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Taybi-Linder syndrome (TALS) is a rare autosomal recessive disorder characterized by severe microcephaly with abnormal gyral pattern, severe growth retardation and bone abnormalities. It is caused by pathogenic variants in the RNU4ATAC gene. Its transcript, the small nuclear RNA U4atac, is involved in the excision of ~850 minor introns. Here, we report a patient presenting with TALS features but no pathogenic variants were found in RNU4ATAC, instead the homozygous RTTN c.2953A>G variant was detected by whole-exome sequencing. After deciphering the impact of the variant on the RTTN protein function at centrosome in engineered RTTN-depleted RPE1 cells and patient fibroblasts, we analysed neural stem cells (NSC) derived from CRISPR/Cas9-edited induced pluripotent stem cells and revealed major cell cycle and mitotic abnormalities, leading to aneuploidy, cell cycle arrest and cell death. In cortical organoids, we discovered an additional function of RTTN in the self-organisation of NSC into neural rosettes, by observing delayed apico-basal polarization of NSC. Altogether, these defects contributed to a marked delay of rosette formation in RTTN-mutated organoids, thus impeding their overall growth and shedding light on mechanisms leading to microcephaly.

This study aims to pioneer an innovative circular intuitionistic fuzzy (C-IF) scoring-mediated median ranking model designed for multiple criteria decision analytics. The primary goal is to establish a comprehensive precedence ranking for competing alternatives, effectively addressing the inherent uncertainties present in decision-analytic challenges within the C-IF environment. The core content delves into the creation of an original scoring mechanism tailored to navigate the complexities of C-IF uncertainties. Moreover, the research introduces a specialized C-IF median ranking model for decision analytics, leveraging the foundational concept of the C-IF scoring mechanism. A significant contribution is made through the formulation of a robust implementation procedure, specifically tailored for the seamless operation of the C-IF scoring-mediated median ranking model within the framework of C-IF information. Drawing from the suggested C-IF scoring mechanism, this research introduces novel concepts related to comprehensive C-IF scoring functions and comprehensive disagreement metrics. Subsequently, a comprehensive disagreement matrix is formulated, with its entries quantifying the extent of disagreement in assigning specific ranks to each alternative across all criterion-wise precedence relationships. This paves the way for the development of a new C-IF scoring-mediated median ranking model, offering decision analysts a tool to navigate intricate C-IF information and derive dependable decision-analytic outcomes.

Abstract T and B cell activation are equally important in triggering and orchestrating adaptive host responses to design multi-epitope African swine fever virus (ASFV) vaccines. However, few design methods have considered the trade-off between T and B cell immunogenicity when identifying promising ASFV epitopes. This work proposed a novel Pareto front-based ASFV screening method PFAS to identify promising epitopes for designing multi-epitope vaccines utilizing five ASFV Georgia 2007/1 sequences. To accurately predict T cell immunogenicity, four scoring methods were used to estimate the T cell activation in the four stages, including proteasomal cleavage probability, transporter associated with antigen processing transport efficiency, class I binding affinity of the major histocompatibility complex, and CD8 + cytotoxic T cell immunogenicity. PFAS ranked promising epitopes using a Pareto front method considering T and B cell immunogenicity. The coefficient of determination between the Pareto ranks of multi-epitope vaccines and survival days of swine vaccinations was R2 = 0.95. Consequently, PFAS scored complete epitope profiles and identified 72 promising top-ranked epitopes, including 46 CD2v epitopes, two p30 epitopes, 10 p72 epitopes, and 14 pp220 epitopes. PFAS is the first method of using the Pareto front approach to identify promising epitopes that considers the objectives of maximizing both T and B cell immunogenicity. The top-ranked promising epitopes can be cost-effectively validated in vitro. The Pareto front approach can be adaptively applied to various epitope predictors for bacterial, viral and cancer vaccine developments. The MATLAB code of the Pareto front method was available at https://github.com/NYCU-ICLAB/PFAS . Graphical Abstract

Abstract Background Lifestyle modification is an essential component of prevention and management of hypertension. Existing instruments in Taiwan focus on assessing lifestyle modifications by evaluating medication adherence or confidence in controlling blood pressure. However, other self-care activities, such as diet, physical activity, weight management, smoking, and alcohol consumption are also important. The Hypertension Self-Care Activity Level Effects (H-SCALE) is one such instrument, but there are no similar tools available in Taiwan. Aim This study aimed to translate the H-SCALE into Chinese and test its validity, and reliability in a sample of adults with hypertension. Methods The English version of the 31-item H-SCALE was translated into Chinese using the forward-backward method. The content validity index (CVI) of the translated scale was determined by five experts in hypertension. Item analysis was conducted with a pilot sample of 20 patients with hypertension. Cronbach’s α was used to establish the internal consistency reliability for the Chinese version of the H-SCALE (H-SCALE-C). Exploratory factor analysis (EFA) explored the structure of the H-SCALE-C. Additionally, construct validity was examined with confirmatory factor analysis (CFA). Patients with hypertension were recruited by convenience sampling from a cardiovascular outpatient clinic of a medical center in northern Taiwan. A total of 318 patients met the inclusion criteria and participated in factor analysis in the study. Results Pilot testing of the scale items indicated most patients could not accurately estimate the number of days of alcohol consumption for the previous week. Therefore, three alcohol-related items were removed. The adaptation resulted in a 28-item H-SCALE-C. EFA revealed a 4-factor solution with 13 items that explained 63.93% of the total variance. CFA indicated a good fit for a 4-factor model and construct validity was acceptable. Internal consistency reliability was acceptable (Cronbach’s alpha for the four subscales ranged from 0.65 to 0.94). Convergent validity was acceptable, and discriminant validity was significant. Conclusions The H-SCALE-C is a valid, reliable tool for promptly assessing life-style activities for patients with hypertension in Taiwan. The instrument is suitable for assisting healthcare providers in evaluating self-care activities, which could be used to facilitate lifestyle modifications for patients with hypertension.

Abstract Background Alzheimer’s disease is characterized by large-scale structural changes in a specific pattern. Recent studies developed morphological similarity networks constructed by brain regions similar in structural features to represent brain structural organization. However, few studies have used local morphological properties to explore inter-regional structural similarity in Alzheimer’s disease. Methods Here, we sourced T1-weighted MRI images of 342 cognitively normal participants and 276 individuals with Alzheimer’s disease from the Alzheimer's Disease Neuroimaging Initiative database. The relationships of grey matter intensity between adjacent voxels were defined and converted to the structural pattern indices. We conducted the information-based similarity method to evaluate the structural similarity of structural pattern organization between brain regions. Besides, we examined the structural randomness on brain regions. Finally, the relationship between the structural randomness and cognitive performance of individuals with Alzheimer’s disease was assessed by stepwise regression. Results Compared to cognitively normal participants, individuals with Alzheimer’s disease showed significant structural pattern changes in the bilateral posterior cingulate gyrus, hippocampus, and olfactory cortex. Additionally, individuals with Alzheimer’s disease showed that the bilateral insula had decreased inter-regional structural similarity with frontal regions, while the bilateral hippocampus had increased inter-regional structural similarity with temporal and subcortical regions. For the structural randomness, we found significant decreases in the temporal and subcortical areas and significant increases in the occipital and frontal regions. The regression analysis showed that the structural randomness of five brain regions was correlated with the Mini-Mental State Examination scores of individuals with Alzheimer’s disease. Conclusions Our study suggested that individuals with Alzheimer’s disease alter micro-structural patterns and morphological similarity with the insula and hippocampus. Structural randomness of individuals with Alzheimer’s disease changed in temporal, frontal, and occipital brain regions. Morphological similarity and randomness provide valuable insight into brain structural organization in Alzheimer’s disease.

BackgroundHyperuricemia, as a very prevalent chronic metabolic disease with increasing prevalence year by year, poses a significant burden on individual patients as well as on the global health care and disease burden, and there is growing evidence that it is associated with other underlying diseases such as hypertension and cardiovascular disease. The association between hyperuricemia and dietary inflammatory index (DII) scores was investigated in this study.MethodsThis study enrolled 13, 040 adult subjects (aged ≥ 20 years) from the US National Health and Nutrition Survey from 2003 to 2018. The inflammatory potential of the diet was assessed by the DII score, and logistic regression was performed to evaluate the relationship between the DII score and the development of hyperuricemia; subgroup analyses were used to discuss the influence of other factors on the relationship.ResultsParticipants in the other quartiles had an increased risk of hyperuricemia compared to those in the lowest quartile of DII scores. Stratification analyses stratified by body mass index (BMI), sex, hypertension, drinking, diabetes, education level and albumin-creatinine-ratio (ACR) revealed that the DII score was also associated with the risk of hyperuricemia (P

The formation of germanene on Ag(111) has been extensively studied and confirmed. However, the nature of the transition stage between the initial Ag_{2}Ge alloy phase at 1/3 monolayer (ML) and the final quasifreestanding phase germanene phase at coverage ≥1 ML still remains elusive. Using angle-resolved photoemission spectroscopy, scanning-tunneling microscopy (STM), and low-energy electron diffraction, we confirm the existence of striped-phase (SP) germanene in the transition stage. Along the armchair direction of SP, the period of higher-order coincidence corresponds to 11a_{AC}=31a_{Ag(111)}, which accommodates four stripes on the bridge sites of the underlying Ag(111) lattice, as manifested in STM topography. On the electronic-structure side, the splitlike surface band of Ag_{2}Ge centered at the surface zone boundary M[over ¯]_{Ag(111)} evidently evolves to a steep, V-shaped interfacial-state band, characteristic of SP germanene. Moreover, an anomalous broad Ag bulk-state band was observed to fully develop upon formation of SP germanene. The bulk-state band originates from the direct transition to the final-state bands of originally d character at ∼22–23eV above the Fermi level. Because of the strong hybridization between germanene π and Ag d orbitals, the unoccupied Ag bulk final-state d bands near the interface take on p_{z} character, inducing the direct transition from the Ag bulk occupied p_{z}-valence band, following the selection rule for the photoemission cross section. A germanene identity of SP is thus confirmed. Our result indicates a very important missing segment of the evolution from the initial surface alloy phase to the final Xene layer, which is the coexistence of both in a common stripe lattice during a continuous transition.

This study examines the thermal performance of building walls under full sunlight conditions using various insulation strategies. Specifically, it evaluates: (1) the effects of heat on building walls and indoor spaces; (2) the impact of groundwater cooling systems on thermal environments; (3) the influence of phenolic aldehyde insulation layers on heat transfer; and (4) the combined effects of groundwater cooling and phenolic aldehyde thermal insulation. Fluent–CFD (Computational Fluid Dynamics) was used in the study to simulate temperature transmission between the sun, the groundwater cooling system, and both indoor and outdoor spaces. Experimental analysis and simulations reveal that both the phenolic aldehyde insulation layer and the groundwater cooling system effectively reduce heat transfer, with the groundwater cooling system demonstrating the most significant impact. The phenolic aldehyde layer decreases the temperature difference between inner and outer walls by approximately 8 °C. The groundwater cooling system further reduces both inner and outer wall temperatures, helping to maintain cooler indoor environments. Simulation results indicate that, while the phenolic aldehyde layer effectively prevents external heat from penetrating into the room, it does not eliminate heat accumulation. In contrast, the groundwater cooling system efficiently dissipates heat, mitigating this issue. Groundwater analysis shows that maximum temperature differences occur at specific times of the day, with water flow effectively cooling the space. The combined use of the phenolic aldehyde insulation layer and the groundwater cooling system offers superior thermal performance. The phenolic layer provides effective heat blocking, while the groundwater system facilitates heat dissipation, optimizing indoor temperature and reducing air conditioning loads. This combination enhances overall comfort and energy efficiency, with the groundwater cooling system benefiting from reduced flow velocity and lower energy consumption.

Renal cell carcinoma (RCC) accounts for nearly 2% of cancers diagnosed worldwide. For metastatic RCC, targeted therapy is one of the most common treatment methods. It can include approaches that target vascular endothelial growth factor (VEGFR) or rely on immune checkpoint inhibitors or mTOR inhibitors. Adenosine A2A receptor (A2AR) is a type of widely distributed G-protein-coupled receptor (GPCR). Recently, an increasing number of studies suggest that the activation of A2AR can downregulate anti-tumor immune responses and prevent tumor growth. Currently, the data on A2AR antagonists in RCC treatment are still limited. Therefore, in this article, we further investigate the clinical trials investigating A2AR drugs in RCC. We also describe the epidemiology and current treatment of RCC, along with the physiological role of A2AR, and the types of A2AR drugs that are associated with tumor treatment.

Identifying and selecting the best cotton fabric from a series of available samples is a challenging multicriteria decision-making (MCDM) problem that includes fuzziness and uncertainty. Pythagorean fuzzy sets (PFSs) are widely used to manage complex and uncertain MCDM issues. The Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE) is a widely used classical MCDM to assess and rank alternatives. In this study, we use the PROMETHEE approach to solve a real case of ranking cotton fabrics in a PFS environment, where alternatives are compared based on the PFS linguistic scales, and a score function is used as a defuzzification function. A comparative analysis is also performed with different score functions. The ranking results of the proposed PF-PROMETHEE method correlate strongly with other score functions, which indicates that the PF-PROMETHEE method is feasible and effective. The salient contributions of the PF-PROMETHEE method are as follows: (1) the method can manage uncertainty better than other methods; (2) uncertainty is evaluated by linguistic scales in the PF environment; (3) the method can effectively select cotton woven fabric; and (4) the method is applicable to a wide variety of MCDM problems in the textile industry.

In the textile industry, selecting the optimal fabric is crucial in the design and production process. The multiple-criteria decision-making (MCDM) technique has been applied to address fabric selection problems. Because the sine trigonometry function maintains the periodicity and symmetry of the origin in nature, it satisfies the preferences of experts over multiple parameters. Considering the advantages of the sine trigonometry function, we introduce sine trigonometry Pythagorean fuzzy sets (ST-PFSs) and weighted averaging (ST-PFWA) and geometric (ST-PFWG) aggregation operators (AOs). Additionally, we propose a novel method based on ST-PFWA and ST-PFWG AOs to solve two different types of fabric selection MCDM problems. The first problem is provided by Pythagorean fuzzy numbers (PFNs), and we apply the proposed method to address the issue and conduct a comparative analysis with other PFS AOs. The second problem is offered with crisp values, and we apply a PFS linguistic term transform system to convert the values into PFNs. Then, we apply ST-PFWA and ST-PFWG AOs to settle the problem and perform a comparative analysis among different PFS linguistic terms. The complete ranking results illustrate that our proposed methodology is more efficient and reliable than previous approaches and can be used in other textile fields.

The comfortability of fabric is essential for improving its wearability, and several properties affect the comfort. Assessment and selection of the best cotton fabrics among these properties involving fuzziness and uncertainty are regarded as a multicriteria decision-making (MCDM) problem. This research proposed the technique for order preference by similarity to ideal solution (TOPSIS) approach under Pythagorean fuzzy sets (PFSs) context to select the best cotton fabric among these properties. The PFSs are used to handle uncertain information on cotton fabrics, and the TOPSIS approach is applied to choose the best cotton fabric. Since the distance measure is a critical factor of TOPSIS, a sensitivity analysis with different parameter settings for the distance measure is performed to investigate the ranking effects. A comparative analysis is conducted between the Hamming and Euclidean distance measurements and sine trigonometric Pythagorean fuzzy weighted average and geometric aggregation operators. The comparative results have significantly high correlation coefficients with other distance measures and aggregation operators. The novelties of the proposed approach are that it not only can offer objective evaluations but also can be easily calculated and obtain reliable and reasonable results, and it can be applied to other textile areas.

Cotton fabric selection is a challenging task in the garment product design and development process, and the selection of optimal alternative under the presence of multiple decision criteria becomes complex, and hence it is considered as a multi-criteria decision-making (MCDM) problem. In addition, the selection process involves fuzziness and uncertainty. In this study, Pythagorean fuzzy sets (PFSs) are introduced to handle uncertain information. Elimination and choice translating reality (ELECTRE) is a well-known outranking method for solving MCDM problems. Therefore, we extend the ELECTRE method under the PFS environment, and a correlation-based closeness coefficient is proposed to compare Pythagorean fuzzy numbers (PFNs). This paper applies the proposed PF-ELECTRE approach in solving a practical case involving the ranking cotton fabrics. To exhibit the superiority and robustness of the suggested method, sensitivity analysis is performed to examine the impacts of weights variation, as well as a comparative analysis is carried out between the PF-ELECTRE with several existing MCDM methods. The research contributes to the advancement and development of outranking MCDM methods through a novel PF-ELECTRE approach that utilizes the weighted correlation coefficient. Moreover, the developed method can obtain reliable results and can be used to other textile domains.

Selecting the best knitted fabric with various comfort properties is considered a complicated multi-criteria decision-making (MCDM) issue that involves ambiguity and vagueness. In such scenarios, Pythagorean fuzzy sets (PFSs) provide an effective tool for addressing uncertainty and ambiguity in MCDM problems that contain human subjective evaluations and judgments. First, this research identifies the factors affecting the comfort of knitted fabrics as the evaluation criteria. Second, the Bayesian best-worst method (BBWM) is preferred for less pairwise comparisons and obtains highly reliable results with a probabilistic perspective for determining the criteria weights. Furthermore, due to its logical computation approach and ease of operation, the technique for order preference by similarity to ideal solution (TOPSIS) is commonly utilized for addressing MCDM problems. Therefore, this research proposes an innovative MCDM framework that combines the BBWM technique with Pythagorean fuzzy TOPSIS (PFTOPSIS). The BBWM determines the criteria weights, and the weighted sine similarity-based PFTOPSIS is utilized to rank alternatives. The proposed BBWM-PFTOPSIS approach was employed to solve a real-world case. Moreover, this article conducts a sensitivity analysis and three comparative analyses to reveal the efficiency and reliability of the BBWM-PFTOPSIS approach. The ranking results establish the viability and effectiveness of BBWM-PFTOPSIS.

This article explores the potential of blockchain technology to enhance podcast content marketing. In the post-pandemic era, more and more enterprises are using podcasts for content marketing. However, the rapid growth of the podcast industry has also raised concerns. This study looks at current podcast advertising methods and uses a 10-step process to examine the need for a blockchain platform. With the decentralization, transparency and traceability of the blockchain and five smart contracts, the new distributed podcast platform improves content marketing metrics and reduces transaction costs. It provides enterprises with a more robust podcast platform, as well as more opportunities for niche creators to showcase and optimize the podcast platform as a useful advertising and marketing tool.

Lung cancer, one of the most common causes of cancer-related death worldwide, has been associated with high treatment cost and imposed great burdens. The 5-year postoperative survival rate of lung cancer (13%) is lower than many other leading cancers indicating the urgent needs to dissect its pathogenic mechanisms and discover specific biomarkers. Although several proteins have been proposed to be potential candidates for the diagnosis of lung cancer, they present low accuracy in clinical settings. Metabolomics has thus emerged as a very promising tool for biomarker discovery. To date, many lung cancer-related metabolites have been highlighted in the literature but no database is available for scientists to retrieve this information. Herein, we construct and introduce the first Lung Cancer Metabolome Database (LCMD), a freely available online database depositing 2013 lung cancer-related metabolites identified from 65 mass spectrometry-based lung cancer metabolomics studies. Researchers are able to explore LCMD via two ways. Firstly, by applying various filters in the “Browse Metabolites” mode, users can access a list of lung cancer-related metabolites that satisfy the filter specifications. For each metabolite, users can acquire the value of the fold change (cancer/normal), statistical significance (p-value) of the fold change, and the comparative research designs of all the mass spectrometry-based lung cancer metabolomics studies that identify this metabolite. Secondly, by applying various filters in the “Browse Studies” mode, users can obtain a list of mass spectrometry-based lung cancer metabolomics studies that satisfy the filter specifications. For each study, users can view the type of studied specimen, mass spectrometry (MS) method, MS data processing software, and differential analysis method, as well as all the identified lung cancer-related metabolites. Furthermore, the overview of each study is clearly illustrated by a graphical summary. The LCMD (http://cosbi7.ee.ncku.edu.tw/LCMD/) is the first database that brings together the meaningful information of lung cancer-related metabolites. The development of the LCMD is envisioned to promote the biomarker discovery of lung cancer.

The forest land carbon storage assessment model proposed in this study belongs to the IPPC Tier-3 method. The model operates through a conceptual model that includes environmental parameters such as Photosynthesis Index (NDVI), Soil Depth Index (TWI) and Canopy Height Model (CHM). The model is verified by the IPPC Tier-2 method, which can effectively construct the distribution of watershed-scale forest carbon stock. The spatial distribution of carbon fluxes can be obtained from the carbon stock information of the two periods. The carbon flux index can be used to describe the distribution of carbon stocks and carbon emissions in the watershed, and then the location of negative carbon flux (vegetation degradation) can be extracted as a value-added application of vegetation restoration hotspots. The accuracy of the model estimation in forest land verification is high, reaching a significant level of 0.1%, which can faithfully reflect the carbon stock of forest land. However, in non-forest lands, carbon stock estimates tend to exhibit carbon storage potential due to land-use disturbances. A combination of conceptual models and environmental indicators is of great help in assessing watershed carbon stocks and fluxes.

Objective To evaluate the effects of classical markers, novel serological biomarkers and other markers on the diagnosis of acute mesenteric ischemia (AMI).Methods PubMed and Embase were searched by computer to collect and evaluate the studies on serum markers of AMI from the estab-lishment of the database to August 15, 2020. Qualitative induction was conducted for the included studies.Results A total of 28 studies, including 5 meta-analysis, 7 prospective studies, 8 retrospective studies, 4 cross-sectional studies and 4 animal studies, were included. The speciality and sensitivity of classic markers (L-lactic acid, D-lactic acid and LDH) were low. The new serological biomarkers (D-dimer, platelet index, neutrophil-lymphocyte ratio, ischemia modifies albumin, 1-fatty acid binding protein, a-glutathione s-transferase, citruline) and other markers of AMI can be improved to some ex-tent, but the diagnostic value is still relatively limited.Conclusion The diagnostic value of serum bi-omarkers of AMI is limited, and it is still difficult for those markers to be used to diagnose AMI in differ-ent types and stages. High-quality and large-sample studies are still needed to confirm it.

Computer-aided methods can be used to screen potential candidate targets and to reduce the time and cost of drug development. In most of these methods, synthetic lethality is used as a therapeutic criterion to identify drug targets. However, these methods do not consider the side effects during the identification stage. This study developed a fuzzy multi-objective optimization for identifying anti-cancer targets that not only evaluated cancer cell mortality, but also minimized side effects due to treatment. We identified potential anti-cancer enzymes and antimetabolites for the treatment of head and neck cancer (HNC). The identified one- and two-target enzymes were primarily involved in six major pathways, namely, purine and pyrimidine metabolism and the pentose phosphate pathway. Most of the identified targets can be regulated by approved drugs; thus, these drugs are potential candidates for drug repurposing as a treatment for HNC. Furthermore, we identified antimetabolites involved in pathways similar to those identified using a gene-centric approach. Moreover, HMGCR knockdown could not block the growth of HNC cells. However, the two-target combinations of (UMPS, HMGCR) and (CAD, HMGCR) could achieve cell mortality and improve metabolic deviation grades over 22% without reducing the cell viability grade.

Abstract This study aimed to explore the associations between renal-related and arterial stiffness biomarkers with all-cause and expanded cardiovascular disease (CVD) mortality in a general Taiwanese population. This prospective community-based cohort study included 4883 subjects aged ≥ 20 years who were followed up until December 31, 2016. Renal-related biomarkers consisted of blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), and urine albumin-to-creatinine ratio (UACR). Arterial stiffness biomarker consisted of brachial-ankle pulse wave velocity (baPWV). The death status of the subjects was ascertained by matching information from death records with the identification number and date of birth of the subjects. Cox proportional hazard models with restricted cubic splines estimated the hazard ratios and 95% confidence intervals for all-cause mortality and expanded CVD mortality. During a mean 8.3 years of follow up, 456 deaths were recorded, 146 of which were due to expanded CVD mortality. The multivariable-adjusted hazard ratios of all-cause mortality was 1.53 (95% CI 1.21–1.94) for BUN (≥ 20 mg/dL vs.

Abstract Background Translational regulation is one important aspect of gene expression regulation. Dysregulation of translation results in abnormal cell physiology and leads to diseases. Ribosome profiling (RP), also called ribo-seq, is a powerful experimental technique to study translational regulation. It can capture a snapshot of translation by deep sequencing of ribosome-protected mRNA fragments. Many ribosome profiling data processing tools have been developed. However, almost all tools analyze ribosome profiling data at the gene level. Since different isoforms of a gene may produce different proteins with distinct biological functions, it is advantageous to analyze ribosome profiling data at the isoform level. To meet this need, previously we developed a pipeline to analyze 610 public human ribosome profiling data at the isoform level and constructed HRPDviewer database. Results To allow other researchers to use our pipeline as well, here we implement our pipeline as an easy-to-use software tool called RPiso. Compared to Ribomap (a widely used tool which provides isoform-level ribosome profiling analyses), our RPiso (1) estimates isoform abundance more accurately, (2) supports analyses on more species, and (3) provides a web-based viewer for interactively visualizing ribosome profiling data on the selected mRNA isoforms. Conclusions In this study, we developed RPiso software tool ( http://cosbi7.ee.ncku.edu.tw/RPiso/ ) to provide isoform-level ribosome profiling analyses. RPiso is very easy to install and execute. RPiso also provides a web-based viewer for interactively visualizing ribosome profiling data on the selected mRNA isoforms. We believe that RPiso is a useful tool for researchers to analyze and visualize their own ribosome profiling data at the isoform level.

Abstract Background Formosan Pangolin (Manis pentadactyla pentadactyla) is one of the three subspecies of Chinese pangolins, it is also an isolated sub-species naturally habitat in Taiwan. Despite earlier report on successful breeding of Sunda (Manis javanica) pangolin, breeding of Formosan pangolins in zoo captive populations is still challenging due to unknown reproductive characterizations of this species in both male and female populations. Results We characterized for the first time, reproductive tract of male Formosan pangolin. We showed pangolin epididymis was a collagen-enriched organ with apparent segmented sub-regions similar to other mammals. However, unlike most mammals exhibited two V-ATPase subunits, Formosan pangolin exhibited only V-ATPase subunit 2. This specific V-ATPase subunit extended its cellular localization throughout the cytoplasm of epididymal clear cells, suggesting pH regulation of luminal microenvironment might be different from other mammals. Electron micrographs showed rod-shaped pangolin sperm cells with multi-lamellar membrane structure at the sperm head. Similar to well-defined capacitation and acrosome reaction membrane changes in other mammals, we reported three distinct patterns (homogenous, punctuated and faded) of pangolin sperm head membrane changes. The concurrent increase in phosphotyrosine protein expression detected at the sperm mid-piece/tail and the emergence of punctuated membrane aggregates likely representing three sperm activation stages, namely inactivated, capacitated and acrosome reacted status of pangolin sperm. Conclusion By revealing unique epididymal V-ATPase distribution and sperm membrane dynamics in Formosan pangolin, we would understand better the fundamental aspects of reproduction parameters of Formosan pangolin.

Abstract Background Papillary thyroid carcinoma (PTC), which is the most common endocrine malignancy, has been steadily increasing worldwide in incidence over the years, while mechanisms underlying the pathogenesis and diagnostic for PTC are incomplete. The purpose of this study is to identify potential biomarkers for diagnosis of PTC, and provide new insights into pathogenesis of PTC. Methods Based on weighted gene co-expression network analysis, Robust Rank Aggregation, functional annotation, GSEA and DNA methylation, were employed for investigating potential biomarkers for diagnosis of PTC. Results Black and turquoise modules were identified in the gene co-expression network constructed by 1807 DEGs that from 6 eligible gene expression profiles of Gene Expression Omnibus database based on Robust Rank Aggregation and weighted gene co-expression network analysis. Hub genes were significantly down-regulated and the expression levels of the hub genes were different in different stages in hub gene verification. ROC curves indicated all hub genes had good diagnostic value for PTC (except for ABCA6 AUC = 89.5%, the 15 genes with AUC > 90%). Methylation analysis showed that hub gene verification ABCA6, ACACB, RMDN1 and TFPI were identified as differentially methylated genes, and the decreased expression level of these genes may relate to abnormal DNA methylation. Moreover, the expression levels of 8 top hub genes were correlated with tumor purity and tumor-infiltrating immune cells. These findings, including functional annotations and GSEA provide new insights into pathogenesis of PTC. Conclusions The hub genes and methylation of hub genes may as potential biomarkers provide new insights for diagnosis of PTC, and all these findings may be the direction to study the mechanisms underlying of PTC in the future.

Abstract Background Bladder cancer is the most common cancer in the urinary system and the fourth most common cancer in males. This study aimed to examine differences in the survival of bladder cancer patients of different ethnicities. Method We used the SEER database to obtain data pertaining to bladder cancer patients from 2010 to 2015. Univariate and multivariate Cox proportional hazards regression analyses were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between ethnicity and death. Kaplan–Meier survival and nomogram analyses were used to compare survival differences among patients with different ethnicities. Results Among 101,364 bladder cancer patients, 90,910 were white, 5893 were black, 337 were American Indian/Alaska Native (AIAN), and 4224 were Asian or Pacific Islander (API). Our multivariate analysis identified differences between different ethnicities. Compared to the API group, the AIAN (HR = 1.31, 95% CI = 1.09–1.57, P

The spatio-temporal distribution of carbon storage is an important parameter in watershed management planning; how to use environmental indicators to estimate carbon storage in a certain area in real time is extremely important in green environmental management. This study proposes an innovative method that uses satellite images combined with digital terrain models to quickly establish a conceptual model for carbon storage estimation in the Liukui Experimental Forest in southern Taiwan based on environmental indicators, which can instantly reflect the spatial distribution of carbon storage. The normalized vegetation index (NDVI) was used to reflect the photosynthetic capacity of the tree community, the topographic wetness index (TWI) was used to reflect the soil depth, and the canopy height model (CHM) was used to reflect the tree volume. The relationship between model estimation and IPCC Tier-2 approach shows that the carbon stock index CSI-st (R2 = 0.8844, p

Introduction Hot flashes, the most bothering symptom of menopause, are linked to a metabolic inflammation. Due to estrogen deficiency in menopause, dysbiosis is observed. The intestinal barrier affects the interaction of microbiota in healthy or unhealthy individuals. This study investigates the relationship between hot flashes and gut permeability in postmenopausal women. Participants and design In this cross-sectional study, we divided 289 women, aged 40–65 years, into four groups based on their hot-flash severity: HF0: never experienced hot flashes; HFm: mild hot flashes; HFM: moderate hot flashes; HFS: severe hot flashes. The measured variables included the clinical parameters; hot flashes experience; fasting plasma levels of zonulin, fatty acid binding protein 2 (FABP2), endotoxin, and cytokines/chemokines. We used multiple linear regression analysis to evaluate the relationship between hot flashes and the previously mentioned gut barrier proteins. Settings The study was performed in a hospital medical center. Results The hot flashes had a positive tendency toward increased levels of circulating FABP2 (P-trend = 0.001), endotoxin (P-trend = 0.031), high-sensitivity C-reactive protein (hs-CRP) (P-trend = 0.033), tumor necrosis factor alpha (TNF-α) (P-trend = 0.017), and interferon-inducible protein-10 (IP10) (P-trend = 0.021). Spearman’s correlation analysis revealed significant correlations of FABP2 with endotoxin, TNF-α, monocyte chemoattractant protein-1, IP10, and hs-CRP in the 289 postmenopausal women included in this study. Linear regression analysis revealed that hot-flash severity had significant assoiciations with FABP2 (P-trend = 0.002), but not with zonulin. After adjusting for body mass index, age, and menopause duration, multivariate linear regression analysis revealed the differences between HFs (% difference (95% confidence interval), 22.36 (8.04, 38.59), P = 0.01) and HF0 groups in terms of FABP2 levels. Conclusions This study shows that hot flashes are significantly associated with FABP2 levels in postmenopausal women. It suggests that severe hot flashes are linked to an increase in intestinal barrier permeability and low-grade systemic inflammation.

As a critical component in green supply chain activities, green supplier selection modelled as the typical multicriteria group decision-making (MCGDM) problem, has received tremendous attention both from scholars and practitioners. This article aims to advance an integrated approach for precisely addressing this urgent problem under Pythagorean fuzzy (PF) scenario. Firstly, analytic hierarchy process (AHP) is utilized for computing criterion weights that comprehensively reflect the intention of decision makers (DMs). Secondly, extend the Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to PF scenario, and apply the newest magnitude comparison method and distance measure of PF sets in the $L_{p} -$ metric equation to accurately acquire the ranking indices, then obtain the different ranks of candidates along with the adjustment of DM's preference value to balance the group utility and individual regret. Thirdly, median ranking method (MRM) is employed to reach a consensus opinion for the differentiated ranks of candidates via the attribute-wise rank and linear programming model. Subsequently, a numerical example for an agri-food company in China is introduced to illustrate the feasibility of our AHP-VIKOR-MRM method. Finally, conduct the comparison with some available MCGDM methods with PF information to interpret the stability and practicability of our presented method.

The aim was to investigate the independent prognostic factors and construct a prognostic risk prediction model to facilitate the formulation of oral squamous cell carcinoma (OSCC) clinical treatment plan. We constructed a prognostic model using univariate COX, Lasso, and multivariate COX regression analysis and conducted statistical analysis. In this study, 195 randomly obtained sample sets were defined as training set, while 390 samples constituted validation set for testing. A prognostic model was constructed using regression analysis based on nine survival-associated metabolic genes, among which PIP5K1B, NAGK, and HADHB significantly down-regulated, while MINPP1, PYGL, AGPAT4, ENTPD1, CA12, and CA9 significantly up-regulated. Statistical analysis used to evaluate the prognostic model showed a significant different between the high and low risk groups and a poor prognosis in the high risk group (P < 0.05) based on the training set. To further clarify, validation sets showed a significant difference between the high-risk group with a worse prognosis and the low-risk group (P < 0.05). Independent prognostic analysis based on the training set and validation set indicated that the risk score was superior as an independent prognostic factor compared to other clinical characteristics. We conducted Gene Set Enrichment Analysis (GSEA) among high-risk and low-risk patients to identify metabolism-related biological pathways. Finally, nomogram incorporating some clinical characteristics and risk score was constructed to predict 1-, 2-, and 3-year survival rates (C-index = 0.7). The proposed nine metabolic gene prognostic model may contribute to a more accurate and individualized prediction for the prognosis of newly diagnosed OSCC patients, and provide advice for clinical treatment and follow-up observations.

IntroductionStudies on the association between adiponectin and leptin and anxiety and depression among postmenopausal women are limited. Therefore, the present study specifically evaluates the mutual relationships between adiponectin and leptin and anxiety and depression in postmenopausal women.Participants and designIn this cross-sectional study, a total of 190 women aged 40-65 years were enrolled. Depression symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D), and anxiety symptoms were evaluated using the Hamilton Anxiety Rating Scale (HAM-A). Fasting specimens were collected to measure sex hormone, glucose, insulin, and adipokine levels. Multiple linear regression analysis was performed to evaluate the associations between depression and anxiety and adipocyte-derived hormones.SettingsThe study was performed in a hospital medical center.ResultsAmong 190 enrolled postmenopausal women, Spearman's rank correlation analysis revealed significant correlations between CES-D and HAM-A (r = 0.715, P < 0.0001), between CES-D and adiponectin (p = 0.009) and leptin (p = 0.015), and between HAM-A and adiponectin (p = 0.01) and leptin (p = 0.001). The subjects with CES-D ≥ 16 and with HAM-A ≥ 18 had higher adiponectin levels than those with CES-D < 16 and HAM-A < 18, respectively. After adjusting for age, body mass index, exercise, alanine amino transferase and parameters of lipid profiles, Log adiponectin levels were found to be significantly associated with both CES-D and HAM-A, and Log leptin levels were only significantly associated with HAM-A.ConclusionsThe data show that adiponectin and leptin levels are significantly associated with depression and anxiety symptoms. These results suggest that higher adiponectin and lower leptin levels may serve as potential markers related to anxiety and mood in postmenopausal women. More future research that is designed to deal with the important confounders (e.g., population heterogeneity) is needed to investigate comprehensively on these associations.

This paper aims to utilize the core structure of linear programming technique for multidimensional analysis of preference (LINMAP) to propose a parametric LINMAP methodology for addressing multiple criteria group decision-making problems based on Pythagorean fuzzy sets. To compare Pythagorean membership grades, this paper presents a Hamming distance-based approach for identifying closeness-based order relations based on Pythagorean fuzzy closeness indices. The concept of comprehensive closeness measures is introduced to measure individual order consistency and inconsistency between subjective preference relations and objective order relations. In the spirit of LINMAP, this paper determines individual goodness of fit and poorness of fit and further constructs a novel parametric LINMAP model. The applicability of the developed approach is explored by a practical application of railway project investment. Some comparative analyses are conducted to demonstrate the usefulness and advantages of the proposed methodology.

This paper aims at developing a novel generalized distance measure of Pythagorean fuzzy (PF) sets and constructing a distance-based compromise approach for multiple criteria decision analysis (MCDA) within PF environments. The theory of Pythagorean fuzziness provides a representative model of nonstandard fuzzy sets; it is valuable for representing complex vague or imprecise information in many practical applications. The distance measure for Pythagorean membership grades is important because it can effectively quantify the separation between PF information. Based on the essential characteristics of PF sets (membership, non-membership, strength, and direction), this paper proposes several distance measures, namely, new Hamming and Euclidean distances and a generalized distance measure that is based on them for Pythagorean membership grades and for PF sets. Moreover, the useful and desirable properties of the proposed PF distance measures are investigated to evaluate their advantages and form a solid theoretical basis. In addition, to evaluate the performance of the proposed distance measures in practice, this paper establishes a PF-distance-based compromise approach for addressing MCDA problems that involve PF information. The effectiveness and practicability of the developed approach are further evaluated through a case study on bridge-superstructure construction methods. According to the application results and comparative analysis, the proposed PF distance measures are accurate and outperform other methods in handling the inherent uncertainties of evaluation information. Furthermore, the PF-distance-based compromise approach can accommodate the much higher degrees of uncertainty in real-life decision scenarios and effectively determine the priority ranking among candidate alternatives for managing complicated MCDA problems.

This paper presents a new compromising approach to multiple criteria group decision-making (MCGDM) for the treatment of uncertainty which is based on Pythagorean fuzzy (PF) sets. The present work intends to propose a novel linear programming technique for multidimensional analysis of preference (LINMAP) by way of some useful concepts related to PF dominance relations, individual consistency and inconsistency levels, and individual fit measurements. The concept of PF scalar function-based dominance measures is defined to conduct intracriterion comparisons concerning uncertain evaluation information based on Pythagorean fuzziness; moreover, several valuable properties are also investigated to demonstrate its effectiveness. For the assessment of overall dominance of alternatives, this paper provides a synthetic index, named a comprehensive dominance measure, which is the aggregation of the weighted dominance measures by combining unknown weight information and PF dominance measures of various criteria. For each decision-maker, this paper employs the proposed measures to evaluate the individual levels of rank consistency and rank inconsistency regarding the obtained overall dominance relations and the decision-maker's preference comparisons over paired alternatives. In the framework of individual fit measurements, this paper constructs bi-objective mathematical programming models and then provides their corresponding parametric linear programming models for generating the best compromise alternative. Realistic applications with some comparative analyses concerning railway project investment are implemented to demonstrate the appropriateness and usefulness of the proposed methodology in addressing actual MCGDM problems.

Taiwan is located in a subtropical region with high temperatures and humidity. Office spaces are located in air-enclosed rooms in buildings, where doors and windows remain closed and only a central air-conditioning system provides temperature adjustment and ventilation. Most offices in this area have office seating areas, document storage areas on both sides of the office, and multi-function devices, which can cause sick office syndrome in the employees. This study applied environmental monitoring technology to analyze the architectural form and indoor and outdoor air quality to propose improvement strategies addressing indoor temperature, relative humidity and air quality. Quality indices were used created to evaluate the improvement efficiency. The analysis results showed that the indoor temperature and relative humidity in staff seating areas can be effectively improved. The statistical analysis results of improved efficiency for PM2.5, PM10 concentrations and total suspended particulates showed that the average indicator values have been raised from 0.05 to 1.5, 2.45 to 4.02 and 0.91 to 3.54, respectively, for staff seating area and −0.01 to 2.82, 0.15 to 3.91 and 1.25 to 7.25, respectively, for photocopier areas. The ambient air quality of this office space has been significantly improved. This study can serve as an example of air quality improvement in traditional common office spaces.

Abstract Background Systemic inflammation associated with sepsis can induce neuronal hyperexcitability, leading to enhanced seizure predisposition and occurrence. Brain microglia are rapidly activated in response to systemic inflammation and, in this activated state, release multiple cytokines and signaling factors that amplify the inflammatory response and increase neuronal excitability. NADPH oxidase (NOX) enzymes promote microglial activation through the generation of reactive oxygen species (ROS), such as superoxide anion. We hypothesized that NOX isoforms, particularly NOX2, are potential targets for prevention of sepsis-associated seizures. Methods To reduce NADPH oxidase 2-derived ROS production, mice with deficits of NOX regulatory subunit/NOX2 organizer p47phox (p47phox−/−) or NOX2 major subunit gp91phox (gp91phox−/−) were used or the NOX2-selective inhibitor diphenyleneiodonium (DPI) was used to treat wild-type (WT) mice. Systemic inflammation was induced by intraperitoneal injection of lipopolysaccharide (LPS). Seizure susceptibility was compared among mouse groups in response to intraperitoneal injection of pentylenetetrazole (PTZ). Brain tissues were assayed for proinflammatory gene and protein expression, and immunofluorescence staining was used to estimate the proportion of activated microglia. Results Increased susceptibility to PTZ-induced seizures following sepsis was significantly attenuated in gp91phox−/− and p47phox−/− mice compared with WT mice. Both gp91phox−/− and p47phox−/− mice exhibited reduced microglia activation and lower brain induction of multiple proconvulsive cytokines, including TNFα, IL-1β, IL-6, and CCL2, compared with WT mice. Administration of DPI following LPS injection significantly attenuated the increased susceptibility to PTZ-induced seizures and reduced both microglia activation and brain proconvulsive cytokine concentrations compared with vehicle-treated controls. DPI also inhibited the upregulation of gp91phox transcripts following LPS injection. Conclusions Our results indicate that NADPH oxidases contribute to the development of increased seizure susceptibility in mice after sepsis. Pharmacologic inhibition of NOX may be a promising therapeutic approach to reducing sepsis-associated neuroinflammation, neuronal hyperexcitability, and seizures.

The purpose of this study was to investigate the protective effects of the water extract of fermented rice bran (FRB) on liver damage and intestinal injury in old rats fed a high-fat (HF) diet. Rice bran (RB) was fermented with Aspergillus kawachii, and FRB was produced based on a previous study. Male Sprague Dawley rats at 36 weeks of age were allowed free access to a standard rodent diet and water for 8 weeks of acclimation then randomly divided into four groups (six rats/group), including a normal control (NC) group (normal diet), HF group (HF diet; 60% of total calories from fat), HF + 1% FRB group (HF diet + 1% FRB w/w), and HF + 5% FRB group (HF diet + 5% FRB w/w). It was found that the antioxidant ability of FRB was significantly increased when compared to RB. After 8 weeks of feeding, the HF group exhibited liver damage including an increased non-alcoholic fatty liver disease score (hepatic steatosis and inflammation) and higher interleukin (IL)-1β levels, while these were attenuated in the FRB-treated groups. Elevated plasma leptin levels were also found in the HF group, but the level was down-regulated by FRB treatment. An altered gut microbiotic composition was observed in the HF group, while beneficial bacteria including of the Lactobacillaceae and Lachnospiraceae had increased after FRB supplementation. In conclusion, it was found that FRB had higher anti-oxidative ability and showed the potential for preventing liver damage induced by a HF diet, which might be achieved through regulating imbalanced adipokines and maintaining a healthier microbiotic composition.

This paper aims to present a novel outranking approach of the preference ranking organization method for enrichment evaluations (PROMETHEEs) based on Pythagorean fuzzy sets for multiple criteria decision analysis. The proposed method utilizes a novel Pythagorean fuzzy precedence index, which is based on the difference of scalar functions under anchored judgments with respect to the superiority/inferiority Pythagorean fuzzy numbers. To appropriately describe the hesitation between indifference and preference in the Pythagorean fuzzy context, this paper introduces useful precedence-based preference functions to establish the precedence relations based on pairwise comparisons. As a multiple criteria measure under Pythagorean fuzzy uncertainty, the concept of overall preference indices is identified at the aggregation stage to exploit certain rules for generating PROMETHEE flows. Next, this paper provides effective Pythagorean fuzzy PROMETHEE I and II ranking procedures to determine partial and complete preorders, respectively, among competing alternatives. The developed Pythagorean fuzzy PROMETHEE-based outranking approach is comparatively validated using a real-world application concerning the selection problem of bridge construction methods. The solution results along with a comparison analysis demonstrate that the proposed methodology outperforms the comparative approach in terms of reasonability and stability.

The aim of this paper is to develop a novel consensus ranking method that uses a mixed choice strategy for multiple criteria decision analysis (MCDA) under complex uncertainty based on Pythagorean fuzzy (PF) sets. The majority of MCDA methods have focused almost exclusively on “criterion-specific”choice tasks that are the tasks in which all alternatives are decomposed into distinct components and evaluated on specific criteria. However, in certain MCDA problems in practical applications, category-based choices tend to be more holistic in nature, especially in affective-like aspects. Therefore, this paper incorporates a mixed choice strategy (i.e., a combination of a category-based strategy and a criterion-specific strategy) into the core structure of the developed MCDA method. Furthermore, this paper utilizes the theory of Pythagorean fuzziness to provide a powerful modeling tool for complex and varied decision-making environments. Employing the developed concepts of a PF precedence index based on PF information and a disagreement indicator based on distances between rankings, this paper proposes a novel consensus ranking method by means of a comprehensive disagreement-based assignment model for addressing a mixed-choice-strategy-based MCDA problem in the PF context. As an application of the proposed methodology, a real-world case study of a luxury car selection problem is investigated. The application results, along with a comparative analysis, demonstrate the practicality and effectiveness of the developed approach, which is capable of handling hybrid category-based and criterion-specific choice tasks and managing complex uncertainty in practical situations.

Vincristine is a clinically used antimicrotubule drug for treating patients with lymphoma. Due to its property of increasing platelet counts, vincristine is also used to treat patients with immune thrombocytopenia. Moreover, antiplatelet agents were reported to be beneficial in thrombotic thrombocytopenic purpura (TTP). Therefore, we investigated the detailed mechanisms underlying the antiplatelet effect of vincristine. Our results revealed that vincristine inhibited platelet aggregation induced by collagen, but not by thrombin, arachidonic acid, and the thromboxane A2 analog U46619, suggesting that vincristine exerts higher inhibitory effects on collagen-mediated platelet aggregation. Vincristine also reduced collagen-mediated platelet granule release and calcium mobilization. In addition, vincristine inhibited glycoprotein VI (GPVI) signaling, including Syk, phospholipase Cγ2, protein kinase C, Akt, and mitogen-activated protein kinases. In addition, the in vitro PFA-100 assay revealed that vincristine did not prolong the closure time, and the in vivo study tail bleeding assay showed that vincristine did not prolong the tail bleeding time; both findings suggested that vincristine may not affect normal hemostasis. In conclusion, we demonstrated that vincristine exerts antiplatelet effects at least in part through the suppression of GPVI signaling. Moreover, this property of antiplatelet activity of vincristine may provide additional benefits in the treatment of TTP.

Abstract The development and differentiation of steroidogenic organs are controlled by Ad4BP/SF-1 (adrenal 4 binding protein/steroidogenic factor 1). Besides, lysosomal activity is required for steroidogenesis and also enables adrenocortical cell to survive during stress. However, the role of lysosomal activity on steroidogenic cell growth is as yet unknown. Here, we showed that lysosomal activity maintained Ad4BP/SF-1 protein stability for proper steroidogenic cell growth. Treatment of cells with lysosomal inhibitors reduced steroidogenic cell growth in vitro. Suppression of autophagy did not affect cell growth indicating that autophagy was dispensable for steroidogenic cell growth. When lysosomal activity was inhibited, the protein stability of Ad4BP/SF-1 was reduced leading to reduced S phase entry. Interestingly, treatment of cells with lysosomal inhibitors reduced glycolytic gene expression and supplying the cells with pyruvate alleviated the growth defect. ChIP-sequence/ChIP studies indicated that Ad4BP/SF-1 binds to the upstream region of Ccne1 (cyclin E1) gene during G1/S phase. In addition, treatment of zebrafish embryo with lysosomal inhibitor reduced the levels of the interrenal (adrenal) gland markers. Thus lysosomal activity maintains steroidogenic cell growth via stabilizing Ad4BP/SF-1 protein.

Ever since the introduction of Pythagorean fuzzy (PF) sets, many scholars have focused on solving multicriteria decision-making (MCDM) problems with PF information. The technique for order preference by similarity to ideal solutions (TOPSIS) is a well-known and effective method for MCDM problems. The objective of this study is to extend the TOPSIS to tackle MCDM problems under the PF environment. In this study, we develop a novel distance measure that considers the length, the angle, and the greater space, which reflect the properties of PF sets. Then, we apply the proposed distance measure in PF-TOPSIS to calculate the distances from the PF positive ideal solution and the PF negative ideal solution. Finally, we take the evaluation of emerging technology commercialization as an MCDM problem to illustrate the proposed approaches, and we then compare these approaches to demonstrate the scalar type PF-TOPSIS is the most feasible and effective approach in practice.

Growth of Xene, referred to as the analog of graphene made of atoms other than carbon, with higher lattice quality and more intrinsic electronic structures, is an important challenge to the development of two-dimensional (2D) materials. We report an approach using Pb-atom deposition to striped-phase (SP) germanene grown on Ag(111) to trigger it to a quasifreestanding phase (QP). Using low-energy electron diffraction (LEED) and scanning tunneling microscopy (STM), we demonstrate that the 2D monatomic Pb layer, instead of being on top, grows side-by-side with QP germanene, not only driving the SP-to-QP transition but further enhancing the lattice order of QP as revealed by the dramatic evolution of LEED-spot shape and uniform STM-imaged array of moiré patterns. Originally oriented at 30° to Ag(111), the QP germanene transits first to a narrow distribution of rotations then to two sharp domains at ±3° from 30°, while the monoatomic Pb domains twist from ±4.3° to ±9.5° with respect to Ag(111). The analysis of higher-order coincidence for both layers on Ag(111) is in complete agreement with LEED results and reveals a picture of two insoluble monatomic layers driving each other to a more optimal configuration. Moreover, the corresponding density of states measured by scanning tunneling spectroscopy for quality-enhanced QP germanene exhibits a clear V-shape distribution at the energy ∼0.4 eV above Fermi level, indicating the Fermi-Dirac cone, which agrees with our density functional theory calculation.

Atmospheric particulate matters (PMs) were measured in an industry-intensive region in central Taiwan in order to investigate the characteristics and possible sources of PMs. The samplings were simultaneously conducted using a 10- and 3-stage Micro Orifice Uniform Deposit Impactor (MOUDI) from 2017 to 2018. In this study, the characteristics of PMs in this region were evaluated by measuring the mass concentration of PMs and analyzing water-soluble ions and metallic elements, as well as dioxins. Additionally, principal component analysis (PCA) was used to identify the potential sources of PMs. The results showed that the mean concentration of coarse (>1.8 μm), fine (0.1–1.8 μm), and ultrafine (3, respectively. In the industry-intensive region, the size distribution of ambient particles showed a bi-modal distribution with a high concentration of coarse particles in the spring and summer, while fine particles were dominant in the autumn and winter. The most abundant water-soluble ions of PMs were NO3−, Cl−, and SO42−, while the majority of metallic elements were Na, Fe, Ca, Al, and Mg in different particle sizes. The results of Pearson’s correlation analysis for metals indicated that the particles in the collected air samples were related to the iron and steelmaking industries, coal burning, vehicle exhausts, and high-tech industries. The dioxin concentration ranged from 0.0006 to 0.0017 pg I-TEQ/Nm3. Principal component analysis (PCA) revealed that the contribution to PMs was associated with sea salt, secondary pollutants, and industrial process.

Corrosion prevention and infrared (IR) stealth are conflicting goals. While graphene nanosheets (GN) provide an excellent physical barrier against corrosive agent diffusion, thus lowering the permeability of anti-corrosion coatings, they have the side-effect of decreasing IR stealth. In this work, the anti-corrosion properties of 100-μm-thick composite epoxy coatings with various concentrations (0.01–1 wt.%) of GN fillers thermally reduced at different temperatures (300 °C, 700 °C, 1100 °C) are first compared. The performance was characterized by potentiodynamic polarization scanning, electrochemical impedance spectroscopy, water contact angle and salt spray tests. The corrosion resistance for coatings was found to be optimum at a very low filler concentration (0.05 wt.%). The corrosion current density was 4.57 × 10−11 A/cm2 for GN reduced at 1100 °C, showing no degradation after 500 h of salt-spray testing: a significant improvement over the anti-corrosion behavior of epoxy coatings. Further, to suppress the high IR thermal signature of GN and epoxy, Al was added to the optimized composite at different concentrations. The increased IR emissivity due to GN was not only eliminated but was in fact reduced relative to the pure epoxy. These optimized coatings of Al-GN-epoxy not only exhibited greatly reduced IR emissivity but also showed no sign of corrosion after 500 h of salt spray test.

Septins are GTP-binding proteins that form heteromeric filaments for proper cell growth and migration. Among the septins, septin7 (SEPT7) is an important component of all septin filaments. Here we show that protein kinase A (PKA) phosphorylates SEPT7 at Thr197, thus disrupting septin filament dynamics and ciliogenesis. The Thr197 residue of SEPT7, a PKA phosphorylating site, was conserved among different species. Treatment with cAMP or overexpression of PKA catalytic subunit (PKACA2) induced SEPT7 phosphorylation, followed by disruption of septin filament formation. Constitutive phosphorylation of SEPT7 at Thr197 reduced SEPT7‒SEPT7 interaction, but did not affect SEPT7‒SEPT6‒SEPT2 or SEPT4 interaction. Moreover, we noted that SEPT7 interacted with PKACA2 via its GTP-binding domain. Furthermore, PKA-mediated SEPT7 phosphorylation disrupted primary cilia formation. Thus, our data uncover the novel biological function of SEPT7 phosphorylation in septin filament polymerization and primary cilia formation.

Combined chemotherapy is an effective and safe treatment for cancers. Co-administration of cisplatin and gemcitabine produces a synergistic effect for bladder cancer treatment, so viscous microemulsions were developed for co-delivery of cisplatin and gemcitabine to extend the retention time and improve the permeability of chemotherapeutic drugs into the urothelium by intravesical administration. Results showed that the deposition amounts of cisplatin and gemcitabine significantly increased in in vitro and in vivo study. The penetration depth in bladder tissue samples increased from 60 to 120 μm. The dual-loaded formulation also showed thermodynamic and chemical stability, demonstrating that these gel-based microemulsions are promising drug delivery carriers for chemotherapy agents by intravesical administration.

Beyond fertility, follicle-stimulating hormone (FSH) may exert action on adipocytes, which are the major source of adiponectin and leptin, linking to insulin resistance. Therefore, we evaluated the relationships between FSH and adipocyte-derived hormones. This cross-sectional study enrolled postmenopausal women aged 40–65 years. The variables measured in this study included clinical parameters, fasting levels of sex hormones, glucose, insulin, and adipokines. A total of 261 women without breast cancer, 88 women with breast cancer receiving tamoxifen, and 59 women with breast cancer receiving additional gonadotropin-releasing hormone analogs were enrolled in this study. Significant differences in the levels of adiponectin, leptin, and FSH were observed between the non-breast cancer group and the breast cancer groups. Spearman’s rank test revealed significant associations of FSH with either body mass index (BMI) or homeostatic model assessment of insulin resistance (HOMA-IR) values in the non-breast cancer group. After adjusting for BMI, age, and menopause duration, FSH levels were significantly associated with adiponectin (p < 0.001) and the leptin-to-adiponectin ratio (p = 0.008) in the non-breast cancer group, but they were only significantly associated with adiponectin (p = 0.001) in the breast cancer group receiving tamoxifen. Our data show that FSH levels are independently associated with adiponectin levels in postmenopausal women, suggesting that adiponectin may link FSH to metabolic relationships in postmenopausal female.

Myocardial infarction and cerebral ischemic stroke during the process of arterial thrombosis are prominently causes of death worldwide. Platelets are anucleated cells and play a critical factor in these diseases. Columbianadin (CBN), a coumarin derivative from plants, inhibits effective platelet activation. In this study, platelet function analysis revealed that the closure time of the platelet plug in human whole blood significantly prolonged by CBN, whereas CBN did not pointedly prolong the bleeding time in mice. BAY11-7082 (an inhibitor of IκB kinase) and MG-132 (an inhibitor of proteasome) inhibited collagen-stimulated platelet aggregation and ATP-release in human platelets, BAY11-7082 exhibited a higher potency than MG-132. Moreover, CBN markedly reduced NF-κB activation (e.g., IκBα and p65 phosphorylation) and reversed IκBα degradation in activated platelets. We investigated intercellular signaling events between mitogen-activated protein kinases and NF-κB, and found that BAY11-7082 abolished JNK1/2 and ERK1/2 phosphorylation. Interestingly, SP600125 (an inhibitor of JNK) but not PD98059 (an inhibitor of ERK) had no effect in NF-κB activation in activated platelets. Moreover, CBN but not BAY11-7082 significantly reduced hydroxyl radical (HO●) formation in platelets. Therefore, we propose that CBN inhibits NF-κB activation in human platelets and could present a potent clinical treatment for thromboembolic diseases.

Intravesical administration of chemotherapeutic agents can enhance drug accumulation in tumors and reduce systemic side effects. Nanocarriers were developed for intravesical administration and exploit the permeation enhancement effect. In vitro permeation evaluation, the drug transdermal amount and accumulation amounts in the tissue of gemcitabine-loaded nanocarriers through biological membrane significantly increased about 14.8~33.0-fold and 1.5~14.1-fold respectively, when compared to a control group of 1% gemcitabine saline solution. In in vivo intravesical administration, the drug accumulation amount in bladder tissue of nanocarrier of 75.2 ± 5.4 μg was revealed as being comparably higher than that of the control group of 44.8 ± 6.4 μg. In confocal laser scanning microscopy imagery, the penetration depth of fluorescent dyes-rhodamine was increased from 80 μm up to 120 μm when a nanocarrier was used. This result implies that the nanocarrier is a promising drug delivery agent for intravesical administration.

The role a pharmacist plays in the care of patients is continually changing and expanding. Most recently, there is movement towards including pharmacists in the physical assessment of patients. We developed a creative movement workshop with the purpose of increasing students’ levels of comfort with touch, ability to interpret non-verbal mannerisms, to increase empathy for the patient, and to increase student comfort in conducting physical exams. In this interventional study, surveys were administered to third year pharmacy students, before and after the creative movement workshop, in order to assess participant’s change in level of comfort with a variety of behaviors needed to conduct effective physical assessment. The two hour workshop involved: partner stretching, mirroring, and creative spatial exploration between bodies. The 11-item survey evaluated students’ perceptions on touch, nonverbal communication, and sharing personal space. Our results showed that the level of comfort improved for the ability to give touch (p = 0.001), the ability to receive touch (p = 0.002), and the ability to share personal space (p = 0.001). Participants commented that the workshop increased their understanding of how important confidence is when performing physical assessment and reported an increased appreciation for how much non-verbal mannerisms can communicate to another. This study explores how an interdisciplinary workshop between pharmacy and dance has the potential to increase student effectiveness as future healthcare professionals, by targeting skills not often focused on within traditional pharmacy curriculums, including: sharing personal space, displaying empathy, and providing a comforting and confident touch.

[This corrects the article DOI: 10.1371/journal.pone.0205953.].