bluuebunny/crossref_metadata_2025 huggingface dataset:
A sterile, injectable, and robust sericin hydrogel prepared by degraded sericin
Authors: Zhang Yeshun , Wang Susu , Li Yurong , Zhang Jingya , Li Xiang , Du Zhanyan , Liu Siyu , Song Yushuo , Li Yanyan , Xi Meilin , Kang Guoping , Zhang Guozheng
Published: September 2023

Sericin hydrogels have been widely studied and applied in tissue engineering, drug delivery and clinical medicine due to their unique properties. However, their poor mechanical strength, fragility behavior and inconvenient sterilization are the key hurdles for applications. To address these challenges, a sericin hydrogel with excellent physical and chemical properties and cytocompatibility was prepared through crosslinking genipin with degraded sericin extracted from fibroin deficient silkworm cocoons by the high temperature and pressure method. Our reported sericin hydrogels possess good elasticity, injectability, and robust behaviors. The sericin hydrogel formed by sericin solution at concentration 8% (w/v) can be smoothly through 16 G needle. The 12% sericin hydrogel was unbroken until its compression ratio reached 70%, and accompanied with the compression strength of 674 kPa. The maximum stretch of 12% sericin hydrogel was 740%, and the breaking strength was 375 kPa in the tensile test. The tensile modulus of the 12% hydrogel is 477 kPa. Besides that, the hydrogel system has excellent cell-adhesive capability, effectively promoting cell attachment, proliferation. The swelling and degradation behaviors of the hydrogels are pH responsiveness. Sericin hydrogel releases drugs in a sustained manner. Furthermore, this study overcomes the problem that sericin hydrogels are difficult to be sterilized (sterilization will inevitably lead to the destruction of their structures). In addition, it breaks the previous idea that sericin extracted at high temperature and pressure is difficult to be directly cross-linked into a stable hydrogel. This hydrogel system developed in this study is promising to be a new multifunctional platform for extending the application area of sericin.
​Experimental investigations on characteristics of water-air two-phase flows during water fillings in undulation pipelines
Authors: Tang Xuelin , Liu Zongku , Zhang Ling , Li Xiaoqin
Published: September 2023

Visual and pressurized pipeline systems with single- and multi-undulation layouts were used to study experimentally and analyze theoretically the transient characteristics of water-air two-phase flow during water fillings in undulation pipelines based on the combination action analyses of both the communicating pipe and the gravity of the water-air two-phase flows in the descending pipe. For the single undulation pipeline, the complex two-phase flow-pattern evolutions including full pipe flow and stratified flow for low, medium, high water-filling velocity cases, respectively, lead to a great difference in transient pressure, flow-pattern and the water-filling duration. Especially for low and medium water-filling velocity cases, the hydraulic theories related to hydraulic drop and hydraulic jump were employed to investigate the entrapped air pocket evolutions in the descending pipe, and the mechanism of negative pressure at the top of the undulation pipes occurrence was analyzed. For the same multi undulating pipeline, due to the different elevations of the three undulating points along flow direction, namely three different types of pipeline layout, high-medium-low case (high elevation undulating point, medium one, and low one), low-medium-high and high-low-medium ones, their water-filling durations are significantly different, i.e. approximately 80.02 s, 227.34 s and 617.78 s. Meanwhile, there are significant differences in flow patterns in water filling, namely larger entrapped air pockets in three descending pipes for high-medium-low case, entrapped air pockets in the first two descending pipes and open channel stratified flow in the last one for low-medium-high case, some bubbles in three descending pipes for the high-low-medium case.
GENESIS CGDYN: large-scale coarse-grained MD simulation with dynamic load balancing for heterogeneous biomolecular systems
Authors: Sugita Yuji , Jung Jaewoon , Tan Cheng
Published: September 2023

Residue-level coarse-grained (CG) molecular dynamics (MD) simulation is widely used to investigate slow biological processes that involve multiple proteins, nucleic acids, and their complexes. Biomolecules in a large simulation system are distributed non-uniformly, limiting computational efficiency with conventional methods. Here, we develop a hierarchical domain decomposition scheme with dynamic load balancing for heterogeneous biomolecular systems to keep computational efficiency even after drastic changes in particle distribution. The new schemes are applied to intrinsically disordered protein (IDP) droplet fusions. The droplet shape changes correlate with mixing IDP chains from two droplets. We also simulate formations of large IDP droplets, whose sizes are almost equivalent to those observed in microscopy. The methods have been implemented in CGDYN of the GENESIS software, which provides a new tool for investigating mesoscopic biological phenomena using the residue-level CG models.
Coal Geochemistry and Potential Environmental Pollution: A Case Study of the Guaíba Coalfield in the Southern Paraná Basin, Brazil
Authors: Job Juliana Martellet , Menegat Rualdo , Vignol-Lelarge Maria Lídia , Dani Norberto
Published: September 2023

Geochemical studies of coal mining projects in Environmental Impact Studies (EIS) are often limited to economic characterization of the mineral resource, resulting in a gap in the understanding and assessment of the potential environmental impact caused by coal exploration. A set of analytical techniques were carried out with the general objective of measuring the potential impact of the possible exploitation of coal from the Guaíba Coalfield located in the southernmost region of Brazil. The results indicate coal deposition in a lacustrine environment with a significant continental contribution from a fan delta and a little marine influence. Most of the analyzed chemical elements present higher contents in the samples than the world average. When associated with organic matter and clay minerals, these elements become more readily available to the environment than sulfides. Among the analyzed elements, arsenic (As), zinc (Zn), and fluoride (F) are the most critical due to their enrichment levels (> 10 times for As and Zn) and potential impact on human health.
Multi-origins of pathological theta oscillation from neuron to network inferred by a hybrid data and model study with cubature Kalman filter
Authors: Wang Jixuan , Deng Bin , Wang Jiang , Lei Xiang , Liu Chen
Published: September 2023

The brain rhythm is strongly associated with the brain function. Alzheimer’s disease (AD) is majorly reflected by the brain rhythm switching from the alpha band (9–12 Hz) to the theta band (4–8 Hz), accompanying with the loss of brain function. However, extracting the implicating intrinsic characteristic variations of the brain network by utilizing the Electroencephalogram (EEG) information is extremely difficult. Kaman observer, as an effective Bayesian technique, can provide a visualization service for probing the intrinsic characteristics underlying the pathological theta oscillations. This work first establishes an excitation-inhibitory neural network model and explores the role of the proportion of the inhibitory neurons and inhibitory synapses in the pathological theta oscillation. The results indicate that the apoptosis of inhibitory neurons and accompanied loss of inhibitory synaptic weight are the main neural bases of the frequency decrease of neural oscillation. Then, we further explore the intrinsic spiking characteristic by considering spike frequency adaptation (SFA) to the inhibitory neurons. The results show that the SFA reduces the firing rate of neurons, which facilitates the theta rhythm. The enhancement of SFA current by increasing time constant of its gating variable can further decrease the theta frequency from 7 Hz to 4 Hz. Finally, for this high-dimensional nonlinear excitation-inhibitory neural network model, cubature Kalman filter (CKF) is employed to estimate the above potential variations from the noisy EEG information. The observation results show that both the proportion of inhibitory neurons and the inhibitory SFA current present descending trends as the degree of AD increases. Collectively, the generation of AD state is speculated to rely on multi-origin inhibitory intrinsic characteristics: a significant attenuation on the proportion of inhibitory neurons, synaptic weight and SFA current. The observation result by CKF from EEG verifies the simulation results from the model. We investigate the parameter effects from both the forward model simulation and the inverse estimation process of network parameters using EEG data. This work enhances the understanding of the role of inhibitory intrinsic characteristics on pathological theta oscillation and provides an effective method to decode the dynamics underlying the neural activities.
Three-Dimensional Covalent Organic Frameworks Constructed from Irregular Polyhedral Building Blocks
Authors: Fang Qianrong , Chang Jianhong , Zhang Zeyue , Zheng Haorui , Li Hui , Suo Jinquan , Ji Chunqing , Chen Fenqian , Valtchev Valentin , Qiu Shilun , Sun Junliang
Published: September 2023

Developing three-dimensional (3D) covalent organic frameworks (COFs) has paramount significance across numerous applications. However, the conventional design approach that relies on regular building blocks significantly restricts the structural diversity of COFs. In this study, we successfully designed and synthesized two 3D COFs, named JUC-643 and JUC-644, employing a novel strategy based on irregular 8-connected (8-c) building blocks. By using a continuous rotation electron diffraction technique combined with powder X-ray diffraction patterns, their structures were solved and revealed a unique linkage with double helical structure, a phenomenon previously unreported in COFs. In order to precisely describe the topology, these structures should be deconstructed into the unprecedented [4+3(+2)]-c nets instead of the traditional [8(+2)]-c or [6(+2)]-c net. Furthermore, one of the materials (JUC-644) has demonstrated exceptional adsorption capability towards C3H8 and n-C4H10 (11.28 and 10.45 mmol g-1 at 298 K and 1 bar respectively), surpassing the adsorption performance of all known porous materials, and breakthrough experiments have also highlighted the remarkable C3H8/C2H6 and n-C4H10/C2H6 selectivity. This pioneering concept of incorporating irregular building blocks in 3D COFs introduces a promising avenue for designing intricate architectures while enhancing their potential application in the recovery of C2H6 from natural gas liquids.
Influence of the Magnetic Flux on the Dynamics of a self-sustained System: Analytical, numerical and analogical investigations
Authors: DANG-RA C. , chamgoue A. cheage , WOUAPI M.K. , FILATRELLA G. , YAMAPI R.
Published: September 2023

This paper investigates the nonlinear dynamics of a ferroelectric enzyme-substrate
reaction modeled by a bi-rhythmic Van der Pol oscillator coupled to a magnetic
flux. We derive the equilibrium points and study their stability,
analyze some bifurcation structures and the variation of the corresponding
Lyapunov exponents. The phenomena of symmetric attractors and the
anti-monotonicity are observed. An increasing the magnetic ﬂux stabilizes the equilibrium points,
tends to control chaotic regimes, and aﬀect regular and quasi-regular ones.
As the magnetic ﬂux increases, the amplitude of oscillations around the equilibrium
point decreases and the limit cycles at the hopf bifurcation tend to disappear. Further increases
the magnetic flux giving rise to chaotic dynamics.
The electrical circuit and analogical simulations are performed using PSpice software.
Analogical and numerical results agree.
A Quality Approach to Smart Sustainable Universities in Digital Natives Era : The Case of King Abdul Aziz University
Authors: Farooq Muhammad , Bakhsh Allah , Watto Waqas Ahmad
Published: September 2023

The authors have requested that this preprint be removed from Research Square.
Biographical Data : A Bibliometrics Study and Visualization Analysis via CiteSpace
Authors: Xu Xiaoqing , Song Guandong
Published: September 2023

Biographical data, a measure of individual tendency to future behavior based on their past life experiences, was often used in the fields of human resources and psychology, and had been expanding to other fields in recent years. A large number of literature on biographical data had been published internationally in the past decades. 464 literature was retrieved from the database of Web of Science core from 1951 to 2022 as the main, quantitatively visualized and analyzed the characteristics of literature, research hotspots, research process in this research field, pointed out the current problems to be solved with the help of CiteSpace. The study found that: Fluctuating upward trend in annual publication of biographical data literature, the authors, the regional scale of cooperation network had been initially formed, the overall view of Europe and the United States to pay more attention to the exploration of biographical data. The study of biographical data dimensions had always been a research hotspot. At present, biographical data still had problems such as information falsification, personal privacy leakage, quantification difficulties. Countries should strengthen academic cooperation to improve the current problems and promote the innovative development of biographical data in the future.
Automated Diagnosis of Schizophrenia based on EEG and Spatial–temporal Residual Graph Convolutional Network
Authors: Xu Xinyi , Zhu Geng , Li Bin , Lin Ping , Li Xiaoou , Wang Zhen
Published: September 2023

Schizophrenia (SZ), a psychiatric disorder for which there is no precise diagnosis, has had a serious impact on the quality of human life and social activities for many years. Therefore, an advanced approach for accurate treatment is required. In this study, we provide a classification approach for SZ patients based on a spatial-temporal residual graph convolutional neural network (STRGCN). The model primarily collects spatial frequency features and temporal frequency features by spatial graph convolution and single channel temporal convolution respectively and blends them both for the classification learning, in contrast to traditional approaches that only evaluate temporal frequency information in EEG and disregard spatial features across brain regions. The spatial frequency features are then obtained by single channel temporal convolution, and the processed matrix is flattened after multiple convolutions and input to the classification model. We conducted extensive experiments on the publicly available dataset Zenodo and our own collected dataset. The classification accuracy of the two datasets on our proposed method reached 96.32% and 85.44%, respectively. In the experiment, the dataset using delta has the best performance in the classification results in the sub-bands.
Hypotension Prediction Index for Prevention of Intraoperative Hypotension in Patients Undergoing General Anesthesia: A Randomized Controlled Trial
Authors: Lai Chih-Jun , Cheng Ya-Jung , Han Yin-Yi , Hsiao Po-Ni , Lin Pei-Lin , Chiu Ching-Tang , Lee Jang-Ming , Tien Yu-Wen , Chien Kuo-Liong
Published: September 2023

Background
Intraoperative hypotension is a common side effect of general anaesthesia. Here we examined whether the Hypotension Prediction Index, a novel warning system, reduce the severity and duration of intraoperative hypotension during general anaesthesia surgery.
Methods
This randomized controlled trial was conducted at the anesthesiology department of a tertiary referral hospital in Taipei, Taiwan. Sixty eligible patients were randomized 1:1 to hemodynamic management with Hypotension Prediction Index guidance (intervention group) or standard of care (control group). Intraoperative hypotension treatment was initiated at a Hypotension Prediction Index > 85 in the intervention and a mean arterial pressure < 65 mmHg in the control group. Primary outcome was the severity of hypotension, defined as a time-weighted average mean arterial pressure < 65mmHg. Secondary outcomes were postoperative complications and mortality within 30 postoperative days.
Results
The intervention group exhibited a significantly lower median time-weighted average mean arterial pressure < 65mmHg (0.02 [Q1, Q3: 0.003, 0.08] vs. 0.37 [0.20, 0.58], P < 0.001) and fewer postoperative gastrointestinal symptoms (6 vs. 14, P = 0.028). The median duration from alarm to first intraoperative hypotension treatment in the intervention group (42.78 [20.4, 79.0] s) was significantly shorter than that silent alarm to first treatment in the control group (200.16 [99.7, 261.8] s) group (P < 0.001).
Conclusions
Hypotension Prediction Index guidance appears to be effective in preventing intraoperative hypotension and reducing postoperative gastrointestinal symptoms.
Trial registration
ClinicalTrials.gov (NCT04966364); 202105065RINA; Date of registration: July 19, 2021; The recruitment date of the first patient: July 22, 2021
Nur77 Inhibit β-catenin Expression to Mediate Hepatoblastoma Progression and Therapeutic Effect of Cisplatin
Authors: Zhou Jianfeng , Liu Xingyu , Yin Hanjun , Zhou Yong , Xu Zhongya , Zhou Kai , Li Tao , Fang Yongjun , Shen Qiyang
Published: September 2023

Hepatoblastoma (HB) is the most common malignant tumor in children under 5 years old, but its pathogenesis remains unclear. Nur77 has been reported to be an important regulator for cancer progression in various cancer types. This study found that Nur77 was downregulated in HB tumors, compared with paracancer tissue. Knockout or overexpression of Nur77 in HB tumor cell line HepG2 and HuH6 could significantly enhance or inhibit the proliferation, migration and invasion of tumor cells both in vitro and in vivo. Further studies illustrated that Nur77 regulated the proliferation of tumor cells by affecting the expression of β-catenin. Nur77 agonist Cns-A effectively enhanced the therapeutic effect of cisplatin on HB tumors both in vitro and in vivo. This study proved that Nur77 could act as a tumor suppressor gene in HB tumors, providing a new direction for improving the clinical responses of HB.
Extruding transcription elongation loops observed in high-resolution single-cell 3D genomes
Authors: Xie Xiaoliang , Wu Honggui , Zhang Jiankun , Tan Longzhi
Published: September 2023

Inside human nuclei, genes are transcribed within a highly packed genome, whose organization is facilitated by cohesin-mediated loop extrusion. However, how cohesin folds transcribed genes and affects transcription remain unclear. Here we report that highly expressed long genes form a “stripe-like” structure termed transcription elongation loop (TEL), which aligns between the transcription start site (TSS) and the transcription termination site (TTS). We proved that TELs formation results from the joint interactions between cohesin-mediated loop extrusion, RNA polymerase II (RNAPII) and topoisomerases. By improving the spatial resolution of single-cell 3D genome mapping to 5 kb with micrococcal nuclease (MNase) in our new single-cell Micro-C (scMicro-C) method, we directly observed the loop expansion of TELs. Furthermore, we demonstrated that TEL-associated genes have higher transcriptional burst frequency and cohesin modulates transcriptional bursting by facilitating the release of RNAPII pausing. Thus, our results demonstrated the fundamental role of cohesin in transcription regulation.
Development and validation of artificial intelligence-based analysis software to support screening system of cervical intraepithelial neoplasia
Authors: Ouh Yung-Taek , Kim Tae Jin , Ju Woong , Kim Sang Wun , Jeon Seob , Kim Soo-Nyung , Kim Kwang Gi , Lee Jae-Kwan
Published: September 2023

Cervical cancer, the fourth most common cancer among women worldwide, often proves fatal and stems from precursor lesions caused by high-risk human papillomavirus (HR-HPV) infection. Accurate and early diagnosis is crucial for effective treatment. Current screening methods, such as the Pap test, liquid-based cytology (LBC), visual inspection with acetic acid (VIA), and HPV DNA testing, have limitations, requiring confirmation through colposcopy. This study introduces CerviCARE® AI, an artificial intelligence (AI) analysis software, to address colposcopy challenges. It automatically analyzes Tele-cervicography images, distinguishing between low-grade and high-grade lesions. In a multicenter retrospective study, CerviCARE® AI achieved a remarkable sensitivity of 98% for high-risk groups (P2, P3, HSIL or higher, CIN2 or higher) and a specificity of 95.5%. These findings underscore CerviCARE® AI's potential as a valuable diagnostic tool for highly accurate identification of cervical precancerous lesions. Its integration into clinical practice could enhance early detection and reduce screening disparities, especially in regions with limited access to skilled colposcopists. While further prospective research is needed to validate its clinical utility, this AI system holds promise for improving cervical cancer screening and lessening the burden of this deadly disease.
Effect of substitutional metallic impurities on the optical absorption properties of TiO2
Authors: Cisternas Eduardo , Aguilera–del–Toro R.H. , Aguilera-Granja F. , Vogel E.
Published: September 2023

(TiO2) is both a natural and artificial compound which is transparent to visible and nearinfrared light. However, it could be prepared with other metals substituting for Ti thus changing its properties. In this article we present density-functional calculations for Ti(1− x )AxO2, where A stands for any of the 8 following substitutional impurities Fe, Ni, Co, Pd, Pt, Cu, Ag and Au, based on the rutile structure of pristine TiO2. We use a fully unconstrained version of the densityfunctional method with the generalized gradient approximation plus the U exchange and correlation as implemented in the QuantumEspresso free distribution. Within the limitations of a finite size cell approximation we report the band structure, energy gaps and absorption spectra for all these cases. Rather than stressing precise values we point to report two general features: location of the impurity levels and general trends of the optical properties through the eight different systems. Our results show that all these substitutional atoms lead to the presence of electronic levels within the pristine gap, and that all of them produce absorptions in the visible and near-infrared ranges of the electromagnetic radiation. Such results make these systems of interest for the fabrications of solar cells. Among the variety of results, Ni and Ag are apparently the most promising substitutional impurities to achieve the better performance to capture the solar radiation at the planet’s surface.
Effect of an Educational Program about Mentorship Competencies on Nurse Mentors' Performance at Port Said Healthcare Authority Hospitals: An intervention study design (pre-test and post-test one group)
Authors: Hagrass Heba Moussa , Ibrahim Sanaa Abd El-Azim , Anany Rasha Ibrahim , El-Gazar Heba Emad
Published: September 2023

Background: Mentorship is a vital part of the nursing profession to improve role transition, job satisfaction, and job retention while facilitating socialization, emotional well-being, and the acquisition of new skills.
Aim: The present study aimed to evaluate the effect of an educational program about mentorship competencies on nurse mentors' performance at Port Said Healthcare Authority hospitals.
Methods: An intervention study design (pre-test and post-test one group) was used to conduct the study at seven Healthcare Authority hospitals in Port Said Governorate, Egypt. The study subjects were consisted of a purposive sample of 30 nurse mentors and 60 intern nursing students. Data were collected using three tools consisted of the Mentor Knowledge Questionnaire, Mentor Competencies Instrument (MCI), and Nurse Mentor Performance Assessment.
Results: the post-test scores of mentorship competencies and performance after implementation of the educational program significantly improved in the studied nurse mentors 56.1 ±13.2, 60.5 ±4.9 compared with pre-test scores with 37.1 ±4.1, 49.7 ±6.9 (P<0.001). As determined by Cohen’s d test, the effect size of an educational program is quite large on the nurse mentors’ performance.
Conclusion: The educational program about mentorship competencies was significantly improve mentorship performance of the studied nurse mentors.
Trial Registration Number (TRN)
The study protocol was approved by the Research Ethics Committee of the Faculty of Nursing, Port Said University (code number: NUR 13/2/2022) (10).
Optimal placement of distributed diesel generators for enhancing the performance of the Iraq distribution network
Authors: Khalaf Saad , Cipcigan Liana , Muhssin Mazin T.
Published: September 2023

The optimal integration of distributed generators such as diesel generators into the Iraq power systems is significant in providing flexibility in localized areas and may support to reduce the number of blackouts. The optimal location and sizing of the diesel generators is a suitable way for improving the operation of distribution networks and increase the generation supply. This paper presents a methodology to obtain the suitable size of diesel generators at the suitable bus locations in the power distribution network of Ziyounah district in the Baghdad area. An optimization tool based GA with an objective of improving the network performance, and reducing the real power losses, stabilizing the grid voltage has been presented. This optimization technique also contributes to reducing acoustic noise level from existing generators that are integrated at the neighbourhood area. Results showed that the selection of capacities and locations of generators based on the highest value of Network Performance Index (NPI) helps to overall system improvement such as voltage profile improvement, and real loss reduction. The result also showed that the obtaining of the suitable locations for connection the diesel generators with the help of NPI leads to savings in electricity due to reduction in the real power loss of the distribution network.
Lifestyle and fruit consumption: an investigation of university students in Uganda
Authors: Kiggwe Musa , Ntayi Joseph , Nabatanzi-Muyimba Annet K. , Byarugaba Jotham , Timothy Esemu , Munene John C.
Published: September 2023

Purpose
Healthy food consumption involves regular fruit intake. Inadequate fruit consumption is associated with disease burdens such as cancer, hypertension, stroke, and diabetes. As such, an individual may choose to avoid health repercussions by adjusting his/her lifestyle. Individuals with long-term healthy lifestyle habits are likely high fruit consumers. However, few studies seem to have focused on the relationship certain aggregated lifestyle factors i.e. screen time; physical exercise; work, and sleep have with fruit consumption. Thus, the study sought to investigate the relationship between these aggregated lifestyle factors and fruit consumption of university students in Uganda.
Methods
The study used a correlational survey that was quantitative in nature. The study population covered 59,998 university students. We sampled 403 students using proportionate stratified random sampling. We collected data through face-to-face interviews using a questionnaire. We analyzed the data using SPSS (V23) and AMOS (V23) software for correlational and Confirmatory factor tests.
Results
The results revealed that a university student’s lifestyle significantly influenced his/her fruit consumption (β = 5.470, t-value = 5.481, p-value = 0.000). The squared Multiple Correlation is 0.176.
Conclusion
Considering the health benefits of fruit consumption and basing on the study results, health educators need to encourage the fruit consumption through adjusting one’s lifestyle (exercises, screen time, work life and sleep time).
Salinity-driven adaptations in freshwater-to-marine microorganisms: Genetic and transcriptional modulation of amino acid encoding
Authors: Astudillo-Garcia Carmen , Tee Hwee Sze , West Annie G. , Hoggard Michael , Lear Gavin , Handley Kim Marie
Published: September 2023

Background. Salinity is among the strongest environmental drivers of microbial community composition, requiring substantial genetic adaptations. Halophilic archaea and some Halanaerobiales bacteria adopt the ‘salt-in’ osmoadaptive strategy supported by proteomes enriched in acidic amino acids. The ‘salt-out’ strategy, employed by most halophilic and halotolerant bacteria, does not require modification of the intracellular proteome, although a slight excess of acidic amino acid residues is found among some marine bacteria. While adaptations to salt have largely been studied in halophilic systems, knowledge across lower salinity gradients is scarce.
Results. We determined microbial adaptations, associated with the 'salt-out' osmoadaptive strategy, across a freshwater-to-marine transect in compositionally distinct water and sediment communities. Changes in amino acid encoding were thus determined according to the predicted cellular location of proteins (cytoplasmic or secreted) using 276 unique prokaryotic metagenome-assembled genomes. The proportion of encoded acidic amino acids (glutamate and aspartate) increased linearly with salinity, and decreased for the basic amino acid, lysine. Trends were strongest in the fraction encoding secreted/periplasmic proteins, and weakest in the cytoplasmic (ribosomal) fraction, indicating differential adaptation of protein-encoding between these cellular locations in water and sediment communities. These salinity-associated differences were evident across diverse phyla, despite lineage-specific codon biases (e.g., typically higher ratios for aspartate among Actinomycetes), and differentiated freshwater or brackish/marine members of lineages found across the estuarine transect, notably those in the Microbacteriaceae Luna cluster. Freshwater-dominant (Rhodoluna) and brackish-dominant (Aquiluna) members of the Luna cluster exhibited distinct genomic and transcriptional charged amino acid encoding, whereby only Aquiluna, modulated transcription in response to progressively higher salinities to increase encoded proteome acidity.
Conclusions. Microorganisms colonising salinity gradients are therefore able to transcriptionally adjust charged amino acid encoding in response to changes in salinity. Moreover, results illustrate that the salt-out strategy, characterised by the increased acidity of secreted proteins exposed to external conditions, is a common adaptation at low brackish-to-marine salinities, contributing to intra-lineage niche differentiation.
Optimizing Gene Selection and Cancer Classification with Hybrid Sine Cosine and Cuckoo Search Algorithm
Authors: Yaqoob Abrar , Verma Navneet Kumar , Aziz Rabia Musheer
Published: September 2023

Gene expression datasets contain extensive data for exploring various biological processes, yet the presence of redundant and irrelevant genes poses a challenge in identifying crucial ones within high-dimensional biological data. To address this, diverse feature selection (FS) methods have been introduced. Enhancing the efficiency and accuracy of FS techniques is vital for selecting significant genes within intricate multidimensional biological information. In this context, we propose an innovative strategy named the Sine Cosine and Cuckoo Search Algorithm (SCACSA) applicable to popular machine learning classifiers like K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Naive Bayes (NB). The efficacy of the hybrid gene selection algorithm is assessed using breast cancer dataset and benchmarked against alternative feature selection techniques. Empirical results demonstrate SCACSA superiority in accuracy metrics such as precision, sensitivity, and specificity. Furthermore, the SCACSA approach showcases computational efficiency and consistency, setting it apart from other methods in terms of variability. Given the significance of gene selection in complex biological datasets, SCACSA emerges as a valuable tool for cancer dataset classification, aiding medical professionals in informed decision-making for cancer diagnosis. aiding medical professionals in informed
The association between high-energy diets, sugar-sweetened beverages on the risk of depression in rural-urban adolescent students
Authors: Gu Linni , Wang Xiaoying , Tian Donghua
Published: September 2023

Background: Depression is one of the most commonly psychological illness in the world. It severely influenced individual’s mood and daily life. In recent year, it has an increased trend in adolescent student in China. It not only influenced adolescent student academic performance, but also transmitted to other students by social network, which was rose as a severe public health issue. Present studies discussed the influence factors that resulted in the depression. This study mainly discussed the association between high-energy diet, sugar-sweetened beverage and the risk of depression in rural-urban adolescent student.
Methods: This study used the China Education Panel Study (CEPS) data to analyze the association between high-energy diets, sugar-sweetened beverages and the risk of depression in adolescent student. A cross-sectional data from the year 2014-2015 was analyzed. In total, 7,944 subjects were participated in this study. Statistical analysis including descriptive analysis, analysis of variance test (ANOVA), ordinary least squares (OLS) and stepwise regression were employed to analyze the association.
Results: The results of stepwise regression presented that high-energy diets, sugar-sweetened beverages had a strong association with the depression of adolescent student. The risk of depression increased with the increase of frequency of high-energy diet, sugar-sweetened beverage intake. If adolescent student increased one-unit high-energy diet and sugar-sweetened beverages intake, the risk of depression would increase about 12.1%.
Conclusion: Depression is a major public health problem in adolescent student in China. With the rate increased in China, school and government should attach great attention on the psychological health. Lifestyle behaviors were important factors that influenced the risk of depression. Based on the results, this study suggested that psychological health of adolescent student must be noticed and detailed measures on control the risk must be formulated in China.
Identifying hot spots of cardiometabolic risk factors in a Swiss city: impact of individual and environmental factors
Authors: Ladoy Anaïs , Marques-Vidal Pedro , Guessous Idris , Joost Stéphane
Published: September 2023

Background: Cardiovascular disease (CVD) remains a major public health concern, and developing effective interventions at the population level requires a thorough understanding of the spatial distribution and contextual determinants of cardiometabolic risk factors (CMRFs). However, knowledge on these issues at small spatial scales is still limited, especially in Europe. The aim of this study was to explore the spatial patterns of CMRFs and to identify key individual and contextual factors associated with these risk factors in the city of Lausanne, Switzerland.Methods: Using individual-level data from a population-based cohort of middle-aged and older adults (CoLaus), we examined hypertension, obesity, diabetes, and dyslipidemia as key CMRFs. Intensity functions were used to identify areas of elevated risk for each outcome. Geographically weighted regressions were then employed to examine local associations between outcomes adjusted for individual confounders, and characteristics of physical and social environments such as air pollution, noise, greenness, street connectivity, socioeconomic position, and ethnic composition.Results: We analyzed data from 3,695 participants (mean age of 64.1 years, 56.8% females). The prevalence of hypertension was 48.2%, obesity 17.7%, diabetes 10.7% and dyslipidemia 33.2%. Among the individual factors associated with CMRFs, older age, male sex, lower education level, and being foreign-born emerged as common contributors. Persistent spatial clusters for hypertension, obesity, and diabetes were identified across the city, as well as areas with concurrent increased risk for multiple CMRFs. After adjustment for individual confounders, a global association between neighborhood income and hypertension, obesity, and diabetes emerged. Obesity showed the strongest contextual influence, with significant local associations identified between obesity and higher unemployment rates, lower income, education, and greenness. Notably, hypertension showed local associations with lower neighborhood income and PM2.5 concentrations, while diabetes was associated with lower income and higher unemployment. Dyslipidemia did not show significant associations with contextual factors.Conclusions: Using individual-level data, the study combined spatial approaches to delineate high-risk areas for CMRFs within an urban area and to reveal significant associations with characteristics of physical and social environments. This methodological framework can be applied elsewhere, providing public health practitioners with essential insights to prioritize and tailor local population-level initiatives for CVD prevention.
Digital Twin For A Human Heart Using Deep Learning and Stream Processing Platforms
Authors: JEMAA Mohamed Hedi , JEMILI Farah , AMRI Charfeddine , MSOLLI Mohamed Amine , KORBAA Ouajdi
Published: September 2023

Cardiovascular diseases (CVDs) constitute a substantial global health challenge, with heart diseases ranking among the leading causes of mortality worldwide. This paper addresses this urgent concern by proposing innovative approaches. The fusion of Digital Twin technology with artificial intelligence offers a unique framework for personalized diagnosis, therapy selection, remote monitoring, and real-time treatment adjustments. By combining virtual patient replicas with medical history, real-time data, and machine learning algorithms, the potential for early detection and prevention of heart diseases becomes a reality. This paper presents a comprehensive exploration of leveraging Digital Twin technology for precise and real-time heart disease prediction, focusing on data management, security, and preprocessing. The research aims to lay a robust foundation for the development of a medical decision support system capable of precise predictions and interventions within the realm of heart disease. By combining virtual patient replicas with medical history, real-time data, and advanced machine learning algorithms, our paper explores the potential for early detection and prevention of heart diseases, centering on the development and detailed analysis of an ECG model. This ECG model leverages Digital Twin technology to enable precise and real-time heart disease prediction.
Analysis of Hadeja-Nguru Wetlands Vegetation and Surface water response to rainfall variability Analysis of Hadeja-Nguru Wetlands Vegetation and Surface water response to rainfall variability
Authors: Jajere Abubakar Ahmed , Nabegu Aliyu Baba , Bibi Umar Muhammed , Kibon Ado Usman , Ismail Muhammed
Published: September 2023

The Hadejia Nguru wetlands are the economic mainstay of the population residing in the basin area. The wetlands, provides means of livelihood to a significant proportion of the human population through; crop production, fisheries, hunting, grazing and water resources. This study assessed the wetlands surface water and vegetation, response climate variability. The study used dekadal eMODIS NIDVI 250 m resolution data from 2003–2018 of the study area. NDVI values were used to classify vegetation according to its vigour (Moderate, high and very high vegetation and surface water) and rainfall records from in situ meteorological data of areas at the upper and downstream parts of the basin. Correlation statistical tool was used in analyzing relationship between rainfall and temperature variability and wetlands components. The findings of the wetlands components yearly temporal variability trend revealed significant variability of 23.3% and 57.2% in surface water and high vegetation, respectively. The relationship between wetlands vegetation and surface water index and upstream rainfall variability is statistically significant at 95% level of significance. The positive relationship between annual rainfall of upstream stations put together and wetlands high vegetation is significant at 99% confidence level. upstream rainfall variability account for 47% variability in wetland high vegetation while the annual rainfall of Jos account for 29% and 27% variability in wetlands high vegetation and surface water respectively. The overall results of analysis revealed that occurrence and persistence of the basin wetlands are function of upstream rainfall pattern.
VIRD: An ensemble transfer learning to improve automatic stratification of types of lumbar intervertebral disc degeneration
Authors: Nakamoto Ichiro , Chen Hua , Wang Rui , Guo Yan , Chen Wei , Feng Jie , Chen Chunmei , Wu Jianfeng
Published: September 2023

The degeneration of the intervertebral discs in the lumbar spine is the common cause of neurological and physical dysfunctions and chronic disability of patients, which can be stratified into single- (e.g., disc herniation, disc prolapse, or disc bulge) and comorbidity-type degeneration (i.e., simultaneous presence of two or more conditions of disc herniation, prolapse, and bulge in a patient) respectively. The degenerative changes of the lumbar spine differentiate in the level of severity and type. A sample of lumbar magnetic resonance images from multiple clinical hospitals in China was collected and used in the proposal assessment. Theoretically, we devised a novel transfer learning framework VIRD by ensembling four pre-trained models including Densenet169, ResNet101, InceptionResNetV2, and VGG16. Thereafter, the proposed approach was applied to the clinical data and achieved 99% accuracy versus 94%, 96%, 96%, 96%, and 98% for compositional benchmark models of VGG16, InceptionResNetV2, DenseNet169, ResNet101, and other ensemble deep learning respectively. Furthermore, improved performance was observed as well for the metric of the area under the curve, producing a 1% increase relative to other ensemble learning, a 2% increase relative to most-studied models, and a 3% increase relative to the baseline models. The novel methodology can be used as a guide in the initial and efficient screening of complex degeneration of lumbar intervertebral discs and assist in the early-stage selection of clinically differentiated treatment options.
Predictors of Partnership and Sexual Satisfaction and dyadic effects in couples affected by endometriosis and infertility
Authors: Eickels Deborah van , Schick Maren , Germeyer Ariane , Rösner Sabine , Strowitzki Thomas , Wischmann Tewes , Ditzen Beate
Published: September 2023

Purpose
Endometriosis and infertility are associated with impaired partnership and sexuality of the patients, but also of their male partners. The aim of this study was to determine the association of different predictors of partnership and sexual satisfaction in couples with endometriosis and infertility, as well as dyadic effects.
Methods
A cross-sectional study was conducted with n = 62 women with endometriosis and n = 46 partners, including a total of n = 44 couples, some of whom were affected by infertility. The questionnaire included items on partnership, sexuality, depression, social support, and childbearing. Multiple linear regression and the actor-partner-interdependence-model were used for analysis.
Results
Depression correlated with lower partnership and sexuality satisfaction and showed in the dyad a significant negative actor effect in men for partnership satisfaction and a negative actor and partner effect in women for sexuality satisfaction (p < .05). For women, social support showed a significant positive actor effect for partnership satisfaction (p < .05), age showed a significant actor and partner effect for sexuality satisfaction (p < .05).
Conclusion
The results show a significant association of endometriosis and infertility with partnership and sexuality satisfaction in both partners and support the importance of including male partners' perspectives in the treatment of endometriosis.
TRIAL REGISTRATION
German Clinical Trials Register DRKS00014362 on the 29.03.2018.
Investigation of the appropriate viscosity of fibrinogen in repairing pleural defects using ventilation and anchoring in an ex vivo pig model
Authors: Fukuda Akihiro , Hashimoto Masaki , Takegawa Yoshitaka , Kondo Nobuyuki , Hasegawa Seiki
Published: September 2023

Objective
Our previous study revealed that the viscosity of fibrinogen could influence the effectiveness of ventilation and anchoring (V/A) methods for controlling air leakages. Here, we examined the association between the viscosity of fibrinogen and effectiveness using an ex vivo pig model.
Methods
The fibrin glue used in this study was BOLHEAL® (KM Biologics Co., Ltd., Kumamoto, Japan). We prepared three types of fibrinogen with different viscosities (higher and lower than normal), including one without additives. Using an ex vivo pig model, a pleural defect was made, and the defect was repaired using three different viscosities of fibrinogen through the V/A method. We measured the rupture pressure at the repair site (N=10) and histologically evaluated the depth of fibrin infiltration into the lung parenchyma at the repair sites.
Results
The median rupture pressure was 51.5 (40–73) cmH2O in Group 1 (lower viscosity), 47.0 (47–88) cmH2O in Group 2 (no change in viscosity), and 35.5 (25¬–61) cmH2O in Group 3 (higher viscosity). There was no statistically significant difference between Groups 1 and 2 (p = 0.819), but the rupture pressure was significantly higher in Group 2 than in Group 3 (p = 0.0136).
Histological evaluation revealed deep infiltration of fibrin into the lung parenchyma in Groups 1 and 2, but no such infiltration was observed in the higher-viscosity group.
Conclusions
The results of this experiment suggested that the V/A method using fibrin glue containing low-viscosity fibrinogen was more effective in controlling air leakage due to pleural defects.
An Investigation of COVID-19 Infection in Patients with Polymyalgia Rheumatica
Authors: Ma Xinlei , Xiao Lanlan , Wu Jinzhi , Lin Jin , Chen Weiqian
Published: September 2023

Objective.
We aimed to investigate the risk and prognosis associated with the coronavirus disease 2019 (COVID-19)infection among patients diagnosed with polymyalgia rheumatica (PMR).
Methods.
In the retrospective study, we included a cohort of PMR patients and followed them over time. The diagnosis of COVID-19 was made based on the clinical manifestations and laboratory tests. We collected the demography information, data on PMR disease activity and treatment, as well as clinical data related to COVID-19.
Results.
In our study, a total of 101 patients diagnosed with PMR were enrolled. Among them, 81 patients (80.2%) were categorized as having a COVID-19 infection, while the remaining 20 patients (19.8%) did not have COVID-19. Among PMR patients with COVID-19, 65 patients (64.4%) were confirmed to have the presence of COVID-19 antigen, while 16 patients (15.8%) tested positive for COVID-19 RNA. Most COVID-19 cases in PMR patients were classified as mild (88.9%). We utilized multivariate logistic regression analysis to identify independent risk factors for COVID-19 infection among PMR patients. The analysis revealed that the baseline of disease activity of PMR was identified as an independent risk factor for COVID-19 infection.
Conclusion.
Our findings suggest that PMR patients may have a lower infection rate and less severe cases of COVID-19 compared to the general population. The baseline disease activity of PMR might contribute to the increased susceptibility to COVID-19.