bluuebunny/crossref_metadata_2025 huggingface dataset:
The uncertain role of substandard and falsified medicines in the emergence and spread of antimicrobial resistance
Authors: Cavany Sean , Nanyonga Stella , Hauk Cathrin , Lim Cherry , Tarning Joel , Sartorius Benn , Dolecek Christiane , Caillet Céline , Newton Paul N. , Cooper Ben S.
Published: October 2023

Approximately 10% of antimicrobials used by humans in low- and middle-income countries are estimated to be substandard or falsified. In addition to their negative impact on morbidity and mortality, they may also be important drivers of antimicrobial resistance. Despite such concerns, our understanding of this relationship remains rudimentary. Substandard and falsified medicines have the potential to either increase or decrease levels of resistance, and here we discuss a range of mechanisms that could drive these changes. Understanding these effects and their relative importance will require an improved understanding of how different drug exposures affect the emergence and spread of resistance and of how the percentage of active pharmaceutical ingredients in substandard and falsified medicines is temporally and spatially distributed.
Microfluidic investigation of the impacts of flow fluctuations on the development of Pseudomonas putida biofilms
Authors: Wei Guanju , Yang Judy Q.
Published: October 2023

Biofilms play critical roles in wastewater treatment, bioremediation, and medical-device-related infections. Understanding the dynamics of biofilm formation and growth is essential for controlling and exploiting their properties. However, the majority of current studies have focused on the impact of steady flows on biofilm growth, while flow fluctuations are common in natural and engineered systems such as water pipes and blood vessels. Here, we reveal the effects of flow fluctuations on the development of Pseudomonas putida biofilms through systematic microfluidic experiments and the development of a theoretical model. Our experimental results showed that biofilm growth under fluctuating flow conditions followed three phases: lag, exponential, and fluctuation phases. In contrast, biofilm growth under steady-flow conditions followed four phases: lag, exponential, stationary, and decline phases. Furthermore, we demonstrated that low-frequency flow fluctuations promoted biofilm growth, while high-frequency fluctuations inhibited its development. We attributed the contradictory impacts of flow fluctuations on biofilm growth to the adjustment time (T0) needed for biofilm to grow after the shear stress changed from high to low. Furthermore, we developed a theoretical model that explains the observed biofilm growth under fluctuating flow conditions. Our insights into the mechanisms underlying biofilm development under fluctuating flows can inform the design of strategies to control biofilm formation in diverse natural and engineered systems.
Adaptive reinforcement learning for task scheduling in aircraft maintenance
Authors: Silva Catarina , Andrade Pedro , Ribeiro Bernardete , F. Santos Bruno
Published: October 2023

This paper proposes using reinforcement learning (RL) to schedule maintenance tasks, which can significantly reduce direct operating costs for airlines. The approach consists of a static algorithm for long-term scheduling and an adaptive algorithm for rescheduling based on new maintenance information. To assess the performance of both approaches, three key performance indicators (KPIs) are defined: Ground Time, representing the hours an aircraft spends on the ground; Time Slack, measuring the proximity of tasks to their due dates; and Change Score, quantifying the similarity level between initial and adapted maintenance plans when new information surfaces. The results demonstrate the efficacy of RL in producing efficient maintenance plans, with the algorithms complementing each other to form a solid foundation for routine tasks and real-time responsiveness to new information. While the static algorithm performs slightly better in terms of Ground Time and Time Slack, the adaptive algorithm excels overwhelmingly in terms of Change Score, offering greater flexibility in handling new maintenance information. The proposed RL-based approach can improve the efficiency of aircraft maintenance and has the potential for further research in this area.
The effect of image fractal properties and its interaction with visual discomfort on gait kinematics
Authors: Burtan D. , Burn J. F. , Spehar B. , Leonards U.
Published: October 2023

Exposure to images of urban environments affords higher cognitive processing demands than exposure to images of nature scenes; an effect potentially related to differences in low-level image statistics such as fractals. The aim of the current study was to investigate whether the fractal dimensions of an abstract scene affect cognitive processing demands, using gait kinematics as a measure of cognitive demand. Participants (n = 40) were asked to walk towards different types of synthetic images which were parametrically varied in their fractal dimensions. At the end of each walk, participants rated each image for its visual discomfort (n = 20) or for its likability (n = 20) as potential confounding factors. Fractal dimensions were predictors of walking speed. Moreover, the interaction between fractal dimensions and subjective visual discomfort but not liking predicted velocity. Overall, these data suggest that fractal dimensions indeed contribute to environmentally induced cognitive processing demands.
Investigation on mechanical properties of nickel open cell metal foam after heat treatment
Authors: Shajari Y. , Nikzad L. , Razavi M.
Published: October 2023

This investigation aims to assess the mechanical behavior and energy absorption properties of the open-cell nickel foams. The metal foams produced by electroforming of nickel on PU foams, also a heat treatment has applied to evaporate the PU foam, then a uniaxial compression test was applied to measure maximum compressive strength, energy absorption density, efficiency, and normalized stresses. The results indicate that compared with typical open-cell nickel foams and polymer precursors when the electroforming time is 12 h and a heat treatment has applied, the aforementioned properties of the metal foams had a significant improvement. Improvement of properties will change by increasing the time of electroforming. The heat treatment improved the energy absorption density of open-cell nickel foams for 3.7 times. For the best sample which is a metal foam with 12 h of electroforming with heat treatment the first maximum compressive strength, energy absorption density, and energy absorption efficiency reach 1.84 (MPa), 3.29 (mJ/mm3), and 73%, respectively.
Sit-to-walk strategy classification in healthy adults using hip and knee joint angles at gait initiation
Authors: Perera Chamalka Kenneth , Gopalai Alpha Agape , Gouwanda Darwin , Ahmad Siti Anom , Salim Mazatulfazura Sf Binti
Published: October 2023

Forward continuation, balance, and sit-to-stand-and-walk (STSW) are three common movement strategies during sit-to-walk (STW) executions. Literature identifies these strategies through biomechanical parameters using gold standard laboratory equipment, which is expensive, bulky, and requires significant post-processing. STW strategy becomes apparent at gait-initiation (GI) and the hip/knee are primary contributors in STW, therefore, this study proposes to use the hip/knee joint angles at GI as an alternate method of strategy classification. To achieve this, K-means clustering was implemented using three clusters corresponding to the three STW strategies; and two feature sets corresponding to the hip/knee angles (derived from motion capture data); from an open access online database (age: 21–80 years; n = 10). The results identified forward continuation with the lowest hip/knee extension, followed by balance and then STSW, at GI. Using this classification, strategy biomechanics were investigated by deriving the established biomechanical quantities from literature. The biomechanical parameters that significantly varied between strategies (P < 0.05) were time, horizontal centre of mass (COM) momentum, braking impulse, centre of pressure (COP) range and velocities, COP–COM separation, hip/knee torque and movement fluency. This alternate method of strategy classification forms a generalized framework for describing STW executions and is consistent with literature, thus validating the joint angle classification method.
Cancer characterization using light backscattering spectroscopy and quantitative ultrasound: an ex vivo study on sarcoma subtypes
Authors: Malinet Cyril , Montcel Bruno , Dutour Aurélie , Fajnorova Iveta , Liebgott Hervé , Muleki-Seya Pauline
Published: October 2023

Histological analysis is the gold standard method for cancer diagnosis. However, it is prone to subjectivity and sampling bias. In response to these limitations, we introduce a quantitative bimodal approach that aims to provide non-invasive guidance towards suspicious regions. Light backscattering spectroscopy and quantitative ultrasound techniques were combined to characterize two different bone tumor types from animal models: chondrosarcomas and osteosarcomas. Two different cell lines were used to induce osteosarcoma growth. Histological analyses were conducted to serve as references. Three ultrasound parameters and intensities of the light reflectance profiles showed significant differences between chondrosarcomas and osteosarcomas at the 5% level. Likewise, variations in the same biomarkers were reported for the two types of osteosarcoma, despite their similar morphology observed in the histological examinations. These observations show the sensitivity of our techniques in probing fine tissue properties. Secondly, the ultrasound spectral-based technique identified the mean size of chondrosarcoma cells and nuclei with relative errors of about 22% and 9% respectively. The optical equivalent technique correctly extracted scatterer size distributions that encompass nuclei and cells for chondrosarcomas and osteosarcomas ($$R^2 = 0.80$$

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2

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0.80

and $$R^2 = 0.73$$

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2

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0.73

respectively). The optical scattering contributions of nuclei were estimated at 52% for the chondrosarcomas and 69% for the osteosarcomas, probably indicating the abundant and the absent extracellular matrix respectively. Thus, the ultrasound and the optical methods brought complementary parameters. They successfully estimated morphological parameters at the cellular and the nuclear scales, making our bimodal technique promising for tumor characterization.
Epidemiology and analysis of SARS-CoV-2 Omicron subvariants BA.1 and 2 in Taiwan
Authors: Liu Li-Teh , Chiou Shyh-Shin , Chen Po-Chih , Chen Chun-Hong , Lin Ping-Chang , Tsai Ching-Yi , Chuang Wan-Long , Hwang Shang-Jyh , Chong Inn-Wen , Tsai Jih-Jin
Published: October 2023

The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first detected in October 2021, possessed many mutations compared to previous variants. We aimed to identify and analyze SARS-CoV-2 Omicron subvariants among coronavirus disease 2019 (COVID-19) patients between January 2022 and September 2022 in Taiwan. The results revealed that BA.2.3.7, featuring K97E and G1251V in the spike protein compared with BA.2, emerged in March 2022 and persistently dominated between April 2022 and August 2022, resulting in the largest COVID-19 outbreak since 2020. The accumulation of amino acid (AA) variations, mainly AA substitution, in the spike protein was accompanied by increasing severity in Omicron-related COVID-19 between April 2022 and January 2023. Older patients were more likely to have severe COVID-19, and comorbidity was a risk factor for COVID-19-related mortality. The accumulated case fatality rate (CFR) dropped drastically after Omicron variants, mainly BA.2.3.7, entered Taiwan after April 2022, and the CFR was 0.16% in Taiwan, which was lower than that worldwide (0.31%) between April 2021 and January 2023. The relatively low CFR in Omicron-related COVID-19 patients can be attributed to adjustments to public health policies, promotion of vaccination programs, effective antiviral drugs, and the lower severity of the Omicron variant.
KaScape: a sequencing-based method for global characterization of protein‒DNA binding affinity
Authors: Chen Hong , Xu Yongping , Jin Jianshi , Su Xiao-dong
Published: October 2023

It is difficult to exhaustively screen all possible DNA binding sequences for a given transcription factor (TF). Here, we developed the KaScape method, in which TFs bind to all possible DNA sequences in the same DNA pool where DNA sequences are prepared by randomized oligo synthesis and the random length can be adjusted to a length such as 4, 5, 6, or 7. After separating bound from unbound double-stranded DNAs (dsDNAs), their sequences are determined by next-generation sequencing. To demonstrate the relative binding affinities of all possible DNA sequences determined by KaScape, we developed three-dimensional KaScape viewing software based on a K-mer graph. We applied KaScape to 12 plant TF family AtWRKY proteins and found that all AtWRKY proteins bound to the core sequence GAC with similar profiles. KaScape can detect not only binding sequences consistent with the consensus W-box “TTGAC(C/T)” but also other sequences with weak affinity. KaScape provides a high-throughput, easy-to-operate, sensitive, and exhaustive method for quantitatively characterizing the relative binding strength of a TF with all possible binding sequences, allowing us to comprehensively characterize the specificity and affinity landscape of transcription factors, particularly for moderate- and low-affinity binding sites.
Predicting compressive strength of RCFST columns under different loading scenarios using machine learning optimization
Authors: Wu Feng , Tang Fei , Lu Ruichen , Cheng Ming
Published: October 2023

Accurate bearing capacity assessment under load conditions is essential for the design of concrete-filled steel tube (CFST) columns. This paper presents an optimization-based machine learning method to estimate the ultimate compressive strength of rectangular concrete-filled steel tube (RCFST) columns. A hybrid model, GS-SVR, was developed based on support vector machine regression (SVR) optimized by the grid search (GS) algorithm. The model was built based on a sample of 1003 axially loaded and 401 eccentrically loaded test data sets. The predictive performance of the proposed model is compared with two commonly used machine learning models and two design codes. The results obtained for the axial loading dataset with R2 of 0.983, MAE of 177.062, RMSE of 240.963, and MAPE of 12.209%, and for the eccentric loading dataset with R2 of 0.984, MAE of 93.234, RMSE of 124.924, and MAPE of 10.032% show that GS-SVR is the best model for predicting the compressive strength of RCFST columns under axial and eccentric loadings. It is an effective alternative method that can be used to assist and guide the design of RCFST columns to save time and cost of some laboratory experiments. Additionally, the impact of input parameters on the output was investigated.
Risk of data leakage in estimating the diagnostic performance of a deep-learning-based computer-aided system for psychiatric disorders
Authors: Lee Hyung-Tak , Cheon Hye-Ran , Lee Seung-Hwan , Shim Miseon , Hwang Han-Jeong
Published: October 2023

Deep-learning approaches with data augmentation have been widely used when developing neuroimaging-based computer-aided diagnosis (CAD) systems. To prevent the inflated diagnostic performance caused by data leakage, a correct cross-validation (CV) method should be employed, but this has been still overlooked in recent deep-learning-based CAD studies. The goal of this study was to investigate the impact of correct and incorrect CV methods on the diagnostic performance of deep-learning-based CAD systems after data augmentation. To this end, resting-state electroencephalogram (EEG) data recorded from post-traumatic stress disorder patients and healthy controls were augmented using a cropping method with different window sizes, respectively. Four different CV approaches were used to estimate the diagnostic performance of the CAD system, i.e., subject-wise CV (sCV), overlapped sCV (oSCV), trial-wise CV (tCV), and overlapped tCV (otCV). Diagnostic performances were evaluated using two deep-learning models based on convolutional neural network. Data augmentation can increase the performance with all CVs, but inflated diagnostic performances were observed when using incorrect CVs (tCV and otCV) due to data leakage. Therefore, the correct CV (sCV and osCV) should be used to develop a deep-learning-based CAD system. We expect that our investigation can provide deep-insight for researchers who plan to develop neuroimaging-based CAD systems for psychiatric disorders using deep-learning algorithms with data augmentation.
Effects of tea, catechins and catechin derivatives on Omicron subvariants of SARS-CoV-2
Authors: Shin-Ya Masaharu , Nakashio Maiko , Ohgitani Eriko , Suganami Akiko , Kawamoto Masaya , Ichitani Masaki , Kobayashi Makoto , Takihara Takanobu , Inaba Tohru , Nukui Yoko , Kinugasa Hitoshi , Ishikura Hiroyasu , Tamura Yutaka , Mazda Osam
Published: October 2023

The Omicron subvariants of SARS-CoV-2 have multiple mutations in the S-proteins and show high transmissibility. We previously reported that tea catechin (−)-epigallocatechin gallate (EGCG) and its derivatives including theaflavin-3,3’-di-O-digallate (TFDG) strongly inactivated the conventional SARS-CoV-2 by binding to the receptor binding domain (RBD) of the S-protein. Here we show that Omicron subvariants were effectively inactivated by green tea, Matcha, and black tea. EGCG and TFDG strongly suppressed infectivity of BA.1 and XE subvariants, while effect on BA.2.75 was weaker. Neutralization assay showed that EGCG and TFDG inhibited interaction between BA.1 RBD and ACE2. In silico analyses suggested that N460K, G446S and F490S mutations in RBDs crucially influenced the binding of EGCG/TFDG to the RBDs. Healthy volunteers consumed a candy containing green tea or black tea, and saliva collected from them immediately after the candy consumption significantly decreased BA.1 virus infectivity in vitro. These results indicate specific amino acid substitutions in RBDs that crucially influence the binding of EGCG/TFDG to the RBDs and different susceptibility of each Omicron subvariant to EGCG/TFDG. The study may suggest molecular basis for potential usefulness of these compounds in suppression of mutant viruses that could emerge in the future and cause next pandemic.
Physico-functional and nutritional characteristics of germinated pigeon pea (Cajanus cajan) flour as a functional food ingredient
Authors: Atuna Richard Atinpoore , Mensah Mary-Ann Sarpong , Koomson Gifty , Akabanda Fortune , Dorvlo Selorm Yaotse , Amagloh Francis Kweku
Published: October 2023

The study investigated the effect of germination on pigeon pea flour’s physico-functional (pH, color, water and oil absorption capacities, swelling and foaming capacities and bulk densities) and proximate, total polyphenols and antioxidant activity. The physico-functional and proximate parameters were determined using standard protocols. The color analysis showed that germination significantly increased the flour samples’ lightness (L*) (70.7; p = 0.009) by almost 1.5-fold. Germination resulted in almost 1.1 times higher oil absorption capacity than the control (219.9%; p = 0.022). The foaming capacity of the germinated samples significantly (p = 0.015) increased by 6.4%. Germination significantly reduced the loose bulk density (0.54 vs 0.63; p = 0.012) but significantly increased the tapped bulk density (0.84 vs 0.77; p = 0.002). The germinated samples recorded significantly (1.62%; p = 0.010) lower crude fat, about 1.2 times lower than the raw flour. Germination significantly increased the flour’s total ash (4.2% vs 3.6%; p = 0.003) and crude protein (11.6% vs 9.4%; p = 0.047) content. Germinated pigeon pea flour will perform better in formulating baked products, aerated foods and food extenders than non-germinated pigeon pea flour. Hence, the germination of pigeon peas should be encouraged because it harnesses the functional and proximate attributes measured.
Size-driven parr-smolt transformation in masu salmon (Oncorhynchus masou)
Authors: Ugachi Yuki , Kitade Haruka , Takahashi Eisuke , Suzuki Shotaro , Hayashi Mizuki , Yamada Taiga , Cui Wenda , Shimizu Munetaka
Published: October 2023

Anadromous salmonids exhibit partial migration, where some individuals within a population migrate down to the ocean through complex interactions between body size and photoperiod. This study aimed to integrate the ontogenetic and seasonal patterns of smoltification, a series of changes for future marine life, in a strain of masu salmon (Oncorhynchus masou). Spring smoltification, as evidenced by the activation of gill Na+,K+-ATPase (NKA), was induced during winter under an advanced photoperiod. In addition, juveniles showed an additional peak in gill NKA activity in August regardless of the photoperiod. When juvenile masu salmon were subjected to feeding manipulations during the first spring/summer, only fish exceeding a fork length of 12 cm exhibited an increased gill NKA activity. We tested whether size-driven smoltification required a long-day period by exposing juveniles to a constant short-day length (9-h light and 15-h dark) from January to November. Juveniles under short-day conditions exceeded 12 cm in June but showed no signs of smoltification. Thus, masu salmon undergo photoperiod-limited, size-driven smoltification during the first summer and size-limited, photoperiod-driven smoltification the following spring. The findings of the present study provide a framework for further elucidation of the physiological mechanisms underlying partial migration in salmonids.
Exploring the role of esketamine in alleviating depressive symptoms in mice via the PGC-1α/irisin/ERK1/2 signaling pathway
Authors: Hu Na , Chen Xuemei , Chen Chengchuan , Liu Xing , Yi Peng , Xu Tianhao , Jia Jing , Feng Jianguo , Zhang Chunxiang , Wang Xiaobin
Published: October 2023

Esketamine provides an immediate and noticeable antidepressant effect, although the underlying molecular processes are yet unclear. Irisin induced by aerobic exercise has been implicated in the alleviation of depressive symptoms, whether irisin expression responds to the administration of esketamine remains unknown. In this study, we found that irisin was reduced in the hippocampus and peripheral blood of chronic unpredictable mild stress (CUMS) mice, whereas the irisin level was rescued by esketamine treatment. The reduction of PGC-1α expression (transcriptional regulator of irisin gene expression) in the CUMS mice was rescued by esketamine treatment, PGC-1α knockdown significantly reduced the irisin level induced by esketamine. Additionally, FNDC5/irisin-knockout mice developed more severe depressant-like behaviors than wild-type mice under CUMS stimulation, with an attenuated the antidepressant effect of esketamine. Further research indicated that irisin-mediated modulation of esketamine on depressive-like behaviors in CUMS mice involved the ERK1/2 pathway. Overall, the PGC-1α/irisin/ERK1/2 signaling activation may be a new mechanism underlying the antidepressant activity of esketamine, denoting that irisin may be a promising therapeutic target for the treatment of depression.
Differential gene expression analysis based on linear mixed model corrects false positive inflation for studying quantitative traits
Authors: Tang Shizhen , Buchman Aron S. , Wang Yanling , Avey Denis , Xu Jishu , Tasaki Shinya , Bennett David A. , Zheng Qi , Yang Jingjing
Published: October 2023

Differential gene expression (DGE) analysis has been widely employed to identify genes expressed differentially with respect to a trait of interest using RNA sequencing (RNA-Seq) data. Recent RNA-Seq data with large samples pose challenges to existing DGE methods, which were mainly developed for dichotomous traits and small sample sizes. Especially, existing DGE methods are likely to result in inflated false positive rates. To address this gap, we employed a linear mixed model (LMM) that has been widely used in genetic association studies for DGE analysis of quantitative traits. We first applied the LMM method to the discovery RNA-Seq data of dorsolateral prefrontal cortex (DLPFC) tissue (n = 632) with four continuous measures of Alzheimer’s Disease (AD) cognitive and neuropathologic traits. The quantile–quantile plots of p-values showed that false positive rates were well calibrated by LMM, whereas other methods not accounting for sample-specific mixed effects led to serious inflation. LMM identified 37 potentially significant genes with differential expression in DLPFC for at least one of the AD traits, 17 of which were replicated in the additional RNA-Seq data of DLPFC, supplemental motor area, spinal cord, and muscle tissues. This application study showed not only well calibrated DGE results by LMM, but also possibly shared gene regulatory mechanisms of AD traits across different relevant tissues.
The effect of increased positive end expiratory pressure on brain tissue oxygenation and intracranial pressure in acute brain injury patients
Authors: Gouvea Bogossian Elisa , Cantos Joaquin , Farinella Anita , Nobile Leda , Njimi Hassane , Coppalini Giacomo , Diosdado Alberto , Salvagno Michele , Oliveira Gomes Fernando , Schuind Sophie , Anderloni Marco , Robba Chiara , Taccone Fabio Silvio
Published: October 2023

Cerebral hypoxia is an important cause of secondary brain injury. Improving systemic oxygenation may increase brain tissue oxygenation (PbtO2). The effects of increased positive end-expiratory pressure (PEEP) on PbtO2 and intracranial pressure (ICP) needs to be further elucidated. This is a single center retrospective cohort study (2016–2021) conducted in a 34-bed Department of Intensive Care unit. All patients with acute brain injury under mechanical ventilation who were monitored with intracranial pressure and brain tissue oxygenation (PbtO2) catheters and underwent at least one PEEP increment were included in the study. Primary outcome was the rate of PbtO2 responders (increase in PbtO2 > 20% of baseline) after PEEP increase. ΔPEEP was defined as the difference between PEEP at 1 h and PEEP at baseline; similarly ΔPbtO2 was defined as the difference between PbtO2 at 1 h after PEEP incrementation and PbtO2 at baseline. We included 112 patients who underwent 295 episodes of PEEP increase. Overall, the median PEEP increased form 6 (IQR 5–8) to 10 (IQR 8–12) cmH2O (p = 0.001), the median PbtO2 increased from 21 (IQR 16–29) mmHg to 23 (IQR 18–30) mmHg (p = 0.001), while ICP remained unchanged [from 12 (7–18) mmHg to 12 (7–17) mmHg; p = 0.42]. Of 163 episode of PEEP increments with concomitant PbtO2 monitoring, 34 (21%) were PbtO2 responders. A lower baseline PbtO2 (OR 0.83 [0.73–0.96)]) was associated with the probability of being responder. ICP increased in 142/295 episodes of PEEP increments (58%); no baseline variable was able to identify this response. In PbtO2 responders there was a moderate positive correlation between ΔPbtO2 and ΔPEEP (r = 0.459 [95% CI 0.133–0.696]. The response in PbtO2 and ICP to PEEP elevations in brain injury patients is highly variable. Lower PbtO2 values at baseline could predict a significant increase in brain oxygenation after PEEP increase.
Probiotic potentials of lactic acid bacteria isolated from Egyptian fermented food
Authors: Abdel Tawab Fatma I. , Abd Elkadr Menna H. , Sultan Amany M. , Hamed Ehdaa O. , El-Zayat Ayatollah S. , Ahmed Marwa N.
Published: October 2023

Lactic acid bacteria (LAB) are of major concern due to their health benefits. Fermented food products comprise variable LAB demonstrating probiotic properties. Discovering and evaluating new probiotics in fermented food products poses a global economic and health importance. Therefore, the present work aimed to investigate and evaluate the probiotic potentials of LAB strains isolated from Egyptian fermented food. In this study, we isolated and functionally characterized 100 bacterial strains isolated from different Egyptian fermented food sources as probiotics. Only four LAB strains amongst the isolated LAB showed probiotic attributes and are considered to be safe for their implementation as feed or dietary supplements. Additionally, they were shown to exert antimicrobial activities against pathogenic bacteria and anticancer effects against the colon cancer cell line Caco-2. The Enterococcus massiliensis IS06 strain was exclusively reported in this study as a probiotic strain with high antimicrobial, antioxidant, and anti-colon cancer activity. Hitherto, few studies have focused on elucidating the impact of probiotic supplementation in vivo. Therefore, in the current study, the safety of the four strains was tested in vivo through the supplementation of rats with potential probiotic strains for 21 days. The results revealed that probiotic bacterial supplementation in rats did not adversely affect the general health of rats. The Lactiplantibacillus plantarum IS07 strain significantly increased the growth performance of rats. Furthermore, the four strains exhibited increased levels of antioxidants such as superoxide dismutase and glutathione in vivo. Consistently, all strains also showed high antioxidant activity of the superoxide dismutase enzyme in vitro. Overall, these findings demonstrated that these isolated potential probiotics harbor desirable characteristics and can be applied widely as feed additives for animals or as dietary supplements for humans to exert their health benefits and combat serious diseases.
Extremal quantum correlation generation using a hybrid channel
Authors: Rahman Atta ur , Ali Hazrat , Zangi S. M. , Qiao Cong-Feng
Published: October 2023

The preservation of quantum correlations requires optimal procedures and the proper design of the transmitting channels. In this regard, we address designing a hybrid channel comprising a single-mode cavity accompanied by a super-Gaussian beam and local dephasing parts based on the dynamics of quantum characteristics. We choose two-level atoms and various functions such as traced-distance discord, concurrence, and local-quantum uncertainty to analyze the effectiveness of the hybrid channel to preserve quantum correlations along with entropy suppression discussed using linear entropy. The joint configuration of the considered fields is found to not only preserve but also generate quantum correlations even in the presence of local dephasing. Most importantly, within certain limits, the proposed channel can be readily regulated to generate maximal quantum correlations and complete suppression of the disorder. Besides, compared to the individual parts, mixing the Fock state cavity, super-Gaussian beam, and local dephasing remains a resourceful choice for the prolonged quantum correlations’ preservation. Finally, we present an interrelationship between the considered two-qubit correlations’ functions, showing the deviation between each two correlations and of the considered state from maximal entanglement under the influence of the assumed hybrid channel.
The landscape ecological view of vertebrate species richness in urban areas across biogeographic realms
Authors: Huang Chun-Wei , Ooi Jia Qing , Yau Si Ying
Published: October 2023

Understanding how the spatial arrangement of remnant green spaces in cities complements biodiversity provides an opportunity for synergy between urban development and biological conservation. However, the geography of urbanization is shifting from Europe and North America to Asia and Africa, and more research is needed for fast-growing regions. To understand how shifting urbanization shapes biodiversity patterns, we analyzed the contribution of landscape factors in explaining vertebrate species richness in urban areas across biogeographic realms. We used variation partitioning to quantify and compare the relative importance of landscape factors (composition and configuration) and environmental factors (climate, elevation, and latitude) in explaining vertebrate species richness in landscapes with at least a million inhabitants across biogeographic realms. Our results pointed out that in the Indo-Malayan, the Afrotropical, and the Neotropical realm (on average of 16.46%) and China and India (11.88%), the influence of landscape factors on vertebrate species richness are significantly higher than that of the Palearctic and Nearctic realms (6.48%). Our findings outline the importance of landscape composition and configuration in shaping biodiversity patterns in regions with fast urban growth during the next two decades, such as Africa, Latin America, and Southeastern Asia. We suggest improving land governance and urban planning to construct eco-friendly landscape structures to mitigate biodiversity loss due to urbanization.
A versatile regulatory toolkit of arabinose-inducible artificial transcription factors for Enterobacteriaceae
Authors: Naseri Gita , Raasch Hannah , Charpentier Emmanuelle , Erhardt Marc
Published: October 2023

The Gram-negative bacteriaSalmonella entericaandEscherichia coliare important model organisms, powerful prokaryotic expression platforms for biotechnological applications, and pathogenic strains constitute major public health threats. To facilitate new approaches for research and biotechnological applications, we here develop a set of arabinose-inducible artificial transcription factors (ATFs) using CRISPR/dCas9 andArabidopsis-derived DNA-binding proteins to control gene expression inE. coliandSalmonellaover a wide inducer concentration range. The transcriptional output of the different ATFs, in particular when expressed inSalmonellarewired for arabinose catabolism, varies over a wide spectrum (up to 35-fold gene activation). As a proof-of-concept, we use the developed ATFs to engineer aSalmonellatwo-input biosensor strain, SALSOR 0.2 (SALmonella biosenSOR 0.2), which detects and quantifies alkaloid drugs through a measurable fluorescent output. Moreover, we use plant-derived ATFs to regulate β-carotene biosynthesis inE. coli, resulting in ~2.1-fold higher β-carotene production compared to expression of the biosynthesis pathway using a strong constitutive promoter.
Accelerating the prediction of CO2 capture at low partial pressures in metal-organic frameworks using new machine learning descriptors
Authors: Orhan Ibrahim B. , Le Tu C. , Babarao Ravichandar , Thornton Aaron W.
Published: October 2023

Metal-Organic frameworks (MOFs) have been considered for various gas storage and separation applications. Theoretically, there are an infinite number of MOFs that can be created; however, a finite amount of resources are available to evaluate each one. Computational methods can be adapted to expedite the process of evaluation. In the context of CO2 capture, this paper investigates the method of screening MOFs using machine learning trained on molecular simulation data. New descriptors are introduced to aid this process. Using all descriptors, it is shown that machine learning can predict the CO2 adsorption, with an R2 of above 0.9. The introduced Effective Point Charge (EPoCh) descriptors, which assign values to frameworks’ partial charges based on the expected CO2 uptake of an equivalent point charge in isolation, are shown to be the second most important group of descriptors, behind the Henry coefficient. Furthermore, the EPoCh descriptors are hundreds of thousands of times faster to obtain compared with the Henry coefficient, and they achieve similar results when identifying top candidates for CO2 capture using pseudo-classification predictions.
Integrating stability metrics with high-throughput computational screening of metal–organic frameworks for CO2 capture
Authors: Mohamed Saad Aldin , Zhao Daohui , Jiang Jianwen
Published: October 2023

Metal–organic frameworks (MOFs) have been considered a unique class of hybrid materials for a wide variety of potential applications. With the existence of almost infinite MOFs, high-throughput computational screening (HTCS) is a robust technique to accelerate the search for promising MOFs. However, conventional HTCS studies reported in the literature neglect the stability of MOFs, which must be considered for practical applications. Here we integrate four stability metrics (thermodynamic, mechanical, thermal, and activation) with HTCS to identify top-performing, synthesizable, and stable hypothetical MOFs for CO2 capture. The thermodynamic and mechanical stabilities are evaluated through molecular dynamics simulations, while the activation and thermal stabilities are predicted using machine learning models. Finally, we identify top-performing hypothetical MOFs satisfying all these stability metrics. This study underlines the central importance of integrating stability metrics when screening MOFs for applications.
Climate change is narrowing and shifting prescribed fire windows in western United States
Authors: Swain Daniel L. , Abatzoglou John T. , Kolden Crystal , Shive Kristen , Kalashnikov Dmitri A. , Singh Deepti , Smith Edward
Published: October 2023

Escalating wildfire activity in the western United States has accelerated adverse societal impacts. Observed increases in wildfire severity and impacts to communities have diverse anthropogenic causes—including the legacy of fire suppression policies, increased development in high-risk zones, and aridification by a warming climate. However, the intentional use of fire as a vegetation management tool, known as “prescribed fire,” can reduce the risk of destructive fires and restore ecosystem resilience. Prescribed fire implementation is subject to multiple constraints, including the number of days characterized by weather and vegetation conditions conducive to achieving desired outcomes. Here, we quantify observed and projected trends in the frequency and seasonality of western United States prescribed fire days. We find that while ~2 C of global warming by 2060 will reduce such days overall (−17%), particularly during spring (−25%) and summer (−31%), winter (+4%) may increasingly emerge as a comparatively favorable window for prescribed fire especially in northern states.
Removal of dyes using polymers of intrinsic microporosity (PIMs): a recent approach
Authors: Gogoi Abinash , Barman Hima , Mandal Susovan , Seth Saona
Published: October 2023

This highlight article discusses the recent advancement of polymers of intrinsic microporosity (PIMs) and PIM based materials for removal of dyes by adsorption, nanofiltration and photocatalytic degradation.
Polyol recognition in catalysis: toward selective modification of glycosylated polypeptides with boronic acid–rhodium(ii) catalysts
Authors: Vargas Reyner D. , Ding Yuxuan , Trial Hallie O. , Qian Rouyu , Ball Zachary T.
Published: October 2023

Dynamic covalent assembly of boronic acid groups with polyol motifs can be utilized to template proximity-driven catalytic peptide modification with diazo reagents.
Molecular insights and optimization strategies for the competitive binding of engineered ACE2 proteins: a multiple replica molecular dynamics study
Authors: Sun Jiahao , Liu Xinguo , Zhang Shaolong , Li Meng , Zhang Qinggang , Chen Jianzhong
Published: October 2023

The exploration mechanism and direction for improvement of engineered ACE2 competitive binding.
The effect of surface hydrophobicity and hydrophilicity on ion–ion interactions at water–solid interfaces
Authors: Guan Dong , Tian Ye , Song Yizhi , Zhao Mengze , Liu Kaihui , Xu Li-Mei , Wang En-Ge , Jiang Ying
Published: October 2023

The investigation of alkali metal cations within the H-bonding network of water on graphite and graphene-Cu(111) surfaces reveals the high sensitivity of ion-ion interactions and ionic ordering to the surface hydrophobicity and hydrophilicity.
Red, yellow, green, and blue light-emitting highly crystallized graphene quantum dots derived from lignin: controllable syntheses and light-emitting diode applications
Authors: Gao Tian , Guo Shengnan , Zhang Jiaojiao , Chen Jintao , Yin Shiru , Peng Na , Cai Qun , Xu Huan , Liu Yi
Published: October 2023

“Lighting up” lignin: synthesis of multicolour-emitting GQDs with high crystallinity from lignin within 12 h and their successful application to multicolour LEDs.
Cu/Fe embedded N-doped carbon as a highly durable oxygen reduction electrocatalyst
Authors: Habib Banafsha , Chen Shaowei , Nichols Forrest , Talib Shamraiz Hussain , Arshad Nasima , Zafar Anham , Mahmood Arshad , Zaman Shahid , Janjua Naveed Kausar
Published: October 2023

Dual metal atoms embedded into carbon are emerging electrocatalysts due to synergistic interaction.
Recent advances in metal directed C–H amidation/amination using sulfonyl azides and phosphoryl azides
Authors: Krishna Rao M. V. , Kareem Shaik , Vali Shaik Ramjan , Subba Reddy B. V.
Published: October 2023

This article reviews the recent advances in the transition metal-catalyzed sulfonamidation and phosphoramidation of a variety of organic compounds. It also covers fundamental concepts and mechanistic aspects, including key intermediates and reaction pathways.
A simple method for N-arylation of secondary amides/amines through a NaH-initiated aryne generation strategy
Authors: Jiang Yuanrui , Zhu Wenjing , Huang Jiawen , Luo Fan , Chen Xiaobei , Fang Chunhui , Chen Xin , Liu Shihui , Hu Yanwei , Zhang Shilei
Published: October 2023

A very simple and practical method has been uncovered for N-arylation of many sets of secondary amides/amines.
Enantioselective construction of substituted hydantoins via chiral phosphoric acid catalyzed annulation/Heyns rearrangement of aryl-substituted ureas with glyoxals
Authors: Wang Yong , Li Jingyuan , Li Yanyan , Pi Chao , Wu Yangjie , Cui Xiuling
Published: October 2023

The de novo organocatalyzed enantioselective construction of hydantoins from urea and glyoxal is presented. Chiral phosphoric acid catalyzed [3 + 2] heteroannulation/enantioselective Heyns rearrangement is proposed to be involved.
A selective dual quenching sensor (EY/BG@CDs) for simultaneous monitoring of gentamicin and ketorolac levels in plasma: a highly efficient platform that caters to the needs of therapeutic drug monitoring
Authors: Alhazzani Khalid , Alanazi Ahmed Z. , Mostafa Aya M. , Barker James , El-Wekil Mohamed M. , Bellah H. Ali Al-Montaser
Published: October 2023

This research work introduces a novel sensor that utilizes two fluorophores to enable simultaneous monitoring of gentamicin sulphate (GNT) and ketorolac tromethamine (KET).
Microwave assisted one-pot access to pyrazolo quinolinone and tetrahydroisoxazolo quinolinone derivatives via T3P®-DMSO catalysed tandem oxidative–condensation reaction
Authors: Gowda Darshini , Harsha Kachigere B. , Shalini Veeresha Gowda , Rangappa Shobith , Rangappa Kanchugarakoppal S.
Published: October 2023

A new strategic approach for the synthesis of two important annulated pyrazolo quinolinone and tetrahydroisoxazolo quinolinone derivatives has been reported for the first time from the alcohols using T3P®-DMSO as a catalyst.
Catalytic depolymerization of calcium lignosulfonate to high-value oxygenated aromatic compounds over the efficient Fe2O3-La0.8Sr0.2FeO3
Authors: Deng Jitong , Zhang Jiaren , Zhang Yongjun , Han Hongjing , Wang Haiying , Yuan Huimin , Zhang Yanan , Chen Yanguang
Published: October 2023

The synergistic effect of Fe2O3-La0.8Sr0.2FeO3enhances the selectivity of aromatic compounds, syringin and guaiacol, in liquid-phase products of calcium lignosulfonate depolymerization.
FeCo alloy nanoparticles encapsulated in hollow N-doped carbon as a bifunctional electrocatalyst for aqueous zinc–air batteries with a low voltage gap
Authors: Li Nan , Yang Ting , Lou Hang , Huang Lijuan , Ma Xiaoyu , Jiang Hao , Xiao Jiaxiang , Xie Chao , Yang Yahui
Published: October 2023

Developing bifunctional catalysts with low reversible oxygen reaction potentials (ΔE) to improve the energy conversion efficiency and cycling stability of rechargeable zinc–air batteries (ZABs) remains a huge challenge.
ZIF-8 derived ZnO: a facile catalyst for ammonium perchlorate thermal decomposition
Authors: Mani Gladiya , Kumar Aswathy V. , Mathew Suresh
Published: October 2023

ZIF-8-derived porous ZnO is a facile, low-cost and environmentally benign catalyst with exceptional catalytic efficiency for ammonium perchlorate thermal decomposition at minimal catalyst usage.
Tip effect assisted high active sites for oxygen evolution reaction tuned using transition metals (Cr, Fe and Mo) doped with CoP
Authors: Zhang Xiaoyun , Zhu Shifan , Xu Yixue , Wang Yuqiao
Published: October 2023

Transition metal (Cr, Fe and Mo) doping into CoP array nanocone alters the tip curvature of CoP to achieve the strengthened tip effect with increasing curvature. The strengthened tip effect is conducive to the high-efficiency catalysis.
Back in bismuth: controlling triplet energy transfer, phosphorescence, and radioluminescence via supramolecular interactions
Authors: Marwitz Alexander C. , Nicholas Aaron D. , Magar Rajani Thapa , Dutta Anuj K. , Swanson Joel , Hartman Tyler , Bertke Jeffery A. , Rack Jeffrey J. , Jacobsohn Luiz G. , Knope Karah E.
Published: October 2023

Five bismuth-organic materials that exhibit fluorescence or phosphorescence and radioluminescence are reported, with the photophysical behavior dependent on both the identity of the outer sphere fluorophore and noncovalent interactions.
Multi-resonance TADF in optical cavities: suppressing excimer emission through efficient energy transfer to the lower polariton states
Authors: Cho Inseong , Kendrick William J. , Stuart Alexandra N. , Ramkissoon Pria , Ghiggino Kenneth P. , Wong Wallace W. H. , Lakhwani Girish
Published: October 2023

Strong light-matter coupling is exploited as a way to reduce aggregation-induced excimer losses in multi-resonance thermally activated delayed fluorescence emitters.
First principles calculations of the electronic configuration and photocatalytic performance of GaSe(Ga2SSe)/MoS2(MoSSe) heterojunctions
Authors: Li Lingxia , Ren Junqiang , Li Junchen , Guo Xin , Liu Maocheng , Lu Xuefeng
Published: October 2023

The electronic structure and photocatalytic performance of GaSe/MoSSe and Ga2SSe/MoS2 heterojunctions are systematically investigated by means of first-principles calculations.
Suitable selection of high-energy state excitation to enhance the thermal stability of Eu3+ and the sensitivity of La2CaSnO6:Eu3+,Mn4+ temperature measuring materials
Authors: Duan Feifei , Wang Lei , Shi Qiufeng , Guo Haijie , Qiao Jianwei , Cui Cai’e , Huang Ping
Published: October 2023

A novel approach to enhance the thermal stability of materials doped with Eu3+ ions.
Bluish-green-to-green thermally activated delayed fluorescent emitters based on β-diketone derivatives exhibiting a horizontal emission dipole orientation ratio of 88% and an external quantum efficiency of nearly 25%
Authors: Hoshi Keigo , Sasabe Hisahiro , Sato Ryoma , Yoshida Naoto , Matsuya Misaki , Chiba Yudai , Kido Junji
Published: October 2023

A series of β-diketone-based TADF emitters named MCzX derivatives are designed and prepared. Among these emitters, MCzDBM exhibits a PLQY of 79%, horizontal emission dipole orientation ratio of 88%, and high EQE of approximately 25%.
How to fix DNA breaks: new insights into the mechanism of non-homologous end joining
Authors: Vogt Alex , He Yuan , Lees-Miller Susan P.
Published: October 2023

Non-homologous end joining (NHEJ) is the major pathway for the repair of ionizing radiation-induced DNA double-strand breaks (DSBs) in human cells and is essential for the generation of mature T and B cells in the adaptive immune system via the process of V(D)J recombination. Here, we review how recently determined structures shed light on how NHEJ complexes function at DNA DSBs, emphasizing how multiple structures containing the DNA-dependent protein kinase catalytic subunit (DNA-PKcs) may function in NHEJ. Together, these studies provide an explanation for how NHEJ proteins assemble to detect and protect DSB ends, then proceed, through DNA-PKcs-dependent autophosphorylation, to a ligation-competent complex.