bluuebunny/crossref_metadata_2025 huggingface dataset:
Amplified therapeutic targets in high-grade serous ovarian carcinoma – a review of the literature with quantitative appraisal
Authors: Talbot Thomas , Lu Haonan , Aboagye Eric O.
Published: February 2023

High-grade serous ovarian carcinoma is a unique cancer characterised by universal TP53 mutations and widespread copy number alterations. These copy number alterations include deletion of tumour suppressors and amplification of driver oncogenes. Given their key oncogenic roles, amplified driver genes are often proposed as therapeutic targets. For example, development of anti-HER2 agents has been clinically successful in treatment of ERBB2-amplified tumours. A wide scope of preclinical work has since investigated numerous amplified genes as potential therapeutic targets in high-grade serous ovarian carcinoma. However, variable experimental procedures (e.g., choice of cell lines), ambiguous phenotypes or lack of validation hinders further clinical translation of many targets. In this review, we collate the genes proposed to be amplified therapeutic targets in high-grade serous ovarian carcinoma, and quantitatively appraise the evidence in support of each candidate gene. Forty-four genes are found to have evidence as amplified therapeutic targets; the five highest scoring genes are CCNE1, PAX8, URI1, PRKCI and FAL1. This review generates an up-to-date list of amplified therapeutic target candidates for further development and proposes comprehensive criteria to assist amplified therapeutic target discovery in the future.
Identification of G protein subunit alpha i2 as a promising therapeutic target of hepatocellular carcinoma
Authors: Chen Minbin , Li Zhifei , Gu Chengtao , Zheng Hao , Chen Yan , Cheng Long
Published: February 2023

Hepatocellular carcinoma (HCC) is a global health problem. Its incidence and mortality are increasing. Exploring novel therapeutic targets against HCC is important and urgent. We here explored the expression and potential function of Gαi2 (G protein subunit alpha i2) in HCC. The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) database shows that the number of Gαi2 transcripts in HCC tissues is significantly higher than that in the normal liver tissues. Moreover, Gαi2 overexpression in HCC correlates with poor prognosis of the patients. Gαi2 mRNA and protein expression are also elevated in local HCC tissues and different human HCC cells. In patient-derived primary HCC cells and immortalized HepG2 cells, Gαi2 silencing (by targeted shRNA) or knockout (KO, by the dCas9-sgRNA method) largely suppressed cell proliferation and motility, while inducing cell cycle arrest and caspase-apoptosis activation. Moreover, Gαi2 silencing or KO-induced reactive oxygen species (ROS) production and oxidative injury in primary and HepG2 HCC cells. Whereas different antioxidants ameliorated Gαi2-shRNA-induced anti-HCC cell activity. Using a lentiviral construct, Gαi2 overexpression further augmented proliferation and motility of primary and immortalized HCC cells. Further studies revealed that the binding between the transcription factor early growth response zinc finger transcription factor 1 (EGR1) and Gαi2 DNA promoter was significantly increased in HCC tissues and cells. In vivo, intratumoral injection of Gαi2 shRNA adeno-associated virus significantly hindered HCC xenograft growth in nude mice. Moreover, the growth of Gαi2-KO HCC xenografts in the nude mice was remarkably slow. Gαi2 depletion, oxidative injury, and apoptosis induction were detected in Gαi2-silenced or Gαi2-KO HCC xenografts. Together, overexpressed Gαi2 is required for HCC cell growth in vitro and in vivo, representing as a novel and promising diagnosis marker and therapeutic target of HCC.
A regulatory network controlling ovarian granulosa cell death
Authors: Yang Liu , Du Xing , Wang Siqi , Lin Chenggang , Li Qiqi , Li Qifa
Published: February 2023

Follicular atresia triggered by granulosa cell (GC) apoptosis severely reduces female fertility and accelerates reproductive aging. GC apoptosis is a complex process regulated by multiple factors, regulatory axes, and signaling pathways. Here, we report a novel, small regulatory network involved in GC apoptosis and follicular atresia. miR-187, a miRNA down-regulated during follicular atresia in sows, maintains TGFBR2 mRNA stability in sow GCs by directly binding to its 5’-UTR. miR-187 activates the transforming growth factor-β (TGF-β) signaling pathway and suppresses GC apoptosis via TGFBR2 activation. NORHA, a pro-apoptotic lncRNA expressed in sow GCs, inhibits TGFBR2-mediated activation of the TGF-β signaling pathway by sponging miR-187. In contrast, NORFA, a functional lncRNA associated with sow follicular atresia and GC apoptosis, enhances miR-187 and TGFBR2 expression by inhibiting NORHA and activating NFIX. Our findings define a simple regulatory network that controls GC apoptosis and follicular atresia, providing new insights into the mechanisms of GC apoptosis, follicular atresia, and female fertility.
Characteristic changes in the structures and properties of polyimides induced by very high pressures up to 8 GPa
Authors: Ando Shinji
Published: February 2023

Various in situ measurement techniques have been applied to investigate changes in the three-dimensional structures and the properties of fully aromatic polymers (mainly aromatic polyimides: PIs) generated at very high pressures up to 8 GPa. In particular, significant changes occurred in the ordered structures, aggregation states, electronic structures, and intermolecular interactions in the repeating units of the PI molecular chains and were observed by applying pressure with a high-pressure optical cell (up to 0.4 GPa, ca. 4000 atm) or a diamond anvil cell (DAC, up to 8.0 GPa, ca. 80,000 atm). In addition, the structural changes in the PI molecular chain repeating units and interchain distances induced by the ultrahigh pressures were observed with wide-angle X-ray diffraction, and they were compared and contrasted with optical absorption, fluorescent and phosphorescent emission spectra, infrared absorption spectra, and refractive indexes observed under the same conditions. These findings obtained at very high pressures provide molecular design guidelines for new PI materials with novel optical, electronic, and thermal functionalities that are not easy to achieve under ambient conditions.
Multilevel proteomic analyses reveal molecular diversity between diffuse-type and intestinal-type gastric cancer
Authors: Shi Wenhao , Wang Yushen , Xu Chen , Li Yan , Ge Sai , Bai Bin , Zhang Kecheng , Wang Yunzhi , Zheng Nairen , Wang Juan , Wang Shiqi , Ji Gang , Li Jipeng , Nie Yongzhan , Liang Wenquan , Wu Xiaosong , Cui Jianxin , Wang Yi , Chen Lin , Zhao Qingchuan , Shen Lin , He Fuchu , Qin Jun , Ding Chen
Published: February 2023

Diffuse-type gastric cancer (DGC) and intestinal-type gastric cancer (IGC) are the major histological types of gastric cancer (GC). The molecular mechanism underlying DGC and IGC differences are poorly understood. In this research, we carry out multilevel proteomic analyses, including proteome, phospho-proteome, and transcription factor (TF) activity profiles, of 196 cases covering DGC and IGC in Chinese patients. Integrative proteogenomic analysis reveals ARIDIA mutation associated with opposite prognostic effects between DGC and IGC, via diverse influences on their corresponding proteomes. Systematical comparison and consensus clustering analysis identify three subtypes of DGC and IGC, respectively, based on distinct patterns of the cell cycle, extracellular matrix organization, and immune response-related proteins expression. TF activity-based subtypes demonstrate that the disease progressions of DGC and IGC were regulated by SWI/SNF and NFKB complexes. Furthermore, inferred immune cell infiltration and immune clustering show Th1/Th2 ratio is an indicator for immunotherapeutic effectiveness, which is validated in an independent GC anti-PD1 therapeutic patient group. Our multilevel proteomic analyses enable a more comprehensive understanding of GC and can further advance the precision medicine.
Ideal acoustic quantum spin Hall phase in a multi-topology platform
Authors: Sun Xiao-Chen , Chen Hao , Lai Hua-Shan , Xia Chu-Hao , He Cheng , Chen Yan-Feng
Published: February 2023

Fermionic time-reversal symmetry ($${T}_{f}$$

T

f

)-protected quantum spin Hall (QSH) materials feature gapless helical edge states when adjacent to arbitrary trivial cladding materials. However, due to symmetry reduction at the boundary, bosonic counterparts usually exhibit gaps and thus require additional cladding crystals to maintain robustness, limiting their applications. In this study, we demonstrate an ideal acoustic QSH with gapless behaviour by constructing a global Tf on both the bulk and the boundary based on bilayer structures. Consequently, a pair of helical edge states robustly winds several times in the first Brillouin zone when coupled to resonators, promising broadband topological slow waves. We further reveal that this ideal QSH phase behaves as a topological phase transition plane that bridges trivial and higher-order phases. Our versatile multi-topology platform sheds light on compact topological slow-wave and lasing devices.
A three-dimensional antifungal wooden cone evaporator for highly efficient solar steam generation
Authors: Xie Meihua , Zhang Ping , Cao Yizhong , Yan Yutao , Wang Zhe , Jin Chunde
Published: February 2023

Interfacial solar energy evaporation is an effective measure to alleviate the current global shortage of clean water resources. However, many solar evaporators are two-dimensional (2D) structured devices developed by coating light-absorbing materials on the surface of host materials, and the efficiency of solar steam generation is limited. For this reason, the present study reports a facile and environment-friendly method to construct a conical three-dimensional (3D) wooden evaporator, which uses flexible wood as the substrate and tannic acid complex as the light-absorbing material and is formed by further convolution. Reasonable structural design and material combination enable the evaporator to show excellent mildew resistance and highly efficient evaporation performance. The black decoration considerably improves the wood light absorption, resulting in high absorbance (>90%) of DW-TA-Fe3+ in the wavelength range of 200–800 nm. The water evaporation rate of the wooden cone evaporator can reach up to 1.79 kg m−2 h−1, about 1.6 times higher than that of the 2D evaporator. Moreover, the evaporator exhibits outstanding biological stability and effective desalination performance. This work is expected to offer a new direction in designing a 3D wooden evaporator for effective solar water desalination.
Potential benefits of public–private partnerships to improve the efficiency of urban wastewater treatment
Authors: Cheng Shulei , Yu Yu , Meng Fanxin , Chen Jiandong , Chen Yongtao , Liu Gengyuan , Fan Wei
Published: February 2023

For emerging economies lacking public budgets, continuous improvement of urban wastewater treatment efficiency (UWTE) requires effective government supervision of wastewater treatment infrastructures (WTIs) and participation of private capital seeking to profit-maximising. However, to what extent this public–private partnership (PPP) model, aimed at a reasonable sharing of benefit and risk, in delivering WTIs can improve the UWTE is unknown. We evaluated the impact of the PPP model on the UWTE by collecting data from 1303 urban wastewater treatment PPP projects in 283 prefecture-level cities in China from 2014 to 2019 and used data envelopment analysis and Tobit regression model. The UWTE was significantly higher in prefecture-level cities that introduced the PPP model in the construction and operation of WTIs, particularly those with a feasibility gap subsidy, competitive procurement, privatised operation, and non-demonstration. Moreover, the effects of PPPs on UWTE were limited by the economic development level, marketisation, and climatic conditions.
Quantifying the physical processes leading to atmospheric hot extremes at a global scale
Authors: Röthlisberger Matthias , Papritz Lukas
Published: February 2023

Heat waves are among the deadliest climate hazards. Yet the relative importance of the physical processes causing their near-surface temperature anomalies (𝑇′)—advection of air from climatologically warmer regions, adiabatic warming in subsiding air and diabatic heating—is still a matter of debate. Here we quantify the importance of these processes by evaluating the 𝑇′ budget along air-parcel backward trajectories. We first show that the extreme near-surface 𝑇′ during the June 2021 heat wave in western North America was produced primarily by diabatic heating and, to a smaller extent, by adiabatic warming. Systematically decomposing 𝑇′ during the hottest days of each year (TX1day events) in 1979–2020 globally, we find strong geographical variations with a dominance of advection over mid-latitude oceans, adiabatic warming near mountain ranges and diabatic heating over tropical and subtropical land masses. In many regions, however, TX1day events arise from a combination of these processes. In the global mean, TX1day anomalies form along trajectories over roughly 60 h and 1,000 km, although with large regional variability. This study thus reveals inherently non-local and regionally distinct formation pathways of hot extremes, quantifies the crucial factors determining their magnitude and enables new quantitative ways of climate model evaluation regarding hot extremes.
Early morning university classes are associated with impaired sleep and academic performance
Authors: Yeo Sing Chen , Lai Clin K. Y. , Tan Jacinda , Lim Samantha , Chandramoghan Yuvan , Tan Teck Kiang , Gooley Joshua J.
Published: February 2023

Attending classes and sleeping well are important for students’ academic success. Here, we tested whether early morning classes are associated with lower attendance, shorter sleep and poorer academic achievement by analysing university students’ digital traces. Wi-Fi connection logs in 23,391 students revealed that lecture attendance was about ten percentage points lower for classes at 08:00 compared with later start times. Diurnal patterns of Learning Management System logins in 39,458 students and actigraphy data in 181 students demonstrated that nocturnal sleep was an hour shorter for early classes because students woke up earlier than usual. Analyses of grades in 33,818 students showed that the number of days per week they had morning classes was negatively correlated with grade point average. These findings suggest concerning associations between early morning classes and learning outcomes.
Genome-wide subcellular protein map for the flagellate parasite Trypanosoma brucei
Authors: Billington Karen , Halliday Clare , Madden Ross , Dyer Philip , Barker Amy Rachel , Moreira-Leite Flávia Fernandes , Carrington Mark , Vaughan Sue , Hertz-Fowler Christiane , Dean Samuel , Sunter Jack Daniel , Wheeler Richard John , Gull Keith
Published: February 2023

Trypanosoma brucei is a model trypanosomatid, an important group of human, animal and plant unicellular parasites. Understanding their complex cell architecture and life cycle is challenging because, as with most eukaryotic microbes, ~50% of genome-encoded proteins have completely unknown functions. Here, using fluorescence microscopy and cell lines expressing endogenously tagged proteins, we mapped the subcellular localization of 89% of the T. brucei proteome, a resource we call TrypTag. We provide clues to function and define lineage-specific organelle adaptations for parasitism, mapping the ultraconserved cellular architecture of eukaryotes, including the first comprehensive ‘cartographic’ analysis of the eukaryotic flagellum, which is vital for morphogenesis and pathology. To demonstrate the power of this resource, we identify novel organelle subdomains and changes in molecular composition through the cell cycle. TrypTag is a transformative resource, important for hypothesis generation for both eukaryotic evolutionary molecular cell biology and fundamental parasite cell biology.
High-throughput microbial culturomics using automation and machine learning
Authors: Huang Yiming , Sheth Ravi U. , Zhao Shijie , Cohen Lucas A. , Dabaghi Kendall , Moody Thomas , Sun Yiwei , Ricaurte Deirdre , Richardson Miles , Velez-Cortes Florencia , Blazejewski Tomasz , Kaufman Andrew , Ronda Carlotta , Wang Harris H.
Published: February 2023

Pure bacterial cultures remain essential for detailed experimental and mechanistic studies in microbiome research, and traditional methods to isolate individual bacteria from complex microbial ecosystems are labor-intensive, difficult-to-scale and lack phenotype–genotype integration. Here we describe an open-source high-throughput robotic strain isolation platform for the rapid generation of isolates on demand. We develop a machine learning approach that leverages colony morphology and genomic data to maximize the diversity of microbes isolated and enable targeted picking of specific genera. Application of this platform on fecal samples from 20 humans yields personalized gut microbiome biobanks totaling 26,997 isolates that represented >80% of all abundant taxa. Spatial analysis on >100,000 visually captured colonies reveals cogrowth patterns between Ruminococcaceae, Bacteroidaceae, Coriobacteriaceae and Bifidobacteriaceae families that suggest important microbial interactions. Comparative analysis of 1,197 high-quality genomes from these biobanks shows interesting intra- and interpersonal strain evolution, selection and horizontal gene transfer. This culturomics framework should empower new research efforts to systematize the collection and quantitative analysis of imaging-based phenotypes with high-resolution genomics data for many emerging microbiome studies.
Relations of hippocampal subfields atrophy patterns with memory and biochemical changes in end stage renal disease
Authors: Jiang Yuhan , Gao Bingbing , Li Mingshuai , Liu Yangyingqiu , Li Yuan , Liu Na , Zhang Yukun , Song Qingwei , Wen Xinyu , Jiang Jian , Wang Weiwei , Wang Nan , Miao Yanwei
Published: February 2023

End-stage renal disease (ESRD) results in hippocampal volume reduction, but the hippocampal subfields atrophy patterns cannot be identified. We explored the volumes and asymmetry of the hippocampal subfields and their relationships with memory function and biochemical changes. Hippocampal global and subfields volumes were derived from 33 ESRD patients and 46 healthy controls (HCs) from structural MRI. We compared the volume and asymmetric index of each subfield, with receiver operating characteristic curve analysis to evaluate the differentiation between ESRD and HCs. The relations of hippocampal subfield volumes with memory performance and biochemical data were investigated in ESRD group. ESRD patients had smaller hippocampal subfield volumes, mainly in the left CA1 body, left fimbria, right molecular layer head, right molecular layer body and right HATA. The right molecular layer body exhibited the highest accuracy for differentiating ESRD from HCs, with a sensitivity of 80.43% and specificity of 72.73%. Worse learning process (r = 0.414, p = 0.032), immediate recall (r = 0.396, p = 0.041) and delayed recall (r = 0.482, p = 0.011) was associated with left fimbria atrophy. The left fimbria volume was positively correlated with Hb (r = 0.388, p = 0.05); the left CA1 body volume was negatively correlated with Urea (r = − 0.469, p = 0.016). ESRD patients showed global and hippocampal subfields atrophy. Left fimbria atrophy was related to memory function. Anemia and Urea level may be associated with the atrophy of left fimbria and CA1 body, respectively.
Elucidation of the (R)-enantiospecific benzylisoquinoline alkaloid biosynthetic pathways in sacred lotus (Nelumbo nucifera)
Authors: Menéndez-Perdomo Ivette M. , Facchini Peter J.
Published: February 2023

Benzylisoquinoline alkaloids (BIAs) are a structurally diverse group of plant specialized metabolites found mainly in members of the order Ranunculales, including opium poppy (Papaver somniferum), for which BIA biosynthetic pathways leading to the critical drugs morphine, noscapine, and sanguinarine have been elucidated. Sacred lotus (Nelumbo nucifera), in the order Proteales, accumulates medicinal BIAs in the proaporphine, aporphine, and bisbenzylisoquinoline structural subgroups with a prevalence of R enantiomers, opposed to the dominant S configuration occurring in the Ranunculales. Nevertheless, distinctive BIA biosynthetic routes in sacred lotus have not been explored. In planta labeling experiments and in vitro assays with recombinant enzymes and plant protein extracts showed that dopamine and 4-hydroxyphenylacetaldehyde derived from l-tyrosine serve as precursors for the formation of (R,S)-norcoclaurine in sacred lotus, whereas only (R)-norcoclaurine byproducts are favored in the plant by action of R-enantiospecific methyltransferases and cytochrome P450 oxidoreductases (CYPs). Enzymes responsible for the R-enantiospecific formation of proaporphine (NnCYP80Q1) and bisbenzylisoquinoline (NnCYP80Q2) scaffolds, and a methylenedioxy bridge introduction on aporphine substrates (NnCYP719A22) were identified, whereas additional aspects of the biosynthetic pathways leading to the distinctive alkaloid profile are discussed. This work expands the availability of molecular tools that can be deployed in synthetic biology platforms for the production of high-value alkaloids.
A logarithmically amortising temperature effect for supervised learning of wheat solar disinfestation of rice weevil Sitophilus oryzae (Coleoptera: Curculionidae) using plastic bags
Authors: Abdelsamea Mohammed M. , Gaber Mohamed Medhat , Ali Aliyuda , Kyriakou Marios , Fawki Shams
Published: February 2023

This work investigates the effectiveness of solar heating using clear polyethylene bags against rice weevil Sitophilus oryzae (L.), which is one of the most destructive insect pests against many strategic grains such as wheat. In this paper, we aim at finding the key parameters that affect the control heating system against stored grain insects while ensuring that the wheat grain quality is maintained. We provide a new benchmark dataset, where the experimental and environmental data was collected based on fieldwork during the summer in Canada. We measure the effectiveness of the solution using a novel formula to describe the amortising temperature effect on rice weevil. We adopted different machine learning models to predict the effectiveness of our solution in reaching a lethal heating condition for insect pests, and hence measure the importance of the parameters. The performance of our machine learning models has been validated using a 10-fold cross-validation, showing a high accuracy of 99.5% with 99.01% recall, 100% precision and 99.5% F1-Score obtained by the Random Forest model. Our experimental study on machine learning with SHAP values as an eXplainable post-hoc model provides the best environmental conditions and parameters that have a significant effect on the disinfestation of rice weevils. Our findings suggest that there is an optimal medium-sized grain amount when using solar bags for thermal insect disinfestation under high ambient temperatures. Machine learning provides us with a versatile model for predicting the lethal temperatures that are most effective for eliminating stored grain insects inside clear plastic bags. Using this powerful technology, we can gain valuable information on the optimal conditions to eliminate these pests. Our model allows us to predict whether a certain combination of parameters will be effective in the treatment of insects using thermal control. We make our dataset publicly available under a Creative Commons Licence to encourage researchers to use it as a benchmark for their studies.
Analysis of quantitative metrics for assessing resilience of human-centered CPPS workstations
Authors: Aruväli Tanel , De Marchi Matteo , Rauch Erwin
Published: February 2023

Manufacturing companies’ preparedness level against external and internal disruptions is complex to assess due to a lack of widely recognized or standardized models. Resilience as the measure to characterize preparedness against disruptions is a concept with various numerical approaches, but still lacking in the industry standard. Therefore, the main contribution of the research is the comparison of existing resilience metrics and the selection of the practically usable quantitative metric that allows manufacturers to start assessing the resilience in digitally supported human-centered workstations more easily. An additional contribution is the detection and highlighting of disruptions that potentially influence manufacturing workstations the most. Using five weighted comparison criteria, the resilience metrics were pairwise compared based on multi-criteria decision-making Analytic Hierarchy Process analysis on a linear scale. The general probabilistic resilience assessment method Penalty of Change that received the highest score considers the probability of disruptions and related cost of potential changes as inputs for resilience calculation. Additionally, manufacturing-related disruptions were extracted from the literature and categorized for a better overview. The Frequency Effect Sizes of the extracted disruptions were calculated to point out the most influencing disruptions. Overall, resilience quantification in manufacturing requires further research to improve its accuracy while maintaining practical usability.
The effect of postmenopausal osteoporosis on subchondral bone pathology in a rat model of knee osteoarthritis
Authors: Wada Hiroyuki , Aso Koji , Izumi Masashi , Ikeuchi Masahiko
Published: February 2023

This study aimed to investigate the additional effect of ovariectomy-induced osteoporosis (OP) on the pathology of knee osteoarthritis (OA) in a rat meniscectomized model, particularly focusing on subchondral bone changes and pain behaviour. Rats were divided into four groups, sham, OP, OA, OP plus OA, and assessed for histology, osteoclast activity, subchondral bone microstructure, and pain-related behaviour. Rats with OP plus OA had significantly increased calcified cartilage and subchondral bone damage scores, increased densities of subchondral osteoclasts in the weight-bearing area, and more porous subchondral trabecular bone compared with rats with OA. Loss of tidemark integrity was observed most frequently in rats with OP plus OA. The density of subchondral osteoclasts correlated with the calcified cartilage and subchondral bone damage score in rats with OA (OA and OP plus OA). No significant differences in the receptor activator of nuclear factor-kappa B ligand (RANKL)/osteoprotegerin (OPG) expression ratio in subchondral bone and pain-related behavioural tests were observed between rats with OA and rats with OP plus OA. In rats with OA, coexisting OP potentially aggravated OA pathology mainly in calcified cartilage and subchondral trabecular bone by increasing subchondral osteoclast activity.
Taguchi optimization and modelling of stir casting process parameters on the percentage elongation of aluminium, pumice and carbonated coal composite
Authors: Ibrahim Tanimu Kogi , Yawas Danjuma Saleh , Dan-asabe Bashar , Adebisi Adetayo Abdulmumin
Published: February 2023

Aluminium matrix composites, which are a subclass of metal matrix composites, have characteristics including low density, high stiffness and strength, better wear resistance, controlled thermal expansion, greater fatigue resistance, and improved stability at high temperatures. The scientific and industrial communities are interested in these composites because they may be used to manufacture a broad variety of components for cutting-edge applications. This has study observed how the stirring speed, processing temperature, and stirring duration of the stir casting process affected the percentage elongation of Al-Pumice (PP)-Carbonized Coal Particles (CCP) hybrid composites. It also looked at the optimal weight of these natural ceramic reinforcements using the Taguchi optimization technique. While optimizing the percentage elongation property, the hard compound such as silica, iron oxide, and alumina, were discovered during the characterisation of the reinforcement, showing that PP and CCP can be used as reinforcement in metal matrix composite. The percentage of elongation of the hybrid composite was shown to be most affected by the PP, followed by processing temperature, stirring speed, CCP, and stirring time, using stir casting process parameter optimization. It was observed at 2.5 wt% of pumice particles, 2.5 wt% of carbonated coal particles, 700 °C processing temperature, 200 rpm stirring speed, and 5 min stirring time, the optimum percentage of elongation was discovered to be 5.6%, which is 25.43% lower than the percentage elongation of Al-alloy without reinforcing. The regression study developed a predictive mathematical model for the percentage elongation (PE) as a function of the stir casting process parameters and offered a high degree of prediction, with R-Square, R-Square (adj), and R-Square (pred) values of 91.60%, 87.41%, and 79.32% respectively.
SARS-CoV-2 alters neural synchronies in the brain with more severe effects in younger individuals
Authors: Valsamis Helen , Baki Samah Abdul , Leung Jason , Ghosn Samer , Lapin Brittany , Chari Geetha , Rasheed Izad-Yar , Park Jaehan , Punia Vineet , Masri Ghinwa , Nair Dileep , Kaniecki Ann Marie , Edhi Muhammad , Saab Carl Y.
Published: February 2023

Coronavirus disease secondary to infection by SARS-CoV-2 (COVID19 or C19) causes respiratory illness, as well as severe neurological symptoms that have not been fully characterized. In a previous study, we developed a computational pipeline for the automated, rapid, high-throughput and objective analysis of electroencephalography (EEG) rhythms. In this retrospective study, we used this pipeline to define the quantitative EEG changes in patients with a PCR-positive diagnosis of C19 (n = 31) in the intensive care unit (ICU) of Cleveland Clinic, compared to a group of age-matched PCR-negative (n = 38) control patients in the same ICU setting. Qualitative assessment of EEG by two independent teams of electroencephalographers confirmed prior reports with regards to the high prevalence of diffuse encephalopathy in C19 patients, although the diagnosis of encephalopathy was inconsistent between teams. Quantitative analysis of EEG showed distinct slowing of brain rhythms in C19 patients compared to control (enhanced delta power and attenuated alpha–beta power). Surprisingly, these C19-related changes in EEG power were more prominent in patients below age 70. Moreover, machine learning algorithms showed consistently higher accuracy in the binary classification of patients as C19 versus control using EEG power for subjects below age 70 compared to older ones, providing further evidence for the more severe impact of SARS-CoV-2 on brain rhythms in younger individuals irrespective of PCR diagnosis or symptomatology, and raising concerns over potential long-term effects of C19 on brain physiology in the adult population and the utility of EEG monitoring in C19 patients.
Taxonomic and enzymatic basis of the cellulolytic microbial consortium KKU-MC1 and its application in enhancing biomethane production
Authors: Wongfaed Nantharat , O-Thong Sompong , Sittijunda Sureewan , Reungsang Alissara
Published: February 2023

Lignocellulosic biomass is a promising substrate for biogas production. However, its recalcitrant structure limits conversion efficiency. This study aims to design a microbial consortium (MC) capable of producing the cellulolytic enzyme and exploring the taxonomic and genetic aspects of lignocellulose degradation. A diverse range of lignocellulolytic bacteria and degrading enzymes from various habitats were enriched for a known KKU-MC1. The KKU-MC1 was found to be abundant in Bacteroidetes (51%), Proteobacteria (29%), Firmicutes (10%), and other phyla (8% unknown, 0.4% unclassified, 0.6% archaea, and the remaining 1% other bacteria with low predominance). Carbohydrate-active enzyme (CAZyme) annotation revealed that the genera Bacteroides,Ruminiclostridium,Enterococcus, and Parabacteroides encoded a diverse set of cellulose and hemicellulose degradation enzymes. Furthermore, the gene families associated with lignin deconstruction were more abundant in the Pseudomonas genera. Subsequently, the effects of MC on methane production from various biomasses were studied in two ways: bioaugmentation and pre-hydrolysis. Methane yield (MY) of pre-hydrolysis cassava bagasse (CB), Napier grass (NG), and sugarcane bagasse (SB) with KKU-MC1 for 5 days improved by 38–56% compared to non-prehydrolysis substrates, while MY of prehydrolysed filter cake (FC) for 15 days improved by 56% compared to raw FC. The MY of CB, NG, and SB (at 4% initial volatile solid concentration (IVC)) with KKU-MC1 augmentation improved by 29–42% compared to the non-augmentation treatment. FC (1% IVC) had 17% higher MY than the non-augmentation treatment. These findings demonstrated that KKU-MC1 released the cellulolytic enzyme capable of decomposing various lignocellulosic biomasses, resulting in increased biogas production.
Self-administration of a Salmonella vaccine by domestic pigs
Authors: Robbins Rebecca C. , Archer Courtney , Giménez-Lirola Luis G. , Mora-Díaz Juan Carlos , McGlone John J.
Published: February 2023

Hand vaccinating is time consuming and inefficient. Oral vaccines delivered by drenching are less likely to be used due to a lack of labor on farms. Current environmental enrichment (EE) technologies do not allow pigs to express certain natural behaviors such as rooting and getting a reward. We developed a sprayer so that domestic pigs can self-apply any liquid. By adding an attractant (pig maternal pheromone), the use of EE devices by individual pigs can be increased. In this study, we used a Salmonella oral vaccine to evaluate efficacy of three delivery methods: (1) Control, no vaccine, (2) hand drenching as labeled, and (3) self-administration by this EE rooting device. All pigs sprayed themselves within 80 min of exposure to the EE device. While control pigs had little or no Salmonella serum and oral fluid IgG or IgA, hand-drenched and self-vaccinated pigs built similar levels of both serum and oral fluid IgA and IgG. We conclude we were able to significantly reduce human labor needed and achieved 100% efficacy in eliciting a serologic response when pigs self-administered a Salmonella vaccine. This technology could benefit commercial pig production while providing an enriched behavioral environment. Self-vaccination could also assist in control or immunization of feral swine and improve domestic pig health and food safety.
Mathematical modelling of the dynamics of image-informed tumor habitats in a murine model of glioma
Authors: Slavkova Kalina P. , Patel Sahil H. , Cacini Zachary , Kazerouni Anum S. , Gardner Andrea L. , Yankeelov Thomas E. , Hormuth David A.
Published: February 2023

Tumors exhibit high molecular, phenotypic, and physiological heterogeneity. In this effort, we employ quantitative magnetic resonance imaging (MRI) data to capture this heterogeneity through imaging-based subregions or “habitats” in a murine model of glioma. We then demonstrate the ability to model and predict the growth of the habitats using coupled ordinary differential equations (ODEs) in the presence and absence of radiotherapy. Female Wistar rats (N = 21) were inoculated intracranially with 106 C6 glioma cells, a subset of which received 20 Gy (N = 5) or 40 Gy (N = 8) of radiation. All rats underwent diffusion-weighted and dynamic contrast-enhanced MRI at up to seven time points. All MRI data at each visit were subsequently clustered using k-means to identify physiological tumor habitats. A family of four models consisting of three coupled ODEs were developed and calibrated to the habitat time series of control and treated rats and evaluated for predictive capability. The Akaike Information Criterion was used for model selection, and the normalized sum-of-square-error (SSE) was used to evaluate goodness-of-fit in model calibration and prediction. Three tumor habitats with significantly different imaging data characteristics (p < 0.05) were identified: high-vascularity high-cellularity, low-vascularity high-cellularity, and low-vascularity low-cellularity. Model selection resulted in a five-parameter model whose predictions of habitat dynamics yielded SSEs that were similar to the SSEs from the calibrated model. It is thus feasible to mathematically describe habitat dynamics in a preclinical model of glioma using biology-based ODEs, showing promise for forecasting heterogeneous tumor behavior.
Rumen-protected glucose stimulates the secretion of reproductive hormones and the mTOR/AKT signaling pathway in the ovaries of early postpartum
Authors: Wang Yan , Jin Chenzhong , Yi Yuzhen , Hu Yihong , Han Xuefeng , Tan Zhiliang , Wang Zheng , Kang Jinhe
Published: February 2023

This study was conducted to determine the response of the reproductive hormones and the mTOR/AKT/PI3K pathway in the ovaries of postpartum dairy cows with dietary rumen-protected glucose (RPG). Twelve Holstein cows were randomly assigned to two groups (n = 6/group): the control group (CT) and the RPG group. Blood samples were collected on d 1, 7, and 14 after calving for the gonadal hormone assay. The expression of the gonadal hormones receptors and PI3K/mTOR/AKT pathways were detected using RT-PCR and Western blot. The RPG addition increased the plasma LH, E2, and P4 concentrations on d 14 after calving and upregulated the mRNA and protein expressions of the ERα, ERβ, 17β-HSD, FSHR, LHR, and CYP17A1 but downregulated StAR expression. Immunohistochemical analysis identified higher expressions of the FSHR and LHR in the ovaries of RPG-fed cows compared to CT cows. Furthermore, the protein expressions of p-AKT/AKT and p-mTOR/mTOR were significantly increased in the ovaries of RPG-fed cows compared to the CT group, but the addition of RPG did not alter the protein expression of p-PI3K/PI3K. In conclusion, the current results indicated that dietary RPG supplementation regulated gonadotropin secretion and stimulated expression of hormone receptors and the mTOR/AKT pathway in the ovaries of early postpartum dairy cows. RPG may be beneficial for the recovery of ovarian activity in post-calving dairy cows.
Risk factors and geographic disparities in premature cardiovascular mortality in US counties: a machine learning approach
Authors: Dong Weichuan , Motairek Issam , Nasir Khurram , Chen Zhuo , Kim Uriel , Khalifa Yassin , Freedman Darcy , Griggs Stephanie , Rajagopalan Sanjay , Al-Kindi Sadeer G.
Published: February 2023

Disparities in premature cardiovascular mortality (PCVM) have been associated with socioeconomic, behavioral, and environmental risk factors. Understanding the “phenotypes”, or combinations of characteristics associated with the highest risk of PCVM, and the geographic distributions of these phenotypes is critical to targeting PCVM interventions. This study applied the classification and regression tree (CART) to identify county phenotypes of PCVM and geographic information systems to examine the distributions of identified phenotypes. Random forest analysis was applied to evaluate the relative importance of risk factors associated with PCVM. The CART analysis identified seven county phenotypes of PCVM, where high-risk phenotypes were characterized by having greater percentages of people with lower income, higher physical inactivity, and higher food insecurity. These high-risk phenotypes were mostly concentrated in the Black Belt of the American South and the Appalachian region. The random forest analysis identified additional important risk factors associated with PCVM, including broadband access, smoking, receipt of Supplemental Nutrition Assistance Program benefits, and educational attainment. Our study demonstrates the use of machine learning approaches in characterizing community-level phenotypes of PCVM. Interventions to reduce PCVM should be tailored according to these phenotypes in corresponding geographic areas.
Bimodal CNN for cardiovascular disease classification by co-training ECG grayscale images and scalograms
Authors: Yoon Taeyoung , Kang Daesung
Published: February 2023

This study aimed to develop a bimodal convolutional neural network (CNN) by co-training grayscale images and scalograms of ECG for cardiovascular disease classification. The bimodal CNN model was developed using a 12-lead ECG database collected from Chapman University and Shaoxing People's Hospital. The preprocessed database contains 10,588 ECG data and 11 heart rhythms labeled by a specialist physician. The preprocessed one-dimensional ECG signals were converted into two-dimensional grayscale images and scalograms, which are fed simultaneously to the bimodal CNN model as dual input images. The proposed model aims to improve the performance of CVDs classification by making use of ECG grayscale images and scalograms. The bimodal CNN model consists of two identical Inception-v3 backbone models, which were pre-trained on the ImageNet database. The proposed model was fine-tuned with 6780 dual-input images, validated with 1694 dual-input images, and tested on 2114 dual-input images. The bimodal CNN model using two identical Inception-v3 backbones achieved best AUC (0.992), accuracy (95.08%), sensitivity (0.942), precision (0.946) and F1-score (0.944) in lead II. Ensemble model of all leads obtained AUC (0.994), accuracy (95.74%), sensitivity (0.950), precision (0.953), and F1-score (0.952). The bimodal CNN model showed better diagnostic performance than logistic regression, XGBoost, LSTM, single CNN model training with grayscale images alone or with scalograms alone. The proposed bimodal CNN model would be of great help in diagnosing cardiovascular diseases.
Environmental and pathological factors affecting the hatching success of the two northernmost loggerhead sea turtle (Caretta caretta) nests
Authors: Pietroluongo Giudo , Centelleghe Cinzia , Sciancalepore Giuseppe , Ceolotto Luca , Danesi Patrizia , Pedrotti Davide , Mazzariol Sandro
Published: February 2023

In recent years, the report of loggerhead sea turtle (Caretta caretta) Mediterranean nesting range has expanded together with new records of nests becoming northward on the Italian coastline of the Tyrrhenian and Adriatic seas. These areas are characterized by intensive human activities, such as tourism, fishery, and marine traffic, all possibly involved in the influence of the use of coastal habitat by marine species. These anthropic threats, in addition to the natural ones and the changing environmental characteristics of the beach, may influence the growth of microorganisms causing hatching failures. Among microorganisms, fungal infection by the genus Fusarium (Link, 1809) is considered one of the main causes of globally declining sea turtle populations. In summer 2021, the two northernmost worldwide loggerhead sea turtle nests were monitored along the Northern Adriatic coastline (Veneto, Italy). These first records may potentially candidate this area as suitable for a large part of the loggerhead turtle’s life cycle and it could represent a minor sea turtle nesting area that, according to Prato and colleagues, remained unnoticed due to the lack of specific monitoring. Sea Turtle Egg Fusariosis (STEF) was deemed to have deeply compromised the hatching success of the northmost one. Climate change and anthropogenic impacts have been scored as one of the highest hazards to sea turtle health and could have played a role in the STEF development. Environmental changes, human activities, and emerging pathogens deserve the highest attention in terms of health research, and conservation management.
Protective effect of Anoectochilus burmannicus extracts and its active compound, kinsenoside on adipocyte differentiation induced by benzyl butyl phthalate and bisphenol A
Authors: Buacheen Pensiri , Karinchai Jirarat , Kammasit Natchapon , Temviriyanukul Piya , Butkinaree Chutikarn , Watthana Santi , Wongnoppavich Ariyaphong , Imsumran Arisa , Pitchakarn Pornsiri
Published: February 2023

Benzyl butyl phthalate (BBP) and bisphenol-A (BPA) are obesogens that have been reported to be associated with obesity. Inhibition of their adipogenic activity could decrease the risk of obesity-related metabolic disorders. This study hypothesized thatAnoectochilus burmannicusethanolic extract (ABE) which has been previously reported its anti-inflammation property and its known active compound, kinsenoside (Kin) abrogate BBP- and BPA-induced adipogenesis. ABE and Kin markedly suppress both BBP- and BPA-stimulated adipogenesis with different modulations on adipogenic-gene expression including C/EBPα, PPARγ, adiponectin, and leptin in 3T3-L1. BBP induced C/EBPα, adiponectin, and leptin mRNA expressions and slightly increased PPARγ mRNA level, whereas BPA markedly induced PPARγ and adiponectin mRNA levels. ABE significantly decreased the expression of C/EBPα and leptin, but not PPARγ and adiponectin in the BBP-treated cells. In the BPA-treated cells, ABE significantly decreased the mRNA expression of C/EBPα and PPARγ, but not adiponectin and leptin. Interestingly, Kin significantly overcame BBP- and BPA-induced C/EBPα, PPARγ, adiponectin, and leptin expressions. This study first provides evidence to support the health benefits of this plant, especially for people exposed to obesogens. Besides, this finding would encourage the conservation and culture of this orchid for development as an economic plant and healthy food.
Important role of stratosphere-troposphere coupling in the Arctic mid-to-upper tropospheric warming in response to sea-ice loss
Authors: Xu Mian , Tian Wenshou , Zhang Jiankai , Screen James A. , Zhang Chongyang , Wang Zhe
Published: February 2023

Recent studies have suggested that deep Arctic warming, extending from the surface to the upper troposphere, could trigger mid-latitude atmospheric circulation changes, while shallow Arctic warming, confined in the lowermost troposphere, induces comparatively weak remote responses. The causes of Arctic mid-to-upper tropospheric warming are less clear compared with near-surface warming. Here, we demonstrate a new dynamical mechanism responsible for the polar mid-to-upper tropospheric warming associated with Arctic sea-ice loss, using both reanalysis and model simulations. The Barents-Kara sea-ice loss enhances the upward propagating waves, leading to the wave convergence anomalies in the sub-polar lower stratosphere and upper troposphere. The consequent eddy feedback leads to clockwise residual overturning anomalies in the sub-polar upper and middle troposphere, accompanied by anomalous descent and consequent adiabatic warming in the Arctic mid-to-upper troposphere. The essential role of stratosphere-troposphere coupling for deep Arctic warming induced by sea-ice loss is confirmed by model simulations with stratospheric variability suppressed, in which only the Arctic lower troposphere is warmed in response to sea-ice loss. Our results suggest that a considerable part of the observed Arctic mid-to-upper warming is caused by a dynamical response to sea-ice loss, in which stratosphere-troposphere coupling plays a major role.