictive of 1p/19q status from preoperative imaging in 555 lower-grade gliomas (LGG), and achieved an area under the curve (AUC) of 0.983 in the testing dataset. They reveal that developing deep learning imaging signatures could be a noninvasive tool for predicting molecular markers in LGG.

Community-supported agriculture (CSA) is an alternative food marketing model in which community members subscribe to receive regular shares of a farm's harvest. Although CSA has the potential to improve access to fresh produce, certain features of CSA membership may prohibit low-income families from participating. A ‘cost-offset’ CSA (CO-CSA) model provides low-income families with purchasing support with the goal of making CSA more affordable. As a first step toward understanding the potential of CO-CSA to improve access to healthy foods among low-income households, we interviewed 24 CSA farmers and 20 full-pay CSA members about their experiences and perceptions of the cost-offset model and specific mechanisms for offsetting the cost of CSA. Audio recordings were transcribed verbatim and coded using a thematic approach. Ensuring that healthy food was accessible to everyone, regardless of income level, was a major theme expressed by both farmers and members. In general, CSA farmers and CSA members favored member donations over other mechanisms for funding the CO-CSA. The potential time burden that could affect CSA farmers when administering a cost-offset was a commonly-mentioned barrier. Future research should investigate various CO-CSA operational models in order to determine which models are most economically viable and sustainable.

To detect and forecast solar weather in advance is of great importance for humankind to protect power infrastructure on ground and communication satellites in orbit from damaging. In this regard, a large space platform consisting of a solar weather detector, long space tether and a sailcraft with actively adjustable lightness number is constructed. Within the elliptic Sun-Earth restricted three-body system (ESERTBS), merely the motion of the platform along the Sun-Earth line is focused on, full nonlinear dimensional and dimensionless dynamics of the system is established with a massless, taut and rigid/flexible tether. A sliding mode controller is developed to make the closed-loop dynamics asymptotically stable and the prescribed constant dimensional distance between the Sun and detector is maintained thereby. The time histories of some critical variables of the closed-loop system are presented to verify the performance of the developed controller, to check the lightness number of the sailcraft required, to show the internal tension/strain within the tether etc. Moreover, the steady-state responses of the closed-loop dynamic system are also presented to give more information. The lightness number of a single sailcraft used for performing the mission is compared to the lightness number of the sailcraft of the proposed platform. Some discussions and suggestions for selecting the tether’s length and elasticity are presented from the aspect of the lightness number required, the internal tension and strain based on numerical simulations.

To identify the indications for hepatocellular carcinoma (HCC) irradiated by intensity-modulated photon radiotherapy (IMRT), proton radiotherapy (PRT) or carbon-ion radiotherapy (CIRT) by comparing of dosimetric parameters and incidences of classic radiation-induced liver disease (RILD). In all, 40 HCCs were divided into group A (tumors located > 1 cm away from gastrointestinal [GI] tract), and group B (tumors located

Objectives This study was performed to internally derive and then validate risk score systems using preoperative and intraoperative variables to predict the occurrence of any-stage (stage 1, 2, 3) and stage-3 acute kidney injury (AKI) within seven days of cardiac surgery. Design Single-center, retrospective, observational study. Setting Single, large, tertiary care center. Participants Adult patients undergoing open cardiac surgery between January 1, 2012, and January 1, 2019. Measurements and Main Results The clinical data were divided into the following two groups: a derivation cohort (n = 43,799) and a validation cohort (n = 14,600). AKI was defined using the Kidney Disease: Improving Global Outcomes criteria. Multivariate logistic regression analysis was used to develop the prediction models. The overall prevalence of any-stage AKI and stage-3 AKI after cardiac surgery were 34.3% and 1.7%, respectively. The discriminatory ability of the any-stage AKI prediction model measured with the area under the curve (AUC) was acceptable (AUC = 0.69, 95% confidence interval 0.68-0.69), and the calibration measured with the Hosmer-Lemeshow test was good (p = 0.95). The AUC for the stage-3 AKI prediction model was 0.84 (95% confidence interval 0.83-0.85), and the Hosmer-Lemeshow test also indicated a good calibration (p = 0.73). Conclusions This research study, which used preoperative and intraoperative variables, derived and internally validated two predictive scoring systems for any-stage AKI and stage-3 AKI as defined by modified Kidney Disease: Improving Global Outcomes criteria using a very large cohort of Chinese cardiac surgical patients.

Recently, salient object detection (SOD) has witnessed vast progress with the rapid development of convolutional neural networks (CNNs). However, the improvement of SOD accuracy comes with the increase in network depth and width, resulting in large network size and heavy computational overhead. This prevents state-of-the-art SOD methods from being deployed into practical platforms, especially mobile devices. To promote the deployment of real-world SOD applications, we aim at developing a lightweight SOD model in this article. Our observation comes from that the primate visual system processes visual signals hierarchically with different receptive fields and eccentricities in different visual cortex areas. Inspired by this, we propose a hierarchical visual perception (HVP) module to imitate the primate visual cortex for hierarchical perception learning. With the HVP module incorporated, we design a lightweight SOD network, namely, HVPNet. Extensive experiments on popular benchmarks demonstrate that HVPNet achieves highly competitive accuracy compared with state-of-the-art SOD methods while running at 4.3 frames/s CPU speed and 333.2 frames/s GPU speed with only 1.23M parameters.

PurposeThis paper investigates individual investors' responses to stock underpricing and how their trading decisions are affected by analysts' forecasts and recommendations.Design/methodology/approachThis empirical study uses mutual fund fire sales as an exogenous source that causes stock underpricing and analysts' forecasts and recommendations as price-correcting information. The study further uses regression analysis to examine individual investors' responses to fire sales and how their responses vary with price-correcting information.FindingsThe authors first show that individual investors respond to mutual fund fire sales by significantly decreasing net buys, and this effect appears to be prolonged. Next, the authors find that the decrease of net buys diminishes following analysts' price-correcting earnings forecast revisions and stock recommendation changes. Hence, the authors suggest that individual investors are not “wise” enough to recognize flow-driven underpricing; however, this response is weakened by analysts' price-correcting information.Originality/valueThere is an ongoing debate in the literature about whether individual investors should be portrayed as unsophisticated traders or informed traders who can predict future returns. The authors study a unique information event and provide new evidence related to both perspectives. Overall, our evidence suggests that the “unsophisticated traders” perspective is predominant, whereas a better information environment significantly reduces individual investors' information disadvantage. This finding could be of interest to both academic researchers and regulators.

Gliomas can be classified into five molecular groups based on the status of IDH mutation, 1p/19q codeletion, and TERT promoter mutation, whereas they need to be obtained by biopsy or surgery. Thus, we aimed to use MRI-based radiomics to noninvasively predict the molecular groups and assess their prognostic value. We retrospectively identified 357 patients with gliomas and extracted radiomic features from their preoperative MRI images. Single-layered radiomic signatures were generated using a single MR sequence using Bayesian-regularization neural networks. Image fusion models were built by combing the significant radiomic signatures. By separately predicting the molecular markers, the predictive molecular groups were obtained. Prognostic nomograms were developed based on the predictive molecular groups and clinicopathologic data to predict progression-free survival (PFS) and overall survival (OS). The results showed that the image fusion model incorporating radiomic signatures from contrast-enhanced T1-weighted imaging (cT1WI) and apparent diffusion coefficient (ADC) achieved an AUC of 0.884 and 0.669 for predicting IDH and TERT status, respectively. cT1WI-based radiomic signature alone yielded favorable performance in predicting 1p/19q status (AUC = 0.815). The predictive molecular groups were comparable to actual ones in predicting PFS (C-index: 0.709 vs. 0.722, P = 0.241) and OS (C-index: 0.703 vs. 0.751, P = 0.359). Subgroup analyses by grades showed similar findings. The prognostic nomograms based on grades and the predictive molecular groups yielded a C-index of 0.736 and 0.735 in predicting PFS and OS, respectively. Accordingly, MRI-based radiomics may be useful for noninvasively detecting molecular groups and predicting survival in gliomas regardless of grades.

The spectral clustering method has notable advantages in segmentation. But the high computational complexity and time consuming limit its application in large-scale and dense airborne Light Detecti...

The study investigated the dosimetric impact of an iterative metal artifact reduction (iMAR) tool on carbon ion therapy for pelvic cancer patients with hip prostheses. An anthropomorphic pelvic phantom with unilateral and bilateral hip prostheses was used to simulate pelvic cancer patients with metal implants. The raw data obtained from phantom CT scanning were reconstructed with a regular filtered back projection (FBP) algorithm and then corrected with iMAR. The phantom without hip prosthesis was also scanned and used as a reference ground truth (GT). The CT images of three prostate and four sarcoma patients with unilateral hip prosthesis were also reconstructed by FBP and iMAR algorithm and compared. iMAR algorithm reduced the metal artifacts and the maximum WEPL deviation in phantom images from −19.1 to −0.4 mm. However, the CT numbers cannot be retrieved using iMAR for periprosthetic bone materials, eventually leading to a WEPL deviation of −3.6 mm. The use of iMAR improved large discrepancies in DVHs of PTVs and the gamma index between FBP and GT images but increased the difference in the bladder DVH for bilateral hip prostheses due to newly introduced artifacts. In the patient study, the discrepancies of dose distribution were small on iMAR images when compared with FBP images for most cases, except for two sarcoma cases where gamma analysis failed and dose coverage in 98% of the PTV maximally reduced due to large volume of dark metal artifacts. iMAR reduced the metal artifacts and improved dose distribution accuracy in carbon ion radiotherapy for pelvic cancer. However, the residual and newly introduced artifacts, especially with bilateral hip prostheses, may potentially increase WEPL inaccuracy and dose uncertainty. The use of iMAR has the potential to improve carbon ion treatment planning of pelvic cancer but should be used with caution.

Owners of small- and medium-sized farms are increasingly interested in engaging in agritourism and direct sales in order to increase income, provide family employment, and educate the public about agriculture, among other reasons. Prior research on agritourism operator motivations largely focuses on economic goals and benefits, while acknowledging the strong influence of non-economic factors. However, more research is needed to better understand the nuances and breadth of non-economic motivations underlying agritourism operator decisions. In addition, research on U.S. agritourism tends to be at the state level, which raises questions about overall national trends and inter-study comparability. To address these gaps, we analyzed transcripts from semistructured interviews with small- and medium-sized farm owners engaged in agritourism from five states across the U.S. We examined the results through the theoretical lens of Allport’s “contact hypothesis” in order to further understand how agritourism helps operators meet stated goals. Our results suggest that consistent with previous literature, nonmonetary motivations are high priorities for farmers engaged in agritourism. In particular, motivations related to community engagement/leadership and quality-of-life emerged as forceful and reoccurring themes. We found that although Allport’s contact hypothesis holds some important explanatory power for understanding agritourism operators’ community-related goals—including reducing prejudice and increasing understanding between farmers and consumers in relation to agriculture—increased inter-group contact also has potential to create new conflicts between farmers and neighbors related to tourism. These findings have important implications for future research as well as for policies and programs aimed at supporting agritourism. Note Correction published on August 21, 2021, to replace references to Allport’s conflict hypothesis to the correct contact hypothesis.

Surface damage of structures is an important indicator that further inspection of the structure is needed. However, existing detection methods rarely detect three-dimensional data of damage. Aiming at the inspection of structural surface damage, this study proposes a method based on 3-D structural surface damage reconstruction techniques for reconstructing and extracting data for damage volume calculation. The surface damage of concrete specimen is three-dimensionally reconstructed using multi-view smartphone-taken images and compared with a depth camera. The point cloud data was obtained, and then the damage plane was fitted and removed by a Random Sample Consensus algorithm to obtain the damage site data, finally, the damage volume was calculated. In the experimental process, accuracy and post-processing difficulty, equipment cost, data acquisition efficiency, and overall applicability of the two methods were compared and analyzed. In conclusion, it was determined that the 3-D damage parameters obtained through the smartphone multi-view stereo reconstruction performs better, at a lower cost and is more convenient for use in inspection work. Finally, the practicability of the method was proved by the damage detection experiment of real building.

The elucidation of intermolecular interactions for the systematic control of nucleation and crystallization is key to produce perovskite photovoltaics with superior performance. In this study, we a...

The Farm Fresh Food Box (F3B) strategy is a hybrid of direct-to-consumer (DTC) and short value chain models that aims to stimulate rural economies, creates an additional sales avenue for small farmers, provides rural grocery stores with increased foot traffic and overcomes barriers for rural consumers who are unable to access local food. The F3B project is a tri-state collaboration of extension and research partners from three states; two on the West Coast and one in the Northeast United States, involving small farmers and retailers from rural communities. This article analyzes F3B consumer surveys from 2 years of project implementation and contributes to the limited body of research on food box models by identifying benefits and barriers of the F3B strategy for consumers, comparing these findings to existing research on food box programs and other DTC market channels, and discussing implications for future model adjustment. Overall, consumers were pleased with all aspects of the F3B. However, the strategy had limited success with reaching a new demographic of local food consumers.

Background: Inflammation is the body’s immune system’s fast coordinating response to irritants caused by pathogens, external injuries, and chemical or radiation effects. The nucleotidebinding oligomerization domain-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome is a critical component of the innate immune system. The dysfunction of NLRP3 inflammasome contributes to various pathogeneses of complex diseases, such as uncontrolled infection, autoimmune diseases, neurodegenerative diseases, and metabolic disorders. This review describes recent progress on the discovery of NLRP3 inflammasome inhibitors and their therapeutic potential. Methods: Based on the mechanism of NLRP3 activation, several types of NLRP3 inhibitors are described and summarized according to their origins, structures, bioactivity, and mechanism of action. Structure-Activity Relationship (SAR) is also listed for different scaffolds, as well as effective pharmacophore. Results: Over one-hundred papers were included in the review. The development of NLRP3 inhibitors has been described from the earliest glyburide in 2001 to the latest progress in 2019. Several series of inhibitors have been categorized, such as JC-series based on glyburide and BC-series based on 2APB. Many other small molecules such as NLRP3 inhibitors are also listed. SAR, application in related therapeutic models, and five different action mechanisms are described. Conclusion: The findings of this review confirmed the importance of developing NLRP3 inflammasome inhibitors. Various NLRP3 inhibitors have been discovered as effective therapeutic treatments for multiple diseases, such as type II diabetes, experimental autoimmune encephalomyelitis, stressrelated mood disorders, etc. The development of a full range of NLRP3 inflammasome inhibitors is still at its foundational phase. We are looking forward to the identification of inhibitory agents that provide the most potent therapeutic strategies and efficiently treat NLRP3 inflammasome-related inflammatory diseases.

Nowadays, sensors are increasingly pursuing the characteristics of miniaturization and high sensitivity. A self-powered ethanol gas sensor based on Ag/ZnO nanowire arrays prepared by two-step hydrothermal method is reported. The piezoelectric output of Ag/ZnO nanowire arrays serves as power supply for self-powered sensors, which also can detect various concentrations of ethanol gas at room temperature. It is verified that the piezoelectric output capability of the sensor increases greatly after Ag-doping. Upon exposure to ethanol gas with concentration increasing from 10 to 1000 ppm, the piezoelectric output voltage for the sensor decreases from 1.75 to 0.2 V. The reason is attributed to the addition of Ag, which plays a strong catalytic role. At the same time, Schottky barrier is formed between Ag and ZnO, which affects the piezoelectric gas sensing performance and accelerates the reaction. The results show that this method is a feasible way to realize self-powered gas sensor for various applications.

Aberrations in the stress response are associated with posttraumatic stress disorder (PTSD) symptom development, maintenance, and severity. Gamma-aminobutyric acid (GABA), the brain’s primary inhibitory neurotransmitter, may play a key role in stress recovery. In this preliminary study, we examined whether plasma GABA levels differed between women with PTSD and trauma-exposed healthy controls. Thirty participants provided plasma samples during two phases of the menstrual cycle: the early follicular phase and the mid-luteal phase. During each phase, blood was drawn after 45 min of rest, and after mild and moderately stressful psychophysiological tasks. Plasma GABA levels were measured using HPLC-mass spectrometry (LC-MS/MS). In analyses using PTSD diagnosis as a categorical group variable, women with and without a diagnosis of PTSD did not differ in plasma GABA levels (ps > .18). However, in analyses examining PTSD symptom severity as a continuous variable, there was a trend-level positive association between more severe PTSD symptoms and higher plasma GABA levels across the four blood draws (p = .06). In analyses examining DSM-IV PTSD symptom clusters separately, dysphoria symptoms were positively and significantly associated with plasma GABA levels (p = .03). Similarly, there was a trend-level positive association between avoidance cluster symptoms and plasma GABA levels (p = .06). Plasma GABA levels were not modulated by experimentally induced stress or menstrual cycle phase. Dysregulation in GABA may be a neurobiological marker and/or potential treatment target for women with PTSD symptom profiles characterized by prominent dysphoria and avoidance cluster symptoms.

In recent years, learning-based image hashing techniques have elicited wide interest among researchers because they can be applied in high-dimensional data such as videos and images. Supervised hashing techniques can achieve a satisfactory retrieval performance, but are excessively reliant on label information, resulting in the appearance of unsupervised hashing methods. However, existing unsupervised hashing methods often fail to obtain effective similarity information from the training set; this causes a large degradation in their retrieval performance. Some pseudo label-based methods partially alleviate this problem, but are sensitive to the pre-defined number of categories. Therefore, in this paper, we mainly discuss a solution to the above-mentioned problems regarding image hashing. We propose a sparse graph based self-supervised hashing method in which a sparse graph is constructed, which not only circumvents the requirement of a predefined number of categories as compared with pseudo label-based methods, but also significantly reduces the memory demand compared with a dense graph-based method. In addition, we also exploit a self-supervised reconstruction constraint to further preserve the semantic information. These items are combined in a linear manner and optimized using an iterative strategy. Four representative datasets, including two single-label and two multi-label datasets, are employed to evaluate our method. The results, based on multiple metrics, show that our method can outperform other state-of-the-art methods.

Most of the behavior models with respect to Web applications focus on sequencing of events, without regard for the changes of parameters or elements and the relationship between trigger conditions of events and Web pages. As a result, these models are not sufficient to effectively represent the dynamic behavior of the Web 2.0 application. Therefore, in this paper, to appropriately describe the dynamic behavior of the client side of Web applications, we define a novel Client-side Behavior Model (CBM) for Web applications and present a user behavior trace-based modeling method to automatically generate and optimize CBMs. To verify the effectiveness of our method, we conduct a series of experiments on six Web applications according to three types of user behavior traces. The experimental results show that our modeling method can construct CBMs automatically and effectively, and the CBMs built are more precise to represent the dynamic behavior of Web applications.

Vehicle types, technologies, and driving conditions are key factors affecting emission factors and fuel consumption. In this study, we measured the hydrocarbon (HC), carbon monoxide (CO), and nitrogen oxide (NOx) emission factors, and fuel consumption of vehicles with a (1) carburetor (CVs), (2) multipoint injection technology and three-way catalyst (MTVs), and (3) multipoint injection technology, three-way catalyst, and exhaust gas recirculation device (MTEVs) under real driving conditions using an OBS-2200 portable emission measurement system. The results showed that both the distance- and fuel-based HC, CO, and NOx emission factors of CVs were 2.7–6.6 times higher than those of MTVs and MTEVs. The average incomplete fuel conversion rates (IFCRs) of CVs were 3.8 and 4.4 times higher than those of MTVs and MTEVs, respectively. The molar ratios of the CO/HC pollutants were 7.6, 5.6, and 2.8 for CVs, MTVs, and MTEVs. Furthermore, the correlation between the vehicle-specific power and fuel consumption rate was significant. The exhaust gas recirculation (EGR) system could improve the fuel combustion efficiency and reduce vehicle emissions, particularly under high-speed and acceleration conditions.

This study analyzed a new drying method using airborne ultrasound combined with microwave vacuum to study its effect on the quality characteristics and microstructure of dehydrated L. edodes. Ultrasonic treatment resulted in many micropores in the product, forming the sponge effect caused by ultrasonic waves, which can promote the rapid evaporation of water in the product. Samples of Lentinula edodes individuals were dried using four methods: hot air drying (HAD), microwave vacuum drying (MVD), microwave vacuum drying after ultrasonic pretreatment (US+MVD) and airborne ultrasonic treatment combined with microwave vacuum drying (USMVD). The results showed that USMVD can reduced the loss of total sugar, total phenol, and total antioxidants in L. edodes, and increased the relative content of ergosterol, sulfur compounds, and free amino acids (p < 0.05). Scanning electron microscope observation revealed that USMVD resulted in a uniform reticular porous structure, which could better maintain desirable levels of nutrients. Therefore, USMVD can produce high quality products. PRACTICAL APPLICATION: Airborne ultrasonic waves combined with MVD provides an innovative drying method for mushrooms, which has not been studied at present. The mixed drying method has great potential in maintaining product quality. It provides a theoretical basis for studying drying technology in the future.

The emergency supply of transboundary water resources is a prominent problem affecting the social and economic development of basin countries. However, current water supply decisions on transboundary water resources may ignore the psychological perception of multi-stakeholders, and the evolution of emergencies increases the uncertainty of decision making. Both factors would lead to the low acceptance of water-related decisions. Utility satisfaction, perceived losses, and quantity satisfaction were selected in this paper to identify the perceived satisfaction of upstream governments, downstream governments, and the public, respectively, over multiple decision-making stages. A modeling framework combining prospect theory and the multi-stage multi-objective programming methodology was then developed to measure the perceived satisfaction of different stakeholders in a watershed under emergency. A two-stage NSGA-II and TOPSIS based approach was adopted to find the optimal compromise solution to solve the model. The framework was applied in the Lancang–Mekong River basin to provide suggestions to decision makers. Upstream decision makers must choose a moderate proportional fairness degree when making emergency decisions to maximize the perceived satisfaction of all stakeholders. Meanwhile, the perceived loss of downstream countries with low water demand should be considered first in the formulation of emergency water supply plans. Furthermore, although water supply from upstream countries can improve perceived water quantity satisfaction of downstream publics, additional actions must still be taken to change the traditional concepts of the public.

The accurate annotation of protein localization is crucial in understanding protein function in tandem with a broad range of applications such as pathological analysis and drug design. Since most proteins do not have experimentally-determined localization information, the computational prediction of protein localization has been an active research area for more than two decades. In particular, recent machine-learning advancements have fueled the development of new methods in protein localization prediction. In this review paper, we first categorize the main features and algorithms used for protein localization prediction. Then, we summarize a list of protein localization prediction tools in terms of their coverage, characteristics, and accessibility to help users find suitable tools based on their needs. Next, we evaluate some of these tools on a benchmark dataset. Finally, we provide an outlook on the future exploration of protein localization methods.

Based on the analysis of the multi-scale-based and sparse representation-based multi-focus image fusion method, we believe that a multi-scale fusion method should consider the directivity of high/low frequency sub-bands and low computational complexity, ensuring the effectiveness and efficiency. Therefore, we propose a novel multi-focus image fusion algorithm based on multi-scale and multi-directional dictionaries. In the proposed method, source images are decomposed by multi-scale transform(MST) to obtain high/low frequency sub-bands. For the high-frequency part, a direction contrast-based fusion rule is presented. For the low-frequency part, the image patches are divided into strong/weak information patches. The strong information patches are merged with a fusion approach based on directional dictionaries, while the weak information patches are fused using weighted average. Finally, the fused image is obtained by performing the inverse MST. The experimental results show that the proposed approach extracts more important effective information from source images, and the computational efficiency is greatly improved.

Background: To develop machine-learning based models to predict the progression-free survival (PFS) and overall survival (OS) in patients with gliomas and explore the effect of different feature selection methods on the prediction. Methods: We included 505 patients (training cohort, n = 354; validation cohort, n = 151) with gliomas between January 1, 2011 and December 31, 2016. The clinical, neuroimaging, and molecular genetic data of patients were retrospectively collected. The multi-causes discovering with structure learning (McDSL) algorithm, least absolute shrinkage and selection operator regression (LASSO), and Cox proportional hazards regression model were employed to discover the predictors for 3-year PFS and OS, respectively. Eight machine learning classifiers with 5-fold cross-validation were developed to predict 3-year PFS and OS. The area under the curve (AUC) was used to evaluate the prognostic performance of classifiers. Results: McDSL identified four causal factors (tumor location, WHO grade, histologic type, and molecular genetic group) for 3-year PFS and OS, whereas LASSO and Cox identified wide-range number of factors associated with 3-year PFS and OS. The performance of each machine learning classifier based on McDSL, LASSO, and Cox was not significantly different. Logistic regression yielded the optimal performance in predicting 3-year PFS based on the McDSL (AUC, 0.872, 95% confidence interval [CI]: 0.828-0.916) and 3-year OS based on the LASSO (AUC, 0.901, 95% CI: 0.861-0.940). Conclusions: McDSL is more reproducible than LASSO and Cox model in the feature selection process. Logistic regression model may have the highest performance in predicting 3-year PFS and OS of gliomas.

Cancer vaccines designed to initiate or amplify tumor-specific T-cell responses have been used as a key approach for effective cancer immunotherapy. Across the history of tumor antigens, now we are entering the era of personalized, antigenic epitope-based molecular cancer vaccine. Unfortunately, the immunotherapeutic efficiency of peptide vaccines in human patients is still limited. The weak immunogenicity of peptide antigens is a major limitation for inducing a satisfactory antitumor T-cell response, thus additional immunoadjuvants and delivery systems for non-covalent peptide encapsulation are commonly used in clinic. Beyond this approach, self-assembled molecular peptide vaccines by chemical conjugation of epitope to a self-assembling peptide or the construction of amphiphilic peptide conjugates hold great promise as next generation peptide vaccines to elicit stronger or broader cellular responses that can dramatically increase the immunotherapy efficiency of peptide vaccines. In this review, we summarize recent approaches and progresses for manufacturing self-assembled, self-adjuvanting, and fully synthetic peptide vaccines and their performance for cancer immunotherapy. We also propose multivalent nanovaccines prepared by co-assembly strategy as the future development of peptide cancer vaccines, as well as vaccination in combination with other treatments including immune checkpoint blockade, immunogenic chemo-/radio-therapy as novel synergetic therapies for cancer.

Adult medulloblastomas are clinically and molecularly understudied due to their rarity. We performed molecular grouping, targeted sequencing, and TERT promoter Sanger sequencing on a cohort of 99 adult medulloblastomas. SHH made up 50% of the cohort, whereas Group 3 (13%) was present in comparable proportion to WNT (19%) and Group 4 (18%). In contrast to paediatric medulloblastomas, molecular groups had no prognostic impact in our adult cohort (p = 0.877). Most frequently mutated genes were TERT (including promoter mutations, mutated in 36% cases), chromatin modifiers KMT2D (31%) and KMT2C (30%), TCF4 (31%), PTCH1 (27%) and DDX3X (24%). Adult WNT patients showed enrichment of TP53 mutations (6/15 WNT cases), and 3/6 TP53-mutant WNT tumours were of large cell/anaplastic histology. Adult SHH medulloblastomas had frequent upstream pathway alterations (PTCH1 and SMO mutations) and few downstream alterations (SUFU mutations, MYCN amplifications). TERT promoter mutations were found in 72% of adult SHH patients, and were restricted to this group. Adult Group 3 tumours lacked hallmark MYC amplifications, but had recurrent mutations in KBTBD4 and NOTCH1. Adult Group 4 tumours harboured recurrent mutations in TCF4 and chromatin modifier genes. Overall, amplifications of MYC and MYCN were rare (3%). Since molecular groups were not prognostic, alternative prognostic markers are needed for adult medulloblastoma. KMT2C mutations were frequently found across molecular groups and were associated with poor survival (p = 0.002). Multivariate analysis identified histological type (p = 0.026), metastasis (p = 0.031) and KMT2C mutational status (p = 0.046) as independent prognosticators in our cohort. In summary, we identified distinct clinical and mutational characteristics of adult medulloblastomas that will inform their risk stratification and treatment.

Background Microsatellite instability (MSI) has been a hot topic in cancer research. Determining MSI status greatly aids tumor prognosis and treatment plans. However, MSI data for Asian cancer patients with prognostic information are scarce. Here, our aim was to clarify MSI status and its prognostic value in a large Chinese cohort with different tumors. Patients and Methods Tissue samples from 600 Chinese cases, including 150 endometrial cancers, 150 colorectal cancers, 150 liver cancers and 150 gastric cancers, were used for IHC and MSI examinations. Two mononucleotide and three dinucleotide markers were used to analyze MSI status. Results In total,17.3% (26/150) of endometrial cancer patients showed positive MSI,10.0% (15/150) in colorectal cancer, 2.7% (4/150) in liver cancer, and 2.7% (4/150) in gastric cancer. Tumor location (P < 0.001 for colorectal cancer) and clinical stage (P =0.038 for gastric cancer) showed significant correlations with MSI status in gastrointestinal carcinogenesis. The mismatch repair (MMR) deficiency was observed in 20 colorectal cases (13.3%) and was significantly more frequent in the MSI-positive group (P < 0.001). Interestingly, the prevalence of MSI-H was mostly occurred in early-stage tumors, and none was in late stage (stage IV). Meanwhile, low clinicopathological stage had significant correlation with longer survival in multiple cancers here. Conclusion The incidence of microsatellite instability varies among different cancer types. And the prevalence of MSI-H mostly occurred early clinicopathological stage. In addition, our study provided a large Asian cohort screened by five loci PCR method and significantly increased knowledge on the prognostic significance of MSI in Asia.

Malnutrition is highly prevalent in hospitalized children and it is associated with severe morbidity and mortality outcomes. In addition malnutrition increases duration of hospitalization and hospital costs. Because of these reasons, so as to prevent the malnutrition several nutritional screening tools have been developed for hospitalized children in the last years. There are nine screening tools available in the literature. The screening tools should be valid and reliable. Beside this it is important that screening tools should be simple and take less time. Currently, there is no standardized nutritional screening tool for pediatric inpatients like adult inpatients. Tools should be revised and reevaluated with using anthropometric measurements, according to WHO growth charts. Besides, the accuracy of screening tools may improve if screening tools are standardized for certain diseases (cancer, kidney failure etc.), certain states (intensive care unit patients) or age groups.

The least square regression (LSR) is a popular framework for multicategory classification because it has simple mathematical formulation and efficient solution. The classification performance of LSR based methods depends heavily on the discriminative capability of the label transformation. In this work, we aim to enhance the discriminative capability of the label transformation by imposing a new class-induced structure constraint. Specifically, we propose to regularize the label transformation matrix by the difference of l 2 , 1 norm and l 2 , 2 norm of the predicted labels of each class. The major advantage of the new regularity is that, it can guarantee the ideal discrimination of the label transformation matrix and make the classification more stable. For better generalization capability, we adopt the existing e -dragging technique to relax the binary label. Leveraging the new regularity term and the label relaxation, we give a group discriminative least square regression (GDLSR) training model to learn the label transformation for multicategory classification. To solve the proposed model, we present an ADMM-like iteration algorithm, which we can guarantee a weak convergency. Experiments on several commonly used datasets show that our method outperforms both related LSR-based methods and some traditional methods.

Background We studied patients with coronavirus disease 2019 (COVID-19) infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a virus that originated in Wuhan, China, and is spreading over the country including Jiangsu Province. We studied the clinical characteristics and therapies of severe cases in Jiangsu Province. Methods A multicenter retrospective cohort study was conducted to analyze clinical, laboratory data and treatment of 60 severe cases with COVID-19 infection in Jiangsu Province between January 24, 2020 and April 20, 2020. The improvement and deterioration subgroups were compared to identify predictors of disease progression. Results A total of 653 infected cases with COVID-19 were reported in Jiangsu Province, of which 60 severe cases were included in this study. Up until April 20, 2020, the mortality of severe patients was 0%. The median age was 57 years. The average body mass index (BMI) of these patients was 25 kg/m². White blood cell counts decreased in 45.0% of patients, lymphopenia in 63.3%, thrombocytopenia in 13.3%, and procalcitonin levels in 88.3% of the patients were less than 0.5 ng/mL. There were no statistically significant differences in immunoglobulin therapy and glucocorticoids therapy between the improvement and deterioration subgroups. Logistic regression analysis identified higher levels of troponin T (odds ratio [OR]: 1.04; 95% confidence interval [CI]: 1.00-1.08; P=0.04), antiviral therapy with aerosol inhalation of interferon (OR: 6.33; 95% CI: 1.18-33.98; P=0.03), and the application of non-invasive mechanical ventilation (OR: 1.99; 95%CI: 1.17-3.41; P=0.01) as predictors of disease progression, whereas higher lymphocyte count (OR: 0.11; 95% CI: 0.02-0.57; P=0.01) and early prone ventilation were associated with improvement (OR: 0.11; 95% CI: 0.01-0.98; P=0.04). Conclusions COVID-19 infection had a low mortality rate in Jiangsu Province, China. The higher levels of troponin T and lower lymphocyte count were predictors of disease progression. Early prone ventilation may be an effective treatment for severe cases.

Some farmers are offering subsidized or “cost-offset” community supported agriculture (CO-CSA) shares as a strategy to counter market saturation and improve low-income families’ access to fresh local foods. However, little is known about farmers’ experiences with this model, particularly in regard to the balance between additional resources required for adoption and subsequent contributions to farm revenue. As part of the Farm Fresh Foods for Healthy Kids Study of the impact of a CO-CSA on dietary behaviors in low-income families, we conducted qualitative interviews with 12 farmers across four states after the first and the third years of CO-CSA implementation. We explored these data to understand what accommodations farmers provided to low-income families, the benefits and challenges of implementing the CO-CSA model, and farmers’ perceptions of its impact on cash flow and profitability. We found that farmers selected pick-up locations that met CO-CSA members’ needs, were responsive to members’ food preferences in selecting CSA contents, and allowed for late payments and pickups, though sometimes this placed an additional burden on farmers’ time and resources. Additionally, weekly payment transactions led to increased recordkeeping. Despite its challenges, most farmers said CO-CSA adoption was a worthwhile addition to their business model. Expanding food access through this mechanism may become more sustainable with the additional support of innovative policies like eased land-use restrictions, operational models, and community strategies to fund and operate CO-CSA programs. This is an area ripe for future research, as there is little documentation on both single farm and multifarm CO-CSA operations.

Postoperative cognitive dysfunction (POCD) is a common complication induced by anesthesia or surgery, which affects the concentration, cognition and memory of patients. Sevoflurane, a clinical anesthetic, could stimulate neuro-inflammation and lead to POCD. Recent studies found that specificity protein 1 (SP1) participates in the development of neurological diseases. Our study aims to elucidate the role of SP1 in sevoflurane-induced POCD pathogenesis. We anesthetized Sprague-Dawley rats and treated the primary hippocampal neurons with sevoflurane to construct the in vivo and in vitro POCD models. Besides, the expression and regulatory mechanism of SP1 in the pathogenesis of POCD were explored. According to the results, sevoflurane anesthesia impaired the cognitive functions of rat, significantly elevated SP1 expression and inactivated the cholinergic anti-inflammatory pathway (CAP) both in vivo and in vitro. Moreover, the sevoflurane-treated rats and neurons also exhibited obvious inflammatory responses and enhanced apoptosis. Loss-of-function assay indicated that SP1 knockdown rescued the deactivation of CAP and alleviated the sevoflurane-induced neuro-inflammation and apoptosis in rat hippocampus. Generally, our study documented that the sevoflurane-induced SP1 up-regulation affected the activation of CAP, leading to the aggravated neuro-inflammation and apoptosis. This may provide a novel sight for POCD therapy.

3D point cloud is one of the most common and basic 3D object representation model that is widely used in virtual/augmented reality applications, e.g., immersive communication. Compression of 3D point cloud is a big challenge because of its huge data volume and irregular data structure. In this paper, we propose a sampling-based compression algorithm for 3D point clouds. First, a 3D point cloud was resampled by a graph filter to obtain a subset of representative 3D points. Then, the representative points were compressed by the G-PCC (geometry-based point cloud compression) encoder software that was released by MPEG. Finally, the decoded representative points were used to reconstruct the original 3D point clouds by a CNN-based up-sampling approach. Experimental results demonstrate that a significant (73.15%) bit rate reduction can be achieved by the proposed 3D point cloud compression algorithm with minimal quality degradation of the reconstructed 3D point clouds.

Significance Acute myeloid leukemia (AML) is the most common acute leukemia in adults, with a 5-y survival of 29%. Immunotherapy is based on the premise that tumors suppress the immune system. We investigated the status of T cell immunity in AML at the time of diagnosis. We found a significant association between T cell percentage in the bone marrow and overall survival in newly diagnosed AML patients. When we evaluated the T cells from the bone marrow of patients with AML, one-third displayed profound functional impairment. Most of these compromised T cells, however, could be rescued using checkpoint inhibitors. Our results support the development of immune checkpoint therapy to combat this deadly disease., Acute myeloid leukemia (AML) is the most common acute leukemia in adults, with approximately four new cases per 100,000 persons per year. Standard treatment for AML consists of induction chemotherapy with remission achieved in 50 to 75% of cases. Unfortunately, most patients will relapse and die from their disease, as 5-y survival is roughly 29%. Therefore, other treatment options are urgently needed. In recent years, immune-based therapies have led to unprecedented rates of survival among patients with some advanced cancers. Suppression of T cell function in the tumor microenvironment is commonly observed and may play a role in AML. We found that there is a significant association between T cell infiltration in the bone marrow microenvironment of newly diagnosed patients with AML and increased overall survival. Functional studies aimed at establishing the degree of T cell suppression in patients with AML revealed impaired T cell function in many patients. In most cases, T cell proliferation could be restored by blocking the immune checkpoint molecules PD-1, CTLA-4, or TIM3. Our data demonstrate that AML establishes an immune suppressive environment in the bone marrow, in part through T cell checkpoint function.

The main recurrence pattern for lung cancer patients after radical surgery is distant metastasis. The probability of pancreatic metastasis in patients diagnosed with lung squamous cell carcinoma is 0.02%, with a poor prognosis. Chemotherapy is the preferred treatment for recurrence. Single lesions or oligometastasis can be surgically resected, and local lesions with compression symptoms can be treated with radiotherapy. The FDA and NMPA have approved first‐line indications for immunotherapy for lung squamous cell carcinoma. Here, we report the case of a 57‐year‐old male patient with lung squamous cell carcinoma who developed pancreatic metastasis after radical resection. The disease progressed after first‐line chemotherapy, and the patient was treated with immunotherapy combined with radiotherapy. We subsequently observed the abscopal effect of intensity modulated radiation therapy (IMRT) and pembrolizumab with disappearance of lung metastasis after radiotherapy for pancreatic metastasis. The patient’s tumor symptoms were relieved with prolonged survival.

PurposeThe purpose of this paper is to investigate the effects of Facebook users' responses to corporate Facebook posts on investor diversity and trading consensus.Design/methodology/approachThe authors collect publicly available data on corporate Facebook posts and user responses to such posts. They use the OLS regression framework to analyze the effects of such Facebook activities on institutional ownership percentage and trading consensus among investors.FindingsThe authors find that Facebook users' responses to corporate Facebook posts reduce large institutional investors' ownership. Their interpretation for this finding is that such Facebook activities increase the visibility of the companies across a more diverse group of investors. This increased visibility especially makes information more accessible to smaller investors so that they are attracted to invest more in these companies. They also find that Facebook activities increase the buy-sell consensus among investors, indicating that the information disseminated through social media reduces the disagreements among investors.Research limitations/implicationsThis paper examines the effects of user reactions to all kinds of corporate Facebook posts without separately identifying the types of posts such as advertising, financial information and corporate news. Future research may try to identify the differential effects of specific types of posts and reactions on investor diversity.Practical implicationsThe results suggest that social media has become a new and effective supplement to traditional disclosure channels in making information available to all investors in the capital market.Originality/valueThis paper is among the first to document the effects of corporate disclosures on social media in changing investor composition and reducing the information gap among investors.

First paragraph: Our food system has been disrupted. Shopping at a grocery store during the COVID-19 pan­demic is not a pleasant experience, and, for some of the most vulnerable, it can be outright dangerous. It may become worse. How long will supply chain disruptions continue and what are upcoming challenges? From illness in the fields where agricultural workers pick our food and the closing of food processing facilities to the threat that trucking lanes may be shut down, the possibilities seem real right now. . . . See the press release for this article.

As a member of the P2Y receptor family with a typical 7-transmembrane structure, P2Y6 purinergic receptor (P2Y6R) belongs to the G-protein-coupled nucleotide receptor activating the phospholipase-C signaling pathway. P2Y6R is widely involved in a range of human diseases, including atherosclerosis and other cardiovascular diseases, gradually attracting attention owing to its inappropriate or excessive activation. In addition, it was reported that P2Y6R might regulate inflammatory responses by governing the maturation and secretion of proinflammatory cytokines. Hence, several P2Y6R antagonists have been subjected to evaluation as new therapeutic strategies in recent years. This review was aimed at summarizing the role of P2Y6R in the pathogenesis of cardiovascular diseases, with an insight into the recent progress on discovery of P2Y6R antagonists.

Microfibers with a core-shell structure can be produced by co-axial electrospinning, allowing for the functionalization of the outer layer with bioactive molecules. In this study, a thermoplastic, degradable polyesteretherurethane (PEEU), consisting of poly(p-dioxanone) (PPDO) and poly(ɛ-caprolactone) (PCL) segments with different PPDO to PCL weight ratios, were processed into fiber meshes by co-axial electrospinning with gelatin. The prepared PEEU fibers have a diameter of 1.3±0.5 μm and an elastic modulus of around 5.1±1.0 MPa as measured by tensile testing in a dry state at 37°C, while the PEEU/Gelatin core-shell fibers with a gelatin content of 12±6 wt% and a diameter of 1.5±0.5 μm possess an elastic modulus of 15.0±1.1 MPa in a dry state at 37 °C but as low as 0.7±0.7 MPa when hydrated at 37 °C. Co-axial electrospinning allowed for the homogeneous distribution of the gelatin shell along the whole microfiber. Gelatin with conjugated Fluorescein (FITC) remained stable on the PEEU fibers after 7 days incubation in Phosphate-buffered saline (PBS) at 37 °C. The gelatin coating on PEEU fibers lead to enhanced human adipose tissue derived mesenchymal stem cell (hADSC) attachment and a proliferation rate 81.7±34.1 % higher in cell number in PEEU50/Gelatin fibers after 7 days of cell culture when compared to PEEU fibers without coating. In this work, we demonstrate that water-soluble gelatin can be incorporated as the outer shell of a polymer fiber via molecular entanglement, with a sustained presence and role in enhancing stem cell attachment and proliferation.

Graphical abstract, Highlights • A reliable Glide docking-based virtual screening (VS) pipeline for P2Y14R was developed. • Several potent P2Y14R antagonists with novel scaffolds were identified utilizing the VS strategy. • P2Y14R inhibitory effect was evaluated by testing cAMP levels in HEK293 cells. • Anti-gout activity of screened compound was detected in MSU-treated THP-1 cells. • The mechanism of test compound in treating acute gouty arthritis was elucidated., P2Y14 nucleotide receptor is a Gi protein-coupled receptor, which is widely involved in physiological and pathologic events. Although several P2Y14R antagonists have been developed thus far, few have successfully been developed into a therapeutic drug. In this study, on the basis of two P2Y14R homology models, Glide docking-based virtual screening (VS) strategy was employed for finding potent P2Y14R antagonists with novel chemical architectures. A total of 19 structurally diverse compounds identified by VS and drug-like properties testing were set to experimental testing. 10 of them showed good inhibitory effects against the P2Y14R (IC50

Increasingly attention has been paid to the transdermal drug delivery systems with microneedles owing to their excellent compliance, high efficiency, and controllable drug release, therefore, become promising alternative with tremendous advantages for delivering specific drugs such as huperzine A (Hup A) for treatment of Alzheimer’s disease (AD) yet with low oral bioavailability. The purpose of the present study is to design, prepare, and evaluate a dissolving microneedle patch (DMNP) as a transdermal delivery system for the Hup A, investigating its in vitro drug release profiles and in vivo pharmacokinetics as well as pharmacodynamics treating of AD. Skin penetration experiments and intradermal dissolution tests showed that the blank DMNP could successfully penetrate the skin with an adequate depth and could be quickly dissolved within 5 min. In vitro transdermal release tests exhibited that more than 80% of the Hup A was accumulatively permeated from DMNP through the skin within three days, indicating a sustained release profile. In vivo pharmacokinetic analysis demonstrated that the DMNP group resulted in longer Tmax (twofold), longer t1/2 (fivefold), lower Cmax (3:4), and larger AUC(0–∞) (twofold), compared with the oral group at the same dose of Hup A. Pharmacodynamic research showed a significant improvement in cognitive function in AD rats treated with DMNP-Hup A and Oral-Hup A, as compared to the model group without treatment. Those results demonstrated that this predesigned DMNP is a promising alternative to deliver Hup A transdermally for the treatment of AD.

The human head pose estimation is an important and challenging problem, which provides the estimation of the head posture in 3D space from 2D image. It is a crucial technique for face recognition, gaze estimation, facial attribute recognition, etc. However, fast head pose estimation executing on the terminal for video edge computation has many challenges due to the computational complexity of the existing algorithms. In this paper, we propose a fast head pose estimation method based on a novel Rotation-Adaptive facial landmark detection powered by Local Binary Feature (RALBF). The landmark detection method is structured through fusing the prior of the rotation information provided by the Progressive Calibration Networks (PCN) face detector to a Local Binary Feature (LBF) based landmark detection method, which improves the robustness against head pose variations and simultaneously keep the computing efficiency. RALBF is trained and tested on 300W dataset and AFLW2000 dataset, it is verified by the accuracy evaluation that RALBF performs better than LBF. To improve the speed of head pose estimation, the 68, 51 and 10 landmarks distribution schemes are explored and compared on speed and accuracy. In the 10 landmarks scheme, the head pose estimation running once only takes 8.3ms on Intel i7-6700HQ CPU and takes 21.8ms on HiSilicon SoC Hi3519AV100, and the average error of Euler angle is 5.9973° when the face yaw angle is between ±35° on AFLW2000 3D dataset. Experiments demonstrate our approach performing well on real scenes.

Sparse representation (SR) and dictionary learning (DL) have been extensively used for feature encoding, aiming to extract the latent classification-friendly feature of observed data. Existing methods use sparsity penalty and learned dictionary to enhance discriminative capability of sparse codes. However, training dictionary for SR is time consuming and the resulted discriminative capability is limited. Rather than learning dictionary, we propose to employ the dictionary at hand, e.g., the training set as the class-specific synthesis dictionary to pursue an ideal discriminative property of SR of the training samples: each data can be represented only by data-in-class. In addition to the discriminative property, we also introduce a smoothing term to enforce the representation vectors to be uniform within class. The discriminative property helps to separate the data from different classes while the smoothing term tends to group the data from the same class and further strengthen the separation. The SRs are used as new features to train a sparse encoder and a classifier. Once the sparse encoder and the classifier are learnt, the test stage is very simple and highly efficient. Specifically, the label of a test sample can be easily computed by multiplying the test sample with the sparse encoder and the classifier. We call our method Classification-Friendly Sparse Encoder and Classifier Learning (CF-SECL). Extensive experiments show that our method outperforms some state-of the-art model-based methods.

The obesity pandemic in the obstetrical population plus increased frequency of Cesarean delivery (CD) has increased vulnerability to surgical site infection (SSI). Here we characterized the microbiome at the site of skin incision before and after CD. Skin and relevant surgical sites were sampled before and after surgical antisepsis from obese (n = 31) and non-obese (n = 27) pregnant women. We quantified bacterial biomass by qPCR, microbial community composition by 16sRNA sequencing, assigned operational taxonomic units, and stained skin biopsies from incision for bacteria and biofilms. In obese women, incision site harbors significantly higher bacterial biomass of lower diversity. Phylum Firmicutes predominated over Actinobacteria, with phylotypes Clostridales and Bacteroidales over commensal Staphylococcus and Propionbacterium spp. Skin dysbiosis increased post-surgical prep and at end of surgery. Biofilms were identified post-prep in the majority (73%) of skin biopsies. At end of surgery, incision had significant gains in bacterial DNA and diversity, and obese women shared more genera with vagina and surgeon’s glove in CD. Our findings suggest microbiota at incision differs between obese and non-obese pregnant women, and changes throughout CD. An interaction between vaginal and cutaneous dysbiosis at the incision site may explain the a priori increased risk for SSI among obese pregnant women.

Purpose: For classical Hodgkin lymphoma (cHL), programmed death-l (PD-1) is a well-recognized attractive target. This multicenter, single-arm, phase II study evaluated the efficacy and safety of camrelizumab, a humanized high-affinity IgG4 mAb against PD-1, in Chinese patients with relapsed or refractory cHL. Patients and Methods: Patients who had failed to achieve a remission or experienced progression after autologous stem cell transplantation or had received at least two lines of systemic chemotherapies were given camrelizumab 200 mg every 2 weeks. The primary endpoint was objective response rate per independent review committee (IRC) assessment. This study is registered with ClinicalTrials.gov (NCT03155425). Results: Between June 9, 2017 and September 18, 2017, 75 patients were enrolled and treated. At a median follow-up of 12.9 months, 57 of 75 (76.0%; 95% CI, 64.7–85.1) patients achieved an IRC-assessed objective response, including 21 (28.0%) and 36 (48.0%) patients who had complete and partial remission, respectively. Median duration of response was not reached (range, 0.0+–12.8+ months). Treatment-related adverse events (AE) occurred in all patients. The most common ones included cutaneous reactive capillary endothelial proliferation (97.3%, 73/75) and pyrexia (42.7%, 32/75). Grade 3 or 4 treatment-related AEs occurred in 20 patients (26.7%); the most common AE was decreased white blood cell count (4.0%, 3/75). There were no grade 5 treatment-related AEs. Conclusions: Camrelizumab demonstrated a high response rate, durable response and controllable safety in Chinese patients with relapsed or refractory cHL, becoming a new safe and effective treatment option in this setting.

Crises in food safety have attracted increased public attention in many countries, typically posing serious threats to public health and causing potential economic, social, and environmental damage. This research applied a green social work framework and developed a family-based and child-centered education model in a Chinese urban context. The green educational model engaged practitioners in a participatory and cooperative learning process to explore practical solutions for food safety that had social and environmental value. Applying action research, this program engaged participant families in extended ways of knowing in educational activities, through which to enhance their emotional connection with the natural environment, and develop critical knowing and reflective action. The program generated useful insights for green social work intervention and public education to improve environmental justice and providing lessons about action research as a method of engagement for social workers.