bluuebunny/crossref_metadata_2025 huggingface dataset:
Web and social media searches highlight menstrual irregularities as a global concern in COVID-19 vaccinations
Authors: Katz Ariel , Tepper Yoav , Birk Ohad , Eran Alal
Published: October 2022

Delineation of public concerns that prevent vaccine compliance is a major step in generating assurances and enhancing the success of COVID-19 prevention programs. We therefore sought to identify public concerns associated with COVID-19 vaccines, as reflected by web and social media searches, with a focus on menstrual irregularities. We used trajectory analyses of web and social media search data in combination with global COVID-19 data to reveal time-dependent correlations between vaccination rates and the relative volume of vaccine and period related searches. A surge of period and vaccine related Google searches followed the introduction of Covid vaccines around the world, and the commencement of vaccination programs in English speaking countries and across the United States. The relative volume of searches such as “Covid vaccine menstrual irregularities”, “Covid vaccine menstrual period”, “Pfizer vaccine menstruation”, and “Moderna vaccine menstruation” was each significantly correlated with vaccination rates (Spearman r = 0.42–0.88, P = 4.33 × 10–34–1.55 × 10–5), and significantly different before and after the introduction of Covid vaccines (Mann–Whitney P = 2.00 × 10–21–7.10 × 10–20). TikTok users were more engaged in period problems in 2021 than ever before. International, national, and state-level correlations between COVID-19 vaccinations and online activity demonstrate a global major concern of vaccine-related menstrual irregularities. Whether it is a potential side effect or an unfounded worry, monitoring of web and social media activity could reveal the public perception of COVID-19 prevention efforts, which could then be directly addressed and translated into insightful public health strategies.
Multi-species occupancy modeling suggests interspecific interaction among the three ungulate species
Authors: Singh Hemant , Sharief Amira , Joshi Bheem Dutt , Kumar Vineet , Mukherjee Tanoy , Chandra Kailash , Bhardwaj Nitin , Thakur Mukesh , Sharma Lalit Kumar
Published: October 2022

Species with sympatric distribution influence ecosystem dynamics and are impacted by the presence of other co-existing species. Assessing the coexistence and the role of interspecific interactions with the landscape variables is necessary to know the species co-occurrence in space. In the Indian Himalayan region, such studies are completely lacking due to limited efforts being made, mainly because of complex terrains and inaccessible landscape features. We used camera trapping and sign survey in a multi-species occupancy framework to understand the influence of environmental variables on occupancy and detection probability of species-specific and pair-wise interaction of the three ungulates in Uttarkashi. Our results concluded that individual species' occupancy probabilities were related both to the environmental variables and the presence or absence of other interacting species. Our top model showed evidence of interspecific interaction among species pairs, and the occupancy probability of species one varied in the presence or absence of another species. The overall activity patterns were similar among all the three species and were found active throughout the day. The activity overlap between sambar—barking deer (Dhat1 value = 0.85) was considerably higher than barking deer—goral (Dhat1 value = 0.78). The findings of the present study will be useful for the conservation and management of ungulates in the Indian Himalayan and adjoining regions.
A pressure driven electric energy generator exploiting a micro- to nano-scale glass porous filter with ion flow originating from water
Authors: Tanaka Yo , Amaya Satoshi , Funano Shun-ichi , Sugawa Hisashi , Nagafuchi Wataru , Ito Yuri , Aishan Yusufu , Liu Xun , Kamamichi Norihiro , Yalikun Yaxiaer
Published: October 2022

We demonstrated a pressure driven energy harvesting device using water and that features a glass filter with porous channels. We employed powder sintering to fabricate the glass filter (2 cm diameter, 3 mm thickness) by packing a powder of borosilicate glass particles into a carbon mold and then thermally fusing this at 700°C under pressure. In constant flow rate experiment, the optimum average pore radius of the filter for power generation was 12 μm. Using this filter, power of 3.8 mW (27 V, 0.14 mA, 0.021% energy efficiency) was generated at a water flow speed of 50 mm/s. In constant pressure experiment, a power generator was equipped with a foot press unit with a 60 kg weight (830 kPa) and 50 mL of water. The optimum average pore radius for power generation in this experiment was 12 μm and power of 4.8 mW (18 V, 0.26 mA, 0.017% energy efficiency) was generated with 1.7 s duration. This was enough power for direct LED lighting and the capacitors could store enough energy to rotate a fan and operate a wireless communicator. Our pressure driven device is suitable for energy harvesting from slow movements like certain human physiological functions, e.g. walking.
Environmentally friendly, highly efficient, and large stokes shift-emitting ZnSe:Mn2+/ZnS core/shell quantum dots for luminescent solar concentrators
Authors: Byambasuren Nyamsuren , Hong A-Ra , Lee Woo-Young , Byun Ji Young , Kang Gumin , Ko Hyungduk , Jang Ho Seong
Published: October 2022

In this study, heavy-metal-free orange light-emitting ZnSe:Mn2+/ZnS doped-core/shell (d-C/S) quantum dots (QDs) were synthesized using a nucleation doping strategy. To synthesize high quality d-C/S QDs with high photoluminescence (PL) quantum yield (QY), the Mn2+ concentration was optimized. The resulting ZnSe:Mn2+(5%)/ZnS d-C/S QDs showed a high PL QY of 83.3%. The optical properties of the synthesized QDs were characterized by absorption and PL spectroscopy. Their structural and compositional properties were studied by X-ray diffraction, transmission electron microscopy, and energy dispersive X-ray spectroscopy. After doping Mn2+ into a ZnSe core, the ZnSe:Mn2+/ZnS d-C/S QDs showed a large Stokes shift of 170 nm. The ZnSe:Mn2+/ZnS d-C/S QDs were embedded in a poly(lauryl methacrylate) (PLMA) polymer matrix and the ZnSe:Mn2+/ZnS-based polymer film was fabricated. The fabricated ZnSe:Mn2+/ZnS-PLMA film was highly transparent in the visible spectral region (transmittance > 83.8% for λ ≥ 450 nm) and it exhibited bright orange light under air mass (AM) 1.5G illumination using a solar simulator. The optical path-dependent PL measurement of the ZnSe:Mn2+/ZnS-PLMA film showed no PL band shift and minimal PL decrease under variation of excitation position. These results indicate that the highly efficient and large Stokes shift-emitting ZnSe:Mn2+/ZnS QDs are promising for application to luminescent solar concentrators.
Chill coma recovery of Ceratitis capitata adults across the Northern Hemisphere
Authors: Moraiti Cleopatra A. , Verykouki Eleni , Papadopoulos Nikos T.
Published: October 2022

The Mediterranean fruit fly,Ceratitis capitata(Diptera: Tephritidae), is an invasive pest, that is currently expanding its geographic distribution from the Mediterranean coasts to more temperate areas of Europe. Given that low temperature is a primary determinant of insect species’ range boundaries especially in the Northern Hemisphere with pronounced seasonality, we used chill coma recovery time for assessing latitudinal clines in basal chill tolerance ofC. capitataadults. We selected six populations obtained from areas with broad climatic variability based on the main bioclimatic variables of temperature and precipitation, spanning a latitudinal range of about 19° from Middle East to Central Europe. Adults were exposed to 0 °C for 4 h, and time to regain the typical standing position of a fly at 25 °C were recorded. The post-stress survival after a period of 8 days was also recorded. Results revealed that adults from Israel and Austria were less chill tolerant than those from Greece, resulting in curvilinear trends with latitude. Analysis of macroclimatic conditions revealed combined effects of latitude (as a proxy of photoperiod) and macroclimatic conditions on chill coma recovery time. Nonetheless, there was not a deleterious effect on post-recovery survival, except for flies obtained from the northern most point (Vienna, Austria). Overall, it seems that evolutionary patterns of basal chill coma recovery time ofC. capitataadults are driven mainly by local climatic variability.
Determinable and interpretable network representation for link prediction
Authors: Deng Yue
Published: October 2022

As an intuitive description of complex physical, social, or brain systems, complex networks have fascinated scientists for decades. Recently, to abstract a network’s topological and dynamical attributes, network representation has been a prevalent technique, which can map a network or substructures (like nodes) into a low-dimensional vector space. Since its mainstream methods are mostly based on machine learning, a black box of an input-output data fitting mechanism, the learned vector’s dimension is indeterminable and the elements are not interpreted. Although massive efforts to cope with this issue have included, say, automated machine learning by computer scientists and learning theory by mathematicians, the root causes still remain unresolved. Consequently, enterprises need to spend enormous computing resources to work out a set of model hyperparameters that can bring good performance, and business personnel still finds difficulties in explaining the learned vector’s practical meaning. Given that, from a physical perspective, this article proposes two determinable and interpretable node representation methods. To evaluate their effectiveness and generalization, this article proposes Adaptive and Interpretable ProbS (AIProbS), a network-based model that can utilize node representations for link prediction. Experimental results showed that the AIProbS can reach state-of-the-art precision beyond baseline models on some small data whose distribution of training and test sets is usually not unified enough for machine learning methods to perform well. Besides, it can make a good trade-off with machine learning methods on precision, determinacy (or robustness), and interpretability. In practice, this work contributes to industrial companies without enough computing resources but who pursue good results based on small data during their early stage of development and who require high interpretability to better understand and carry out their business.
Prediction of malignant lymph nodes in NSCLC by machine-learning classifiers using EBUS-TBNA and PET/CT
Authors: Guberina Maja , Herrmann Ken , Pöttgen Christoph , Guberina Nika , Hautzel Hubertus , Gauler Thomas , Ploenes Till , Umutlu Lale , Wetter Axel , Theegarten Dirk , Aigner Clemens , Eberhardt Wilfried E. E. , Metzenmacher Martin , Wiesweg Marcel , Schuler Martin , Karpf-Wissel Rüdiger , Santiago Garcia Alina , Darwiche Kaid , Stuschke Martin
Published: October 2022

Accurate determination of lymph-node (LN) metastases is a prerequisite for high precision radiotherapy. The primary aim is to characterise the performance of PET/CT-based machine-learning classifiers to predict LN-involvement by endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) in stage-III NSCLC. Prediction models for LN-positivity based on [18F]FDG-PET/CT features were built using logistic regression and machine-learning models random forest (RF) and multilayer perceptron neural network (MLP) for stage-III NSCLC before radiochemotherapy. A total of 675 LN-stations were sampled in 180 patients. The logistic and RF models identified SUVmax, the short-axis LN-diameter and the echelon of the considered LN among the most important parameters for EBUS-positivity. Adjusting the sensitivity of machine-learning classifiers to that of the expert-rater of 94.5%, MLP (P = 0.0061) and RF models (P = 0.038) showed lower misclassification rates (MCR) than the standard-report, weighting false positives and false negatives equally. Increasing the sensitivity of classifiers from 94.5 to 99.3% resulted in increase of MCR from 13.3/14.5 to 29.8/34.2% for MLP/RF, respectively. PET/CT-based machine-learning classifiers can achieve a high sensitivity (94.5%) to detect EBUS-positive LNs at a low misclassification rate. As the specificity decreases rapidly above that level, a combined test of a PET/CT-based MLP/RF classifier and EBUS-TBNA is recommended for radiation target volume definition.
Oral supplementation with selected Lactobacillus acidophilus triggers IL-17-dependent innate defense response, activation of innate lymphoid cells type 3 and improves colitis
Authors: Hrdý Jiří , Couturier-Maillard Aurélie , Boutillier Denise , Lapadatescu Carmen , Blanc Philippe , Procházka Jan , Pot Bruno , Ryffel Bernhard , Grangette Corinne , Chamaillard Mathias
Published: October 2022

Live biotherapeutic products constitute an emerging therapeutic approach to prevent or treat inflammatory bowel diseases. Lactobacillus acidophilus is a constituent of the human microbiota with probiotic potential, that is illustrated by improvement of intestinal inflammation and antimicrobial activity against several pathogens. In this study, we evaluated the immunomodulatory properties of the L. acidophilus strain BIO5768 at steady state and upon acute inflammation. Supplementation of naïve mice with BIO5768 heightened the transcript level of some IL-17 target genes encoding for protein with microbicidal activity independently of NOD2 signaling. Of these, the BIO5768-induced expression of Angiogenin-4 was blunted in monocolonized mice that are deficient for the receptor of IL-17 (but not for NOD2). Interestingly, priming of bone marrow derived dendritic cells by BIO5768 enhanced their ability to support the secretion of IL-17 by CD4+ T cells. Equally of importance, the production of IL-22 by type 3 innate lymphoid cells is concomitantly heightened in response to BIO5768. When administered alone or in combination with Bifidobacterium animalis spp. lactis BIO5764 and Limosilactobacillus reuteri, BIO5768 was able to alleviate at least partially intestinal inflammation induced by Citrobacter rodentium infection. Furthermore, BIO5768 was also able to improve colitis induced by 2,4,6-trinitrobenzene sulfonic acid (TNBS). In conclusion, we identify a new potential probiotic strain for the management of inflammatory bowel diseases, and provide some insights into its IL-17-dependent and independent mode of action.
Effect of pre-operative carbohydrate loading on aspiration risk evaluated with ultrasonography in type 2 diabetes patients: a prospective observational pilot study
Authors: Lee Seohee , Sohn Jin Young , Lee Ho-jin , Yoon Susie , Bahk Jae-Hyon , Kim Bo Rim
Published: October 2022

Owing to concerns about delayed gastric emptying or hyperglycemia, evidence is lacking regarding whether pre-operative carbohydrate loading can be routinely administered to patients with type 2 diabetes. The objective of this study was to determine the aspiration risk and gastric volume after pre-operative carbohydrate loading in patients with type 2 diabetes. A prospective, single-center, observational cohort study. The study was conducted at a tertiary teaching hospital in Seoul, Korea, from May 2020 to May 2021. Patients (n = 49) with type 2 diabetes underwent elective noncardiac surgery. All patients were administered carbohydrate loading two hours before surgery. Once in the operating room, they underwent gastric ultrasonography to determine gastric volume. The anesthesiologists monitored the patients' glucose concentrations during and after surgery. The primary outcome was the predicted risk of aspiration. The secondary outcomes were gastric volume, antral grade, satisfaction score, and perioperative glucose profile. Forty-nine patients were analyzed. All patients had a low risk of aspiration after carbohydrate loading, as follows: 33 (67.3%) patients classified as antral grade 0 and 16 (32.7%) patients classified as antral grade 1. The median time from carbohydrate drink ingestion to ultrasound examination was 120 min (IQR 115–139). After carbohydrate loading, the median gastric volume in the right-lateral position after carbohydrate loading was 2.64 ml (IQR 0.00–32.05). The mean glucose concentrations (SD) were 134 (24) mg/dl, 159 (37) mg/dl, 150 (32) mg/dl, and 165 (36) mg/dl at baseline, after induction, 30 min after surgery, and in the post anesthesia care unit, respectively. The median satisfaction score of the patients was 5 (IQR 4–5). Pre-operative carbohydrate loading may be feasible for patients with type 2 diabetes and without complications.

Trial registration: ClinicalTrials.gov (NCT04456166). Registered on 2 July 2020.
Mental distress and associated factors among college students in Kemisie district, Ethiopia
Authors: Siraji Aziza , Molla Asressie , Ayele Wolde Melese , Kebede Natnael
Published: October 2022

Mental health problems such as distress affect society in a non-differential fashion. In recent decades, mental distress is becoming a common health problem among students. In this regard, there is limited information about the problem available in Ethiopia. Therefore, this study aimed to determine the prevalence and associated factors of mental distress among college students in Kemisie district, Ethiopia. An institution-based cross-sectional study was conducted among 408 students from February 11 to 14 2020. A stratified sampling technique was used to select the study participants. Data were collected using a structured self-administered questionnaire. Self-reporting questionnaire (referred to as the SRQ-20) is a standardized questionnaire having 20-item questions and was used as a tool for mental distress. Appropriate descriptive statistics was done. A binary logistic regression model was used to identify factors associated with mental distress. An adjusted odds ratio with a 95% confidence interval was computed to determine the level of significance. Apvalue < 0.05 was used to declare the statistical significance of the variables. Prevalence of mental distress among students was 17.6% (95% CI 13.8–21.4%). Not having close friends (AOR = 3.61; 95% CI 1.61–8.14), attend religious programs (AOR = 0.23; 95% CI 0.14–0.53), conflict with friend (AOR = 3.07; 95% CI 1.44–6.33), not having pocket money (AOR = 2.72; 95% CI 1.27–25.80), ever use of Chat (AOR = 5.06; 95% CI 2.12–11.80), current use of Chat (AOR = 3.12; 95% CI 1.04–9.82), decreased grade than anticipated (AOR = 3.20; 95% CI 1.436–7.16), and low and moderate social support (AOR = 3.34; 95% CI 1.41–7.92) and (AOR = 1.47; 95% CI 1.08–5.68), respectively were statistically significantly associated factors of mental distress. The overall prevalence of mental distress among students in Kemisie district, Ethiopia was high. In Ethiopia, along with the current economic crisis and the absence of social support, the problem could be increased. Therefore, the mental health needs of the college students require attention with special emphasis on not having close friends, never attending religious programs, conflict with friends, absence of pocket money, students who use Khat, and those who have low social support.
A study on the impact of role stress on engineer intention to leave in Indian construction firms
Authors: Hazeen Fathima M. , Umarani C.
Published: October 2022

Construction jobs are stressful, and high employee turnover is one of the significant issues affecting the growth and development of construction firms worldwide. This study examines the relationship between role stress and intentions to leave, as well as the role of emotional exhaustion and job satisfaction as mediators in the role stress and intention to leave of engineers working in the construction sector. The sample of this study consists of three hundred and sixty engineers working in private construction firms across southern parts of India. The relationship between the study variables is examined using structural equation modeling. The result of the study reveals a significant positive relationship between role conflict and intention to leave, whereas the direct relationship between role ambiguity, role overload, and intention to leave is not significant. In terms of mediation, emotional exhaustion plays a significant mediator between all the components of role stress and intention to leave. At the same time, the role of job satisfaction is significant only between role ambiguity and intention to leave. Role ambiguity negatively influences job satisfaction, subsequently increasing engineers’ turnover intention. Emotional exhaustion caused due to role stress is identified as one of the significant predictors of engineers’ intention to leave. Thus, construction organizations should focus on redesigning construction jobs to reduce role stress and emotional exhaustion to retain engineers working with them.
Motif and conserved module analysis in DNA (promoters, enhancers) and RNA (lncRNA, mRNA) using AlModules
Authors: Aydinli Muharrem , Liang Chunguang , Dandekar Thomas
Published: October 2022

Nucleic acid motifs consist of conserved and variable nucleotide regions. For functional action, several motifs are combined to modules. The tool AIModules allows identification of such motifs including combinations of them and conservation in several nucleic acid stretches. AIModules recognizes conserved motifs and combinations of motifs (modules) allowing a number of interesting biological applications such as analysis of promoter and transcription factor binding sites (TFBS), identification of conserved modules shared between several gene families, e.g. promoter regions, but also analysis of shared and conserved other DNA motifs such as enhancers and silencers, in mRNA (motifs or regulatory elements e.g. for polyadenylation) and lncRNAs. The tool AIModules presented here is an integrated solution for motif analysis, offered as a Web service as well as downloadable software. Several nucleotide sequences are queried for TFBSs using predefined matrices from the JASPAR DB or by using one’s own matrices for diverse types of DNA or RNA motif discovery. Furthermore, AIModules can find TFBSs common to two or more sequences. Demanding high or low conservation, AIModules outperforms other solutions in speed and finds more modules (specific combinations of TFBS) than alternative available software. The application also searches RNA motifs such as polyadenylation site or RNA–protein binding motifs as well as DNA motifs such as enhancers as well as user-specified motif combinations (https://bioinfo-wuerz.de/aimodules/; alternative entry pages:https://aimodules.heinzelab.deorhttps://www.biozentrum.uni-wuerzburg.de/bioinfo/computing/aimodules). The application is free and open source whether used online, on-site, or locally.
Micro-expression recognition model based on TV-L1 optical flow method and improved ShuffleNet
Authors: Liu Yanju , Li Yange , Yi Xinhan , Hu Zuojin , Zhang Huiyu , Liu Yanzhong
Published: October 2022

Micro-expression is a kind of facial action that reflects the real emotional state of a person, and has high objectivity in emotion detection. Therefore, micro-expression recognition has become one of the research hotspots in the field of computer vision in recent years. Research with neural networks with convolutional structure is still one of the main methods of recognition. This method has the advantage of high operational efficiency and low computational complexity, but the disadvantage is its localization of feature extraction. In recent years, there are more and more plug-and-play self-attentive modules being used in convolutional neural networks to improve the ability of the model to extract global features of the samples. In this paper, we propose the ShuffleNet model combined with a miniature self-attentive module, which has only 1.53 million training parameters. First, the start frame and vertex frame of each sample will be taken out, and its TV-L1 optical flow features will be extracted. After that, the optical flow features are fed into the model for pre-training. Finally, the weights obtained from the pre-training are used as initialization weights for the model to train the complete micro-expression samples and classify them by the SVM classifier. To evaluate the effectiveness of the method, it was trained and tested on a composite dataset consisting of CASMEII, SMIC, and SAMM, and the model achieved competitive results compared to state-of-the-art methods through cross-validation of leave-one-out subjects.
PM2.5 forecasting for an urban area based on deep learning and decomposition method
Authors: Zaini Nur’atiah , Ean Lee Woen , Ahmed Ali Najah , Abdul Malek Marlinda , Chow Ming Fai
Published: October 2022

Rapid growth in industrialization and urbanization have resulted in high concentration of air pollutants in the environment and thus causing severe air pollution. Excessive emission of particulate matter to ambient air has negatively impacted the health and well-being of human society. Therefore, accurate forecasting of air pollutant concentration is crucial to mitigate the associated health risk. This study aims to predict the hourly PM2.5 concentration for an urban area in Malaysia using a hybrid deep learning model. Ensemble empirical mode decomposition (EEMD) was employed to decompose the original sequence data of particulate matter into several subseries. Long short-term memory (LSTM) was used to individually forecast the decomposed subseries considering the influence of air pollutant parameters for 1-h ahead forecasting. Then, the outputs of each forecast were aggregated to obtain the final forecasting of PM2.5 concentration. This study utilized two air quality datasets from two monitoring stations to validate the performance of proposed hybrid EEMD-LSTM model based on various data distributions. The spatial and temporal correlation for the proposed dataset were analysed to determine the significant input parameters for the forecasting model. The LSTM architecture consists of two LSTM layers and the data decomposition method is added in the data pre-processing stage to improve the forecasting accuracy. Finally, a comparison analysis was conducted to compare the performance of the proposed model with other deep learning models. The results illustrated that EEMD-LSTM yielded the highest accuracy results among other deep learning models, and the hybrid forecasting model was proved to have superior performance as compared to individual models.
Waterbody loss due to urban expansion of large Chinese cities in last three decades
Authors: Xiao Wu , Chen Wenqi , Yue Wenze , Mu Jingxuan , Xu Jianpeng
Published: October 2022

Urban waterbodies are one of the most pertinent issues involved in multiple aspects of Sustainable Development Goals (SDGs). However, waterbodies in large Chinese cities are highly vulnerable to urban-land expansion, which is mostly due to economic development, population growth, and rural–urban migration. In this work, we selected 159 Chinese cities of over one million in population to investigate the encroachment on waterbodies due to rapid urbanization from 1990 to 2018. Overall, 20.6% of natural waterbody area was lost during this period to urban expansion, and this fraction varied from city to city which was related to waterbody abundance. With the acceleration of urbanization, waterbody occupation is becoming more serious (P < 0.01). However, in all cities, this encroachment has eased since 2010, which justifies the effective implementation of national-scale policies to conserve urban waterbodies. Meanwhile, gains have occurred during urbanization, in addition to the loss of waterbodies. Especially, cities lacking waterbody placed a greater emphasis on ecological factors, whose urban waterbody areas showed an increasing trend. In the future, ecological resources, including waterbody, should be considered in urban planning to provide reasonable protection to waterbodies in the quest for urban sustainability.
Role of the E3 ubiquitin-ligase Hakai in intestinal inflammation and cancer bowel disease
Authors: Roca-Lema Daniel , Quiroga Macarena , Khare Vineeta , Díaz-Díaz Andrea , Barreiro-Alonso Aida , Rodríguez-Alonso Andrea , Concha Ángel , Romay Gabriela , Cerdán M. Esperanza , Gasche Christoph , Figueroa Angélica
Published: October 2022

The E3 ubiquitin-ligases are important for cellular protein homeostasis and their deregulation is implicated in cancer. The E3 ubiquitin-ligase Hakai is involved in tumour progression and metastasis, through the regulation of the tumour suppressor E-cadherin. Hakai is overexpressed in colon cancer, however, the implication in colitis-associated cancer is unknown. Here, we investigated the potential role of Hakai in intestinal inflammation and cancer bowel disease. Several mouse models of colitis and associated cancer were used to analyse Hakai expression by immunohistochemistry. We also analysed Hakai expression in patients with inflamed colon biopsies from ulcerative colitis and Crohn's disease. By Hakai interactome analysis, it was identified Fatty Acid Synthase (FASN) as a novel Hakai-interacting protein. Moreover, we show that Hakai induces FASN ubiquitination and degradation via lysosome, thus regulating FASN-mediated lipid accumulation. An inverse expression of FASN and Hakai was detected in inflammatory AOM/DSS mouse model. In conclusion, Hakai regulates FASN ubiquitination and degradation, resulting in the regulation of FASN-mediated lipid accumulation, which is associated to the development of inflammatory bowel disease. The interaction between Hakai and FASN may be an important mechanism for the homeostasis of intestinal barrier function and in the pathogenesis of this disease.
Mitochondrial biogenesis, telomere length and cellular senescence in Parkinson’s disease and Lewy body dementia
Authors: Asghar Muhammad , Odeh Amani , Fattahi Ahmad Jouni , Henriksson Alexandra Edwards , Miglar Aurelie , Khosousi Shervin , Svenningsson Per
Published: October 2022

Progressive age is the single major risk factor for neurodegenerative diseases. Cellular aging markers during Parkinson’s disease (PD) have been implicated in previous studies, however the majority of studies have investigated the association of individual cellular aging hallmarks with PD but not jointly. Here, we have studied the association of PD with three aging hallmarks (telomere attrition, mitochondrial dysfunction, and cellular senescence) in blood and the brain tissue. Our results show that PD patients had 20% lower mitochondrial DNA copies but 26% longer telomeres in blood compared to controls. Moreover, telomere length in blood was positively correlated with medication (Levodopa Equivalent Daily Dose, LEDD) and disease duration. Similar results were found in brain tissue, where patients with Parkinson’s disease (PD), Parkinson’s disease dementia (PDD) and Dementia with Lewy Bodies (DLB) showed (46–95%) depleted mtDNA copies, but (7–9%) longer telomeres compared to controls. In addition, patients had lower mitochondrial biogenesis (PGC-1α and PGC-1β) and higher load of a cellular senescence marker in postmortem prefrontal cortex tissue, with DLB showing the highest effect among the patient groups. Our results suggest that mitochondrial dysfunction (copy number and biogenesis) in blood might be a valuable marker to assess the risk of PD. However, further studies with larger sample size are needed to evaluate these findings.
Study of a new method for the instant preparation of ice particles in ice abrasive air jet
Authors: Li Zhiping , Zhu Ying , Liu Yong , Cao Chenxu , Wu Jiaojiao , Huang Fei
Published: October 2022

The ice abrasive air jet is a clean surface treatment technology, which currently has limitations such as high energy consumption, uncontrollable particle size and hardness. Realizing the instant preparation and utilization of ice particles are crucial for solving the energy consumption problem. This paper based on the icing principle of heterogeneous nucleation, proposed a new method of ice making, the heat transfer mechanism of low temperature droplets was studied, and the method was proved to be feasible. Using the FLUENT solidification and melting model combined with the VOF model to calculate the freezing process of droplets, the effects of droplet particle size, initial temperature, and wall temperature on the freezing time were analyzed, and the calculation equation of the freezing time was determined, which was corrected by the icing test results. The results showed that the outside of the droplet freezes first, the liquid–solid boundary is parabolic, and the parabolic concavity increases with time and droplet size. In the freezing process, the larger the droplet size, the longer the droplet phase transition time; the higher the droplet initial temperature, the longer it took to reach the phase transition; the higher the wall temperature, the longer the ice formation time.
Establishment of a novel mouse model of adenomyosis suitable for longitudinal and quantitative analysis and perinatal outcome studies
Authors: Elsherbini Mohammed , Koga Kaori , Hiraoka Takehiro , Kumasawa Keiichi , Maki Eiko , Satake Erina , Taguchi Ayumi , Makabe Tomoko , Takeuchi Arisa , Izumi Gentaro , Takamura Masashi , Harada Miyuki , Hirata Tetsuya , Hirota Yasushi , Wada-Hiraike Osamu , Osuga Yutaka
Published: October 2022

The purpose of this study was to establish a novel mouse model of adenomyosis suitable for longitudinal and quantitative analyses and perinatal outcome studies. Using a 30 G needle, the entire uterine wall of one horn was mechanically punctured at a frequency of 100 times/1 cm (adenomyosis horn). The other horn was left unpunctured (control horn). Balb/c mice were sacrificed on day 14 (D14) or day 65 (D65) (n = 3 each). The uterus was fixed, paraffin-embedded, sliced, and stained. Lesions were detected and counted, and their volumes were measured. Cell proliferation and fibrosis were assessed by Ki67 and Masson’s Trichrome staining, respectively. Blood vessels were detected using CD31 immunostaining. Some of the mice (n = 4), were mated and the date of delivery, litter size, number of implantations, and number and volume of postpartum lesions were measured. The number of lesions per horn did not differ between D14 and D65. The volume of the entire lesion was significantly greater on D65 than on D14 (p < 0.0001). The volume of the epithelial part of the lesion was significantly greater in D65 (p < 0.0001). The volume of the stromal part of the lesion was also greater on D65 (p < 0.0001). The percentage of Ki67 positive cells in the epithelial part of the lesion was significantly higher on D14 (p < 0.05). In contrast, the percentage of Ki67-positive cells in the stromal part was significantly higher on D65 (p < 0.01). Vascular density in the lesions was higher in on D65 (p < 0.05). The percentage of fibrotic area was significantly higher on D65 (p < 0.01). The date of delivery was slightly earlier than that reported for healthy mice of the same strain. The litter size was smaller than that reported in previous research. The number of implantation sites did not differ between the control and the adenomyosis horn. The number and volume of lesions did not differ between the non-pregnant and postpartum groups. This model can be applied to evaluate the pathogenesis of adenomyosis, validate the efficacy of therapeutic agents, and evaluate the effect of adenomyosis on pregnancy and vice versa.
A mouse model of hepatic encephalopathy: bile duct ligation induces brain ammonia overload, glial cell activation and neuroinflammation
Authors: Claeys Wouter , Van Hoecke Lien , Geerts Anja , Van Vlierberghe Hans , Lefere Sander , Van Imschoot Griet , Van Wonterghem Elien , Ghesquière Bart , Vandenbroucke Roosmarijn E. , Van Steenkiste Christophe
Published: October 2022

Hepatic encephalopathy (HE) is a common complication of chronic liver disease, characterized by an altered mental state and hyperammonemia. Insight into the brain pathophysiology of HE is limited due to a paucity of well-characterized HE models beyond the rat bile duct ligation (BDL) model. Here, we assess the presence of HE characteristics in the mouse BDL model. We show that BDL in C57Bl/6j mice induces motor dysfunction, progressive liver fibrosis, liver function failure and hyperammonemia, all hallmarks of HE. Swiss mice however fail to replicate the same phenotype, underscoring the importance of careful strain selection. Next, in-depth characterisation of metabolic disturbances in the cerebrospinal fluid of BDL mice shows glutamine accumulation and transient decreases in taurine and choline, indicative of brain ammonia overload. Moreover, mouse BDL induces glial cell dysfunction, namely microglial morphological changes with neuroinflammation and astrocyte reactivity with blood–brain barrier (BBB) disruption. Finally, we identify putative novel mechanisms involved in central HE pathophysiology, like bile acid accumulation and tryptophan–kynurenine pathway alterations. Our study provides the first comprehensive evaluation of a mouse model of HE in chronic liver disease. Additionally, this study further underscores the importance of neuroinflammation in the central effects of chronic liver disease.
Comparative effectiveness of neutralising monoclonal antibodies in high risk COVID-19 patients: a Bayesian network meta-analysis
Authors: McConnell David , Harte Marie , Walsh Cathal , Murphy Desmond , Nichol Alistair , Barry Michael , Adams Roisin
Published: October 2022

The purpose of this work was to review and synthesise the evidence on the comparative effectiveness of neutralising monoclonal antibody (nMAB) therapies in individuals exposed to or infected with SARS-CoV-2 and at high risk of developing severe COVID-19. Outcomes of interest were mortality, healthcare utilisation, and safety. A rapid systematic review was undertaken to identify and synthesise relevant RCT evidence using a Bayesian Network Meta-Analysis. Relative treatment effects for individual nMABs (compared with placebo and one another) were estimated. Pooled effects for the nMAB class compared with placebo were estimated. Relative effects were combined with baseline natural history models to predict the expected risk reductions per 1000 patients treated. Eight articles investigating four nMABs (bamlanivimab, bamlanivimab/etesevimab, casirivimab/imdevimab, sotrovimab) were identified. All four therapies were associated with a statistically significant reduction in hospitalisation (70–80% reduction in relative risk; absolute reduction of 35–40 hospitalisations per 1000 patients). For mortality, ICU admission, and invasive ventilation, the risk was lower for all nMABs compared with placebo with moderate to high uncertainty due to small event numbers. Rates of serious AEs and infusion reactions were comparable between nMABs and placebo. Pairwise comparisons between nMABs were typically uncertain, with broadly comparable efficacy. In conclusion, nMABs are effective at reducing hospitalisation among infected individuals at high-risk of severe COVID-19, and are likely to reduce mortality, ICU admission, and invasive ventilation rates; the effect on these latter outcomes is more uncertain. Widespread vaccination and the emergence of nMAB-resistant variants make the generalisability of these results to current patient populations difficult.
Vibrational characteristics of aluminum–phosphate compounds by an experimental and theoretical approach
Authors: Goj Pawel , Handke Bartosz , Stoch Pawel
Published: October 2022

Aluminum phosphates are materials with relatively wide potential applications in many industries. The vibrational features of selected compounds were established on Raman and infrared spectroscopy. The experimentally determined spectra are compared to those calculated by ab initio methods. This gives a unique possibility of a proper assignment of the experimental spectral features to specific modes of vibration. In the results, it was evidenced that the spectra are characterized by two specific intense bands in the mid- and high-frequency range due to the P–O–P and P–O bonds in [PO4] tetrahedron vibrations. The position of the high-frequency band is related to the number of bridging oxygen atoms connecting [PO4] tetrahedrons in the unit cell. Additionally, the differences in the spectra were evidenced as a result of different polymorphic forms of the selected compounds. Therefore, the results may be useful in determining the phase composition of polyphase materials or structural features of aluminum–phosphate glasses and glass–ceramic materials.
The LRP1/CD91 ligands, tissue-type plasminogen activator, α2-macroglobulin, and soluble cellular prion protein have distinct co-receptor requirements for activation of cell-signaling
Authors: Mantuano Elisabetta , Azmoon Pardis , Banki Michael A. , Gunner Cory B. , Gonias Steven L.
Published: October 2022

LDL Receptor-related Protein-1 (LRP1/CD91) binds diverse ligands, many of which activate cell-signaling. Herein, we compared three LRP1 ligands that inhibit inflammatory responses triggered by lipopolysaccharide (LPS), including: enzymatically-inactive tissue-type plasminogen activator (EI-tPA); activated α2-macroglobulin (α2M); and S-PrP, a soluble derivative of nonpathogenic cellular prion protein (PrPC). In bone marrow-derived macrophages, the N-methyl-D-aspartate receptor was essential for all three LRP1 ligands to activate cell-signaling and inhibit LPS-induced cytokine expression. Intact lipid rafts also were essential. Only α2M absolutely required LRP1. LRP1 decreased the EI-tPA concentration required to activate cell-signaling and antagonize LPS but was not essential, mimicking its role as a S-PrP co-receptor. Membrane-anchored PrPC also functioned as a co-receptor for EI-tPA and α2M, decreasing the ligand concentration required for cell-signaling and LPS antagonism; however, when the concentration of EI-tPA or α2M was sufficiently increased, cell-signaling and LPS antagonism occurred independently of PrPC. S-PrP is the only LRP1 ligand in this group that activated cell-signaling independently of membrane-anchored PrPC. EI-tPA, α2M, and S-PrP inhibited LPS-induced LRP1 shedding from macrophages, a process that converts LRP1 into a pro-inflammatory product. Differences in the co-receptors required for anti-inflammatory activity may explain why LRP1 ligands vary in ability to target macrophages in different differentiation states.
Deep learning-based classification for lung opacities in chest x-ray radiographs through batch control and sensitivity regulation
Authors: Chang I-Yun , Huang Teng-Yi
Published: October 2022

In this study, we implemented a system to classify lung opacities from frontal chest x-ray radiographs. We also proposed a training method to address the class imbalance problem presented in the dataset. We participated in the Radiological Society of America (RSNA) 2018 Pneumonia Detection Challenge and used the datasets provided by the RSNA for further research. Using convolutional neural networks, we implemented a training procedure termed batch control to manipulate the data distribution of positive and negative cases in each training batch. The batch control method regulated and stabilized the performance of the deep-learning models, allowing the adaptive sensitivity of the network models to meet the specific application. The convolutional neural network is practical for classifying lung opacities on chest x-ray radiographs. The batch control method is advantageous for sensitivity regulation and optimization for class-unbalanced datasets.
Entropy generation minimization of higher-order endothermic/exothermic chemical reaction with activation energy on MHD mixed convective flow over a stretching surface
Authors: Sharma B. K. , Gandhi Rishu , Mishra Nidhish K , Al-Mdallal Qasem M.
Published: October 2022

The present investigation aims to analyze higher-order endothermic/exothermic chemical reactions with activation energy by considering thermophoresis and Brownian motion effects on MHD mixed convective flow across a vertical stretching surface. The influence of velocity slip, thermal slip, and concentration slip along with an inclined external magnetic field is also considered. The governing coupled non-linear partial differential equations are transformed into ordinary differential equations using similarity transformation. The resulting system of non-linear ODEs is solved by the Newton Raphson shooting technique using the RK-4 algorithm. The impact of various physical parameters discovered in the problem viz. endothermic/exothermic reaction variable, thermophoresis parameter, activation energy parameter, Brownian motion parameter, chemical reaction parameter have been analyzed on velocity profile, temperature profile, and concentration profile. The effects of these parameters on skin-friction coefficient, Nusselt number, and Sherwood number are displayed in tabular form as well as surface plots. The impact of various physical parameters that appeared in the entropy generation is shown using surface and contour plots. The numerical findings are in good agreement with the previously published results. It is observed that an increment in thermophoresis and Brownian motion parameters results in a declination of entropy profiles, whereas an increment in Bejan number profiles is observed. A small region near the surface exhibits an inclination in concentration profiles with an increase in the order of the chemical reaction. In contrast, the opposite effect is analyzed near the boundary layer. Also, the contour and surface plots are displayed to portray real-world applications in industrial and technical processes and the physical depiction of flow characteristics that arise in the current study.
Trainable joint bilateral filters for enhanced prediction stability in low-dose CT
Authors: Wagner Fabian , Thies Mareike , Denzinger Felix , Gu Mingxuan , Patwari Mayank , Ploner Stefan , Maul Noah , Pfaff Laura , Huang Yixing , Maier Andreas
Published: October 2022

Low-dose computed tomography (CT) denoising algorithms aim to enable reduced patient dose in routine CT acquisitions while maintaining high image quality. Recently, deep learning (DL)-based methods were introduced, outperforming conventional denoising algorithms on this task due to their high model capacity. However, for the transition of DL-based denoising to clinical practice, these data-driven approaches must generalize robustly beyond the seen training data. We, therefore, propose a hybrid denoising approach consisting of a set of trainable joint bilateral filters (JBFs) combined with a convolutional DL-based denoising network to predict the guidance image. Our proposed denoising pipeline combines the high model capacity enabled by DL-based feature extraction with the reliability of the conventional JBF. The pipeline’s ability to generalize is demonstrated by training on abdomen CT scans without metal implants and testing on abdomen scans with metal implants as well as on head CT data. When embedding RED-CNN/QAE, two well-established DL-based denoisers in our pipeline, the denoising performance is improved by 10%/82% (RMSE) and 3%/81% (PSNR) in regions containing metal and by 6%/78% (RMSE) and 2%/4% (PSNR) on head CT data, compared to the respective vanilla model. Concluding, the proposed trainable JBFs limit the error bound of deep neural networks to facilitate the applicability of DL-based denoisers in low-dose CT pipelines.