bluuebunny/crossref_metadata_2025 huggingface dataset:
Histopathological Features of Pendred Syndrome Thyroids Align with Differences in the Expression of Thyroid-Specific Markers, Apical Iodide Transporters, and Ciliogenesis Process
Authors: Vázquez-Román V. , Cameselle-Teijeiro J. M. , Fernández-Santos J. M. , Ríos-Moreno M. J. , Loidi L. , Ortiz T. , Martín-Lacave I.
Published: October 2022

Pendred syndrome (PDS) is an autosomal recessive disorder caused by mutations in the gene that encodes pendrin. Pendred thyroid tissue is supposedly altered by the absence of functional pendrin, but it is still unknown whether other iodide exchangers could compensate for the loss of the protein. Moreover, we have recently described that primary cilium, a conserved structure present at the apical surface of normal follicular cells, suffers different alterations in functional thyroid diseases. We aimed (1) to better understand the histopathological changes experienced by PDS thyroids, (2) to analyze the expression of different thyroid-specific genes and alternative iodide transporters and, finally, (3) to determine whether those changes may alter the morphological pattern of primary cilia in follicular cells. Thyroid samples from a series of four PDS patients were analyzed by immunohistochemistry, double immunofluorescence, and morphometry to evaluate changes in primary cilia frequency and length. We found thyroid follicular nodular disease in all PDS thyroids, frequently in association with follicular adenomas. There were only slight changes in the expression of thyroid-specific markers. Although no positivity for pendrin was found, cytoplasmic immunostaining for ANO-1, CLC-5, and CFTR was stronger in diffuse hyperplastic areas when compared to areas with highly cellular follicular nodules (HCFNs). HCFNs and follicular adenomas always showed diminished ciliary frequency and length. Our results suggest a direct relationship between the absence of functional pendrin and the loss of the normal thyroid architecture in PDS patients, which was also accompanied by differences in the expression of specific immunohistochemical markers and altered ciliogenesis. The present data may help the pathologist in screening for PDS.
Kramers–Moyal analysis of interplanetary magnetic field fluctuations at sub-ion scales
Authors: Benella Simone , Stumpo Mirko , Consolini Giuseppe , Alberti Tommaso , Laurenza Monica , Yordanova Emiliya
Published: October 2022

In the framework of statistical time series analysis of complex dynamics, we present a multiscale characterization of solar wind turbulence in the near-earth environment. The data analysis, based on the Markov process theory, is meant to estimate the Kramers–Moyal coefficients associated with the measured magnetic field fluctuations. In fact, when the scale-to-scale dynamics can be successfully described as a Markov process, first- and second-order Kramers–Moyal coefficients provide a complete description of the dynamics in terms of Langevin stochastic process. The analysis is carried out using high-resolution magnetic field measurements gathered by Cluster during a fast solar wind period on January 20, 2007. This analysis extends recent findings in the near-Sun environment with the aim of testing the universality of the Markovian nature of the magnetic field fluctuations in the sub-ion/kinetic domain.
Modelling Human Word Learning and Recognition Using Visually Grounded Speech
Authors: Merkx Danny , Scholten Sebastiaan , Frank Stefan L. , Ernestus Mirjam , Scharenborg Odette
Published: October 2022

Many computational models of speech recognition assume that the set of target words is already given. This implies that these models learn to recognise speech in a biologically unrealistic manner, i.e. with prior lexical knowledge and explicit supervision. In contrast, visually grounded speech models learn to recognise speech without prior lexical knowledge by exploiting statistical dependencies between spoken and visual input. While it has previously been shown that visually grounded speech models learn to recognise the presence of words in the input, we explicitly investigate such a model as a model of human speech recognition. We investigate the time course of noun and verb recognition as simulated by the model using a gating paradigm to test whether its recognition is affected by well-known word competition effects in human speech processing. We furthermore investigate whether vector quantisation, a technique for discrete representation learning, aids the model in the discovery and recognition of words. Our experiments show that the model is able to recognise nouns in isolation and even learns to properly differentiate between plural and singular nouns. We also find that recognition is influenced by word competition from the word-initial cohort and neighbourhood density, mirroring word competition effects in human speech comprehension. Lastly, we find no evidence that vector quantisation is helpful in discovering and recognising words, though our gating experiment does show that the LSTM-VQ model is able to recognise the target words earlier.
High expression of RUVBL1 and HNRNPU is associated with poor overall survival in stage I and II non-small cell lung cancer patients
Authors: Durślewicz Justyna , Jóźwicki Jakub , Klimaszewska-Wiśniewska Anna , Zielińska Aleksandra , Antosik Paulina , Grzanka Dariusz , Braun Marcin
Published: October 2022

The present study aimed to investigate expression levels and prognostic significance of RUVBL1 and HNRNPU in stage I and II non–small-cell lung cancer (NSCLC) patients. Therefore, we evaluated immunohistochemical staining of RUVBL1 and HNRNPU, as well as RNA-seq data from public sources, and the results were evaluated concerning overall survival (OS) and clinicopathological features. We found that RUVBL1 and HNRNPU proteins and mRNA levels were higher in tumor tissues as compared to adjacent/normal tissues. RUVBL1 (p = 0.013) and HNRNPU (p = 0.021) high protein levels were independent prognostic factors for poor OS. Also, the multivariate analysis in the TCGA dataset revealed that high RUVBL1 (p = 0.064) and HNRNPU (p = 0.181) mRNA levels were not significantly associated with prognosis. However, the co-expression status of these markers (R + H +) was independently associated with poor OS both in the TCGA dataset (p = 0.027) and in our cohort (p = 0.001). In conclusion, combined and individual expression of RUVBL1 and HNRNPU proteins, as well as R + H + mRNA status, may serve as potential prognostic biomarkers for NSCLC. This study adds to the previous observations that RUVBL1 and HNRNPU might be novel and promising therapeutic targets and markers for prognostic evaluation.
A novel metaheuristic optimisation approach for text sentiment analysis
Authors: Hosseinalipour Ali , Ghanbarzadeh Reza
Published: October 2022

Automated sentiment analysis is considered an area in natural language processing research that seeks to understand a text author's mood, thoughts, and feelings. New opportunities and challenges have arisen in this field due to the popularity and accessibility of a variety of resources of ideas, such as online review websites, personal blogs, and social media. Feature selection, which can be conducted using metaheuristic algorithms, is one of the steps of sentiment analysis. It is crucial to use high-performing algorithms for feature selection. This paper applies the Horse herd Optimisation Algorithm (HOA) for feature selection in text sentiment analysis. HOA is a metaheuristic algorithm and uses six key behaviours to simulate the social performance of horses of various ages, to solve high-dimensional optimisation problems. In order to improve HOA, this paper adds another behaviour of horses to the basic algorithm; thus, the new algorithm uses seven key behaviours of horses of different ages to imitate their social performance. It is then discretised and converted to a multi-objective algorithm. The improved algorithm's performance is evaluated using 15 CEC benchmark functions, and the results are compared to the Binary Social Spider Algorithm, the Binary Grey Wolf Optimizer, and the Binary Butterfly Optimization Algorithm. The new algorithm, the Multi-objective Binary Horse herd Optimisation Algorithm (MBHOA), excels at solving high-dimensional complex problems. To evaluate the algorithm's performance in feature selection, as a practical example, it is employed in text sentiment analysis and examined on various data sets. The simulation results indicate that MBHOA has a better performance in analysing sentiment compared to similar approaches.
Wetland Conservation and Its Effects on Mosquito Populations
Authors: Dworrak Tarja V. , Sauer Felix G. , Kiel Ellen
Published: October 2022

To stop the worldwide decline of wetlands, conservation measures like restoration, protection and construction of these ecosystems are indispensable. However, wetland conservation could influence mosquito populations. We analysed how conservation measures affect the species composition and abundance of mosquitoes by conducting a systematic literature review and generated results from 113 selected articles. Thereby, we separately assessed conservation measures in constructed, for example polders, and natural, non-constructed, wetlands. An increase in overall mosquito abundance was more prevalent in constructed wetlands, but not in studies conducted in non-constructed wetlands. Besides assessing overall mosquito abundance, we developed a scheme to rank mosquito species-specific nuisance after conservation measures. Mosquito species can differ in their nuisance potential according to their biting and host-seeking behaviors. We further assessed the effects of mosquito management practices on specific mosquito species and discussed different practices between constructed and non-constructed wetlands. Whereas in constructed wetlands more management practices could be applied, practices in non-constructed wetlands were limited. In conclusion, we were not able to reject entirely the hypothesis that mosquito populations change after conservation measures in wetlands.
Somatosensation and the First Person
Authors: Serrahima Carlota
Published: October 2022

Experientialism about the sense of bodily ownership is the view that there is something it is like to feel a body as one’s own. In this paper I argue for a particular experientialist thesis. I first present a puzzle about the relation between bodily awareness and self-consciousness, and introduce a somewhat underappreciated view on the sense of bodily ownership, Implicit Reflexivity, that points us in the right direction as to how to address this puzzle. I argue that Implicit Reflexivity, however, does not provide a full solution to the puzzle. I then introduce a novel view on the sense of bodily ownership that inherits a central tenet, Reflexivity, from the above view, without having its flaws. According to Reflexivity, the sense of bodily ownership consists in the reflexive character of bodily sensations, namely in the fact that bodily sensations have experience-dependent properties as part of their content. Cashed out this way, Reflexivity is an attractive way of explicating the notion that bodily sensations are experiences of the body as subject. Reflexivity also highlights a central, but so far neglected, connection between the sense of bodily ownership and the sense of experience ownership.
Should organic animals be slaughtered differently from non-organic animals? A cluster analysis of German consumers
Authors: Kühl Sarah , Bayer Elisa , Busch Gesa
Published: October 2022

Public criticism of livestock husbandry is increasing, and better animal welfare is a main buying motive for organic animal products. The slaughter process is a crucial point for animal welfare impacts, but there are no specific regulations regarding slaughtering methods according to the European organic label. Research is missing on what (organic) consumers expect and what they demand from slaughter when considering organic meat. We examined these questions in a survey with 1,604 consumers in Germany. We identified three groups of participants based on their different views on the treatment of organic and non-organic animals at slaughter. The results show that especially organic consumers expect specific regulations for the slaughter of organic animals to be in place already, and they therewith perceive advantages for meat quality. However, the cluster analysis reveals one group (36.8%) that is for a different slaughtering of organic animals and simultaneously favors the equal treatment of all animals at slaughter. Consumers in this ambivalent cluster justify their meat consumption by buying organic meat more often, which might be a coping strategy with the moral dilemma of meat consumption (“meat paradox”). A second cluster (32.4%) rejects different slaughtering methods and is highly interested in animal welfare. These consumers seem to plead for general animal welfare improvements. A third cluster (30.8%) is not interested in the slaughter methods at all. The results show that specific regulations for the slaughter of organic animals might reduce the risk of losing consumer trust and open up further differentiation strategies.
The challenge of recruiting multimorbid older patients identified in a hospital database to a randomised controlled trial
Authors: Biegus Karol R. , Frobell Richard B. , Wallin Åsa K. , Ekdahl Anne W.
Published: October 2022

Background

Research involving multimorbid older patients is gaining momentum. However, little is known about how to plan a randomised controlled trial (RCT) involving this group of patients. An evidence-based approach to the challenges of a recruitment process could guide researchers and help prevent underpowered trials.

Aim

To define the number of multimorbid older patients that need to be identified and the number of eligible patients that need to be invited to achieve the desired recruitment number to a RCT.

Method

We used recruitment data from the GerMoT trial, a RCT comparing proactive outpatient care based on Comprehensive Geriatric Assessment with usual care. Multimorbid older patients with high healthcare utilisation were recruited to the trial.

Results

Of the 1212 patients identified in a database as meeting the inclusion criteria 838 (70%) could be invited to participate in the trial. The rest could not be invited for a variety of reasons; 162 had moved out of area or into nursing homes and 86 had died before they could be contacted. 113 could not be reached. 450 (54%) of the invited patients agreed to participate.

Conclusions

In our study, we have shown that it is possible to achieve a good consent rate despite older participants with multimorbidity. This can be used when planning an RCT for this patient group, who are often excluded from clinical trials. Our results are specific to a context that provides similar abilities to identify and recruit patients as can be seen in Sweden.
An efficient method for train–track–substructure dynamic interaction analysis by implicit-explicit integration and multi-time-step solution
Authors: Xu Lei , Zhai Wanming , Zhu Shengyang , Liu Weizheng
Published: October 2022

In this work, a method is put forward to obtain the dynamic solution efficiently and accurately for a large-scale train–track–substructure (TTS) system. It is called implicit-explicit integration and multi-time-step solution method (abbreviated as mI-nE-MTS method). The TTS system is divided into train–track subsystem and substructure subsystem. Considering that the root cause of low efficiency of obtaining TTS solution lies in solving the algebraic equation of the substructures, the high-efficient Zhai method, an explicit integration scheme, can be introduced to avoid matrix inversion process. The train–track system is solved by implicitly Park method. Moreover, it is known that the requirement of time step size differs for different sub-systems, integration methods and structural frequency response characteristics. A multi-time-step solution is proposed, in which time step size for the train–track subsystem and the substructure subsystem can be arbitrarily chosen once satisfying stability and precision demand, namely the time spent for m implicit integral steps is equal to n explicit integral steps, i.e., mI = nE as mentioned above. The numerical examples show the accuracy, efficiency, and engineering practicality of the proposed method.
Integrated scheduling of distributed production and distribution in group manufacturing with uncertain travel time
Authors: Guo Jun , Liu Wenjun , Peng Zhao , Du Baigang
Published: October 2022

This paper presents a novel integrated distributed production and distribution scheduling problem in group manufacturing with uncertain travel time (IDPDSP-GM-UTT), in which products are firstly produced in several distributed hybrid flow shops and then delivered to several retailers in batches. The proposed model considers both geographical dispersion of multi-factories and variable travel time between factories and retailers caused by time-varying dynamics of road network, which describes the production environment more authentic. Additionally, a mathematical model is developed to find the optimal quantity of raw material, delivery plan, and punishment of earliness and tardiness with the objective of minimizing total costs. Then, an improved genetic algorithm with two-stage heuristic mutation scheduling strategy and tabu search for local optimization (GA-2HMS&TS) is designed to solve the proposed model. To verify the performances of the proposed method, several experiments by adopting test experimental examples with different scales are performed. The computational results exhibit that the GA-2HMS&TS not only significantly reduces the total cost of production and distribution, but also outperforms all of its rivals. In addition, the robustness of the proposed models is also analyzed with regard to the different road conditions.
Wind speed and global radiation forecasting based on differential, deep and stochastic machine learning of patterns in 2-level historical meteo-quantity sets
Authors: Zjavka Ladislav
Published: October 2022

Accurate forecasting of wind speed and solar radiation can help operators of wind farms and Photo-Voltaic (PV) plants prepare efficient and practicable production plans to balance the supply with demand in the generation and consumption of Renewable Energy (RE). Reliable Artificial Intelligence (AI) forecast models can minimize the effect of wind and solar power fluctuations, eliminating their intermittent character in system dispatch planning and utilization. Intelligent wind and solar energy management is essential in load scheduling and decision-making processes to meet user requirements. The proposed 24-h prediction schemes involve the beginning detection and secondary similarity re-evaluation of optimal day-data sequences, which is a notable incremental improvement against state-of-the-art in the consequent application of statistical AI learning. 2-level altitude measurements allow the identification of data relationships between two surface layers (hill and lowland) and adequate interpretation of various meteorological situations, whose differentiate information is used by AI models to recognize upcoming changes in the mid-term day horizon. Observations at two professional meteorological stations comprise specific quantities, of which the most valuable are automatically selected as input for the day model. Differential learning is a novel designed unconventional neurocomputing approach that combines derivative components produced in selected network nodes in the weighted modular output. The complexity of the node-stepwise composed model corresponds to the patterns included in the training data. It allows for representation of high uncertain and nonlinear dynamic systems, dependent on local RE production, not substantially reducing the input vector dimensionality leading to model over simplifications as standard AI does. Available angular and frequency time data (e.g., wind direction, humidity, and irradiation cycles) are combined with the amplitudes to solve reduced Partial Differential Equations (PDEs), defined in network nodes, in the periodical complex form. This is a substantial improvement over the previous publication design. The comparative results show better efficiency and reliability of differential learning in representing the modular uncertainty and PDE dynamics of patterns on a day horizon, taking into account recent deep and stochastic learning. A free available C++ parametric software together with the processed meteo-data sets allow additional comparisons with the presented model results.
Progress of Materials and Devices for Neuromorphic Vision Sensors
Authors: Cho Sung Woon , Jo Chanho , Kim Yong-Hoon , Park Sung Kyu
Published: October 2022

The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords: smaller, faster, and smarter. (1) Smaller: Devices are becoming more compact by integrating previously separated components such as sensors, memory, and processing units. As a prime example, the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits, such as simpler circuitry, lower power consumption, and less data redundancy. (2) Swifter: Owing to the nature of physics, smaller and more integrated devices can detect, process, and react to input more quickly. In addition, the methods for sensing and processing optical information using various materials (such as oxide semiconductors) are evolving. (3) Smarter: Owing to these two main research directions, we can expect advanced applications such as adaptive vision sensors, collision sensors, and nociceptive sensors. This review mainly focuses on the recent progress, working mechanisms, image pre-processing techniques, and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies. "Image missing"
Effects of combined sewer overflow on water quality: a case study of Hatirjheel Lake in Dhaka
Authors: Atauzzaman M. , Ali M. A.
Published: October 2022

This paper presents a case study focusing on the impacts of combined sewer overflows on the water quality of the receiving water body, Hatirjheel. Hatirjheel, the largest surface water body in Dhaka City with an area of about 1.012 km2, receives discharges from nine combined sewer overflow (CSO) structures. The water quality of Hatirjheel is poor throughout the year, but particularly during the wet season (June to October) near the CSO structures through which significant rainwater-sewage overflows. The water has been found to contain high concentrations of 5-day biochemical oxygen demand (BOD5) and chemical oxygen demand; some of the BOD5 values exceed the national discharge standards for treated effluents. Total ammonia concentration in Hatirjheel water increases during the wet season, often exceeding 20 mg/l; the concentration continues to increase after the end of the wet season, most likely due to the ammonification process. Nitrate concentration in Hatirjheel water increases at the end of the wet season, possibly due to nitrification; subsequent reduction in nitrate and ammonia concentration is possibly due to incorporation of nitrogen into algal mass. Excessive phosphorus in Hatirjheel promotes eutrophication, resulting in the visible greenish color of the water. This study highlights the significant adverse impact of combined sewer overflows, particularly for a densely populated city like Dhaka, where most of the rainfall occurs within a relatively short period during monsoon.

ArticleHighlights

Combined sewer overflows could significantly deteriorate the water quality of the receiving water bodies.

Sewer overflows create a significant spatiotemporal variation of water quality, with higher pollution close to the overflowing combined sewer overflow structures.

Because of its significant adverse impact on water quality and ecology, combined sewer systems may not be viable for high-density urban areas.
A Novel Visual-Based Terrain Relative Navigation System for Planetary Applications Based on Mask R-CNN and Projective Invariants
Authors: Del Prete Roberto , Renga Alfredo
Published: October 2022

In the framework of autonomous spacecraft navigation, this manuscript proposes a novel vision-based terrain relative navigation (TRN) system called FederNet. The developed system exploits a pattern of observed craters to perform an absolute position measurement. The obtained measurements are thus integrated into a navigation filter to estimate the spacecraft state in terms of position and velocity. Recovering crater locations from elevation imagery is not an easy task since sensors can generate images with vastly different appearances and qualities. Hence, several problems have been faced. First, the crater detection problem from elevation images, second, the crater matching problem with known craters, the spacecraft position estimation problem from retrieved matches, and its integration with a navigation filter. The first problem was countered with the robust approach of deep learning. Then, a crater matching algorithm based on geometric descriptors was developed to solve the pattern recognition problem. Finally, a position estimation algorithm was integrated with an Extended Kalman Filter, built with a Keplerian propagator. This key choice highlights the performance achieved by the developed system that could benefit from more accurate propagators. FederNet system has been validated with an experimental analysis on real elevation images. Results showed that FederNet is capable to cruise with a navigation accuracy below 400 meters when a sufficient number of well-distributed craters is available for matching. FederNet capabilities can be further improved with higher resolution data and a data fusion integration with other sensor measurements, such as the lunar GPS, nowadays under investigation by many researchers.
Valorisation of alum sludge to produce green and durable mortar
Authors: Jia Qiong , Zhuge Yan , Duan Weiwei , Liu Yue , Yang Jing , Youssf Osama , Lu Jinsuo
Published: October 2022

Alum sludge is a typical by-product of drinking water treatment processes. Most sludge is disposed of at landfill sites, and such a disposal method may cause significant environmental concern due to its vast amount. This paper assessed the feasibility of reusing sludge as a supplementary cementitious material, which could efficiently exhaust stockpiled sludge. Specifically, the pozzolanic reactivity of sludge at different temperatures, the reaction mechanism of the sludge–cement binder, and the resistance of sludge-derived mortar to microbially induced corrosion were investigated. The obtained results indicated that 800 °C was the optimal calcination temperature for sludge. Mortar containing sludge up to 30% by weight showed comparable physical properties at a curing age of 90 days. Mortar with 10% cement replaced by sludge can significantly improve the resistance to biogenic corrosion due to the formation of Al-bearing phases with high resistance to acidic media, e.g., Ca4Al2O7·xH2O and strätlingite.

Graphical abstract
Identifying relevant topics and training methods for emergency department flow training
Authors: Young Christina , Patey Christopher , Norman Paul , Chan Teresa , Hurley Oliver , Swab Michelle , Asghari Shabnam
Published: October 2022

Purpose

Despite the importance of patient flow to emergency department (ED) management, there is a need to strengthen and expand training in flow strategies for practicing ED staff. To date, there has been limited academic inquiry into the skills and training that ED staff require to improve patient flow. As part of a quality improvement initiative, our team aimed to identify the topics and training methods that should be included in flow training for ED staff.

Methods

We conducted an integrative review and modified Delphi. For the integrative review, we sought to identify appropriate skills, training strategies, and training modalities to include in a curriculum for ED staff. The findings from the review were compiled and distributed to Canadian experts in ED efficiency through a modified Delphi, including physicians, nurses, and nurse practitioners.

Results

Our literature search retrieved 8359 articles, of which 46 were included in the review. We identified 19 skills, 9 training strategies, and 12 training modalities used to improve ED efficiency in the literature. For the modified Delphi, we received responses from 39 participants in round one and 28 in round two, with response rates of 57% and 41%, respectively. The topics chosen by the most respondents were: “flow decisions,” “teamwork,” “backlog and surge management,” “leadership,” and “situational awareness.”

Conclusion

Our findings suggest that flow training should teach ED staff how to make decisions that improve flow, work more effectively as a team, manage patient backlog and surge, improve leadership skills, and develop situational awareness. These findings add to a gap in the academic literature regarding the training ED staff require to improve patient flow.
The Psychological Impact of Isolation on Hospitalised Patients with COVID-19 Infection in the UAE
Authors: Ahmed Nahida Nayaz , Juber Nirmin F. , AlKaabi Reem , AlShehhi Fatema , AlObeidli Mohamed , Salem Ahlam , Galadari Alaa , Wanigaratne Shamil , Ahmad Amar
Published: October 2022

Infection prevention and control measures for COVID-19 may include immediate admission to an isolation facility for the infected. However, the mental health impact of this isolation worldwide is not fully documented. This study aims to contribute to global data on the psychological impact of COVID-19 and to be the first study to assess psychological distress among hospitalised patients with COVID-19 in the UAE. Using a cross-sectional study design on 132 hospitalised patients, we found that 90% of participants scored within the normal levels for psychological distress. The length of stay was associated with higher levels of psychological distress and those aged 41–60 years had lower levels of psychological distress compared to the 31–40 years group. Our results contributed to global data on the psychological impact of COVID-19 and may help to identify those at risk for psychological distress due to COVID-19 hospitalisation for targeted prevention and future pandemic preparedness plans.
Loss of CASZ1 tumor suppressor linked to oncogenic subversion of neuroblastoma core regulatory circuitry
Authors: Liu Zhihui , Zhang Xiyuan , Xu Man , Lei Haiyan , Shern Jack F. , Thiele Carol J.
Published: October 2022

The neural crest lineage regulatory transcription factors (TFs) form a core regulatory circuitry (CRC) in neuroblastoma (NB) to specify a noradrenergic tumor phenotype. Oncogenic subversion of CRC TFs is well documented, but the role of loss of tumor suppressors plays remains unclear. Zinc-finger TF CASZ1 is a chromosome 1p36 (chr1p36) tumor suppressor. Single-cell RNA sequencing data analyses indicate that CASZ1 is highly expressed in developing chromaffin cells coincident with an expression of NB CRC TFs. In NB tumor cells, the CASZ1 tumor suppressor is silenced while CRC components are highly expressed. We find the NB CRC component HAND2 directly represses CASZ1 expression. ChIP-seq and transcriptomic analyses reveal that restoration of CASZ1 upregulates noradrenergic neuronal genes and represses expression of CRC components by remodeling enhancer activity. Our study identifies that the restored CASZ1 forms a negative feedback regulatory circuit with the established NB CRC to induce noradrenergic neuronal differentiation of NB.
MCM2 promotes the stemness and sorafenib resistance of hepatocellular carcinoma cells via hippo signaling
Authors: Zhou Xin , Luo Jianzhu , Xie Haixiang , Wei Zhongliu , Li Tianman , Liu Junqi , Liao Xiwen , Zhu Guangzhi , Peng Tao
Published: October 2022

Object: A large number of studies have suggested that stemness is an essential mechanism for drug resistance, metastasis and relapse in hepatocellular carcinoma (HCC). The aim of this study was to determine the impact of MCM2 on stemness and identify potential mechanisms that complement the stemness regulatory network in HCC. Methods: MCM2 expression features and prognostic significance were analyzed in multiple cohorts, including TCGA LIHC dataset, GSE14520 dataset, Guangxi cohort, and GSE76427 dataset. Stemness-related molecules and phenotypes were examined to evaluate the impact of MCM2 on stemness. The expression levels of key molecules of the hippo signaling pathway together with downstream target genes were examined to evaluate the effect of MCM2 on hippo signaling. This was further demonstrated by rescue experiments with hippo signaling pathway inhibitors (super-TDU). Sorafenib-resistant cells were constructed to assess the effect of MCM2 on drug resistance. A xenotransplantation model of nude mice was constructed to validate the role of MCM2 in vivo. Results: MCM2, which is expressed at higher levels in HCC tissue than in normal liver tissues, is a good indicator for distinguishing tumor tissues from normal liver tissues and can help differentiate HCC patients at different BCLC stages. The annotation of the differentially expressed genes in the MCM2 high and low expression groups indicated that MCM2 may be associated with the hippo signaling pathway. In addition, the expression of MCM2 in HCC tissues was correlated with the expression of YAP1/TAZ, which are key molecules of the hippo signaling pathway. It indicated that manipulation of MCM2 expression affects hippo signaling and stemness, while the inhibition of hippo signaling significantly reversed the effect of MCM2 on stemness. Disruption of MCM2 expression significantly elevated the sensitivity of sorafenib-resistant cells to sorafenib, as evidenced by the decrease in IC50 and diminished sphere-forming capacity. The in vivo assays showed that MCM2 effectively enhanced the efficacy of sorafenib. Conclusion: MCM2 is a good prognostic marker. MCM2 enhances the stemness of HCC cells by affecting the Hippo signaling pathway, while the downregulation of MCM2 inhibits resistance towards sorafenib.
Long-term reduction in morning and nighttime blood pressure after renal denervation: 36-month results from SPYRAL HTN-ON MED trial
Authors: Kario Kazuomi , Mahfoud Felix , Kandzari David E. , Townsend Raymond R. , Weber Michael A. , Schmieder Roland E. , Tsioufis Konstantinos , Pocock Stuart , Brar Sandeep , Hettrick Douglas A. , Fahy Martin , Böhm Michael
Published: October 2022

Elevated morning and nighttime blood pressures (BP) are associated with increased risk of cardiovascular events such as stroke and myocardial infarction. We compared the long-term changes in morning and nighttime BP in patients with uncontrolled hypertension (office systolic BP between 150 and <180 mmHg/diastolic BP ≥ 90 mmHg; mean ambulatory systolic BP (SBP) between 140 and <170 mmHg; 1–3 prescribed antihypertensive medications). Eighty patients were randomized to RDN or sham control. In patients taking at least 3 antihypertensive medications at 36 months (N = 23 RDN group; N = 23 sham group), the 24 h ambulatory SBP as well as morning (7:00–9:00AM) and nighttime (1:00–6:00AM) ambulatory SBP were significantly lower for the RDN group compared to sham control (24 h SBP: −20.2 vs. −10.2, p = 0.0087; morning SBP: −23.9 vs. −8.0 mmHg, p = 0.029; nighttime SBP: −20.8 vs. −7.2 mmHg, p = 0.0011). At 36 months, 24 h SBP was controlled to <130 mmHg in 40% of RDN patients in the morning compared to 6% for the sham group; P = 0.021 and in 80% of the RDN patients at night compared to 39% in the sham group; P = 0.019. Major adverse events through 36 months were rare in both groups, and there were no renal artery re-interventions or vascular complications. Morning and nighttime SBP were significantly lower in patients prescribed at least 3 antihypertensive medications at 36 months in the SPYRAL HTN-ON MED trial for RDN compared with sham control. The results suggest RDN has significant benefit when the risk of cardiovascular events is highest.
In vitro assembly, positioning and contraction of a division ring in minimal cells
Authors: Kohyama Shunshi , Merino-Salomón Adrián , Schwille Petra
Published: October 2022

Constructing a minimal machinery for autonomous self-division of synthetic cells is a major goal of bottom-up synthetic biology. One paradigm has been the E. coli divisome, with the MinCDE protein system guiding assembly and positioning of a presumably contractile ring based on FtsZ and its membrane adaptor FtsA. Here, we demonstrate the full in vitro reconstitution of this machinery consisting of five proteins within lipid vesicles, allowing to observe the following sequence of events in real time: 1) Assembly of an isotropic filamentous FtsZ network, 2) its condensation into a ring-like structure, along with pole-to-pole mode selection of Min oscillations resulting in equatorial positioning, and 3) onset of ring constriction, deforming the vesicles from spherical shape. Besides demonstrating these essential features, we highlight the importance of decisive experimental factors, such as macromolecular crowding. Our results provide an exceptional showcase of the emergence of cell division in a minimal system, and may represent a step towards developing a synthetic cell.
High-resolution neutron imaging of salt precipitation and water transport in zero-gap CO2 electrolysis
Authors: Disch Joey , Bohn Luca , Koch Susanne , Schulz Michael , Han Yiyong , Tengattini Alessandro , Helfen Lukas , Breitwieser Matthias , Vierrath Severin
Published: October 2022

The electrochemical reduction of CO2 is a pivotal technology for the defossilization of the chemical industry. Although pilot-scale electrolyzers exist, water management and salt precipitation remain a major hurdle to long-term operation. In this work, we present high-resolution neutron imaging (6 μm) of a zero-gap CO2 electrolyzer to uncover water distribution and salt precipitation under application-relevant operating conditions (200 mA cm−2 at a cell voltage of 2.8 V with a Faraday efficiency for CO of 99%). Precipitated salts penetrating the cathode gas diffusion layer can be observed, which are believed to block the CO2 gas transport and are therefore the major cause for the commonly observed decay in Faraday efficiency. Neutron imaging further shows higher salt accumulation under the cathode channel of the flow field compared to the land.
Maintenance of neurotransmitter identity by Hox proteins through a homeostatic mechanism
Authors: Feng Weidong , Destain Honorine , Smith Jayson J. , Kratsios Paschalis
Published: October 2022

Hox transcription factors play fundamental roles during early patterning, but they are also expressed continuously, from embryonic stages through adulthood, in the nervous system. However, the functional significance of their sustained expression remains unclear. In C. elegans motor neurons (MNs), we find that LIN-39 (Scr/Dfd/Hox4-5) is continuously required during post-embryonic life to maintain neurotransmitter identity, a core element of neuronal function. LIN-39 acts directly to co-regulate genes that define cholinergic identity (e.g., unc-17/VAChT, cho-1/ChT). We further show that LIN-39, MAB-5 (Antp/Hox6-8) and the transcription factor UNC-3 (Collier/Ebf) operate in a positive feedforward loop to ensure continuous and robust expression of cholinergic identity genes. Finally, we identify a two-component design principle for homeostatic control of Hox gene expression in adult MNs: Hox transcriptional autoregulation is counterbalanced by negative UNC-3 feedback. These findings uncover a noncanonical role for Hox proteins during post-embryonic life, critically broadening their functional repertoire from early patterning to the control of neurotransmitter identity.
Structural basis for recognition of antihistamine drug by human histamine receptor
Authors: Peng Xueqian , Yang Linlin , Liu Zixuan , Lou Siyi , Mei Shiliu , Li Meiling , Chen Zhong , Zhang Haitao
Published: October 2022

The histamine receptors belong to the G protein-coupled receptor (GPCR) superfamily, and play important roles in the regulation of histamine and other neurotransmitters in the central nervous system, as potential targets for the treatment of neurologic and psychiatric disorders. Here we report the crystal structure of human histamine receptor H3R bound to an antagonist PF-03654746 at 2.6 Å resolution. Combined with the computational and functional assays, our structure reveals binding modes of the antagonist and allosteric cholesterol. Molecular dynamic simulations and molecular docking of different antihistamines further elucidate the conserved ligand-binding modes. These findings are therefore expected to facilitate the structure-based design of novel antihistamines.
Essential role of TMPRSS2 in SARS-CoV-2 infection in murine airways
Authors: Iwata-Yoshikawa Naoko , Kakizaki Masatoshi , Shiwa-Sudo Nozomi , Okura Takashi , Tahara Maino , Fukushi Shuetsu , Maeda Ken , Kawase Miyuki , Asanuma Hideki , Tomita Yuriko , Takayama Ikuyo , Matsuyama Shutoku , Shirato Kazuya , Suzuki Tadaki , Nagata Noriyo , Takeda Makoto
Published: October 2022

In cultured cells, SARS-CoV-2 infects cells via multiple pathways using different host proteases. Recent studies have shown that the furin and TMPRSS2 (furin/TMPRSS2)-dependent pathway plays a minor role in infection of the Omicron variant. Here, we confirm that Omicron uses the furin/TMPRSS2-dependent pathway inefficiently and enters cells mainly using the cathepsin-dependent endocytosis pathway in TMPRSS2-expressing VeroE6/TMPRSS2 and Calu-3 cells. This is the case despite efficient cleavage of the spike protein of Omicron. However, in the airways of TMPRSS2-knockout mice, Omicron infection is significantly reduced. We furthermore show that propagation of the mouse-adapted SARS-CoV-2 QHmusX strain and human clinical isolates of Beta and Gamma is reduced in TMPRSS2-knockout mice. Therefore, the Omicron variant isn’t an exception in using TMPRSS2 in vivo, and analysis with TMPRSS2-knockout mice is important when evaluating SARS-CoV-2 variants. In conclusion, this study shows that TMPRSS2 is critically important for SARS-CoV-2 infection of murine airways, including the Omicron variant.
Using former carers’ expertise in peer support for carers of people with Parkinson’s Disease
Authors: Geerlings Angelika D. , Meinders Marjan J. , Bloem Bastiaan R. , van der Marck Marjolein A.
Published: October 2022

Informal carers gain unique experience and knowledge when caring for a loved person. However, this knowledge often remains unused after their loved one with Parkinson’s disease (PD) has passed away. Hence, two opportunities are currently being missed: sharing this unique experience could support current informal carers and offer the bereaved former carers the option to continue to fulfil a meaningful role. This study aimed to identify the unmet needs of current carers, and to examine the interest, willingness and requirements of both current and former carers for peer-to-peer support. Data were collected from August 2020 to February 2021 through questionnaires examining (1) resources and needs for support; (2) topics for support and advice; and (3) preferences for peer-to-peer initiatives. Open questions were analyzed thematically, after open coding. In total, 141 current and 15 former informal carers participated. Current carers were mainly women (68%) and partner of a person with PD (86%). Former carers were mainly women (80%) who had cared for a partner or parent (53%; 47%) with PD. Almost half of the current carers expressed need for additional support in finding balance, changing relationships, and learning how to cope with lack of emotions and motivation. Half of the carers were positive about the opportunity to exchange experiences and knowledge with former carers. Willingness among former carers for providing peer-to-peer support was high (87%). In both groups, having a degree of commonality with peers was considered an essential requirement. These findings provide guidance for developing peer-to-peer support programs, incorporating former carers.
The impact of bilateral injuries on the pathophysiology and functional outcomes of volumetric muscle loss
Authors: Dolan Connor P. , Clark Andrew R. , Motherwell Jessica M. , Janakiram Naveena B. , Valerio Michael S. , Dearth Christopher L. , Goldman Stephen M.
Published: October 2022

Volumetric muscle loss (VML)—defined as the irrecoverable loss of skeletal muscle tissue with associated persistent functional deficits—is among the most common and highly debilitating combat-related extremity injuries. This is particularly true in cases of severe polytrauma wherein multiple extremities may be involved as a result of high energy wounding mechanisms. As such, significant investment and effort has been made toward developing a clinically viable intervention capable of restoring the form and function of the affected musculature. While these investigations conducted to date have varied with respect to the species, breed, and sex of the chosen pre-clinical in-vivo model system, the majority of these studies have been performed in unilateral injury models, an aspect which may not fully exemplify the clinical representation of the multiply injured patient. Furthermore, while various components of the basal pathophysiology of VML (e.g., fibrosis and inflammation) have been investigated, relatively little effort has focused on how the pathophysiology and efficacy of pro-regenerative technologies is altered when there are multiple VML injuries. Thus, the purpose of this study was two-fold: (1) to investigate if/how the pathophysiology of unilateral VML injuries differs from bilateral VML injuries and (2) to interrogate the effect of bilateral VML injuries on the efficacy of a well-characterized regenerative therapy, minced muscle autograft (MMG). In contrast to our hypothesis, we show that bilateral VML injuries exhibit a similar systemic inflammatory response and improved muscle functional recovery, compared to unilateral injured animals. Furthermore, MMG treatment was found to only be effective at promoting an increase in functional outcomes in unilateral VML injuries. The findings presented herein add to the growing knowledge base of the pathophysiology of VML, and, importantly, reiterate the importance of comprehensively characterizing preclinical models which are utilized for early-stage screening of putative therapies as they can directly influence the translational research pipeline.
GABB: A global dataset of alpine breeding birds and their ecological traits
Authors: de Zwaan Devin R. , Scridel Davide , Altamirano Tomás A. , Gokhale Pranav , Kumar R. Suresh , Sevillano-Ríos Steven , Barras Arnaud G. , Arredondo-Amezcua Libertad , Asefa Addisu , Carrillo Ricardo A. , Green Ken , Gutiérrez-Chávez Carlos A. , Lehikoinen Aleksi , Li Shaobin , Lin Ruey-Shing , Norment Christopher J. , Oswald Krista N. , Romanov Alexey A. , Salvador Julio , Weston Kerry A. , Martin Kathy
Published: October 2022

Alpine ecosystems represent varied climates and vegetation structures globally, with the potential to support rich and functionally diverse avian communities. High mountain habitats and species are under significant threat from climate change and other anthropogenic factors. Yet, no global database of alpine birds exists, with most mountain systems lacking basic information on species breeding in alpine habitats, their status and trends, or potential cryptic diversity (i.e., sub-species distributions). To address these critical knowledge gaps, we combined published literature, regional monitoring schemes, and expert knowledge from often inaccessible, data-deficient mountain ranges to develop a global list of alpine breeding bird species with their associated distributions and select ecological traits. This dataset compiles alpine breeding records for 1,310 birds, representing 12.0% of extant species and covering all major mountain regions across each continent, excluding Antarctica. The Global Alpine Breeding Bird dataset (GABB) is an essential resource for research on the ecological and evolutionary factors shaping alpine communities, as well as documenting the value of these high elevation, climate-sensitive habitats for conserving biodiversity.