bluuebunny/crossref_metadata_2025 huggingface dataset:
A Methodology for Vulnerability Assessment of Cultural Heritage in Extreme Climate Changes
Authors: Cacciotti Riccardo , Sardella Alessandro , Drdácký Miloš , Bonazza Alessandra
Published: June 2024

Vulnerability evaluation plays a key role in risk assessment and reduction and is essential for defining strategies for climate change adaptation and mitigation. In dealing with the safeguarding of cultural heritage at risk, we are still far from adopting and applying an agreed methodology for vulnerability assessment. With the aim to support practitioners, heritage managers, and policy and decision makers to undertake actions that address the protection of cultural heritage at risk, the methodology set up in the framework of the Interreg Central Europe STRENCH is illustrated and discussed here. Based on three major requirements (susceptibility, exposure, and resilience) and a continuous consultation with local stakeholders, the proposed methodology is applicable for evaluating the vulnerability of built heritage and cultural landscape exposed to hydrometeorological hazards, such as heavy rains, floods, and droughts. The results obtained through its validation on 15 case studies from seven Central European regions are shown to underline the strengths and limitations of the methodological approach. Iterative consultation with local stakeholders was fundamental for the definition of the criteria/subcriteria and related values for the assessment of the requirements. Application to further sites in other contexts would surely contribute to strengthening the reliability of the methodological approach.
A Jacobian smoothing inexact Newton method for solving the nonlinear complementary problem
Authors: Sánchez W. , Arias C. A. , Perez R.
Published: June 2024

In this paper, we propose a Jacobian smoothing inexact Newton-type algorithm for solving the nonlinear complementarity problem by reformulating it as a system of nonlinear equations. We show that the algorithm converges up to q-quadratically and present numerical experiments that show its good local performance. In order to compare in terms of time our algorithm with other known algorithms, we introduce a new normalized measurement that we call time index.
The importance of ultrasound-guided biopsy: lesson from a case of liver metastasis from uveal melanoma
Authors: Boe Maria , Vicari Susanna , Boccatonda Andrea , Piscaglia Fabio
Published: June 2024

Melanoma is an extremely aggressive malignant neoplasm. Uveal melanoma is the most common primary intraocular malignancy in adults, representing 3–5% of all melanomas. Liver metastases can be clinically detected in 10–20% of patients with metastatic disease from cutaneous melanoma. However, while liver is typically not the first site of disease spread in cutaneous melanoma, ocular melanoma has been showed to primarily metastasize from the eye to the liver; indeed, liver metastases are detected in approximately 87% of patients with metastatic uveal melanoma. Therefore, liver metastasis can be challenging to identify in early stages, thus being essentially asymptomatic until the disease has advanced. Here we report the case of a patient who came to our ultrasound unit reporting a large liver mass. Both contrast-enhanced abdominal computed tomography and magnetic resonance imaging did not establish a definitive diagnosis. The final diagnosis was made only through an ultrasound-guided biopsy of the mass, thus revealing a uveal melanoma metastasis. This is followed by a review of the literature on imaging follow-up of patients with melanoma.
‘You Also Have to Let People Go’—Effects of Formative Experiences with Dying and Death on Medical Trainees’ Attitudes
Authors: Jedlicska Nana , Rossmanith Carolin , Lichtenberg Sabrina , Srnová Dagmara , Wijnen-Meijer Marjo , Gartmeier Martin , Berberat Pascal O.
Published: June 2024

This study investigates the effects of medical students’ and residents’ formative patient death experiences on their understanding of the role of the physician in dealing with dying patients. Analyses revealed a change in attitude, an acceptance of death as ‘part of life’. Thoughtful and comprehensive care, allowing patients to die and enabling them to have a beautiful death, were identified as the physician’s duty. Honesty, well timing and completeness were determined as the guiding principles of communication. The importance of distancing and keeping in control to practice the medical profession was stressed. The burdensome nature of making therapeutic decisions was emphasized.
Lithospheric Evolution of the South‐Central United States Constrained by Joint Inversion of Receiver Functions and Surface Wave Dispersion
Authors: Wang Tuo , Gao Stephen S. , Liu Kelly H. , Mickus Kevin L. , Chen Ling
Published: June 2024

In the present study, we use broadband seismic data recorded by 190 stations of the EarthScope program's Transportable Array to construct a 3‐D shear wave velocity model for the upper 180 km using a non‐linear Bayesian Monte‐Carlo joint inversion of receiver functions (RFs) and Rayleigh wave dispersion curves. Ambient noise and teleseismic data are used for obtaining Rayleigh wave phase velocity dispersion curves. A resonance removal filtering technique is applied to the RFs contaminated by reverberations from the thick sedimentary layers that cover most of the region. Our observations of the higher crustal shear velocities (∼3.40 km/s) beneath the Sabine Block (SB), along with the estimated relatively thicker crust (∼34.0 km) and lower crustal Vp/Vs estimates (∼1.80) in comparison with the rest of the Gulf Coastal Plain (GCP) (∼3.10 km/s for crustal shear velocities, ∼29.0 km for crustal thickness, and ∼1.90 for crustal Vp/Vs estimates), indicating that this crustal block has different crustal properties from the surrounding coastal plain regions. The southern Ouachita Mountains have a thin crust (∼30.0 km) and low mean crustal Vp/Vs value (∼1.73), suggesting that lower crustal delamination has occurred in this region. Low velocities in the upper mantle beneath most of the GCP are interpreted as a combined result of thin lithosphere, higher‐than‐normal temperatures, and possibly compositional variations.
The Responses of Soil Nitrogen Transformations to Rainfall Reduction Mainly Occurred in the Early Growing‐Season in a Temperate Meadow
Authors: Yang Xuechen , Sternberg Marcelo , Song Wenzheng , Zhong Shangzhi , Chai Hua , Li Junqin , Yao Yuan , Meng Bo , You Mengyang , Jiang Qi , Yue Xiuquan , Li Lu‐Jun , Ma Jian‐Ying , Sun Wei
Published: June 2024

Drought is expected to increase in temperate regions in the coming decades due to global climate change and will strongly affect nitrogen (N) transformation and balance. However, the underlying mechanisms (soil microenvironment vs. biotic community) of rainfall reduction induced changes in soil N transformation rates, and whether the responses of soil N transformation rates to rainfall reduction vary over time remains poorly understood. In this study, we experimentally examined rainfall reduction effects on soil N transformation rates over two (the second and third experimental years) growing‐seasons in a temperate meadow. We applied four treatments: ambient rainfall, 30%, 50%, and 70% reduction in rainfall. Our findings demonstrated that, 70% rainfall reduction significantly decreased the average net N mineralization and nitrification rates by 68.4% and 72.0%, respectively. Soil nitrous oxide emission was profoundly varied between the experimental years, with it was sensitive no only to changes in annual precipitation amount, but also to seasonal distribution, the highest emissions appeared at the early growing‐season. Moreover, plant diversity, microbial biomass, and soil NO3−‐N content mainly regulated soil N transformation rates in response to rainfall reduction in the greater annual precipitation year; but soil N transformation rates were mainly controlled by soil water content in the less annual precipitation year. We suggest that to accurately project future ecosystem functions and improving the prediction of N cycling responses to changing precipitation patterns, stronger focus should be allocated not only to changes in precipitation amounts, but also to inter‐ and intra‐annual differences in precipitation distribution.
Stochastic Latent Transformer: Efficient Modeling of Stochastically Forced Zonal Jets
Authors: Shokar Ira J. S. , Kerswell Rich R. , Haynes Peter H.
Published: June 2024

We present a novel probabilistic deep learning approach, the “stochastic latent transformer” (SLT), designed for the efficient reduced‐order modeling of stochastic partial differential equations. Stochastically driven flow models are pertinent to a diverse range of natural phenomena, including jets on giant planets, ocean circulation, and the variability of midlatitude weather. However, much of the recent progress in deep learning has predominantly focused on deterministic systems. The SLT comprises a stochastically‐forced transformer paired with a translation‐equivariant autoencoder, trained toward the Continuous Ranked Probability Score. We showcase its effectiveness by applying it to a well‐researched zonal jet system, where the interaction between stochastically forced eddies and the zonal mean flow results in a rich low‐frequency variability. The SLT accurately reproduces system dynamics across various integration periods, validated through quantitative diagnostics that include spectral properties and the rate of transitions between distinct states. The SLT achieves a five‐order‐of‐magnitude speedup in emulating the zonally‐averaged flow compared to direct numerical simulations. This acceleration facilitates the cost‐effective generation of large ensembles, enabling the exploration of statistical questions concerning the probabilities of spontaneous transition events.
Metabolic Characterization and Geochemical Drivers of Active Hydrocarbon‐Degrading Microorganisms
Authors: Li Jibing , Huang Qihui , Cai Xixi , Zhao Xuan , Luo Chunling , Zhang Gan
Published: June 2024

Understanding the metabolic characteristics and controlled geochemical factors of functional microorganisms in petroleum‐contaminated areas at different locations is pivotal for enhancing pollutant removal strategies. To address the existing research gap in this domain, we employed stable‐isotope‐probing (SIP) with multi‐isotope labeling substrates, combined with 16S amplicon sequencing, metagenomic sequencing, and geochemical factor analysis. Utilizing n‐hexadecane and phenanthrene as model compounds, our study revealed location‐specific differences in the composition of functional microorganisms. Despite these variances, key players such as Pseudomonas, Marinobacter, Alcanivorax, Ochrobactrum, and Sphingomonas consistently emerged as active degraders of n‐hexadecane and/or phenanthrene. Several genera, including Pseudomonas, Ochrobactrum, Alcanivorax, Nitriliruptoraceae, and Sphingobacterium, demonstrated versatility by effectively degrading both contaminants. SIP‐metagenomic binning facilitated the acquisition of genomes from key active degraders, such as Pseudomonas sp., Ochrobactrum sp., Sphingomonas sp., and Shinella sp. This enabled a comprehensive analysis of petroleum hydrocarbon degradation pathways and genes, encompassing PAH dioxygenase genes, alkB genes, phthalate, and salicylate‐related pathways. Environmental factor and variation partitioning analysis revealed that oil pollution significantly influences the functional microbial community (12%), followed by available potassium and available nitrogen. Geochemical parameters and geographic location independently explained 14% and 21% of total variations, respectively. Intriguingly, more than half (51%) of the variation in functional microbial community structure remains unexplained, possibly due to unmeasured environmental variables. Our study contributes valuable insights into the in situ bioremediation mechanism for petroleum‐contaminated soil, elucidating factors influencing functional microbial structures across locations. These findings provide a vital theoretical reference for in situ regulation and bioremediation of petroleum hydrocarbon pollution in diverse environmental contexts.
Snapshot imaging of ultrashort electron bunches
Authors: Döpp Andreas
Published: June 2024

New measurements combine spatial and temporal information from optical transition radiation to estimate the three-dimensional structure of electron bunches from a laser wakefield accelerator.
Inhibition of key DNA double strand break repair protein kinases enhances radiosensitivity of head and neck cancer cells to X-ray and proton irradiation
Authors: Fabbrizi Maria Rita , Doggett Thomas J. , Hughes Jonathan R. , Melia Emma , Dufficy Elizabeth R. , Hill Rhianna M. , Goula Amalia , Phoenix Ben , Parsons Jason L.
Published: June 2024

Ionising radiation (IR) is widely used in cancer treatment, including for head and neck squamous cell carcinoma (HNSCC), where it induces significant DNA damage leading ultimately to tumour cell death. Among these lesions, DNA double strand breaks (DSBs) are the most threatening lesion to cell survival. The two main repair mechanisms that detect and repair DSBs are non-homologous end joining (NHEJ) and homologous recombination (HR). Among these pathways, the protein kinases ataxia telangiectasia mutated (ATM), ataxia telangiectasia and Rad3-related (ATR) and the DNA dependent protein kinase catalytic subunit (DNA-Pkcs) play key roles in the sensing of the DSB and subsequent coordination of the downstream repair events. Consequently, targeting these kinases with potent and specific inhibitors is considered an approach to enhance the radiosensitivity of tumour cells. Here, we have investigated the impact of inhibition of ATM, ATR and DNA-Pkcs on the survival and growth of six radioresistant HPV-negative HNSCC cell lines in combination with either X-ray irradiation or proton beam therapy, and confirmed the mechanistic pathway leading to cell radiosensitisation. Using inhibitors targeting ATM (AZD1390), ATR (AZD6738) and DNA-Pkcs (AZD7648), we observed that this led to significantly decreased clonogenic survival of HNSCC cell lines following both X-ray and proton irradiation. Radiosensitisation of HNSCC cells grown as 3D spheroids was also observed, particularly following ATM and DNA-Pkcs inhibition. We confirmed that the inhibitors in combination with X-rays and protons led to DSB persistence, and increased micronuclei formation. Cumulatively, our data suggest that targeting DSB repair, particularly via ATM and DNA-Pkcs inhibition, can exacerbate the impact of ionising radiation in sensitising HNSCC cell models.
Acoustic assessment in mandarin-speaking Parkinson’s disease patients and disease progression monitoring and brain impairment within the speech subsystem
Authors: Diao Yu , Xie Hutao , Wang Yanwen , Zhao Baotian , Yang Anchao , Hlavnicka Jan , Zhang Jianguo
Published: June 2024

Approximately 90% of Parkinson’s patients (PD) suffer from dysarthria. However, there is currently a lack of research on acoustic measurements and speech impairment patterns among Mandarin-speaking individuals with PD. This study aims to assess the diagnosis and disease monitoring possibility in Mandarin-speaking PD patients through the recommended speech paradigm for non-tonal languages, and to explore the anatomical and functional substrates. We examined total of 160 native Mandarin-speaking Chinese participants consisting of 80 PD patients, 40 healthy controls (HC), and 40 MRI controls. We screened the optimal acoustic metric combination for PD diagnosis. Finally, we used the objective metrics to predict the patient’s motor status using the Naïve Bayes model and analyzed the correlations between cortical thickness, subcortical volumes, functional connectivity, and network properties. Comprehensive acoustic screening based on prosodic, articulation, and phonation abnormalities allows differentiation between HC and PD with an area under the curve of 0.931. Patients with slowed reading exhibited atrophy of the fusiform gyrus (FDR p = 0.010, R = 0.391), reduced functional connectivity between the fusiform gyrus and motor cortex, and increased nodal local efficiency (NLE) and nodal efficiency (NE) in bilateral pallidum. Patients with prolonged pauses demonstrated atrophy in the left hippocampus, along with decreased NLE and NE. The acoustic assessment in Mandarin proves effective in diagnosis and disease monitoring for Mandarin-speaking PD patients, generalizing standardized acoustic guidelines beyond non-tonal languages. The speech impairment in Mandarin-speaking PD patients not only involves motor aspects of speech but also encompasses the cognitive processes underlying language generation.
Using a smartwatch and smartphone to assess early Parkinson’s disease in the WATCH-PD study over 12 months
Authors: Adams Jamie L. , Kangarloo Tairmae , Gong Yishu , Khachadourian Vahe , Tracey Brian , Volfson Dmitri , Latzman Robert D. , Cosman Joshua , Edgerton Jeremy , Anderson David , Best Allen , Kostrzebski Melissa A. , Auinger Peggy , Wilmot Peter , Pohlson Yvonne , Jensen-Roberts Stella , Müller Martijn L. T. M. , Stephenson Diane , Dorsey E. Ray ,   the Parkinson Study Group Watch-PD Study Investigators and Collaborators, Adams Jamie L. , Tarolli Christopher , Waddell Emma , Jensen-Roberts Stella , Soto Julia , Hogarth Penelope , Wahedi Mastura , Wakeman Katrina , Espay Alberto J. , Gunzler Steven A. , Kilbane Camila , Spindler Meredith , Barrett Matthew J. , Mari Zoltan , Dumitrescu Liliana , Wyant Kara J. , Chou Kelvin L. , Poon Cynthia , Simuni Tanya , Williams Karen , Tanner Nijee Luthra Caroline , Yilmaz Eda , Feuerstein Jeanne , Shprecher David , Feigin Andrew , Botting Erica
Published: June 2024

Digital measures may provide objective, sensitive, real-world measures of disease progression in Parkinson’s disease (PD). However, multicenter longitudinal assessments of such measures are few. We recently demonstrated that baseline assessments of gait, tremor, finger tapping, and speech from a commercially available smartwatch, smartphone, and research-grade wearable sensors differed significantly between 82 individuals with early, untreated PD and 50 age-matched controls. Here, we evaluated the longitudinal change in these assessments over 12 months in a multicenter observational study using a generalized additive model, which permitted flexible modeling of at-home data. All measurements were included until participants started medications for PD. Over one year, individuals with early PD experienced significant declines in several measures of gait, an increase in the proportion of day with tremor, modest changes in speech, and few changes in psychomotor function. As measured by the smartwatch, the average (SD) arm swing in-clinic decreased from 25.9 (15.3) degrees at baseline to 19.9 degrees (13.7) at month 12 (P = 0.004). The proportion of awake time an individual with early PD had tremor increased from 19.3% (18.0%) to 25.6% (21.4%; P < 0.001). Activity, as measured by the number of steps taken per day, decreased from 3052 (1306) steps per day to 2331 (2010; P = 0.16), but this analysis was restricted to 10 participants due to the exclusion of those that had started PD medications and lost the data. The change of these digital measures over 12 months was generally larger than the corresponding change in individual items on the Movement Disorder Society—Unified Parkinson’s Disease Rating Scale but not greater than the change in the overall scale. Successful implementation of digital measures in future clinical trials will require improvements in study conduct, especially data capture. Nonetheless, gait and tremor measures derived from a commercially available smartwatch and smartphone hold promise for assessing the efficacy of therapeutics in early PD.
A multimodal generative AI copilot for human pathology
Authors: Lu Ming Y. , Chen Bowen , Williamson Drew F. K. , Chen Richard J. , Zhao Melissa , Chow Aaron K. , Ikemura Kenji , Kim Ahrong , Pouli Dimitra , Patel Ankush , Soliman Amr , Chen Chengkuan , Ding Tong , Wang Judy J. , Gerber Georg , Liang Ivy , Le Long Phi , Parwani Anil V. , Weishaupt Luca L. , Mahmood Faisal
Published: June 2024

Computational pathology1,2 has witnessed considerable progress in the development of both task-specific predictive models and task-agnostic self-supervised vision encoders3,4. However, despite the explosive growth of generative artificial intelligence (AI), there have been few studies on building general-purpose multimodal AI assistants and copilots5 tailored to pathology. Here we present PathChat, a vision-language generalist AI assistant for human pathology. We built PathChat by adapting a foundational vision encoder for pathology, combining it with a pretrained large language model and fine-tuning the whole system on over 456,000 diverse visual-language instructions consisting of 999,202 question and answer turns. We compare PathChat with several multimodal vision-language AI assistants and GPT-4V, which powers the commercially available multimodal general-purpose AI assistant ChatGPT-4 (ref. 6). PathChat achieved state-of-the-art performance on multiple-choice diagnostic questions from cases with diverse tissue origins and disease models. Furthermore, using open-ended questions and human expert evaluation, we found that overall PathChat produced more accurate and pathologist-preferable responses to diverse queries related to pathology. As an interactive vision-language AI copilot that can flexibly handle both visual and natural language inputs, PathChat may potentially find impactful applications in pathology education, research and human-in-the-loop clinical decision-making.
Chromosome-scale genome assembly of medicinal plant Tinospora sagittata (Oliv.) Gagnep. from the Menispermaceae family
Authors: Alami Mohammad Murtaza , Shu Shaohua , Liu Sanbo , Ouyang Zhen , Zhang Yipeng , Lv Meijia , Sang Yonghui , Gong Dalin , Yang Guozheng , Feng Shengqiu , Mei Zhinan , Xie De-Yu , Wang Xuekui
Published: June 2024

Tinospora sagittata (Oliv.) Gagnep. is an important medicinal tetraploid plant in the Menispermaceae family. Its tuber, Radix Tinosporae, used in traditional Chinese medicine, is rich in diterpenoids and benzylisoquinoline alkaloids (BIAs). To enhance our understanding of medicinal compounds’ biosynthesis and Menispermaceae’s evolution, we herein report assembling a high-quality chromosome-scale genome with both PacBio HiFi and Illumina sequencing technologies. PacBio Sequel II generated 2.5 million circular consensus sequencing (CCS) reads, and a hybrid assembly strategy with Illumina sequencing resulted in 4483 contigs. The assembled genome size was 2.33 Gb, consisting of 4070 scaffolds (N50 = 42.06 Mb), of which 92.05% were assigned to 26 pseudochromosomes. T. sagittata’s chromosomal-scale genome assembly, the first species in Menispermaceae, aids Menispermaceae evolution and T. sagittata’s secondary metabolites biosynthesis understanding.
Single-nucleus chromatin landscape dataset of mouse brain development and aging
Authors: Ma Yuting , Guo Sicheng , Chen Yixi , Peng Yushan , Su Xi , Jiang Hui , Lin Xiumei , Zhang Jianguo
Published: June 2024

The development and aging of the brain constitute a lifelong dynamic process, marked by structural and functional changes that entail highly coordinated cellular differentiation and epigenetic regulatory mechanisms. Chromatin accessibility serves as the foundational basis for genetic activity. However, the holistic and dynamic chromatin landscape that spans various brain regions throughout development and ageing remains predominantly unexplored. In this study, we employed single-nucleus ATAC-seq to generate comprehensive chromatin accessibility maps, incorporating data from 69,178 cells obtained from four distinct brain regions – namely, the olfactory bulb (OB), cerebellum (CB), prefrontal cortex (PFC), and hippocampus (HP) – across key developmental time points at 7 P, 3 M, 12 M, and 18 M. We delineated the distribution of cell types across different age stages and brain regions, providing insight into chromatin accessible regions and key transcription factors specific to different cell types. Our data contribute to understanding the epigenetic basis of the formation of different brain regions, providing a dynamic landscape and comprehensive resource for revealing gene regulatory programs during brain development and aging.
A dataset on survey designs and quality of social and behavioral science surveys during the COVID-19 pandemic
Authors: Gummer Tobias , Skora Thomas , von Glasenapp Karolina , Naumann Elias
Published: June 2024

In the social and behavioral sciences, surveys are frequently used to collect data. During the COVID-19 pandemic, surveys provided political actors and public health professionals with timely insights on the attitudes and behaviors of the general population. These insights were key in guiding actions to fight the pandemic. However, the data quality of these surveys remains unclear because systematic knowledge about how the survey data were collected during the COVID-19 pandemic is lacking. This is unfortunate, since decades of survey research have shown that survey design impacts data. Our Survey Data Collection and the COVID-19 Pandemic (SDCCP) project deals with this research gap. We collected rich metadata on survey design for 717 social and behavioral science surveys carried out in Germany during the first two years of the COVID-19 pandemic. In this data descriptor, we present a unique resource for a systematic assessment of the survey data collection practices and quality of surveys conducted in Germany during the COVID-19 pandemic.
Differential gene expression in irradiated potato tubers contributed to sprout inhibition and quality retention during a commercial scale storage
Authors: Kumar Sanjeev , Bandyopadhyay Nilantana , Saxena Sudhanshu , Hajare Sachin N. , More Varsha , Tripathi Jyoti , Dahia Yogesh , Gautam Satyendra
Published: June 2024

Current study is the first ever storage cum market trial of radiation processed (28 tons) of potato conducted in India at a commercial scale. The objective was to affirm the efficacy of very low dose of gamma radiation processing of potato for extended storage with retained quality and to understand the plausible mechanism at the gene modulation level for suppression of potato sprouting. Genes pertaining to abscisic acid (ABA) biosynthesis were upregulated whereas its catabolism was downregulated in irradiated potatoes. Additionally, genes related to auxin buildup were downregulated in irradiated potatoes. The change in the endogenous phytohormone contents in irradiated potato with respect to the control were found to be correlated well with the differential expression level of certain related genes. Irradiated potatoes showed retention of processing attributes including cooking and chip-making qualities, which could be attributed to the elevated expression of invertase inhibitor in these tubers. Further, quality retention in radiation treated potatoes may also be related to inhibition in the physiological changes due to sprout inhibition. Ecological and economical analysis of national and global data showed that successful adoption of radiation processing may gradually replace sprout suppressants like isopropyl N-(3-chlorophenyl) carbamate (CIPC), known to leave residue in the commodity, stabilize the wholesale annual market price, and provide a boost to the industries involved in product manufacturing.
OsTH1 is a key player in thiamin biosynthesis in rice
Authors: Faustino Maria , Lourenço Tiago , Strobbe Simon , Cao Da , Fonseca André , Rocha Isabel , Van Der Straeten Dominique , Oliveira M. Margarida
Published: June 2024

Thiamin is a vital nutrient that acts as a cofactor for several enzymes primarily localized in the mitochondria. These thiamin-dependent enzymes are involved in energy metabolism, nucleic acid biosynthesis, and antioxidant machinery. The enzyme HMP-P kinase/thiamin monophosphate synthase (TH1) holds a key position in thiamin biosynthesis, being responsible for the phosphorylation of HMP-P into HMP-PP and for the condensation of HMP-PP and HET-P to form TMP. Through mathematical kinetic model, we have identified TH1 as a critical player for thiamin biofortification in rice. We further focused on the functional characterization of OsTH1. Sequence and gene expression analysis, along with phylogenetic studies, provided insights into OsTH1 bifunctional features and evolution. The indispensable role of OsTH1 in thiamin biosynthesis was validated by heterologous expression of OsTH1 and successful complementation of yeast knock-out mutants impaired in thiamin production. We also proved that the sole OsTH1 overexpression in rice callus significantly improves B1 concentration, resulting in 50% increase in thiamin accumulation. Our study underscores the critical role of OsTH1 in thiamin biosynthesis, shedding light on its bifunctional nature and evolutionary significance. The significant enhancement of thiamin accumulation in rice callus upon OsTH1 overexpression constitutes evidence of its potential application in biofortification strategies.
Scintillation of polyester fabric and clothing via proton irradiation and its utilization in surface imaging of proton pencil beams
Authors: Yamamoto Seiichi , Yamashita Tomohiro , Yoshino Masao , Kamada Kei , Yoshikawa Akira , Nishio Teiji , Kataoka Jun
Published: June 2024

In the realm of radiation therapy, a conspicuous obstacle lies in the dearth of external observation concerning radiation beams aimed at the patient. While real-time monitoring of such beams on the patient's surface during therapy holds promise, the imaging of particle beams has thus far proven to be a formidable task. Here, we show our discovery of polyester fabrics and cloths as auspicious scintillating materials, ideally suited for the visualization of radiation beams upon the patient's surface. The light output of polyester fabrics ranged from 10 to 20% of that observed in plastic scintillators. When exposed to spot scanning proton beams, clear beam spots emerged on the surface of the polyester cloths. The movement of these scanning beams was effectively captured using a CMOS camera in a light-shield-free with lights-off environment. The resulting images provided a means for evaluating spills of the proton beams. The inherent flexibility of polyester fabrics and clothing enhances their appeal for applications in the intricate landscape of radiation therapy, promising a bright future for surface beam imaging endeavors.
Anti-depressant effect of Naringenin-loaded hybridized nanoparticles in diabetic rats via PPARγ/NLRP3 pathway
Authors: El-Marasy Salma A. , AbouSamra Mona M. , Moustafa Passant E. , Mabrok Hoda B. , Ahmed-Farid Omar A. , Galal Asmaa F. , Farouk Hadir
Published: June 2024

Naringenin (NAR) has various biological activities but low bioavailability. The current study examines the effect of Naringenin-loaded hybridized nanoparticles (NAR-HNPs) and NAR on depression induced by streptozotocin (STZ) in rats. NAR-HNPs formula with the highest in vitro NAR released profile, lowest polydispersity index value (0.21 ± 0.02), highest entrapment efficiency (98.7 ± 2.01%), as well as an acceptable particle size and zeta potential of 415.2 ± 9.54 nm and 52.8 ± 1.04 mV, respectively, was considered the optimum formulation. It was characterized by differential scanning calorimetry, examined using a transmission electron microscope, and a stability study was conducted at different temperatures to monitor its stability efficiency showing that NAR-HNP formulation maintains stability at 4 °C. The selected formulation was subjected to an acute toxicological test, a pharmacokinetic analysis, and a Diabetes mellitus (DM) experimental model. STZ (50 mg/kg) given as a single i.p. rendered rats diabetic. Diabetic rat groups were allocated into 4 groups: one group received no treatment, while the remaining three received oral doses of unloaded HNPs, NAR (50 mg/kg), NAR-HNPs (50 mg/kg) and NAR (50 mg/kg) + peroxisome proliferator-activated receptor-γ (PPAR-γ) antagonist, GW9662 (1mg/kg, i.p.) for three weeks. Additional four non-diabetic rat groups received: distilled water (normal), free NAR, and NAR-HNPs, respectively for three weeks. NAR and NAR-HNPs reduced immobility time in forced swimming test and serum blood glucose while increasing serum insulin level. They also reduced cortical and hippocampal 5-hydroxyindoeacetic acid, 3,4-Dihydroxy-phenylacetic acid, malondialdehyde, NLR family pyrin domain containing-3 (NLRP3) and interleukin-1beta content while raised serotonin, nor-epinephrine, dopamine and glutathione level. PPAR-γ gene expression was elevated too. So, NAR and NAR-HNPs reduced DM-induced depression by influencing brain neurotransmitters and exhibiting anti-oxidant and anti-inflammatory effects through the activation PPAR-γ/ NLRP3 pathway. NAR-HNPs showed the best pharmacokinetic and therapeutic results.
TPRO-NET: an EEG-based emotion recognition method reflecting subtle changes in emotion
Authors: Zhang Xinyi , Cheng Xiankai , Liu Hui
Published: June 2024

Emotion recognition based on Electroencephalogram (EEG) has been applied in various fields, including human–computer interaction and healthcare. However, for the popular Valence-Arousal-Dominance emotion model, researchers often classify the dimensions into high and low categories, which cannot reflect subtle changes in emotion. Furthermore, there are issues with the design of EEG features and the efficiency of transformer. To address these issues, we have designed TPRO-NET, a neural network that takes differential entropy and enhanced differential entropy features as input and outputs emotion categories through convolutional layers and improved transformer encoders. For our experiments, we categorized the emotions in the DEAP dataset into 8 classes and those in the DREAMER dataset into 5 classes. On the DEAP and the DREAMER datasets, TPRO-NET achieved average accuracy rates of 97.63%/97.47%/97.88% and 98.18%/98.37%/98.40%, respectively, on the Valence/Arousal/Dominance dimension for the subject-dependent experiments. Compared to other advanced methods, TPRO-NET demonstrates superior performance.
A systematic review and bayesian meta-analysis of medical devices used in chronic pain management
Authors: Shetty Ashish , Delanerolle Gayathri , Deng Chunli , Thillainathan Anish , Cavalini Heitor , Yang Xiaojie , Bouchareb Yassine , Boyd Amy , Phiri Peter , Shi Jian Qing , Deer Timothy
Published: June 2024

Whilst. pharmacological therapies remain the cornerstone of pain management in chronic pain, factors including the current opioid epidemic have led to non-pharmacological techniques becoming a more attractive proposition. We explored the prevalence of medical device use and their treatment efficacy in non-cancer pain management. A systematic methodology was developed, peer reviewed and published in PROSPERO (CRD42021235384). Key words of medical device, pain management devices, chronic pain, lower back pain, back pain, leg pain and chronic pelvic pain using Science direct, PubMed, Web of Science, PROSPERO, MEDLINE, EMBASE, PorQuest and ClinicalTrials.gov. All clinical trials, epidemiology and mixed methods studies that reported the use of medical devices for non-cancer chronic pain management published between the 1st of January 1990 and the 30th of April 2022 were included. 13 studies were included in systematic review, of these 6 were used in the meta-analysis. Our meta-analysis for pain reduction showed that transcutaneous electrical nerve stimulation combined with instrument-assisted soft tissue mobilization treatment and pulsed electromagnetic therapy produced significant treatment on chronic lower back pain patients. Pooled evidence revealed the use of medical device related interventions resulted in 0.7 degree of pain reduction under a 0–10 scale. Significant improvement in disability scores, with a 7.44 degree reduction in disability level compared to a placebo using a 50 score range was also seen. Our analysis has shown that the optimal use of medical devices in a sustainable manner requires further research, needing larger cohort studies, greater gender parity, in a more diverse range of geographical locations.
Single-cell transcriptome analysis reveals secretin as a hallmark of human enteroendocrine cell maturation
Authors: Hysenaj Franc , Lauber Michael , Bast-Habersbrunner Andrea , List Markus , Klingenspor Martin
Published: June 2024

The traditional nomenclature of enteroendocrine cells (EECs), established in 1977, applied the “one cell - one hormone” dogma, which distinguishes subpopulations based on the secretion of a specific hormone. These hormone-specific subpopulations included S cells for secretin (SCT), K cells for glucose-dependent insulinotropic polypeptide (GIP), N cells producing neurotensin (NTS), I cells producing cholecystokinin (CCK), D cells producing somatostatin (SST), and others. In the past 15 years, reinvestigations into murine and human organoid-derived EECs, however, strongly questioned this dogma and established that certain EECs coexpress multiple hormones. Using the Gut Cell Atlas, the largest available single-cell transcriptome dataset of human intestinal cells, this study consolidates that the original dogma is outdated not only for murine and human organoid-derived EECs, but also for primary human EECs, showing that the expression of certain hormones is not restricted to their designated cell type. Moreover, specific analyses into SCT-expressing cells reject the presence of any cell population that exhibits significantly elevated secretin expression compared to other cell populations, previously referred to as S cells. Instead, this investigation indicates that secretin production is realized jointly by other enteroendocrine subpopulations, validating corresponding observations in murine EECs also for human EECs. Furthermore, our findings corroborate that SCT expression peaks in mature EECs, in contrast, progenitor EECs exhibit markedly lower expression levels, supporting the hypothesis that SCT expression is a hallmark of EEC maturation.
Enhancing the yield of Xenocoumacin 1 in Xenorhabdus nematophila YL001 by optimizing the fermentation process
Authors: Han Yunfei , Zhang Shujing , Wang Yang , Gao Jiangtao , Han Jinhua , Yan Zhiqiang , Ta Yongquan , Wang Yonghong
Published: June 2024

Xenocoumacin 1 (Xcn 1), antibiotic discovered from secondary metabolites of Xenorhabdus nematophila, had the potential to develop into a new pesticide due to its excellent activity against bacteria, oomycetes and fungi. However, the current low yield of Xcn1 limits its development and utilization. To improve the yield of Xcn1, response surface methodology was used to determine the optimal composition of fermentation medium and one factor at a time approach was utilized to optimize the fermentation process. The optimal medium composed of in g/L: proteose peptone 20.8; maltose 12.74; K2HPO4 3.77. The optimal fermentation conditions were that 25 °C, initial pH 7.0, inoculum size 10%, culture medium 75 mL in a 250 mL shake flask with an agitation rate of 150 rpm for 48 h. Xenorhabdus nematophila YL001 was produced the highest Xcn1 yield (173.99 mg/L) when arginine was added to the broth with 3 mmol/L at the 12th h. Compared with Tryptic Soy Broth medium, the optimized fermentation process resulted in a 243.38% increase in Xcn1 production. The obtained results confirmed that optimizing fermentation technology led to an increase in Xcn1 yield. This work would be helpful for efficient Xcn1 production and lay a foundation for its industrial production.
Design of intelligent controller for obstacle avoidance and navigation of electric patrol mobile robot based on PLC
Authors: Liu Zhenfang , Li Mengyuan , Fu Dongshuai , Zhang Shuai
Published: June 2024

Currently, the obstacle avoidance control of patrol robots based on intelligent vision lacks professional controller module assistance. Therefore, this paper proposes a design method of intelligent controller for obstacle avoidance and navigation of electrical inspection mobile robot based on PLC control. The controller designs a laser range finder to determine the required position of electrical patrol inspection. Use PLC as the core controller, and combine sensors, actuators, communication module and PLC selection module in the process of hardware design to achieve autonomous navigation and obstacle avoidance functions of the robot. Then design the software including the PLC compiler system and the virtual machine module. Based on the above steps, design the control module of obstacle avoidance navigation, which realizes the key link of robot autonomous navigation. The test results show that the controller can successfully avoid obstacles, improve the efficiency and quality of inspection, and achieve accurate and fast obstacle avoidance navigation for the electrical inspection mobile robot.
An enhanced nonparametric quality control chart with application related to industrial process
Authors: Abid Muhammad , Sun Mei , Shabbir Aroosa , Bakr M. E. , Abbas Tahir
Published: June 2024

In various practical situations, the information about the process distribution is sometimes partially or completely unavailable. In these instances, practitioners prefer to use nonparametric charts as they don’t restrict the assumption of normality or specific distribution. In this current article, a nonparametric double homogeneously weighted moving average control chart based on the Wilcoxon signed-rank statistic is developed for monitoring the location parameter of the process. The run-length profiles of the newly developed chart are obtained by using Monte Carlo simulations. Comparisons are made based on various performance metrics of run-length distribution among proposed and existing nonparametric counterparts charts. The extra quadratic loss is used to evaluate the overall performance of the proposed and existing charts. The newly developed scheme showed comparatively better results than its existing counterparts. For practical implementation of the suggested scheme, the real-world dataset related to the inside diameter of the automobile piston rings is also used.
Thermotactic behaviour in lacustrine and riverine forms of Salmo trutta and its relevance to an emerging parasitic disease (PKD) in the wake of climate change
Authors: Ros Albert , Brinker Alexander
Published: June 2024

The thermotactic response of brown trout (Salmo trutta) was examined with the goal to investigate potential effects of the emerging temperature-dependent fatal trout disease PKD (proliferative kidney disease). First the differences in cold-water preferences of two forms of brown trout, lacustrine (migratory) and riverine, were determined. Second, it was studied whether this preference was changed in fish infected with PKD. The experiment involved a one-week habituation period at 14 °C in a two-chamber runway followed by a week of 3 °C temperature difference between the two runways. The fish could freely move between lanes via an opening at the end where food was provided. The temperature manipulation was repeated twice, and there were 3 trials per experimental group. All fish developed a clear spatial preference in the test. Lacustrine trout demonstrated a preference for warmer water, while riverine trout preferred cooler water. This may increase the risk to PKD in the lacustrine form. Most strikingly, riverine trout experimentally exposed to Tetracapsuloides bryosalmonae, the parasite that causes PKD, demonstrated stronger cold-seeking behaviour than control fish. Cold seeking behaviour suggests the occurrence of a disease-induced behavioural chill response, which may play an important role in disease recovery. This demonstrates the significance of protecting river connectivity and cold-water sanctuaries as management strategies for preserving salmonid populations in a warming climate.
Protein embeddings predict binding residues in disordered regions
Authors: Jahn Laura R. , Marquet Céline , Heinzinger Michael , Rost Burkhard
Published: June 2024

The identification of protein binding residues helps to understand their biological processes as protein function is often defined through ligand binding, such as to other proteins, small molecules, ions, or nucleotides. Methods predicting binding residues often err for intrinsically disordered proteins or regions (IDPs/IDPRs), often also referred to as molecular recognition features (MoRFs). Here, we presented a novel machine learning (ML) model trained to specifically predict binding regions in IDPRs. The proposed model, IDBindT5, leveraged embeddings from the protein language model (pLM) ProtT5 to reach a balanced accuracy of 57.2 ± 3.6% (95% confidence interval). Assessed on the same data set, this did not differ at the 95% CI from the state-of-the-art (SOTA) methods ANCHOR2 and DeepDISOBind that rely on expert-crafted features and evolutionary information from multiple sequence alignments (MSAs). Assessed on other data, methods such as SPOT-MoRF reached higher MCCs. IDBindT5’s SOTA predictions are much faster than other methods, easily enabling full-proteome analyses. Our findings emphasize the potential of pLMs as a promising approach for exploring and predicting features of disordered proteins. The model and a comprehensive manual are publicly available at https://github.com/jahnl/binding_in_disorder.
DCRELM: dual correlation reduction network-based extreme learning machine for single-cell RNA-seq data clustering
Authors: Gao Qingyun , Ai Qing
Published: June 2024

Single-cell ribonucleic acid sequencing (scRNA-seq) is a high-throughput genomic technique that is utilized to investigate single-cell transcriptomes. Cluster analysis can effectively reveal the heterogeneity and diversity of cells in scRNA-seq data, but existing clustering algorithms struggle with the inherent high dimensionality, noise, and sparsity of scRNA-seq data. To overcome these limitations, we propose a clustering algorithm: the Dual Correlation Reduction network-based Extreme Learning Machine (DCRELM). First, DCRELM obtains the low-dimensional and dense result features of scRNA-seq data in an extreme learning machine (ELM) random mapping space. Second, the ELM graph distortion module is employed to obtain a dual view of the resulting features, effectively enhancing their robustness. Third, the autoencoder fusion module is employed to learn the attributes and structural information of the resulting features, and merge these two types of information to generate consistent latent representations of these features. Fourth, the dual information reduction network is used to filter the redundant information and noise in the dual consistent latent representations. Last, a triplet self-supervised learning mechanism is utilized to further improve the clustering performance. Extensive experiments show that the DCRELM performs well in terms of clustering performance and robustness. The code is available at https://github.com/gaoqingyun-lucky/awesome-DCRELM.