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Limited research exists on the mechanisms underlying asthenozoospermia associated with acquired ciliary dyskinesia. Primary ciliary dyskinesia links respiratory pathology with infertility and provides a basis for a potential mechanism. The aetiology of asthenozoospermia is often unclear and may be secondary to direct or indirect effects on sperm motility. Here, we report a case – with a brief clinical review – of recovering sperm motility after diagnosis of complete asthenozoospermia coinciding with resolution of chronic respiratory infections. The patient is a 36-year-old male, with initial semen analysis demonstrating 100% immotile sperm. Following the resolution of chronic respiratory infection, subsequent analysis demonstrated functional improvement with 76 million sperm/mL, 8% progressive motility and 4% strict morphology. Our case reinforces a potentially underappreciated role of environmental risk factors in infertility, with a focus on the patient’s history of infections and other risk factors for acquired ciliary dyskinesia, which should be kept in mind when treating patients with asthenozoospermia.

Abstract Objective Patients with advanced laryngeal cancer are typically presented with divergent treatment options, namely chemoradiation versus total laryngectomy. This study aims to understand general perspectives of the factors involved in this decision‐making process. Methods Surveys were constructed using specialized conjoint analysis software. Seven attributes integral to the decision‐making process for advanced laryngeal cancer treatment were included. Results Three hundred one healthy adult volunteers completed the decision‐making program. The relative impact of each treatment attribute on decision making across all participants was scored with an average importance score (standard deviation) as follows: Lifespan 22.2% (±8.5), Voicing 21.4% (±5.9), Swallowing 19.1% (±7.3), Cancer Cure 14.9% (±6.2), Mode of Breathing 11.0% (±3.7), Self‐Image 6.7% (±2.9), and Treatment Type 4.8% (±3.0). Conclusions General public opinion ranked lifespan, voicing, and swallowing aspects as similarly important, and all were ranked more important than probability of cure. These data demonstrate a variety of priorities among participants and the need for tailored discussions when determining treatment choice for advanced laryngeal cancer. Level of Evidence Level 4.

Murine syngeneic tumor models have been used extensively for cancer research for several decades and have been instrumental in driving the discovery and development of cancer immunotherapies. These tumor models are very simplistic cancer models, but recent reports have, however, indicated that the different inoculated cancer cell lines can lead to the formation of unique tumor microenvironments (TMEs). To gain more knowledge from studies based on syngeneic tumor models, it is essential to obtain an in-depth understanding of the cellular and molecular composition of the TME in the different models. Additionally, other parameters that are important for cancer progression, such as collagen content and mechanical tissue stiffness across syngeneic tumor models have not previously been reported. Here, we compare the TME of tumors derived from six common syngeneic tumor models. Using flow cytometry and transcriptomic analyses, we show that strikingly unique TMEs are formed by the different cancer cell lines. The differences are reflected as changes in abundance and phenotype of myeloid, lymphoid, and stromal cells in the tumors. Gene expression analyses support the different cellular composition of the TMEs and indicate that distinct immunosuppressive mechanisms are employed depending on the tumor model. Cancer-associated fibroblasts (CAFs) also acquire very different phenotypes across the tumor models. These differences include differential expression of genes encoding extracellular matrix (ECM) proteins, matrix metalloproteinases (MMPs), and immunosuppressive factors. The gene expression profiles suggest that CAFs can contribute to the formation of an immunosuppressive TME, and flow cytometry analyses show increased PD-L1 expression by CAFs in the immunogenic tumor models, MC38 and CT26. Comparison with CAF subsets identified in other studies shows that CAFs are skewed towards specific subsets depending on the model. In athymic mice lacking tumor-infiltrating cytotoxic T cells, CAFs express lower levels of PD-L1 and lower levels of fibroblast activation markers. Our data underscores that CAFs can be involved in the formation of an immunosuppressive TME.

This article reconstructs a theory of mind in the Mengzi 孟子. It argues that recent studies in favor of mind-body dualism import Cartesianism through the vocabulary their arguments are couched in. This article exposes this “Cartesian language game” in order to effect a gestalt shift in our understanding of Mengzian philosophy. It then appeals to John Dewey’s conception of mind as both “minding” and “discourse” where mind is a function of attentive engagement predicated on a background of traditional values and meanings. This article then shows how the Mengzi’s concepts of ren 仁 and tian 天 contribute to a theory of mind where the former is defined as xin 心 thus to be understood as “mindful engagement” and the latter implies tradition as shared reservoir of social and cultural meaning. Through the interpretive comparison of the philosophies of the Mengzi and Dewey, we can reconstruct a Mengzian theory of mind.

Case studies in Britain, Canada, and the United States illustrate the wide range of projects using tools and techniques associated with the digital humanities that are expanding the scope and scale of enquiry in tourism and travel histories. Discussions about their research programmes with key figures associated with the development of these tools reveal a set of common interests, ambitions, and limitations, as well as ways in which digital humanities approaches can be incorporated profitably within projects to advance theoretical paradigms, related to spatialities and post-colonial studies, for instance.

BackgroundGay, bisexual, and other men who have sex with men (MSM) with a higher perceived risk of HIV are more aware of and willing to use pre-exposure prophylaxis (PrEP). PrEP is an effective HIV prevention strategy, but there is a lack of data on how PrEP use might moderate the relationship between sexual risk behavior and perceived risk of HIV. Moreover, most studies measure perceived risk of HIV via a single question. ObjectiveWe estimated the moderating effect of PrEP use on the association between sexual risk behavior and perceived risk of HIV, measured with the 8-item Perceived Risk of HIV Scale (PRHS), among Brazilian MSM. MethodsA cross-sectional, web-based survey was completed by Brazilian Hornet app users aged ≥18 years between February and March 2020. We included data from cisgender men who reported sex with men in the previous 6 months. We evaluated the moderating effect of current PrEP use on the association between sexual risk behavior, measured via the HIV Incidence Risk Index for MSM (HIRI-MSM), and perceived risk of HIV, measured by the PRHS. Higher HIRI-MSM (range 0-45) and PRHS (range 10-40) scores indicate greater sexual behavioral risk and perceived risk of HIV, respectively. Both were standardized to z scores for use in multivariable linear regression models. ResultsAmong 4344 cisgender MSM, 448 (10.3%) were currently taking PrEP. Current PrEP users had a higher mean HIRI-MSM score (mean 21.0, SD 9.4 vs mean 13.2, SD 8.1; P

The expansion of Advanced Metering Infrastructure (AMI) has provided building operators and researchers detailed information on building energy consumption. The majority of AMI systems, however, record data at relatively low resolutions of 15, 30, or 60 minutes, due to cost, storage and bandwidth limitations. Emerging applications in power flow analysis, Quasi-Static Time-Series Simulation (QSTS), smart grid integration and load matching, however, require data at higher resolutions. Short-term energy demand can deviate significantly from long-term averages, with an unknown magnitude and frequency when only low-resolution load profile data is available. This paper presents a novel data-driven approach to predict characteristics of the missing high-resolution information in a low-resolution signal, applicable to both measured and modeled building load profile data, utilizing machine learning regression algorithms. In the proposed framework, the relationship between characteristics of high-resolution and low-resolution signals is learned from the decomposition and characterization of a subset of high-resolution building data. This paper validates the underlying hypotheses and methodology of this approach through a single-building case study, training a variety of machine learning models on one year of data, and using the resulting models to predict high-resolution characteristics in a different year. An Ensemble Tree regression model demonstrates a high predictive accuracy (R2 of 0.79-0.92) for several statistical metrics of the high-resolution load profile. These results support the broader potential for leveraging low-resolution information to accurately constrain predictions of missing high-resolution information in building load profiles, which may greatly increase the utility of both measured and modeled data in many practical and research applications. Generalizing such models will require analysis of high-resolution data from a diverse set of building types.

In the era of burgeoning electric vehicle (EV) popularity, understanding the patterns of EV users’ behavior is imperative. This paper examines the trends in household charging sessions’ timing, duration, and energy consumption by analyzing real-world residential charging data. By leveraging the information collected from each session, a novel framework is introduced for the efficient, real-time prediction of important charging characteristics. Utilizing historical data and user-specific features, machine learning models are trained to predict the connection duration, charging duration, charging demand, and time until the next session. These models enhance the understanding of EV users’ behavior and provide practical tools for optimizing the EV charging infrastructure and effectively managing the charging demand. As the transportation sector becomes increasingly electrified, this work aims to empower stakeholders with insights and reliable models, enabling them to anticipate the localized demand and contribute to the sustainable integration of electric vehicles into the grid.

Abstract Background Causal mediation analysis is one way to bridge this gap by exploring the causal pathways of a given intervention. The aim of this study was to assess whether scapular motion, position, and periscapular muscle strength are mediators for pain and shoulder disability outcomes following a scapular stabilization intervention for patients with subacromial pain syndrome. Methods Sixty patients were randomized into two groups: scapular stabilization or periscapular strengthening exercises. The intervention consisted of three sessions per week for 8 weeks. The primary outcome measures were pain and disability and the following outcome measures were considered as potential mediators: scapular motion, scapular position, periscapular muscle strength, age, duration of symptoms, and side of the complaint. A model-based inference approach with bootstrap simulations was used to estimate the average causal mediation effect, average direct effect, and the average total effect from the data of a randomized clinical trial that evaluated the effect of adding scapular stabilization exercises to a scapulothoracic strengthening program in people with subacromial pain syndrome. Results The results demonstrated that none of the putative mediators were influenced by the intervention. However, muscle strength of serratus anterior, upper, middle, and lower trapezius muscles was associated with shoulder disability. Conclusion Scapular kinematic and periscapular muscle strength did not mediate the effect of scapular stabilization exercises on shoulder pain or disability scores in subjects with subacromial pain syndrome. Muscle strength of serratus anterior, upper, middle and lower trapezius were associated with shoulder disability scores at 8-weeks follow-up.

In the setting of ischemic steal syndrome with tissue loss, patients with radiocephalic fistulas have limited options to preserve their conduit and treat their ischemic symptoms. To address this, we have proposed the technique of proximalization through one incision of a wrist arteriovenous fistula (POWR) with distal revascularization with interval ligation (DRIL) procedure. In the present retrospective, single-center, case series, we evaluated the outcomes of three patients with radiocephalic fistulas who had undergone POWR DRIL from 2017 to 2021. Their ischemic symptoms were monitored for regression. All three patients showed signs of regressing ischemia. The POWR DRIL represents an efficient procedure to address tissue loss and preserve the autogenous conduit.

This paper presents an experiential learning exercise to (a) Provide students with an effective analogy of the way entrepreneurs identify opportunities and solve problems in the development of new products, (b) Help them to reflect on the importance of defining a Creative Workflow in entrepreneurial endeavors, and (c) Encouraging students to practice Empathy. The proposed exercise is built on using cooking as a metaphor for design-driven innovation. The exercise design is grounded on effectuation, human-centered design, and pedagogic approaches relying on co-creation and prototyping (Aalto Design Factory, 2017). The exercise was created during the pandemic as part of a broader attempt to migrate an entrepreneurship course online. Since the course intensively used prototyping and design exercises, there was a need to find effective ways to transfer these teaching experiments to a virtual environment. The exercise was demoed to academic instructors during a virtual international conference on design-driven innovation. The experts’ feedback and reactions were collected through the video recording of the session and follow-up conversations. This paper will present the exercise in detail, lessons learned, and reflections extracted from the demo session.

Tumors feature elevated sialoglycoprotein content. Sialoglycoproteins promote tumor progression and are linked to immune suppression via the sialic acid-Siglec axis. Understanding factors that increase sialoglycoprotein biosynthesis in tumors could identify approaches to improve patient response to immunotherapy. We quantified higher levels of sialoglycoproteins in the fibrotic regions within human breast tumor tissues. Human breast tumor subtypes, which are more fibrotic, similarly featured increased sialoglycoprotein content. Further analysis revealed the breast cancer cells as the primary cell type synthesizing and secreting the tumor tissue sialoglycoproteins and confirmed that the more aggressive, fibrotic breast cancer subtypes expressed the highest levels of sialoglycoprotein biosynthetic genes. The more aggressive breast cancer subtypes also featured greater infiltration of immunosuppressive SIGLEC7, SIGLEC9, and SIGLEC10-pos myeloid cells, indicating that triple-negative breast tumors had higher expression of both immunosuppressive Siglec receptors and their cognate ligands. The findings link sialoglycoprotein biosynthesis and secretion to tumor fibrosis and aggression in human breast tumors. The data suggest targeting of the sialic acid-Siglec axis may comprise an attractive therapeutic target particularly for the more aggressive HER2+ and triple-negative breast cancer subtypes.

The toxicity of the form of nanoparticles is presently not well understood. The purpose of this study consists in comparing the toxicity of various forms of silver nanoparticles (nAg) in juvenile rainbow trout Oncorhynchus mykiss. Juveniles were exposed to various forms of polyvinyl-coated nAg of similar size for 96 h at 15 °C. After the exposure period, the gills were isolated and analyzed for Ag uptake/distribution, oxidative stress, glucose metabolism, and genotoxicity. Higher levels of Ag were detected in gills in fish exposed to dissolved Ag followed by spherical, cubic, and prismatic nAg. Size-exclusion chromatography of gill fractions revealed that the dissolution of nAg was observed for all forms of nAg where prismatic nAg released more important levels of Ag in the protein pool as in fish exposed to dissolved Ag as well. The aggregation of nAg was more important for cubic nAg in respect of the other forms of nAg. The data revealed that lipid peroxidation was closely associated with protein aggregation and viscosity. Biomarkers revealed changes in lipid/oxidative stress and genotoxicity, which were related to the loss of protein aggregation and inflammation (NO2 levels), respectively. In general, the observed effects were found for all forms of nAg where the effects from prismatic nAg were generally higher than for spherical and cubic nAg. The strong relationship between genotoxicity and inflammation response suggests the participation of the immune system in the observed responses of juvenile fish gills.

Recent technology development and penetration of advanced metering infrastructure (AMI), advanced building control systems, and the internet-of-things (IoT) in the built environment are providing detailed information on building operation, performance, and user’s comfort and behavior. Building owners can obtain a wide range of energy consumption details at various levels of time granularity to augment their decisions as they manage the building operation and interact with the grid. AMI data are providing a new level of detail and visibility that may enhance building services and assets in the smart grid domain and make buildings inch closer to becoming a grid-interactive energy efficient buildings (GEB). While utility-installed AMI typically records energy consumption at a 15, 30, or 60-minute resolution, building-owner-installed metering can record energy consumption at one-minute or sub-minute time scales, providing information about how much the energy consumption varies from one sub-minute to the other (i.e. variability) at a finer time resolutions than typically available from AMI. This paper examines one-minute building load profile data sets and presents a framework to study, define, extract, quantify and analyze variability in buildings’ load profiles. The discussion of variability and its analysis is based on a case study of an actual sub-minute time-resolution data set, collected in 2019, for two buildings in a Midwest state in the USA. The result shows that for the case studies, the level of variability in an end-use category is not simply proportional to its consumption. Furthermore, distinct and predictable daily variability patterns emerge in end-use load categories. This information is useful for a host of applications including prediction, forecasting, and modeling.

The power consumption of buildings over the course of each minute, hour, day and season plays a major role in how this load influences the Electric Power System voltage and frequency, and vice versa. This consumption is based on the building’s load component types, efficiencies, and how they consume power and react to changes in real time. Due to this complexity, standard full-building load models are typically voltage-invariant. This paper proposes a novel framework to transform these voltage-invariant building load models into fully time- and voltage-dependent load profiles using available data on the voltage sensitivity of individual load components. While a voltage-dependent building model could theoretically be generated from static load models of every component in a building, this approach faces two challenges: first, load models representing all load components are impractical to develop for all possible load component types; second, building energy consumption is never measured or modeled at the individual component level. The proposed framework compiles available component data in the form of static ZIP load model parameters, and maps them into the end use categories utilized by standard building modeling programs. The voltage sensitivity of each end use category is then bounded by the extrema of the component models within it. This framework is applied to a load profile case study representing the aggregate U.S. residential building stock. In addition to the minimum/maximum conditions, a load profile based on typical load composition and weighted ZIP parameters is generated for the same building stock. The results show that for a 10% drop in voltage, using the least sensitive ZIP parameters, active power is expected to be 3% to 14% lower than nominal, depending on the season and time of day. Using the most sensitive ZIP parameters, the active power is expected to be 9% to 20% lower than nominal, also depending on the season and time of day.

The penetration of distributed energy resources (DERs) on the electric power system is changing traditional power flow and analysis studies. DERs may cause the systems' protection and control equipment to operate outside their intended parameters, due to DERs' variability and dispatchability. As this penetration grows, hosting capacity studies as well as protection and control impact mitigation become critical components to advance this penetration. In order to conduct such studies accurately, the electric power system's distribution components should be modeled correctly, and will require realistic time series loads at varying temporal and spatial conditions. The load component consists of the built environment and its load profiles. However, large-scale building load profiles are scarce, expensive, and hard to obtain. This article proposes a framework to fill this gap by developing detailed and scalable synthesized building load profile data sets. Specifically, a framework to extract load variability characteristics from a subset of buildings' empirical load profiles is presented. Thirty-four discrete wavelet transform functions with three levels of decomposition are used to extract a taxonomy of load variability profiles. The profiles are then applied to modeled building load profiles, developed using the energy simulation program EnergyPlus®, to generate synthetic load profiles. The synthesized load profiles are variations of realistic representations of measured load profiles, containing load variabilities observed in actual buildings served by the electric power system. The paper focuses on the framework development with emphasis on variability extraction and application to develop 750 synthesized load profiles at a 15-minute time resolution.

The environmental impacts of nanoparticle mixtures in the aquatic environment is not well understood. The purpose of this study examined the sub-lethal toxicity of low concentrations (ug/L range) of selected nanoparticles alone and in mixtures in juvenile trout. Fish were exposed to to individual and two environmentally relevant mixtures of silver (nAg), copper oxide (nCuO) and cerium oxide (nCeO) nanoparticles for 96 h at 15 °C. After the exposure period, fish were depurated overnight and tissue levels in Ag, Ce, Cu and Zn were determined along with a suite of effects biomarkers such as oxidative stress/inflammation, denatured protein tagging (ubiquitin), DNA strand breaks (genotoxicity) and acetylcholinesterase (AChE) activity. The data showed that these nanoparticles behaved as suspended matter but were nevertheless bioavailable for fish with bioconcentration factors of 6, 8 and 2 for nAg, nCeO and nCuO respectively. Only nCuO alone increased malonaldehyde (lipid peroxidation) contents but all nanoparticles increased DNA damage, protein-ubiquitin labeling, and decreased AChE activity. Globally, the toxicity of nCeO and nCuO was generally stronger than nAg, and antagonist effects were found in the mixtures. The interactions involved in these antagonisms are not well understood but do not involve the liberation of free ions and labile zinc in tissues. In conclusion, the bioavailability and toxicity of these nanoparticles are influenced by mixtures of nanoparticles, which is likely to occur in contaminated environments.

Whether we analyze phonological processes using a system of rules or constraints, the resulting map from underlying representations to surface pronunciations can be characterized as a function. Viewing processes as mathematical objects in this way allows us to study properties of phonology that hold no matter how it is implemented. Work in this vein has found that a majority of phonological processes only consider information within a finite window, placing them in the highly restrictive class of Strictly Local (SL) functions (Chandlee 2014; Chandlee et al. 2014; 2015). Long-distance phonological processes, however, lie outside the capabilities of the SL functions since they consider information that can be arbitrarily distant. The more powerful class of subsequential functions has been offered as a potential characterization of long-distance phonology (Heinz & Lai 2013; Luo 2017; Payne 2017), but we argue that an intermediate class offers a more natural model. Specifically, by incorporating an autosegmental tier (e.g., Goldsmith 1976) into the structure of an SL function, the non-local information crucial for applying long- distance processes can be rendered local. In addition to assessing the typological coverage of these Tier-based Strictly Local functions (Burness & McMullin 2019; Hao & Andersson 2019; Hao & Bowers 2019), we show that they fail to generate two pathological behaviours (minimum distance requirements and modulo counting) that can be accomplished with a subsequential function. We therefore conclude that tier-based computation is a better characterization of long-distance phonology than subsequential computation.

Abstract EFSA was asked by the European Commission to provide information on the levels of domoic acid (DA) in whole scallops that would ensure that levels in edible parts are below the regulatory limit after shucking. This should include five species of scallops. In addition, EFSA was asked to recommend the number of scallops to be used in an analytical sample. To address these questions, EFSA received suitable data on DA for only one scallop species, Pecten maximus, i.e. data on pooled samples of edible and non‐edible parts. A large part of the concentration levels was above the limit of quantification (LOQ) and only these data were used for the assessment. Shucking in most cases resulted in a strong decrease in the toxin levels. Statistical analysis of the data showed that levels in whole scallops should not exceed 24 mg DA/kg, 59 mg DA/kg and 127 mg DA/kg to ensure that levels in, respectively, gonads, muscle and muscle plus gonads are below the regulatory limit of 20 mg DA/kg with 99% certainty. Such an analysis was not possible for the other scallop species. In the absence of data from member states, published data of variations between scallops were used to calculate the sample size to ensure a 95% correct prediction on whether the level in scallops in an area or lot is correctly predicted to be compliant/non‐compliant. It was shown that 10 scallops per sample would be sufficient to predict with 95% certainty if DA levels in the area/lot were twofold below or above the regulatory limit for the highest reported coefficient of variance (CV) of 1.06. To predict with 95% certainty for levels between 15 and 27 mg DA/kg, a pooled sample of more than 30 scallops would have to be tested.

Abstract EFSA was asked by the European Commission to provide information on levels of lipophilic shellfish toxins in whole scallops that would ensure levels in edible parts below the regulatory limits after shucking, i.e. removal of non‐edible parts. This should include the okadaic acid (OA), the azaspiracid (AZA) and the yessotoxin (YTX) groups, and five species of scallops. In addition, EFSA was asked to recommend the number of scallops in an analytical sample. To address these questions, EFSA received suitable data on the three toxin groups in two scallop species, Aequipecten opercularis and Pecten maximus, i.e. data on individual and pooled samples of edible and non‐edible parts from contamination incidents. The majority of the concentration levels were below limit of quantification (LOQ)/limit of detection (LOD), especially in adductor muscle but also in gonads. Shucking in most cases resulted in a strong decrease in the toxin levels. For Pecten maximus, statistical analysis showed that levels in whole scallops should not exceed 256 μg OA eq/kg or 217 μg AZA1 eq/kg to ensure that levels in gonads are below the regulatory limits of 160 μg OA or AZA1 eq/kg with 99% certainty. Such an analysis was not possible for yessotoxins or any toxin in Aequipecten opercularis and an assessment could only be based on upper bound levels. To ensure a 95% correct prediction on whether the level in scallops in an area or lot is correctly predicted to be compliant/non‐compliant, it was shown that 10 scallops per sample would be sufficient to predict with 95% certainty if levels of OA‐group toxins in the area/lot were 25% below or above the regulatory limit. However, to predict with a 95% certainty for levels between 140 and 180 μg OA eq/kg, a pooled sample of more than 30 scallops would have to be tested.

Membranoproliferative glomerulonephritis (MPGN), C3 glomerulopathy (C3G), atypical haemolytic uraemic syndrome (aHUS) and age-related macular degeneration (AMD) have all been strongly linked with dysfunction of the alternative pathway (AP) of complement. A significant proportion of individuals with MPGN, C3G, aHUS and AMD carry rare genetic variants in the CFH gene that cause functional or quantitative deficiencies in the factor H (FH) protein, an important regulator of the AP. In silico analysis of the deleteriousness of rare genetic variants in CFH is not reliable and careful biochemical assessment remains the gold standard. Six N-terminal variants of uncertain significance in CFH were identified in patients with these diseases of the AP and selected for analysis. The variants were produced in Pichia Pastoris in the setting of FH CCPs 1–4, purified by nickel affinity chromatography and size exclusion and characterized by surface plasmon resonance and haemolytic assays as well as by cofactor assays in the fluid phase. A single variant, Q81P demonstrated a profound loss of binding to C3b with consequent loss of cofactor and decay accelerating activity. A further 2 variants, G69E and D130N, demonstrated only subtle defects which could conceivably over time lead to disease progression of more chronic AP diseases such as C3G and AMD. In the variants S159N, A161S, and M162V any functional defect was below the capacity of the experimental assays to reliably detect. This study further underlines the importance of careful biochemical assessment when assigning functional consequences to rare genetic variants that may alter clinical decisions for patients.

Abstract Biotechnological processes use microbes to convert abundant molecules, such as glucose, into high-value products, such as pharmaceuticals, commodity and fine chemicals, and energy. However, from the outset of the development of a new bioprocess, it is difficult to determine the feasibility, expected yields, and targets for engineering. In this review, we describe a methodology that uses rough estimates to assess the feasibility of a process, approximate the expected product titer of a biological system, and identify variables to manipulate in order to achieve the desired performance. This methodology uses estimates from literature and biological intuition, and can be applied in the early stages of a project to help plan future engineering. We highlight recent literature examples, as well as two case studies from our own work, to demonstrate the use and power of rough estimates. Describing and predicting biological function using estimates guides the research and development phase of new bioprocesses and is a useful first step to understand and build a new microbial factory.

An 81-year-old woman presented to our institution with a contained ruptured mycotic aortic aneurysm involving the takeoff of the celiac artery that required ligation of the celiac trunk, resulting in foregut ischemia and the need for revascularization. The technique of aortic reconstruction with delayed hepatic artery revascularization by a common iliac artery to hepatic artery bypass is described. Keywords: Mycotic aneurysm, Celiac artery aneurysm

As archaeologists continue to utilize digital 3D visualization technologies, instruction can also benefit from purpose-driven uses of these data. This paper outlines a pilot project that used previously captured 3D data in a large-scale immersive environment to supplement the instruction of basic archaeological concepts to an undergraduate introductory anthropology class. The flexibility of the platform allowed excavation trenches to be investigated in three-dimensions, enhancing the understanding of excavation methods and providing additional insight in the choices of the excavators. Additionally, virtual investigation of the artifacts provided a way for students to interact with objects on the other side of the world in a more complete way. Instructor-led immersive virtual experiences have significant potential to widen the interest in archaeology and enhance the instruction of archaeological concepts. They allow students to interact with the content, guided by an expert, and in the presence of each other. While the facilities are not available at every university at the current time, the cost effectiveness and ability to deliver these experiences via head-mounted displays represents an exciting potential extension for complementary self-paced, yet guided, exploration.

This paper reports on a series of artificial grammar learning experiments focused on locality relations in patterns of long-distance consonant agreement (harmony) and disagreement (dissimilation). Participants in experimental conditions were exposed to dependencies affecting stem-suffix pairs of liquids at either a short-range (transvocalic, CVCVLV-LV) or medium-range (beyond-transvocalic, CVLVCV-LV) distance. Two experiments used a poverty of stimulus paradigm, offering no information about the other distance level; participants interpreted short-range interaction as a strictly transvocalic dependency but medium-range interaction as unbounded, generalizing to other distances. Two experiments employed a ‘rich stimulus’ paradigm, where training data unambiguously indicated the absence of any dependency at the other distance; this enabled probing of specific locality patterns, in particular strictly beyond-transvocalic dependencies. The constraint-based Agreement by Correspondence model of non-adjacent consonant interactions predicts such patterns to be possible for dissimilation but not harmony. The results do not support this hypothesis: Participants seem to have serious difficulty learning strictly beyond-transvocalic dependencies of either kind. Our findings are more consistent with recent proposals that the space of learnable phonotactic restrictions is delimited by the Tier-based Strictly 2-Local class of formal languages. Strictly transvocalic and unbounded dependencies lie within this region, whereas strictly beyond-transvocalic dependencies are more complex, falling outside the learner’s hypothesis space.

Plug-in Electric Vehicle (PEV) user charging behavior has a significant influence on a distribution network and its reliability. Generally, monitoring energy consumption has become one of the most important factors in green and micro grids; therefore, predicting the charging demand of PEVs (the energy consumed during the charging session) could help to efficiently manage the electric grid. Consequently, three machine learning methods are applied in this research to predict the charging demand for the PEV user after a charging session starts. This approach is validated using a dataset consisting of seven years of charging events collected from public charging stations in the state of Nebraska, USA. The results show that the regression method, XGBoost, slightly outperforms the other methods in predicting the charging demand, with an RMSE equal to 6.68 kWh and R2 equal to 51.9%. The relative importance of input variables is also discussed, showing that the user’s historical average demand has the most predictive value. Accurate prediction of session charging demand, as opposed to the daily or hourly demand of multiple users, has many possible applications for utility companies and charging networks, including scheduling, grid stability, and smart grid integration.

Adherence to the advice of medical practitioners is critical to successful treatment outcomes and has been much researched in human health, but is less well studied in the veterinary and clinical animal behavior fields. Given that the management of behavior problems often requires substantial change in established client behavior, it is likely that adherence is a substantive issue affecting success. However, little is known about the relationships between relevant factors, and there is no established way of assessing these. Therefore, the aim of this study was to develop an instrument for coding factors likely to impinge on pet owner adherence to behavior advice and validate its utility through the identification of the factors appearing to relate most closely to a successful treatment outcome in a sample population from our clinic. Potential factors affecting adherence were identified from human health and animal behavior studies, and a survey instrument developed with items matched to these factors. Forty-two dog owners who had attended the University of Lincoln Animal Behavior Clinic over a 2-year period provided data used in the analysis. The assessment of treatment outcome success by clients and clinicians was correlated, but clinicians tended to overestimate success by half a point on a 5-point scale. Eleven items relating to adherence were found to correlate with client ratings of treatment success in a univariate analysis, with three of these remaining in an ordinal logistic regression model. These three related to trust in the advice given by the clinician, concern over distress caused to the pet in the longer term and the perceived recommendation of treatment measures that had failed. By further examining the relationship between all of these factors in a hierarchical cluster analysis, we were able to postulate ways in which we might be able to improve client adherence and thus treatment success. This provides a model for the application of the instrument in any veterinary behavior practice wishing to use client feedback to rationalize areas of the consultation which might be improved.

Sistemas eletromagnéticos para análise de movimento são conhecidos como precisos para registrar a posição e orientação dos segmentos do corpo humano. Até o momento, a confiabilidade do registro eletromagnético foi descrita apenas para a dinâmica da escápula, não sendo encontrados estudos de confiabilidade da posição de repouso ou postura da mesma. O objetivo deste estudo foi a análise da confiabilidade intra- e inter-sessão e erros absolutos do registro eletromagnético da posição e orientação da escápula na postura habitual de repouso de indivíduos saudáveis. Foram voluntários no estudo 22 indivíduos sem sintomas no complexo articular do ombro e não-praticantes amadores ou profissionais de esporte e atividade física envolvendo os membros superiores. O equipamento utilizado foi o sistema 3SPACE Liberty (Polhemus Inc.). Um mesmo avaliador coletou os dados cinemáticos em duas sessões diferentes com um intervalo de sete a dez dias. O Coeficiente de Correlação Intraclasse (ICC2,1 e ICC2,k) e o Erro Padrão de Medida (EPM) foram calculados. A confiabilidade intersessão variou entre boa a excelente (ICC de 0,66 a 0,96) e a confiabilidade intra-sessão foi sempre excelente (ICC ≥ 0,97). Os valores de EPM encontrados para as distâncias lineares foram menores que 0,02 cm e para as rotações da escápula relativa ao tórax variaram entre 0,72 º e 5,48 º. Os resultados deste estudo demonstraram que o registro eletromagnético da posição habitual de repouso da escápula é confiável para determinar a posição e a orientação da mesma em um população sedentária e sem sintomas no complexo articular do ombro.

Glioblastoma (GBM) is the most common and most aggressive primary brain malignancy and, as it stands, is virtually incurable. With the current standard-of-care, maximum feasible surgical resection followed by radical radiotherapy and adjuvant temozolomide, survival rates are at a median of 14.6 months from diagnosis in molecularly unselected patients(1). Collectively, the current knowledge suggests that the continued tumor growth and survival is in part due to failure to mount an effective immune response. While this tolerance is subtended by the tumor being utterly self, it is to a great extent due to local and systemic immune compromise mediated by the tumor. Different cell modalities including lymphokine-activated killer (LAK) cells, natural killer (NK) cells, cytotoxic T lymphocytes (CTL), and transgenic chimeric antigen receptor (CAR)- or αβ T cell receptor (TCR) grafted T cells are being explored to recover and or redirect the specificity of the cellular arm of the immune system towards the tumor complex. Promising phase I/II trials of such modalities have shown early indications of potential efficacy while maintaining a favorable toxicity profile. Efficacy will need to be formally tested in phase II/III clinical trials. Given the high morbidity and mortality of GBM, it is imperative to further investigate and possibly integrate such novel cell-based therapies into the current standards-of-care and herein we collectively assess and critique the state-of-the-knowledge pertaining to these efforts.

BackgroundPolycystic ovary syndrome (PCOS) is an endocrine disrupting disorder affecting about 10% of reproductive-aged women. PCOS diagnosis may be delayed several years and may require multiple physicians, resulting in lost time for risk-reducing interventions. Menstrual tracking apps are a potential tool to alert women of their risk while also prompting evaluation from a medical professional. ObjectiveThe primary objective of this study was to develop and pilot test the irregular cycle feature, a predictive model that generated a PCOS risk score, in the menstrual tracking app, Clue. The secondary objectives were to run the model using virtual test subjects, create a quantitative risk score, compare the feature’s risk score with that of a physician, and determine the sensitivity and specificity of the model before empirical testing on human subjects. MethodsA literature review was conducted to generate a list of signs and symptoms of PCOS, termed variables. Variables were then assigned a probability and built into a Bayesian network. Questions were created based on these variables. A total of 9 virtual test subjects were identified using self-reported menstrual cycles and answers to the feature’s questions. Upon completion of the questionnaire, a Result Screen and Doctor’s Report summarizing the probability of having PCOS was displayed. This provided information about PCOS and data to facilitate diagnosis by a medical professional. To assess the accuracy of the feature, the same set of 9 virtual test subjects was assigned probabilities by the feature and the physician, who served as the gold standard. The feature recommended individuals with a score greater than or equal to 25% to follow-up with a physician. Differences between the feature and physician scores were evaluated using a t test and a Pearson correlation coefficient in 8 of the 9 virtual test subjects. A second iteration was conducted to assess the feature’s probability capabilities. ResultsThe irregular cycle feature’s first iteration produced 1 false-positive compared with the physician score and had an absolute mean difference of 15.5% (SD 15.1%) among the virtual test subjects. The second iteration had 2 false positives compared with the physician score and had an absolute mean difference of 18.8% (SD 13.6%). The feature overpredicted the virtual test subjects’ risk of PCOS compared with the physician. However, a significant positive correlation existed between the feature and physician score (Pearson correlation coefficient=0.82; P=.01). The second iteration performed worse, with a Pearson correlation coefficient of 0.73 (P=.03). ConclusionsThe first iteration of the feature outperformed the second and better predicted the probability of PCOS. Although further research is needed with a more robust sample size, this pilot study indicates the potential value for developing a screening tool to prompt high-risk subjects to seek evaluation by a medical professional.

Mindful of the challenges to long-term operation, especially the severe safety and environmental consequences shown through historical nuclear power plant accidents (e.g. Fukoshima, Chernobyl, etc), it is imperative that European research and innovation focuses on demonstrating reliable long-term operation. Five examples of European Commission supported projects meeting such objectives are INCEFA+, SOTERIA, ATLAS+, MEACTOS and NUGENIA+. There are economies of scale within, and synergies across these projects which enable further advantage to be gained. Additionally, since researchers are well engaged internationally, this brings into European Organisations latest developments in understanding from further afield (e.g. USA, Japan), further enabling safety assurance advances, and enabling work overseas to be influenced consistent with European requirements. Through examples, this paper provides evidence of the advances claimed, whilst being careful to also declare areas of interest for which further work is still a priority.

Morphogens provide positional information and their concentration is key to the organized development of multicellular organisms. Nitrogen-fixing root nodules are unique organs induced by Nod factor-producing bacteria. Localized production of Nod factors establishes a developmental field within the root where plant cells are reprogrammed to form infection threads and primordia. We found that regulation of Nod factor levels by Lotus japonicus is required for the formation of nitrogen-fixing organs, determining the fate of this induced developmental program. Our analysis of plant and bacterial mutants shows that a host chitinase modulates Nod factor levels possibly in a structure-dependent manner. In Lotus, this is required for maintaining Nod factor signalling in parallel with the elongation of infection threads within the nodule cortex, while root hair infection and primordia formation are not influenced. Our study shows that infected nodules require balanced levels of Nod factors for completing their transition to functional, nitrogen-fixing organs.