bluuebunny/crossref_metadata_2025 huggingface dataset:
Duck Tembusu virus induces incomplete autophagy via the ERK/mTOR and AMPK/mTOR signalling pathways to promote viral replication in neuronal cells
Authors: Wang Qing , Jiang Yaqian , Bao Guangbin , Yao Weiping , Yang Qing , Chen Shuyue , Wang Guijun
Published: May 2023

Duck Tembusu virus (DTMUV) is a neurotropic virus belonging to the genus Flavivirus, and causes massive economic losses to the poultry industry in China and neighbouring countries. Autophagy plays a pivotal role in cellular responses to pathogens and viral pathogenesis. However, little is known about the roles of autophagy in DTMUV replication and virus pathogenesis, especially in neuropathogenesis. In this study, mouse neuroblastoma cells (Neuro-2a) were used to establish a DTMUV infection cell model. Our experiments indicated that DTMUV infection induced incomplete autophagy in Neuro-2a cells. Then, autophagy induced by DTMUV was altered with different autophagy regulators, and we found that incomplete autophagy promoted DTMUV replication. Furthermore, we showed that DTMUV infection activated both the ERK and AMPK pathways, resulting in decreased phosphorylation levels of the autophagy repressor mTOR, subsequently leading to autophagic induction. In addition, we utilized ICR mice as the DTMUV-infected animal model to evaluate the autophagic responses in brain tissues and investigate the effects of autophagy on viral replication and tissue lesions. As a result, we confirmed that DTMUV induced incomplete autophagy in mouse brain tissues and that autophagy inducer treatment promoted DTMUV replication and aggravated DTMUV-induced lesions, whereas autophagy inhibitor treatment led to the opposite effects. Collectively, DTMUV infection induced incomplete autophagy through the ERK/mTOR and AMPK/mTOR signalling pathways to promote viral replication in mouse neuronal cells, and DTMUV-induced incomplete autophagy contributed to the neuropathogenesis of DTMUV.
NIR Light-Controlled DNA Nanodevice for Amplified mRNA Imaging and Precise Gene Therapy
Authors: Xiang Miaomiao , Jiang Yuelin , zhou jiajia , Bao Guochen , Luo Xianzhu , Zhang Le , Jin Dayong , Xian Yuezhong , Zhang Cuiling
Published: May 2023

Accurately delivering antisense oligonucleotides (ASOs) to tumor cells for gene therapy poses a significant challenge. To address this issue, we develop a NIR light-activable DNA nanodevice to target survivin mRNA and simultaneously release ASOs in tumor cells, which allows high-precision spatiotemporal imaging with high sensitivity and efficient gene therapy. The concept is based on upconversion nanoparticles, which can convert NIR light into UV emissions to activate an entropy-driven DNA walking system that further determines mRNA in tumor cells. The intramolecular toehold-mediated entropy-driven catalytic reaction generates a large amount of Bcl-2 ASOs, which allows accurate delivery of ASOs for gene therapy due to the specific targeting of mRNA in tumor cells. Both in vitro and in vivo results show that the NIR light induced-DNA nanodevice can detect mRNA with high sensitivity by DNA walking amplification system and high precision in gene delivery. Moreover, the released ASOs from DNA walking system deregulate the expression of Bcl-2 anti-apoptosis protein and induce tumor cell apoptosis, thereby suppressing tumor growth without a transfection reagent. The NIR-light-controlled DNA nanodevice holds great potential for precise gene therapy in clinical applications.
Assessing the impact of banning the single use plastic carrier bags: A case study for Kenyan marine environment
Authors: Kosore Charles , Waiyaki Edward , Kimanga Faith
Published: May 2023

Poor waste management and unsustainable collective and individual behaviors, have led to the accumulation of plastic litter in many habitats worldwide. Assessment of plastic pollution in Kenyan marine environment was conducted focusing on the impact of banning the single use plastic bags in Kenya. The quantification, composition and distribution of plastics were determined at eleven (11) beaches along Kenyan coastline. A total of 750 plastics were determined with only 53 pieces being single use plastic bags. A great number of plastics (n = 383), including the single use carrier bags were identified by their original use, with packaging plastics being the most common (n = 221). Macroplastics were dominant at 67%, mesoplastics (21%) and microplastics (12%). Low density polyethylene (LDPE) was the dominant polymer (44%), followed by polypropylene (PP), 34%, polystyrene (PS) and polyethylene tetraphthalate (PET), 8% each and polyvinyl chloride (PVC), 6%. The absence of single use plastic bags in various beaches signified the effectiveness of the ban in Kenya. Monitoring of trends and sources of plastic debris is encouraged to help enhance the science-policy linkage aimed at reducing marine plastic pollution.
Harnessing the Synergistic Potential of 3D Printed Buccal Films and Nanostructured Lipid Carriers (NLCs) For Personalised Cannabidiol Delivery
Authors: Abdella Sadikalmahdi , Kim Sangseo , Afinjuomo Franklin , Song Yunmei , Upton Richard , Garg Sanjay
Published: May 2023

Introduction: Cannabidio(CBD) has been recognized for its numerous therapeutic benefits, such as neuroprotection, anti-inflammatory effects, and cardioprotection. However, CBD has some limitations, including unpredictable pharmacokinetics and low oral bioavailability. To overcome the challenges associated with CBD delivery, we employed Design of Experiments (DoE), lipid carriers, and 3D printing techniques to optimize and develop buccal film loaded with CBD-NLCs.
Methods: Three-factor Box-Behnken Design was carried out to optimise the NLCs and analyse the effect of independent factors on dependent factors. The emulsification-ultrasonication technique was used to prepare the NLCs. A pressure-assisted micro-syringe printing technique was used to produce the films. The produced films were studied for physicochemical, and mechanical properties, release profiles, and predicted in vivo performance.
Results: The observed particle size of the NLCs ranged from 12.17 to 84.91nm whereas the PDI varied from 0.099 to 0.298. Lipid and sonication time positively affected the particle size whereas the surfactant concentration was inversely related. CBD was incorporated into the optimal formulation and the observed particle size, PDI, and zeta potential for the CBD-NLCs were 94.2 ±0.47nm, 0.11± 0.01 and−11.8 ± 0.52 mV. Hydroxyethyl cellulose (HEC)-based gel containing the CBD-NLCs was prepared and used as a feed for 3D printing. The CBD-NLCs film demonstrated a two-phase in vitro release profile, wherein an initial burst release of 47% occurred within the first 2h. The predicted AUC0–10h, Cmax, and Tmax were 201.5µg·h/L, 0.74 µg/L, and 1.28 h for a film with 0.4 mg of CBD, respectively.
Conclusion: The finding demonstrates that a buccal film of CBD-NLCs can be fabricated using 3D printing.
Targeted suppression of siRNA biogenesis in Arabidopsis pollen reveals distinct Pol IV activities in the sperm and vegetative cell lineages
Authors: Pachamuthu Kannan , Simon Matthieu , Borges Filipe
Published: May 2023

In plants, small-interfering RNAs (siRNAs) are mainly produced from transposable elements (TEs) within the RNA-directed DNA methylation pathway (RdDM), which is particularly important during reproductive development in many plant species. However, there is limited understanding of the origins, dynamics and function of TE-derived siRNAs acting in different cellular and developmental contexts. Here, we used the RNaseIII-like protein RTL1 to suppress siRNA biogenesis specifically in Arabidopsis pollen, and found distinct siRNA subsets produced in the sperm and vegetative cell lineages via RNA polymerase IV (Pol IV). We show that gametophytic siRNAs produced in the vegetative cell reinforce RdDM in pollen and interploidy hybridization barriers in the seed, while siRNAs produced specifically in sperm cells do not impact the epigenome and are dispensable for the “triploid block”. These results demonstrate that active siRNA biogenesis in the two pollen cell types has contrasting roles in transposon silencing and transgenerational epigenetic inheritance.
The development of a novel sexual health promotion intervention for young people with mental ill-health: the PROSPEct project.
Authors: Nolan Hayley , O'Donoghue Brian , Simmons Magenta , Zbukvic Isabel , Ratcliff Sophia , Milton Alyssa , Hughes Elizabeth , Thompson Andrew , Brown Ellie
Published: May 2023

Background
Young people with mental ill-health have higher rates of high-risk sexual behaviour, poorer sexual health outcomes, and lower satisfaction with their sexual wellbeing compared to their peers. Ensuring good sexual health in this cohort is a public health concern, but best practice intervention in the area remains under-researched. The study aimed to co-produce a novel intervention to address the sexual health needs of young people with mental ill-health to test its effectiveness in a future trial.
Methods
We followed the 2022 Medical Research Council (MRC) guidelines for developing and evaluating complex interventions. This involved synthesising evidence from the 'top down' (published evidence) and 'bottom up' (stakeholder views). We combined systematic review findings with data elicited from qualitative interviews and focus groups with young people, carers, and clinicians and identified critical cultural issues.
Results
Existing evidence in the field of sexual health in youth mental health was limited but suggested the need to address sexual wellbeing as a concept broader than an absence of negative health outcomes. The Information-Motivation-Belief model was chosen as the theoretical Framework on which to base the intervention. Interviews/focus groups were conducted with 29 stakeholders (18 clinicians, three carers, and eight young people). Synthesis of the evidence gathered resulted in the co-design of a novel intervention consisting of an initial consultation and four 60-90-minute sessions delivered individually by a clinician with additional training in sexual health. Barriers and supports to intervention success were also identified.
Conclusions
Using the MRC Framework has guided the co-development of a potentially promising intervention that addresses the sexual health needs of young people with mental ill-health. The next step is to test the intervention in a one-arm feasibility trial.
Automatic anomaly detection in engineering diagrams using machine learning
Authors: Shin Ho-Jin , Lee Ga-Young , Lee Chul-Jin
Published: May 2023

This study implements a method of automating anomaly detection in engineering diagrams by extracting patterns within graphs after recognizing graphs from Piping and Instrumentation Diagram (P&ID). The framework consists of three parts: graph generation, subgraph extraction, and graph classification. Graphs are generated through symbol recognition and line recognition, and subgraphs are extracted using the frequent subgraph mining algorithm. The graph classification targets are divided into two categories according to the frequency of the main equipment of the extracted subgraph. If the frequency is low, it is classified through whether to include a user-defined subgraph, and if it is high, it is trained in a support vector machine (SVM) algorithm after vector embedding to generate a classification model. K-fold cross-validation is also applied to increase classification accuracy. The proposed framework shows 85% accuracy for a given test drawing through cross-validation. These outcomes contribute to the field of plant diagram analysis and have potential applications in various industries.
Periodic Law Patterns of Sequence Stratigraphy
Authors: Li Shaohu
Published: May 2023

Based on the current theory of sequence stratigraphy, this study employs stillstand normal regression (SNR) to replace the method of highstand normal regression (HNR) to establish shoreline trajectory and sediment supply models of off-lap and onlap-type sequences, respectively. The basic principle of the digital model-driven approach in this study is to decompose the shoreline trajectory (fst) and sediment supply trajectory (fss) into their vertical and horizontal projection vectors to establish periodic sufficient condition of shoreline trajectory and sediment supply trajectory, aiming to obtain the remnant maximum flooding surface (RMFS) and/or its intersecting subaerial unconformity (ISU) sequence model: HST (SNR)-FSST (FR)-LST (LNR)-TST (T). This model established the synchronic necessary condition of shoreline trajectory and sediment supply trajectory and obtained the periodic law patterns of sequence stratigraphy, proposed as “two rhombuses sandwiching one subaerial unconformity”. This study defines a sequence as: a sequence is a stratigraphic unit constrained by periodic sufficient condition and synchronic necessary condition of shoreline and sediment supply trajectories and is composed of a relatively conformable succession of genetically interrelated strata bounded at their top and base by RMFS and/or intersecting subaerial unconformities (ISU). Moreover, the periodic laws of sequence stratigraphy show that the RMFS is almost potentially correlative to the lower boundary of the stage B (global boundary stratotype section and point) of chronostratigraphic units and close to the biohorizon or first appearance datums (first appearance datums) of biostratigraphic units.
Policy and Women Entrepreneurs in MSEs in Ethiopia: Does Gender Moderate the Relationship between Policy Component of the Entrepreneurial Ecosystem and the Performance of MSEs?
Authors: Wube Mulugeta Chane , Atwal Heena
Published: May 2023

The authors have requested that this preprint be removed from Research Square.
Mid-infrared photodetector spectrometer concept based on ultra-thin all-dielectric metamaterial with azimuth-incidence-angle tuned perfect optical absorption: Design and analysis
Authors: Avrahamy Roy , Zohar Moshe , Milgrom Benjamin , Auslender Mark
Published: May 2023

Novel concepts for efficient compact spectroscopy are extensively researched due to their fundamental applications in prominent fields such as biology, pharmaceutical, chemistry, physics, and environment. Here we aim to introduce such a concept with potentially unprecedented, to the best of our knowledge, resolution in the impinging radiation's spectra and azimuth. Though it can be employed in various spectral regions, we exemplify the concept in the mid-infrared, in which its advantages are paramount and have yet to be established industrially. The concept is based on the design and instrumentation of optical absorption spectral tuning (or sensitivity) to the azimuthal component of light impinging on specifically-designed metamaterials. We exemplify the concept with vacuum-wavelength (λ0) scale thick metamaterials optimized for perfect photo-absorption inside an embedded λ0/200 ultra-thin layer of lead telluride. We propose and analyze two small-footprint system designs to instrument the spectral-azimuth-angle tuning for spectrometry. The first is based on a single or few spinning metamaterial layout elements (pixels), and the second, to avoid spinning, follows a fixed focal-plane-array approach. The latter exploits the inherent variations in the local azimuthal-incidence angle instead of the typically utilized slightly varying polar angles. While low absorption is the Achilles heel of conventional mid-infrared photodetector spectrometers, the optimized pixels, in addition to their unique spectral-azimuth-angle tuning functionality, provide giant absorption enhancement, which facilitates higher resolution and even smaller in-plane form factor.
The highlighted concept opens an additional dimension to encode and decode spectral information, which yields profound advantages over conventional designs as diffraction gratings based.
Tree architecture modulates the trends in greenness and water content of European forest canopies
Authors: Alkama Ramdane , Girardello Marco , Ceccherini Guido , Forzieri Giovanni , Koffi Ernest N. , Roebroek Caspar , Cescatti Alessandro
Published: May 2023

The ongoing rapid changes in climate pose significant pressures on forests’ health and growth with modalities that are still poorly understood1–3. Trees’ structural properties like tree height, leaf and root biomass, result from the interplay between plant physiology and key environmental factors like temperature and water. On the other hand, the combination of these structural properties and site characteristics controls the functioning of trees and their sensitivity to environmental stressors. The unbalance between tree architecture and environmental conditions driven by climate change may therefore affect plant growth, vulnerability and mortality, ultimately affecting the stability of the terrestrial carbon cycle and the mitigation potential of land-based climate solutions 4 . Here we use satellite data and machine learning to assess the response of European forests to changing climate over 2001-2020. We show that tree architecture, topography and soil characteristics largely control the recent trend in forest greenness and dryness. Specifically, our results show that tree height and the vertical distribution of leaves have a strong effect on the canopy decline observed in large areas of Europe, with toller trees having leaves close to the top that show browning and drying signals. In addition, we demonstrate that the negative impact of recent climate trends is exacerbated on south-facing slopes and in nutrient-rich soil with high bulk density. These architectural and environmental controls of the trees’ response to climate are currently not accounted for in vegetation models, which therefore poorly represent the recent pattern of forest dieback 5,6, and may therefore underestimate the risks of natural disturbances and tree mortality. These findings unveil the drivers of the worrying trends in EU forest conditions. In parallel, they offer valuable insights for the development of climate-effective practices for the management of EU forests under the pressure of climate change.
Selection on size has generated distinctive paired wing flight systems for butterfly flight and migration
Authors: Childers Richard Rabideau , Cai Liming , Chowdhury Shawan , Crall James , Cornwall Mark , Sipe Rachel Hawkins , Maier Crystal , Maunsell Sarah , Talavera Gerard , Tsai Cheng-Chia , Angier Katherine , Barve Vijay , Dankowicz Evan , Hinolan Jomar , Itliong Micael , Naive Mark Arcebal , Johnson Gunnar , Matos Francisco , Morgan Valentina , Plotkin David , Salcedo Mary , Shirey Vaughn , Vermilya Kimberly , Winstanley Jalen , Wu Amy , Guralnick Robert , Kawahara Akito , Lohman David , Ries Leslie , Soucy Edward , Vila Roger , Yu Nanfang , Pierce Naomi , Chan Wei-Ping
Published: May 2023

Butterfly migration across great distances is testimony to their impressive aeronautical skills. Wing size and shape are two key determinants of flight performance, and in butterflies, the specific configuration of forewings to hindwings including the overlapping area between them can have profound effects on overall size and shape. Here we use quantitative morphometrics to analyze the wing size, shape, and flight performance of 190 exemplar species representing a tribal-level phylogeny of Papilionoidea. We identify three morphological ‘flight systems’ that are characterized by these fore- and hindwing configurations (small [beating], medium, and large [gliding]), and our data suggest that the emergence of these systems coincided with periods of paleoclimatic upheaval. A higher proportion of migratory species have wings characteristic of gliders, and their degree of host specialization appears to be more flexible than that of counterparts with beating wings.
On-Line Data-Driven Control for Uncertain Systems Based on Greedy Algorithm
Authors: Shen Jiahui , Liu Xinggao
Published: May 2023

Considering a result that persistently exciting data can used to replace the linear system model, this paper is devoted to applying this result in the field of data-driven control of nonlinear systems. An on-line iteration based on greedy algorithm to stabilize uncertain discrete-time systems is proposed. The method tends to obtain the approximate optimal control through solving a series of programming problems. Every programming problem is linear for the convenience of solving. Besides, in particular, the methods requires few prior conditions, as long as the system is controllable and observable and the equilibrium state of the system is known. First, we prove that under certain circumstances, the solution of our linear matrix inequality can stabilize the system. Next, a multi-objective programming problem is proposed to dealing with situations where the required conditions are unknown. Finally, an on-line iteration is used to enhance robustness as well as real-time evaluation. The method is illustrated to be effective through a simulation on a discretized inverted pendulum system under repeated experiments.
Your smartphone could act as a pulse-oximeter and as a single-lead ECG
Authors: Mehmood Ahsan , Sarouji Asma , Rahman Muhammad Mahboob Ur , Al-Naffouri Tareq
Published: May 2023

In the post-covid19 era, every new wave of the pandemic causes an increased concern/interest among the masses to learnmore about their state of well-being. Therefore, it is the need of the hour to come up with ubiquitous, low-cost, non-invasivetools for rapid and continuous monitoring of body vitals that reflect the status of one’s overall health. In this backdrop, this workproposes a deep learning approach to turn a smartphone—the popular hand-held personal gadget—into a diagnostic tool tomeasure/monitor the three most important body vitals, i.e., pulse rate (PR), blood oxygen saturation level (aka SpO2), andrespiratory rate (RR). Furthermore, we propose another method that could extract a single-lead electrocardiograph (ECG)of the subject. The proposed methods include the following core steps: subject records a small video of his/her fingertip byplacing his/her finger on the rear camera of the smartphone, and the recorded video is pre-processed to extract the filteredand/or detrended video-photoplethysmography (vPPG) signal, which is then fed to custom-built convolutional neural networks(CNN), which eventually spit-out the vitals (PR, SpO2, and RR) as well as a single-lead ECG of the subject. To be precise,the contribution of this paper is two-fold: 1) estimation of the three body vitals (PR, SpO2, RR) from the vPPG data usingcustom-built CNNs, vision transformer, and most importantly by CLIP model (a popular image-caption-generator model); 2) anovel discrete cosine transform+feedforward neural network-based method that translates the recorded video-PPG signal to asingle-lead ECG signal. The significance of this work is two-fold: i) it allows rapid self-testing of body vitals (e.g., self-monitoringfor covid19 symptoms), ii) it enables rapid self-acquisition of a single-lead ECG, and thus allows early detection of atrialfibrillation (abormal heart beat or arrhythmia), which in turn could enable early intervention in response to a range of cardiovascular diseases,and could help save many precious lives. Our work could help reduce the burden on healthcare facilities and could lead toreduction in health insurance costs.
Polyphenol addition to cooked ham modifies the abundance of fecal volatile metabolites involved in the formation of preneoplastic colon lesions
Authors: Giménez-Campillo Claudia , Campillo Natalia , Arroyo-Manzanares Natalia , Martínez Carlos M. , Minguela Carlos de Torre , Viñas Pilar
Published: May 2023

Epidemiological studies have shown that haem iron from processed meat is a key element involved in the colon carcinogenesis. The haem iron induces lipid peroxidation in the colon lumen during digestion, enabling the formation of cytotoxic molecules derived from these reactions. The cytotoxic molecules generated are highly dependent on dietary factors such as lipid sources, calcium levels or the presence of antioxidants during digestion. Here, we investigated whether nitrite substitution by polyphenols as a food additive could modulate the in vivo luminal lipid peroxidation in the colon and consequently, reduce the formation of mucin-depleted foci in a chemical-induced colon cancer rat model. The addition of polyphenols to the cooked ham increases its antioxidant capacity, reducing the lipid peroxidation measured before and during the digestion. We observed a reduction in cytotoxic aldehydes in fecal water from animals fed with polyphenols as well as a decrease in the formation of mucin-depleted foci. The antioxidant capacity derived from polyphenols modifies the luminal environment of the colon, allowing the identification of a specific molecular signature derived from the analysis of fecal volatile organic compounds. In this molecular signature is included the reduction in the abundance of (2E,4E)-2,4-hexadienal, a carcinogenic aldehyde derived from lipid peroxidation.
Machine-learning predictions for acute kidney injuries after coronary artery bypass grafting: A real-life muticenter retrospective cohort study
Authors: Jia Tianchen , Xu Kai , Bai Yun , Lv Mengwei , Shan Lingtong , Li Wei , Zhang Xiaobin , Li Zhi , Wang Zhenhua , Zhao Xin , Li Mingliang , Zhang Yangyang
Published: May 2023

Background
Acute kidney injury (AKI) after coronary artery bypass grafting (CABG) surgery is associated with poor outcomes. The objective of this study was to apply a new machine learning (ML) method to establish prediction models of AKI after CABG.
Methods
Totally 2780 patients from two medical centers in East China who underwent primary isolated CABG were enrolled. Then the dataset was randomly divided for model training (80%) and model testing (20%). Four ML models based on LightGBM, Support vector machine (SVM), Softmax and random forest (RF) algorithms respectively were established on Python. A total of 2051 patients from two other medical centers were assigned to an external validation group to verify the performances of the ML prediction models. The models were evaluated using the area under the receiver operating characteristics curve (AUC), Hosmer-Lemeshow goodness-of-fit statistic, Bland-Altman plots, and decision curve analysis. The outcome of the LightGBM model was interpreted using SHapley Additive exPlanations (SHAP).
Results
The incidence of postoperative AKI in the modeling group was 13.4%. Similarly, the incidence of postoperative AKI of the two medical centers in the external validation group was 8.2% and 13.6% respectively. LightGBM performed the best in predicting, with an AUC of 0.8027 in internal validation group and 0.8798 and 0.7801 in the external validation group. The SHAP revealed the top 20 predictors of postoperative AKI ranked according to the importance, and the top three features on prediction were the serum creatinine in the first 24h after operation, the last preoperative Scr level, and body surface area.
Conclusion
This study provides a LightGBM predictive model that can make accurate predictions for AKI after CABG surgery. This ML model shows good predictive ability in both internal and external validation. It can help cardiac surgeons identify high-risk patients who may experience AKI after CABG surgery.
Reproductive behavior of Ogre-faced spider, Deinopis cf. cylindracea, in its natural habitat
Authors: Ponte Rafael Pereira da , Stefani Vanessa , Villanueva-Bonilla German Antonio , Vasconcellos-Neto João
Published: May 2023

In the present study, the reproductive behavior of a representative of the Deinopidae family, Deinopis cf. cylindracea, has been described for the first time. The behavioral aspects observed were the construction of the male’s spermatic web, male’s approach to fertilization, and end of the couple’s pairing. As soon as a male found a female, he was observed to promote sperm induction. The spermatic web is a Y-shaped web, whose internal space forms a flat surface onto which the male deposits his gametes, which are then collected by his copulatory bulbs from the opposite side of the web. After transferring the spermatic drops to the pedipalp, the male walked towards the female, approaching her from the dorsal-abdominal region using the dragline thread of the web. The male used his legs to touch both the web and female spider, inducing the female to let go, and positioned her ventral region towards her cephalothorax. The couple hung upside down, with the cephalothorax suspended perpendicular to the floor by a silk thread. In this position, the male inserted the plunger of the copulatory bulb into the female epigynum and transferred the sperm. The male separated quickly by extending his legs and moving away, returning to a superior position in relation to the female. The female, in turn, returned to the prey-ready posture, clipping the capture net again and positioning herself in the same manner as before the reproductive behavior.
Predicting diagnosis and survival of bone metastasis in breast cancer using machine learning
Authors: Zhong Xugang , Lin Yanze , Zhang Wei , Bi Qing
Published: May 2023

Background This study aimed at establishing more accurate predictive models based on novel machine learning algorithms, with the overarching goal of providing clinicians with effective decision-making assistance.Methods We retrospectively analyzed 283,373 breast cancer patients recorded in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2016. Multivariable logistic regression analyses were used to identify risk factors for bone metastases in breast cancer, whereas Cox proportional hazards regression analyses were used to identify prognostic factors for breast cancer with bone metastasis (BCBM). Based on the identified risk and prognostic factors, we developed diagnostic and prognostic models that incorporate six machine learning classifiers. We then used the area under the receiver operating characteristic (ROC) curve (AUC), learning curve, precision curve, calibration plot, and decision curve analysis to evaluate performance of the machine learning models.Results Univariable and multivariable logistic regression analyses showed that bone metastases were significantly associated with age, race, sex, grade, T stage, N stage, surgery, radiotherapy, chemotherapy, tumor size, brain metastasis, liver metastasis, lung metastasis, breast subtype, and PR. Univariate and multivariate Cox regression analyses revealed that age, race, marital status, grade, surgery, radiotherapy, chemotherapy, brain metastasis, liver metastasis, lung metastasis, breast subtype, ER, and PR were closely associated with the prognosis of BCBM. Among the six machine learning models, the XGBoost algorithm predicted the most accurate results (AUC = 0.98; AUC = 0.88). According to the Shapley additive explanations (SHAP), the most critical feature of the diagnostic model was surgery, followed by N stage. Interestingly, surgery was also the most critical feature of prognostic model, followed by liver metastasis.Conclusions Based on the XGBoost algorithm, we could effectively predict the occurrence of bone metastases in breast cancer and provide targeted references for the treatment of BCBM patients.
Dysnatremia and Subsequent Serum Sodium Level Changes Following Various Intravenous Treatments in Infants with Acute Gastroenteritis
Authors: Sakkongviseth Wattanaporn , Sommai Kanokwan , Sumboonnanonda Achra , Pattaragarn Anirut , Supavekin Suroj , Piyaphanee Nuntawan , Lomjansook Kraisoon , Thunsiribuddhichai Yarnarin , Chaiyapak Thanaporn
Published: May 2023

Purpose
Acute gastroenteritis (AGE) is one of the main causes of electrolyte imbalance in infants. We aimed to determine the incidence of and factors associated with early dysnatremia and establish the ideal intravenous (IV) treatment scheme.
Methods
The records of hospitalized infants aged 1–12 months with community-acquired AGE between January 2017 and March 2021 were retrospectively reviewed. Factors associated with early dysnatremia were analyzed by multivariable logistic regression analysis. Subsequent serum sodium levels 4–24 hours after IV fluid treatments, which were categorized into 3 groups, were determined in the subgroup of infants with early isonatremia.
Results
In total, 347 infants with a median age of 8.0 (5.0, 10.0) months were included. The incidence of early dysnatremia was 14.4% (hyponatremia 12.4% and hypernatremia 2.0%). Severe dehydration was associated with early dysnatremia (p = 0.048). Among 70 infants with early isonatremia, the median serum sodium change was highest in the D-5NS group, with changes of + 3 (0.5, 5), + 1 (-2, 2) and − 2.5 (-4, 2.3) mmol/L in infants who received D5-NS, D-1/2NS, and D5-1/3 − 1/5NS, respectively (p = 0.003). Four out of 39 infants (10.3%) developed hyponatremia while receiving D5-1/2NS. None of those who received D5-NS developed subsequent dysnatremia.
Conclusions
The incidence of early dysnatremia among infants with AGE was 14.4%. Severe dehydration was a strong factor associated with early dysnatremia, so electrolyte levels need to be assessed. The use of isotonic solution did not promote acquired dysnatremia. We therefore recommend that isotonic solution be considered for infants with AGE.
Changes in proprioception at different time points following anterior cruciate ligament injury or reconstruction
Authors: Zhao Yixuan , Chen Ze , Li Longfei , Wu Xipeng , Li Wei
Published: May 2023

Purpose:To investigate the changes in 30° and 60° position sense in patients with anterior cruciate ligament (ACL) injury at different time points after injury and reconstruction.
Methods：Patients were divided into six groups according to time after ACL injury and reconstruction: group A (ACL injury 1.5–6 months), group B (ACL injury 6–12 months), group C (ACL injury >12 months), group D (postoperative ACL reconstruction 1–6 months), group E (postoperative ACL reconstruction >6 months), and group F consisting of 14 healthy adults (control group). The ability of the affected leg to reproduce the same joint position during knee flexion was tested using active joint position sense assays to assess proprioception in both the lower extremities of the patient or between the patient and the control group.
Results:Proprioception decreased rapidly during the early stages of ACL injury. Significant difference in the affected side at 30° compared to the healthy side (Group A: 4.70(4.78,9.00) vs 4.15(3.35,6.13), P=0.03; Group B: 2.90(0.48,4.56) vs 8.30(4.18,10.43), P=0.001; Group E: 6.25(2.55,11.60) vs 9.60(3.90,12.73), P=0.009). However, no significant differences were detected for a double lower limb contrast of 60°(Group A: 5.1(1.00,8.00) vs 3.00(0.75,3.55), P=0.044). Finally, significant differences were found between patients on the affected side and healthy subjects (P<0.01).
Conclusion: ACL injury had a greater impact on the patient's 30° position sense, with only a small impact for 60°. Further, the early and middle proprioception recovery stages after ACL injury were the best before surgery. Finally, proprioception recovery training should be performed soon after injury.
Transplantation of thermosensitive hydrogel encapsulated miR-216a-5p overexpressing mesenchymal stem cells for functional recovery of spinal cord injury
Authors: Dou Zhi , He Liangliang , Yue Jianning , Zhao Wenxing , Yang Liqiang
Published: May 2023

Spinal cord injury (SCI) is one of the most incapacitating conditions, with neuropathic pain (NP) as a comorbidity that is the most difficult to treatment. In recent years, microRNAs (miRNAs) have been studied more thoroughly in SCI. In this study, based on the construction of the SCI rat model, miR-216a-5p expression was reduced in SCI rats through experimental validation analysis. And human mesenchymal stem cells (hMSCs) overexpressing miR-216a-5p were loaded by constructing thermosensitive hydrogels and transplanted into SCI rats. It was found that the constructed hydrogel system exhibited temperature-dependent phase change behavior and biodegradability, and rats with spinal cord injury showed considerable behavioral recovery and significantly reduced cellular mortality after transplantation. Mechanistic studies revealed that sustained release of miR-216a-5p was able to bind to the 3'UTR of NUDT21 and involve in the regulation of recovery after SCI through modulation of NUDT21, thus greatly increasing recovery after spinal cord injury. Thus, thermosensitive hydrogel-encapsulated human mesenchymal stem cells overexpressing miR-216a-5p provide a microenvironmentally responsive and noninvasive pathway for recovery from spinal cord injury, we hypothesized that miR-216a-5p could be a potential biomarker for neuropathic pain.
The clarity and adaptability of instructions preventing the spread of the Covid-19 virus. Perceptions of staff in care of older people in Sweden and their association with individual factors and organisational factors regarding the psychosocial work environment. A cross-sectional study
Authors: Hammar Lena Marmstål , Alam Moudud , Eklund Caroline , Boström Anne-Marie , Löwenmark Annica
Published: May 2023

Background Older people in residential care had the highest mortality rates, followed by those who received home care during the COVID-19 pandemic in Sweden. Staff working in the care of older persons assumed responsibility for preventing the spread of the virus in spite of lacking the prerequisites and training to do so. This study aimed to investigate how staff in the care of older people described their psychosocial work environment during the COVID-19 pandemic; it also aimed to examine the perceived clarity of the instructions and the staff’s ability to follow the instructions to prevent the spread of the virus and its association with individual factors and organisational factors regarding the psychosocial work environment.Methods A cross-sectional web survey was conducted for the data collection. The staff’s perceptions of their psychosocial environment were analysed using descriptive statistics. The association between organisational and individual factors, as well as the degree of clarity of the instructions and the staff’s ability to follow them, were assessed using multivariate (ordinal) regression analysis.Results The main findings were that perceptions of the clarity and adaptability of the instructions were primarily correlated with organisational factors, as higher responses (positive) for the subscales focusing on positive challenges, role clarity, control, support and encouragement in leadership at work were associated with the belief that the instructions were clear. Similarly, those indicating high job demands and high individual learning demands were less likely to report that the instructions were clear.Conclusions High job demands and individual learning demands were demonstrated to decrease the staffs understanding and adoption of instructions. These findings are significant on an organisational level, since the work environment must be prepared for potential future pandemics to promote quality improvement and to generally increase patient safety as well as the health of staff.
Pulse-Poled Porous BaTiO3 Ceramic for Piezocatalysis Applications
Authors: Gaur Akshay , Porwal Chirag , Boukhris Imed , Mahmoud Z. , Chauhan Vishal Singh , Vaish Rahul
Published: May 2023

The porous ceramic BaTiO3 pellets were synthesized by using polymethyl methacrylate (PMMA) as a pore former in 0–30 wt% proportion through solid route reaction method. Further, the synthesized porous BaTiO3 ceramic pellets were poled via pulse poling; a non traditional poling technique and their piezoactivity were examined by means of piezovoltage. There was significant enhancement in piezoelectric coefficient (d33) of porous BaTiO3 ceramic pellets using pulse poling technique. Later on, in the present study a quantitative analysis was done through comparision by degrading an organic dye by using poled/ unpoled porous BaTiO3 sample.
Response of Meiyu Process Considering the Temporal and Spatial Characteristics of GNSS PWV
Authors: Ke Fuyang , Zhao Pan , Yu Wei , Hong Guan , Tian Jianing , Ming lulu
Published: May 2023

This study explores the spatiotemporal characteristics of Global Navigation Satellite System (GNSS) Precipitable Water Vapor (PWV) and its relationship with the Meiyu process. Using multiple sources of atmospheric PWV data and meteorological information, the study quantitatively analyzes PWV's spatiotemporal characteristics and its association with the onset and withdrawal of the Meiyu season. The research findings are as follows: (1)PWV's spatiotemporal evolution provides indications for the Meiyu season. The daily variation of water vapor content generally follows a camelback shape. Before the Meiyu season begins, PWV exhibits an upward trend with content below 40mm. After the onset of the Meiyu season, PWV gradually accumulates during the early Meiyu season with content exceeding 50mm, accompanied by rainfall. In the late Meiyu season, water vapor releases, leading to a decrease in PWV content. After the Meiyu season ends, PWV gradually declines but remains relatively high, linked to moisture transport during the Jianghuai flood season. (2)Anomaly analysis reveals that water vapor activity is highest during the Meiyu season, showing good correspondence with special Meiyu years. This provides new insights for monitoring and forecasting abnormal Meiyu events. (3)Spatially, PWV distribution during the Meiyu season exhibits a pattern of more water vapor in southern regions and less in northern areas. This pattern is influenced by the stronger atmospheric water storage capacity in low-latitude areas and the gradual weakening of monsoon water vapor during northward and westward transport.
The Power of Progressive Active Learning in Floorplan Images for Energy Assessment
Authors: Al-Turki Dhoyazan , Kyriakou Marios , Basurra Shadi , Gaber Mohamed Medhat , Abdelsamea Mohammed M.
Published: May 2023

Floorplan energy assessments present a highly efficient method for evaluating the energy efficiency of residential properties without requiring physical presence. By employing computer modeling, accurate determination of the building’s heat loss or gain can be achieved, enabling planners and homeowners to devise energy-efficient renovation or redevelopment plans. However, the creation of an AI model for floorplan element detection necessitates the manual annotation of a substantial collection of floorplans, which poses a daunting task. This paper introduces a novel active learning model designed to detect and annotate the primary elements within floorplan images, aiming to assist energy assessors in automating the analysis of such images—an inherently challenging problem due to the time-intensive nature of the annotation process. Our active learning approach initially trained on a set of 500 annotated images and progressively learned from a larger dataset comprising 4,500 unlabeled images. This iterative process resulted in an mean average precision score of 0.833, precision score of 0.972, and recall score of 0.950. The annotated dataset will be made publicly available under a Creative Commons license.
The Effect PSO/ABC, ABC/BFO, PSO/BFO and CS/BFO Hybrid Techniques on Power System Buses for Voltage Stability Margin Improvement
Authors: Ikeli ndubuisi , Ashigwuike Chinemezu
Published: May 2023

This paper presents and investigates new approaches inspired by nature to determine the optimal placement of UPFC for enhancing voltage stability margin of power system network. Voltage collapse phenomenon has remained an operational problem yet to be solved by power system engineers. To improve the voltage stability of the power system network, new optimisation techniques viz: PSO/ABC, ABC/BFO, PSO/BFO AND CS/BFO hybrids are investigated for their performance on power system buses for voltage stability improvement.
The performance of the proposed hybrid methods are examined on the practical Nigerian 56 - bus network for voltage stability improvement. The simulation results has shown that ABC/BFO technique is better than
BFO/PSO by 3.44% in improving voltage stability of margin of power system, PSO/ABC gives additional improvement of 4.07%, totalling 7.51% and lastly BFO/CS technique improved voltage stability margin of power system further by 5% totalling 12.51%. Also this research revealed that the smaller the gamma value the better the UPFC contribution to voltage stability enhancement. BFO/CS technique yielded the smallest gamma values of 0. 74532 and 0.830913 in both Nigerian practical network and IEEE – 14 bus network as shown in the analysis.
Policy frameworks to maximize sustainability benefits of bioenergy systems
Authors: Thornley Patricia , Roeder Mirjam
Published: May 2023

Background Bioenergy is a significant contributor to renewable power generation, renewable transport fuel and renewable heat. However, the deployed capacity significantly lags identified potential and has not seen the same rapid response to policy stimuli observed in the solar and wind sectors. This work analyses the historical trajectory of UK bioenergy development to discern potential underpinning reasons for that.Results It is noted that the technology landscape is arguably more complex than in other renewables, with multiple feedstocks, pre-treatment and conversion technologies involved in potentially hundreds of different pathways/combinations; not all of these pathways/combinations deliver greenhouse gas reductions, and most have other impacts (positive and negative) that go beyond energy and greenhouse gas balances to interact with atmospheric, aquatic, land, economic and social systems. We apply a risk management approach to show how disaggregation of the system can support more appropriate decision-making and provide greater resilience to the inherent variability associated with natural, land-based systems.Conclusions It is concluded that disaggregation of bioenergy systems into 3 sub-systems allows management of the most significant risks to be placed with the parties most able to deal with them and that a simple, semi-quantitative assessment of the performance of each sub-system facilitates an effective ranking of the “best” use of biomass in line with policy objectives; supporting effective decision making about priority feedstocks, technologies and demand sectors.
An adsorption isotherm identification method based on CNN-LSTM neural network
Authors: Liu Kaidi , Xie Xiaohan , Yan Juanting , Zhang Sizong , Zhang Hui
Published: May 2023

Context: Adsorption isotherm is integral to comprehending the adsorption mechanism and catalytic processes. Despite the well-established research on isotherm classification methods, existing techniques for isotherm identification are hampered by inefficiency, human interference, insufficient feature information extracting and the fact that specific types isotherm of identification can be achieved. To overcome these limitations, an end-to-end isotherm identification method based on a CNN-LSTM neural network is proposed, which employs a combination of Convolutional Neural Network (CNN) and Long Short-Term Memory network (LSTM) to extract the features of adsorption isotherm. Additionally, dataset is constructed for training and validating the neural network using various theoretical adsorption isotherm equations, thereby eliminating the need for time-consuming and expensive repetitive experiments. The results indicate that the model achieves identification accuracy of 100% on both the training and validation sets constructed using theoretical adsorption equations. The model's F1-score on the test set, which consists of five categories actual adsorption isotherms, is 88.85%, and there has been a 20% enhancement in the mean precision of isotherm identification compared to the traditional method. All these results demonstrate that the proposed method can accurately identify adsorption isotherm.
Method: Pycharm was used as the experimental and testing platform, python 3.9 was used as the programming language, Tensorflow 2.11.0 and Keras 2.10.0 were used to train and test the CNN-LSTM model, numpy 1.21.5 and scipy 1.81 were used to generate the train and validation dataset.