bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Music and White Noise Exposure on the Gut Microbiota, Oxidative Stress, and Immune-Related Gene Expression of Mice
Authors: Zhang Zhenyu , Wu Yinqiang , Zhou Shizheng , Fu Pengcheng , Yan Hong
Published: September 2023

The microbiota in gastrointestinal tracts is recognized to play a pivotal role in the health of their hosts. Music and noise are prevalent environmental factors in human society and animal production and are reported to impact their welfare and physiological conditions; however, the information on the relationship between the microbiota, physiological status, and sound is limited. This study investigated the impact of music and white noise exposure in mice through 16s rRNA gene sequencing, enzyme assay, and qPCR. The results demonstrate that white noise induced oxidative stress in animals by decreasing serum SOD and GSH-PX activity while increasing LDH activity and MDA levels (p < 0.05). Conversely, no oxidative stress was observed in the music treatment group. The relative gene expression of IFN-γ and IL-1β decreased in the white noise group compared to the music and control groups. The 16s rRNA gene amplicon sequencing revealed that Bacteroidetes, Firmicutes, Verrucomicrobia, and Proteobacteria were dominant among all the groups. Furthermore, the proportion of Firmicutes increased in the music treatment group but decreased in the white noise treatment group compared to the control group. In conclusion, white noise has detrimental impacts on the gut microbiota, antioxidant activity, and immunity of mice, while music is potentially beneficial.
Comparison of Structural Features of CRISPR-Cas Systems in Thermophilic Bacteria
Authors: Wang Chuan , Yang Yuze , Tang Shaoqing , Liu Yuanzi , Wei Yaqin , Wan Xuerui , Liu Yajuan , Zhang Zhao , Sunkang Yongjie
Published: September 2023

The clustered regularly interspaced short palindromic repeat (CRISPR) is an adaptive immune system that defends most archaea and many bacteria from foreign DNA, such as phages, viruses, and plasmids. The link between the CRISPR-Cas system and the optimum growth temperature of thermophilic bacteria remains unclear. To investigate the relationship between the structural characteristics, diversity, and distribution properties of the CRISPR-Cas system and the optimum growth temperature in thermophilic bacteria, genomes of 61 species of thermophilic bacteria with complete genome sequences were downloaded from GenBank in this study. We used CRISPRFinder to extensively study CRISPR structures and CRISPR-associated genes (cas) from thermophilic bacteria. We statistically analyzed the association between the CRISPR-Cas system and the optimum growth temperature of thermophilic bacteria. The results revealed that 59 strains of 61 thermophilic bacteria had at least one CRISPR locus, accounting for 96.72% of the total. Additionally, a total of 362 CRISPR loci, 209 entirely distinct repetitive sequences, 131 cas genes, and 7744 spacer sequences were discovered. The average number of CRISPR loci and the average minimum free energy (MFE) of the RNA secondary structure of repeat sequences were positively correlated with temperature whereas the average length of CRISPR loci and the average number of spacers were negatively correlated. The temperature did not affect the average number of CRISPR loci, the average length of repeats, or the guanine-cytosine (GC) content of repeats. The average number of CRISPR loci, the average length of the repeats, and the GC content of the repeats did not reflect temperature dependence. This study may provide a new basis for the study of the thermophilic bacterial adaptation mechanisms of thermophilic bacteria.
Diversity and Network Relationship Construction of Soil Fungal Communities in Lactarius hatsudake Tanaka Orchard during Harvest
Authors: Shen Airong , Shen Baoming , Liu Lina , Tan Yun , Zeng Liangbin , Tan Zhuming , Li Jilie
Published: September 2023

Lactarius hatsudake Tanaka is a mycorrhizal edible mushroom with rich economic and nutritional value. Although it is artificially planted, its yield is unstable. Soil fungi, including L. hatsudake, coexist with many other microorganisms and plants. Therefore, complex microbial communities have an influence on the fruiting body formation of L. hatsudake. L. hatsudake and its interactions with the rest of the fungal community over time are not completely understood. In this study, we performed high-throughput sequencing of microorganisms in the basal soil of the fruiting body (JT), mycorrhizosphere soil (JG), and non-mushroom-producing soil (CK) in a 6-year-old L. hatsudake plantation at harvest. The results showed that the soil of the L. hatsudake plantation was rich in fungal communities and a total of 10 phyla, 19 classes, 53 orders, 90 families, 139 genera, and 149 species of fungi were detected. At the phylum level, the major groups were Basidiomycota and Ascomycota. At the genus level, the dominant groups were Lactarius, Trichoderma, Suillus, and Penicillium. Among them, L. hatsudake had an absolute dominant position in the soil fungal community of the plantation, and was the only group of Lactarius in the plantation soil. Penicillium cryptum and Penicillium adametzii were unique to the JT soil sample. Chaetopsphaeria, Myxocephala, Devriesia, and Psathyrella were positively correlated with L. hatsudake. In the constructed fungal network, the total number of nodes were ranked in descending order as JG (441) > CK (405) > JT (399), while the total number of edges were ranked in descending order as CK (1360) > JG (647) > JT (586). Analysis of the fungal assembly process revealed that groups CK and JG have determinative processes that dominated community building, while the JT group exhibited a dominant random process with a 0.60 probability. The results indicated that L. hatsudake was successfully colonized in the plantation soil. During harvest, the CK group exhibited the largest network size and the most complex fungal interactions, while the fungal community structure in the mushroom cultivation zone (JT and JG) was stable and less susceptible to external environmental interference. L. hatsudake affects the fungal community in the soil surrounding its fruiting body.
Design and Assessment of a Novel In Silico Approach for Developing a Next-Generation Multi-Epitope Universal Vaccine Targeting Coronaviruses
Authors: Rasheed Muhammad Asif , Raza Sohail , Alonazi Wadi B. , Ashraf Muhammad Adnan , Navid Muhammad Tariq , Aslam Irfana , Iqbal Muhammad Nasir , Rahman Sarfraz Ur , Riaz Muhammad Ilyas
Published: September 2023

In the past two decades, there have been three coronavirus outbreaks that have caused significant economic and health crises. Biologists predict that more coronaviruses may emerge in the near future. Therefore, it is crucial to develop preventive vaccines that can effectively combat multiple coronaviruses. In this study, we employed computational approaches to analyze genetically related coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants, focusing on the spike glycoprotein as a potential vaccine candidate. By predicting common epitopes, we identified the top epitopes and combined them to create a multi-epitope candidate vaccine. The overall quality of the candidate vaccine was validated through in silico analyses, confirming its antigenicity, immunogenicity, and stability. In silico docking and simulation studies suggested a stable interaction between the multi-epitope candidate vaccine and human toll-like receptor 2 (TLR2). In silico codon optimization and cloning were used to further explore the successful expression of the designed candidate vaccine in a prokaryotic expression system. Based on computational analysis, the designed candidate vaccine was found to be stable and non-allergenic in the human body. The efficiency of the multi-epitope vaccine in triggering effective cellular and humoral immune responses was assessed through immune stimulation, demonstrating that the designed candidate vaccine can elicit specific immune responses against multiple coronaviruses. Therefore, it holds promise as a potential candidate vaccine against existing and future coronaviruses.
Past and Ongoing Field-Based Studies of Myxomycetes
Authors: Stephenson Steven L.
Published: September 2023

Evidence from molecular studies indicates that myxomycetes (also called myxogastrids or plasmodial slime molds) have a long evolutionary history, and the oldest known fossil is from the mid-Cretaceous. However, they were not “discovered” until 1654, when a brief description and a woodcut depicting what is almost certainly the common species Lycogala epidendrum was published. First thought to be fungi, myxomycetes were not universally recognized as completely distinct until well into the twentieth century. Biodiversity surveys for the group being carried out over several years are relatively recent, with what is apparently the first example being carried out in the 1930s. Beginning in the 1980s, a series of such surveys yielded large bodies of data on the occurrence and distribution of myxomycetes in terrestrial ecosystems. The most notable of these were the All Taxa Biodiversity Inventory (ATBI) project carried out in the Great Smoky Mountains National Park, the Planetary Biodiversity Inventory Project (PBI) carried out in localities throughout the world, and the Myxotropic project being carried out throughout the Neotropics. The datasets available from both past and ongoing surveys now allow global and biogeographical patterns of myxomycetes to be assessed for the first time.
The Association between Gut Microbiota and Depression in the Japanese Population
Authors: Yang Yichi , Mori Mone , Wai Kyi Mar , Jiang Tao , Sugimura Yoshikuni , Munakata Wataru , Mikami Tatsuya , Murashita Koichi , Nakaji Shigeyuki , Ihara Kazushige
Published: September 2023

Depression is a leading cause of disease worldwide. The association between gut microbiota and depression has barely been investigated in the Japanese population. We analyzed Iwaki health check-up data collected from 2017 to 2019 and constructed generalized linear mixed models. The independent variable was the relative abundance of each of the 37 gut microbiota genera that were reported to be associated with depression. The dependent variable was the presence of depression assessed by the Center for Epidemiologic Studies Depression Scale. Potential confounders, including grip strength, gender, height, weight, smoking, and drinking habits, were adjusted in the regression models. Nine genera’s regression coefficients (Alistipes, Blautia, Coprococcus, Dorea, Faecalibacterium, Holdemania, Lactobacillus, Mitsuokella, and Oscillibacter) showed statistical significance after multiple comparisons adjustment. Among these nine gut bacteria genera, Alistipes, Blautia, Coprococcus, Dorea, Faecalibacterium, and Oscillibacter were reported to be associated with butyrate production in the intestine. Our results indicate that gut microbiotas may influence the depression condition of the host via the butyrate-producing process.
Development and Assessment of 1,5–Diarylpyrazole/Oxime Hybrids Targeting EGFR and JNK–2 as Antiproliferative Agents: A Comprehensive Study through Synthesis, Molecular Docking, and Evaluation
Authors: Abdelrahman Kamal S. , Hassan Heba A. , Abdel-Aziz Salah A. , Marzouk Adel A. , Shams Raef , Osawa Keima , Abdel-Aziz Mohamed , Konno Hiroyuki
Published: September 2023

New 1,5-diarylpyrazole oxime hybrid derivatives (scaffolds A and B) were designed, synthesized, and then their purity was verified using a variety of spectroscopic methods. A panel of five cancer cell lines known to express EGFR and JNK-2, including human colorectal adenocarcinoma cell line DLD-1, human cervical cancer cell line Hela, human leukemia cell line K562, human pancreatic cell line SUIT-2, and human hepatocellular carcinoma cell line HepG2, were used to biologically evaluate for their in vitro cytotoxicity for all the synthesized compounds 7a–j, 8a–j, 9a–c, and 10a–c. The oxime containing compounds 8a–j and 10a–c were more active as antiproliferative agents than their non-oxime congeners 7a–j and 9a–c. Compounds 8d, 8g, 8i, and 10c inhibited EGFR with IC50 values ranging from 8 to 21 µM when compared with sorafenib. Compound 8i inhibited JNK-2 as effectively as sorafenib, with an IC50 of 1.0 µM. Furthermore, compound 8g showed cell cycle arrest at the G2/M phase in the cell cycle analysis of the Hela cell line, whereas compound 8i showed combined S phase and G2 phase arrest. According to docking studies, oxime hybrid compounds 8d, 8g, 8i, and 10c exhibited binding free energies ranging from −12.98 to 32.30 kcal/mol at the EGFR binding site whereas compounds 8d and 8i had binding free energies ranging from −9.16 to −12.00 kcal/mol at the JNK-2 binding site.
Development and Comparative Evaluation of Two Different Label-Free and Sensitive Fluorescence Platforms for Analysis of Olaparib: A Recently FDA-Approved Drug for the Treatment of Ovarian and Breast Cancer
Authors: Darwish Ibrahim A. , Khalil Nasr Y.
Published: September 2023

Olaparib (OLA) is a PARP inhibitor drug which has been recently approved by the Food and Drug Administration (FDA) for the treatment of ovarian and breast cancer. A convenient analytical tool for the quantitation of OLA in its dosage form and plasma samples was urgently needed. This study describes, for the first time, the development of two different label-free and sensitive fluorescence-based platforms for the pharmaceutical and bioanalysis of OLA. These platforms were microwell-assisted with a fluorescence microplate reader (MW-FLR) and high-performance liquid chromatography with fluorescence detection (HPLC-FD). Both MW-FLR and HPLC-FD employed the native fluorescence of OLA as an analytical signal. The MW-FLR involved measuring the fluorescence signals in 96-well white-opaque plates. The HPLC-FD involved chromatographic separation of OLA and duvelisib (DUV), as an internal standard on a Nucleosil-CN HPLC column (250 mm length × 4.6 mm i.d., 5 µm particle diameter) with a mobile phase composed of acetonitrile: water (25:75, v/v) pumped at a flow rate of 1.7 mL/min. Elution of OLA and DUV was detected using a fluorescence detector. The optimal conditions of both MW-FLR and HPLC-FD were established, and they were validated according to the guidelines of the International Council for Harmonization for the validation of analytical procedures. The linear ranges of MW-FLR and HPLC-FD were 25–1000 and 5–200 ng/mL, respectively, with limits of detection of 15 and 1.7 ng/mL, respectively. The accuracy and precision of both platforms were confirmed as the recovery values were ≥98.2% and the relative standard deviations (RSD) were ≤2.89%. Both methodologies were satisfactorily applied to the quantitation of OLA in its commercial dosage form (Lynparza® tablets) and plasma samples with high accuracy and precision. The greenness of both MW-FLR and HPLC-FD was assessed using two different multiple parameter-based metric tools, and the results proved their greenness and adherence to the requirements of green analytical approaches. Both platforms have simple procedures and acceptable levels of analytical throughput. In conclusion, the proposed MW-FLR and HPLC-FD are valuable tools for routine use in quality control and clinical laboratories for the quantitation of OLA for the purposes of pharmaceutical quality control, pharmacokinetic studies, and bioequivalence testing.
The Competition between 4-Nitrophenol Reduction and BH4− Hydrolysis on Metal Nanoparticle Catalysts
Authors: Varshney Shalaka , Meyerstein Dan , Bar-Ziv Ronen , Zidki Tomer
Published: September 2023

Assessing competitive environmental catalytic reduction processes via NaBH4 is essential, as BH4− is both an energy carrier (as H2) and a reducing agent. A comprehensive catalytic study of the competition between the borohydride hydrolysis reaction (BHR, releasing H2) and 4-nitrophenol reduction via BH4− on M0- and M/M′ (alloy)-nanoparticle catalysts is reported. The results reveal an inverse correlation between the catalytic efficiency for BH4− hydrolysis and 4-nitrophenol reduction, indicating that catalysts performing well in one process exhibit lower activity in the other. Plausible catalytic mechanisms are discussed, focusing on the impact of reaction products such as 4-aminophenol and borate on the rate and yield of BH4− hydrolysis. The investigated catalysts were Ag0, Au0, Pt0, and Ag/Pt-alloy nanoparticles synthesized without any added stabilizer. Notably, the observed rate constants for the 4-nitrophenol reduction on Ag0, Ag-Pt (9:1), and Au0 are significantly higher than the corresponding rate constants for BH4− hydrolysis, suggesting that most reductions do not proceed through surface-adsorbed hydrogen atoms, as observed for Pt0 nanoparticles. This research emphasizes the conflicting nature of BH4− hydrolysis and reduction processes, provides insights for designing improved catalysts for competitive reactions, and sheds light on the catalyst properties required for each specific process.
Screening of Anti-Inflammatory Activity and Metabolomics Analysis of Endophytic Fungal Extracts; Identification and Characterization of Perylenequinones and Terpenoids from the Interesting Active Alternaria Endophyte
Authors: Spina Rosella , Ropars Armelle , Bouazzi Sihem , Dadi Safa , Lemiere Pascal , Dupire François , Khiralla Afra , Yagi Sakina , Frippiat Jean-Pol , Laurain-Mattar Dominique
Published: September 2023

Patients suffering from inflammatory chronic diseases are classically treated with anti-inflammatory drugs but unfortunately are highly susceptible to becoming resistant to their treatment. Finding new drugs is therefore crucial and urgent and research on endophytic fungi is a promising way forward. Endophytic fungi are microorganisms that colonize healthy plants and live within their intercellular tissues. They are able to produce a large variety of secondary metabolites while allowing their host to stay healthy. A number of these molecules are endowed with antioxidant or antimicrobial as well as cytotoxic properties, making them very interesting/promising in the field of human therapy. The aim of our study was to investigate whether extracts from five endophytic fungi isolated from plants are endowed with anti-inflammatory activity. Extracts of the endophytic fungi Alternaria alternata from Calotropis procera leaves and Aspergillus terreus from Trigonella foenum-graecum seeds were able to counteract the lipopolysaccharide (LPS) pro-inflammatory effect on THP-1 cells differentiated into macrophages. Moreover, they were able to induce an anti-inflammatory state, rendering them less sensitive to the LPS pro-inflammatory stimulus. Taken together, these results show that these both endophytic fungi could be interesting alternatives to conventional anti-inflammatory drugs. To gain more detailed knowledge of their chemical richness, phytochemical analysis of the ethyl acetate extracts of the five endophytic fungi studied was performed using HPTLC, GC-MS and LC-MS with the Global Natural Products Social (GNPS) platform and the MolNetEnhancer tool. A large family of metabolites (carboxylic acids and derivatives, steroid derivatives, alkaloids, hydroxyanthraquinones, valerolactones and perylenequinones) were detected. The purification of endophytic fungus extract of Alternaria alternate, which diminished TNF-α production of 66% at 20 µg/mL, incubated one hour before LPS addition, led to the characterization of eight pure compounds. These molecules are altertoxins I, II, III, tricycloalternarenes 3a, 1b, 2b, anthranilic acid, and o-acetamidobenzoic acid. In the future, all these pure compounds will be evaluated for their anti-inflammatory activity, while altertoxin II has been shown in the literature as the most active mycotoxin in terms of anti-inflammatory activity.
The Impact of Different Cooking Methods on the Flavor Profile of Fermented Chinese Spicy Cabbage
Authors: Li Huamin , Guan Hui , Zhang Xiru , Xing Shaohua , Liu Wenli , Kim In-Cheol , Gong Hansheng
Published: September 2023

Chinese spicy cabbage (CSC) is a common traditional fermented vegetable mainly made of Chinese cabbage. In addition to eating raw, boiling and stir-frying are the most common cooking methods for CSC. To identify the impacts of boiling or stir-frying on the quality of CSC, the physicochemical properties, flavor compounds, and sensory properties of CSC were analyzed. A total of 47 volatile flavor compounds (VFCs) were detected by gas chromatography–mass spectrometry. Sulfide was determined as the main flavor compound of CSC, mainly contributed by cabbage, garlic, and onion odors. The content of sulfide decreased significantly after cooking. Nonanal, geranyl acetate, and linalool were newly generated after boiling with odor activity value (OAV) > 1, and contributed fatty, sweet, fruity, and floral odors to BL-CSC. 1-Octen-3-one, 1-octen-3-ol, octanal, nonanal, and (E)-2-nonenal were newly generated after stir-frying with OAV > 1, and contributed mushroom, fatty, and green odors to SF-CSC. Diallyl trisulfide, nonanal, (E)-β-ionone, β-sesquiphellandrene, and (E)-2-decenal were considered as the potential key aroma compounds (KACs) to distinguish the CSCs after different heat treatment. After cooking, the total titratable acidity of CSC increased and the sensory properties changed significantly. This study provides valuable information and guidance on the sensory and flavor changes of thermal processing fermented vegetables.
Learning Multi-Types of Neighbor Node Attributes and Semantics by Heterogeneous Graph Transformer and Multi-View Attention for Drug-Related Side-Effect Prediction
Authors: Xuan Ping , Li Peiru , Cui Hui , Wang Meng , Nakaguchi Toshiya , Zhang Tiangang
Published: September 2023

Since side-effects of drugs are one of the primary reasons for their failure in clinical trials, predicting their side-effects can help reduce drug development costs. We proposed a method based on heterogeneous graph transformer and capsule networks for side-effect-drug-association prediction (TCSD). The method encodes and integrates attributes from multiple types of neighbor nodes, connection semantics, and multi-view pairwise information. In each drug-side-effect heterogeneous graph, a target node has two types of neighbor nodes, the drug nodes and the side-effect ones. We proposed a new heterogeneous graph transformer-based context representation learning module. The module is able to encode specific topology and the contextual relations among multiple kinds of nodes. There are similarity and association connections between the target node and its various types of neighbor nodes, and these connections imply semantic diversity. Therefore, we designed a new strategy to measure the importance of a neighboring node to the target node and incorporate different semantics of the connections between the target node and its multi-type neighbors. Furthermore, we designed attentions at the neighbor node type level and at the graph level, respectively, to obtain enhanced informative neighbor node features and multi-graph features. Finally, a pairwise multi-view feature learning module based on capsule networks was built to learn the pairwise attributes from the heterogeneous graphs. Our prediction model was evaluated using a public dataset, and the cross-validation results showed it achieved superior performance to several state-of-the-art methods. Ablation experiments undertaken demonstrated the effectiveness of heterogeneous graph transformer-based context encoding, the position enhanced pairwise attribute learning, and the neighborhood node category-level attention. Case studies on five drugs further showed TCSD’s ability in retrieving potential drug-related side-effect candidates, and TCSD inferred the candidate side-effects for 708 drugs.
Antioxidant and Antibacterial Activity of Mexican Oregano Essential Oil, Extracted from Plants Occurring Naturally in Semiarid Areas and Cultivated in the Field and Greenhouse in Northern Mexico
Authors: Marin-Tinoco Ruben I. , Ortega-Ramírez Angie Tatiana , Esteban-Mendez Maricela , Silva-Marrufo Oscar , Barragan-Ledesma Laura E. , Valenzuela-Núñez Luis M. , Briceño-Contreras Edwin A. , Sariñana-Navarrete Maria A. , Camacho-Luis Abelardo , Navarrete-Molina Cayetano
Published: September 2023

In recent years, the determination of the antioxidant and antibacterial activity of essential oils in wild plants, such as Mexican oregano (Lippia graveolens Kunth), has become increasingly important. The objective was to compare the antioxidant and antibacterial activity of Mexican oregano essential oil obtained from plants occurring naturally in semiarid areas (Wild1 and Wild2), and those cultivated in the field (CField) and greenhouse (CGreenhouse) in northern Mexico. The Mexican oregano essential oil extraction was performed using the hydrodistillation method, the antioxidant activity was determined using the ABTS method, and the antibacterial activity was assessed through bioassays under the microwell method at nine different concentrations. The aim was to determine the diameter of the inhibition zone and, consequently, understand the sensitivity level for four bacterial species. The results revealed an antioxidant activity ranging from 90% to 94% at the sampling sites, with Wild1 standing out for having the highest average antioxidant activity values. Likewise, six out of the nine concentrations analyzed showed some degree of sensitivity for all the sampling sites. In this regard, the 25 µL mL−1 concentration showed the highest diameter of inhibition zone values, highlighting the Wild2 site, which showed an average diameter greater than 30 mm for the four bacteria tested. Only in the case of S. typhi did the CGreenhouse site surpass the Wild2, with an average diameter of the inhibition zone of 36.7 mm. These findings contribute to the search for new antioxidant and antibacterial options, addressing the challenges that humanity faces in the quest for opportunities to increase life expectancy.
Complexity-Building ESIPT-Assisted Synthesis of Fused Polyheterocyclic Sulfonamides
Authors: Beduru Srinivas , Kutateladze Andrei G.
Published: September 2023

Excited State Intramolecular Proton Transfer (ESIPT), originally discovered and explored in depth in a number of extensive photophysical studies, is more recently rediscovered as a powerful synthetic tool, offering rapid access to complex polyheterocycles. In our prior work we have employed ESIPT in aromatic o-keto amines and amides, leading to diverse primary photoproducts—complex quinolinols or azacanes possessing a fused lactam moiety—which could additionally be modified in short, high-yielding postphotochemical reactions to further grow complexity of the heterocyclic core scaffold and/or to decorate it with additional functional groups. Given that sulfonamides are generally known as privileged substructures, in this study we pursued two goals: (i) To explore whether sulfonamides could behave as proton donors in the context of ESIPT-initiated photoinduced reactions; (ii) To assess the scope of subsequent complexity-building photochemical and postphotochemical steps, which give access to polyheterocyclic molecular cores with fused cyclic sulfonamide moieties. In this work we show that this is indeed the case. Simple sulfonamide-containing photoprecursors produced the sought-after heterocyclic products in experimentally simple photochemical reactions accompanied by significant step-normalized complexity increases as corroborated by the Böttcher complexity scores.
The Critical Role of Pharmacists in the Clinical Delivery of Pharmacogenetics in the U.S
Authors: Haga Susanne B.
Published: September 2023

Since the rebirth of pharmacogenomics (PGx) in the 1990s and 2000s, with new discoveries of genetic variation underlying adverse drug response and new analytical technologies such as sequencing and microarrays, there has been much interest in the clinical application of PGx testing. The early involvement of pharmacists in clinical studies and the establishment of organizations to support the dissemination of information about PGx variants have naturally resulted in leaders in clinical implementation. This paper presents an overview of the evolving role of pharmacists, and discusses potential challenges and future paths, primarily focused in the U.S. Pharmacists have positioned themselves as leaders in clinical PGx testing, and will prepare the next generation to utilize PGx testing in their scope of practice.
A Filtering-Based Stochastic Gradient Estimation Method for Multivariate Pseudo-Linear Systems Using the Partial Coupling Concept
Authors: Ma Ping , Liu Yuan , Chen Yiyang
Published: September 2023

Solutions for enhancing parameter identification effects for multivariate equation-error systems in random interference and parameter coupling conditions are considered in this paper. For the purpose of avoiding the impact of colored noises on parameter identification precision, an appropriate filter is utilized to process the autoregressive moving average noise. Then, the filtered system is transformed into a number of sub-identification models based on system output dimensions. Founded on negative gradient search, a new multivariate filtering algorithm employing a partial coupling approach is proposed, and a conventional gradient algorithm is derived for comparison. Parameter identification for multivariate equation-error systems has a high estimation accuracy and an efficient calculation speed with the application of the partial coupling approach and the data filtering method. Two simulations are performed to reveal the proposed method’s effectiveness.
Automated Shape and Process Parameter Optimization for Scaling Up Geometrically Non-Similar Bioreactors
Authors: Seidel Stefan , Mozaffari Fruhar , Maschke Rüdiger W. , Kraume Matthias , Eibl-Schindler Regine , Eibl Dieter
Published: September 2023

Scaling bioprocesses remains a major challenge. Since it is physically impossible to increase all process parameters equally, a suitable scale-up strategy must be selected for a successful bioprocess. One of the most widely used criteria when scaling up bioprocesses is the specific power input. However, this represents only an average value. This study aims to determine the Kolmogorov length scale distribution by means of computational fluid dynamics (CFD) and to use it as an alternative scale-up criterion for geometrically non-similar bioreactors for the first time. In order to obtain a comparable Kolmogorov length scale distribution, an automated geometry and process parameter optimization was carried out using the open-source tools OpenFOAM and DAKOTA. The Kolmogorov–Smirnov test statistic was used for optimization. A HEK293-F cell expansion (batch mode) from benchtop (Infors Minifors 2 with 4 L working volume) to pilot scale (D-DCU from Sartorius with 30 L working volume) was carried out. As a reference cultivation, the classical scale-up approach with constant specific power input (233 W m−3) was used, where a maximum viable cell density (VCDmax) of 5.02·106 cells mL−1 was achieved (VCDmax at laboratory scale 5.77·106 cells mL−1). Through the automated optimization of the stirrer geometry (three parameters), position and speed, comparable cultivation results were achieved as in the small scale with a maximum VCD of 5.60·106 cells mL−1. In addition, even on the pilot scale, cell aggregate size distribution was seen to strictly follow a geometric distribution and can be predicted with the help of CFD with the previously published correlation.
TBM Rapid Tunneling Roadway Support Parameters Design and Process Research
Authors: Hou Tao , Xie Zhonghui , Zhang Ling , Cui Guogang , Ding Ziwei , Qiu Huafu , Li Yuhang
Published: September 2023

Taking the specific production geological conditions of the auxiliary transportation lane in the west area of Gaojiabao coal mine of Shaanxi Zhengtong Coal Industry as the research background, based on the anchorage support theory and the characteristics of the TBM digging process, numerical simulation, theoretical analysis, and other research methods were used to investigate the depth of the destruction of the plastic zone of the surrounding rock of the roadway to form the reasonable support parameters of a large cross-section of hard rock roadway suitable for TBM digging and to propose an intelligent digging and support process of the TBM corresponding to the on-site practice. The proposed intelligent tunneling support technology corresponds to a field practice of TBM. The study shows that: combined with the field industrial test and adjusted by the peripheral rock deformation and damage law, the anchor diameter of 20 mm, the length of 2500 mm left-hand threaded steel anchors, row spacing of 1100 mm, spacing of 1200 mm, and the anchor diameter of Φ21.8 mm, the length of 6200 mm left-handed threaded steel anchors, row spacing of 1100 mm, spacing of 1200 mm are the most reasonable solutions, which can ensure the control of the tunnel peripheral rock. The program is the most economically efficient in ensuring the control of deformation of the roadway perimeter rock and maintaining normal use.
The Kinetic Mechanism of the Thermal Decomposition Reaction of Small Particles of Limestone at Steelmaking Temperatures
Authors: Li Chenxiao , Zhang Yun , Xue Yuekai , Zhang Kaixuan , Wang Shuhuan , Sun Huakang , Xie Huaqing
Published: September 2023

Converter blowing limestone powder making slag steelmaking process has the advantages of low carbon and high efficiency, and can realize the resource utilization of CO2 in the metallurgical process, which is in line with the development direction of green metallurgy. Based on a thermogravimetric-differential thermal analyzer, the kinetic mechanism of decomposition of small limestone at steelmaking temperatures was investigated by a modified double extrapolation method. The results showed that with a higher rate of heating, limestone decomposition lagged, and decomposition temperature increased. Furthermore, the smaller the limestone particle size, the lower the activation energy of decomposition. Compared with N2, air, and O2, small limestone powder used for converter blowing could complete more rapid decomposition, and the time required for decomposition shortened by about 1/3, although the decomposition temperature increased in the CO2. The limestone decomposition rate increased and then decreased at low to high CO2 partial pressures. With a limiting link, the inhibition was more significant under high CO2 partial pressure, but the reaction can be fully completed by 1000 °C. The decomposition type modeled was stochastic nucleation and subsequent growth. As the partial pressure of CO2 increased from 25% to 100%, the number of reaction stages, n, increased.
Design and Simulation of a Feedback Controller for an Active Suspension System: A Simplified Approach
Authors: Provatas Vasileios , Ipsakis Dimitris
Published: September 2023

The concept of controlling vehicle comfort is a common problem that is faced in most under- and postgraduate courses in Engineering Schools. The aim of this study is to provide a simplified approach for the feedback control design and simulation of active suspension systems, which are applied in vehicles. Firstly, the mathematical model of an active suspension system (a quarter model of a car) which consists of a passive spring, a passive damper and an actuator is provided. In this study, we chose to design and compare the following controllers: (a) conventional P, PI and PID controllers that were tuned through two conventional methodologies (Ziegler–Nichols and Tyreus–Luyben); (b) an optimal PID controller that was tuned with a genetic algorithm (GA) optimization framework in terms of the minimization of certain performance criteria and (c) an internal model controller (IMC) based on the process transfer function. The controllers’ performance was assessed in a series of realistic scenarios that included set-point tracking with and without disturbances. In all cases, the IMC controller and the optimal PID showed superior performance. On the other hand, the P and PI controllers showed a rather insufficient behavior that involved persistent errors, overshoots and eventually, uncomfortable ride oscillations. Clearly, a step-by-step approach such as this, that includes modeling, control design and simulation scenarios can be applied to numerous other engineering examples, which we envisage to lead more students into the area of automatic control.
Visualisation in Late-Medieval Franciscan Passion Literature from the Low Countries: Cransken van minnen (Wreath of Love), 1518
Authors: Polkowski Marcin
Published: September 2023

Late-medieval devotional literature embraced visualization as a means of providing the reader-devotee with the experience of being a virtual witness during a text-guided meditation. Based on a new reading of Cransken van minnen, a Middle Dutch prayer book from Franciscan milieus, this paper will propose a framework based on the interrelations between visualization and other key aspects pointed out in recent research as significant for understanding this type of literature: affective reactions, anamnesis and virtual witnessing. This framework entails two assumptions. The first is that visualization, especially with Mary as the compassionate “focaliser”, was instrumental in achieving the goal of devotion, which was to promote an affective reaction (contrition). The second is that this prayer book offered devotees an experience of anamnesis (“recalling”) that depended on the provision of sensory perceptions through which readers could become virtual witnesses to the events meditated upon. Using a combination of philological and literary–historical methods, the structure and content of this prayer book are scrutinized in detail to provide new insights into the strategies used by the compiler to infuse the prayer discourse with elements suggesting visual perception.
Registration of Large Optical and SAR Images with Non-Flat Terrain by Investigating Reliable Sparse Correspondences
Authors: Zhang Han , Lei Lin , Ni Weiping , Cheng Kenan , Tang Tao , Wang Peizhong , Kuang Gangyao
Published: September 2023

Optical and SAR image registration is the primary procedure to exploit the complementary information from the two different image modal types. Although extensive research has been conducted to narrow down the vast radiometric and geometric gaps so as to extract homogeneous characters for feature point matching, few works have considered the registration issue for non-flat terrains, which will bring in more difficulties for not only sparse feature point matching but also outlier removal and geometric relationship estimation. This article addresses these issues with a novel and effective optical-SAR image registration framework. Firstly, sparse feature points are detected based on the phase congruency moment map of the textureless SAR image (SAR-PC-Moment), which helps to identify salient local regions. Then a template matching process using very large local image patches is conducted, which increases the matching accuracy by a significant margin. Secondly, a mutual verification-based initial outlier removal method is proposed, which takes advantage of the different mechanisms of sparse and dense matching and requires no geometric consistency assumption within the inliers. These two procedures will produce a putative correspondence feature point (CP) set with a low outlier ratio and high reliability. In the third step, the putative CPs are used to segment the large input image of non-flat terrain into dozens of locally flat areas using a recursive random sample consensus (RANSAC) method, with each locally flat area co-registered using an affine transformation. As for the mountainous areas with sharp elevation variations, anchor CPs are first identified, and then optical flow-based pixelwise dense matching is conducted. In the experimental section, ablation studies using four precisely co-registered optical-SAR image pairs of flat terrain quantitatively verify the effectiveness of the proposed SAR-PC-Moment-based feature point detector, big template matching strategy, and mutual verification-based outlier removal method. Registration results on four 1 m-resolution non-flat image pairs prove that the proposed framework is able to produce robust and quite accurate registration results.
Anthropogenic Object Localization: Evaluation of Broad-Area High-Resolution Imagery Scans Using Deep Learning in Overhead Imagery
Authors: Hurt J. Alex , Popescu Ilinca , Davis Curt H. , Scott Grant J.
Published: September 2023

Too often, the testing and evaluation of object detection, as well as the classification techniques for high-resolution remote sensing imagery, are confined to clean, discretely partitioned datasets, i.e., the closed-world model. In recent years, the performance on a number of benchmark datasets has exceeded 99% when evaluated using cross-validation techniques. However, real-world remote sensing data are truly big data, which often exceed billions of pixels. Therefore, one of the greatest challenges regarding the evaluation of machine learning models taken out of the clean laboratory setting and into the real world is the difficulty of measuring performance. It is necessary to evaluate these models on a grander scale, namely, tens of thousands of square kilometers, where it is intractable to the ground truth and the ever-changing anthropogenic surface of Earth. The ultimate goal of computer vision model development for automated analysis and broad area search and discovery is to augment and assist humans, specifically human–machine teaming for real-world tasks. In this research, various models have been trained using object classes from benchmark datasets such as UC Merced, PatternNet, RESISC-45, and MDSv2. We detail techniques to scan broad swaths of the Earth with deep convolutional neural networks. We present algorithms for localizing object detection results, as well as a methodology for the evaluation of the results of broad-area scans. Our research explores the challenges of transitioning these models out of the training–validation laboratory setting and into the real-world application domain. We show a scalable approach to leverage state-of-the-art deep convolutional neural networks for the search, detection, and annotation of objects within large swaths of imagery, with the ultimate goal of providing a methodology for evaluating object detection machine learning models in real-world scenarios.
Cross-Contamination of Ignitable Liquid Residues on Wildfire Debris—Detection and Characterization in Matrices Commonly Encountered at Wildfire Scenes
Authors: Boegelsack Nadin , Walker James , Sandau Court D. , Withey Jonathan M. , McMartin Dena W. , O'Sullivan Gwen
Published: September 2023

Ignitable liquid residue (ILR) samples play an important role in fire investigations. Similar to other types of forensic evidence, maintaining sample integrity depends on the prevention of cross-contamination during both storage and transport. This study examines cross-contamination in ILR samples on various sample matrices (gravel, soil, wood). After inducing leaks in a controlled environment, sample analysis by GC×GC-ToF MS allowed for sensitive detection and in-depth characterization of cross-contamination processes. The potential for false positive identification of ILR is notably present due to cross-contamination. Compound transmission for a mid-range ILR (gasoline), for instance, was detectable after a 1 h exposure, with a complete profile transfer occurring after 8 h regardless of the matrix type. Visual comparisons and uptake rate calculations further confirmed matrix interaction effects taking place in the form of inherent native compound interference and adsorbate–adsorbate interaction during transmission and extraction processes for soil and wood matrices. Chemometric analysis highlighted the advantage of employing statistical analysis when investigating samples under matrix interactions by identifying several statistically significant compounds for reliably differentiating cross-contamination from background and simulated positive samples in different volatility ranges and compound classes. Untargeted analysis tentatively identified three additional compounds of interest within compound classes not currently investigated in routine analysis. The resulting classification between background, contaminated, and simulated positive samples showed no potential for false positive ILR identification and improved false negative errors, as evidenced by classification confidences progressing from 88% for targeted and 93% for untargeted to 95% for a diagnostic ratio analysis of three ratios deployed in tandem.
Examining Spatial Inequalities in Public Green Space Accessibility: A Focus on Disadvantaged Groups in England
Authors: Bao Ziqian , Bai Yihang , Geng Tao
Published: September 2023

Green spaces have been recognised for their positive impact on residents’ health and well-being. However, equitable access to these spaces remains a concern as certain social groups face barriers to reaching public green areas (PGS). Existing studies have explored the relationship between green spaces and vulnerable populations but have often overlooked the spatial variations in accessibility experienced by these groups. This research aimed to investigate the spatial association between green space accessibility and five key variables representing vulnerability: age, educational deprivation, health deprivation, crime rates, and housing barriers. Ordinary least squares and multi-scale geographically weighted regression (MGWR) techniques were employed to analyse the relationship between the nearest distance to public green spaces and the challenges experienced by vulnerable groups based on socioeconomic factors in England. The findings highlight disparities in open green space access for vulnerable groups, particularly older adults and individuals with limited education and housing accessibility, who are more likely to face restricted access to green spaces. There was a negative correlation found between health deprivation and the accessibility of green spaces, indicating people who suffer from the disease may live closer to green spaces. Surprisingly, although a positive association was observed between crime risk and distance to public green space in most areas, there were specific areas that exhibit a negative correlation between them. This study emphasises the importance of considering the perspectives of vulnerable groups in addressing PGS inequality and underscores the need for inclusive public green space planning and policy development.
Effect of Air Pollution on the Basal DNA Damage of Mother–Newborn Couples of México City
Authors: Valverde Mahara , Granados Adriana , Milić Mirta , Ceppi Marcello , Sollano Leticia , Bonassi Stefano , Rojas Emilio
Published: September 2023

Environmental pollution of megacities can cause early biological damage such as DNA strand breaks and micronuclei formation. Comet assay tail length (TL) reflects exposure in the uterus to high levels of air pollution, primarily ozone and air particles (PM10), including mothers’ smoking habits during pregnancy, conditions which can lead to low birth weight. In this biomonitoring study, we evaluated basal DNA damage in the cord blood cells of newborn children from Mexico City. We found a correlation between DNA damage in mothers and their newborns, including various parameters of environmental exposure and complications during pregnancy, particularly respiratory difficulties, malformations, obstetric trauma, neuropathies, and nutritional deficiencies. Mothers living in the southern part of the city showed double DNA damage compared to those living in the northern part (TL 8.64 μm vs. 4.18 μm, p < 0.05). Additionally, mothers’ DNA damage correlates with exposure to NOx (range 0.77–1.52 ppm) and PM10 (range 58.32–75.89 μg/m3), as well maternal age >29. These results highlight the sensitivity of the comet assay in identifying differential in utero exposure for newborns whose mothers were exposed during pregnancy. They also suggest the importance of antioxidants during pregnancy and the role of the placental barrier in protecting the newborn from the DNA-damaging effects of oxidative pollution.