bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of knowledge, attitude, and practice regarding HIV post-exposure prophylaxis after occupational exposure among doctors working at Royal Care International Hospital (2021)
Authors: Khalid Rawan , Mohamed Raheeg , Abdelrahman Elmuiz , Mohammed Hassan , Makki Ahmed , Abdeldaim Abdulrahman , Idrees Malaz , Magzoub Yumna , Gaafar Nada , AbdAlla Eltayeb
Published: June 2024

Background: Despite the high rates of needle stick injuries, post-exposure prophylaxis usage is mainly unreported. Healthcare workers are at high risk of contracting HIV due to occupational exposure to blood and bodily fluids. The purpose of this study is to evaluate physicians working at Royal Care International Hospital regarding their knowledge, attitudes, and practices regarding HIV post-exposure prophylaxis (PEP).Methods: From Janury to march 2021, 204 doctors participated in a facility-based cross-sectional study at Royal Care International Hospital. The study used a structured self-administered questionnaire that included questions about demographic information, knowledge, attitudes, and practices regarding HIV PEP.Results: While 74% of participants knew that HIV PEP existed, the majority of participants (79.4%) knew very little about it. Only 69.6% of participants knew when it is best to begin HIV PEP after exposure, and the majority of participants were unable to name the conditions under which it is recommended. All of the participants thought HIV PEP was important, and 82.4% of them thought it was generally a good thing. Of the participants, 63 (30.9%) reported having been exposed to HIV-risky situations at work; however, only 42 (66.6%) of them disclosed this information, and only 27 (42.8%) of them received HIV PEP.Conclusion: While a considerable proportion of the participants had experienced an HIV-risky condition, the study found that there was a low reporting rate and low use of HIV PEP among them. Additionally, the majority of the participants had a positive attitude towards HIV PEP.
Characterization and proteomic analysis of plasma-derived small extracellular vesicles in locally advanced rectal cancer patients
Authors: Chen Haiyan , Fang Yimin , Dai Siqi , Jiang Kai , Shen Li , Zhao Jian , Huang Kanghua , Zhou Xiaofeng , Ding Kefeng
Published: June 2024

Background
Neoadjuvant chemoradiotherapy (nCRT) stands as a pivotal therapeutic approach for locally advanced rectal cancer (LARC), yet the absence of a reliable biomarker to forecast its efficacy remains a challenge. Thus, this study aimed to assess whether the proteomic compositions of small extracellular vesicles (sEVs) might offer predictive insights into nCRT response among patients with LARC, while also delving into the proteomic alterations within sEVs post nCRT.
Methods
Plasma samples were obtained from LARC patients both pre- and post-nCRT. Plasma-derived sEVs were isolated utilizing the TIO2-based method, followed by LC-MS/MS-based proteomic analysis. Subsequently, pathway enrichment analysis were performed to the Differentially Expressed Proteins (DEPs). Additionally, ROC curves were generated to evaluate the predictive potential of sEV proteins in determining nCRT response. Public databases were interrogated to identify sEV protein-associated genes that are correlated with the response to nCRT in LARC.
Results
A total of 16 patients were enrolled. Among them, 8 patients achieved a pathological complete response (good responders, GR), while the remaining 8 did not achieve a complete response (poor responders, PR). Our analysis of pretreatment plasma-derived sEVs revealed 67 significantly up-regulated DEPs and 9 significantly down-regulated DEPs. Notably, PROC (AUC: 0.922), F7 (AUC: 0.953) and AZU1 (AUC: 0.906) demonstrated high AUC values and significant differences (P value < 0.05) in discriminating between GR and PR patients. Furthermore, a signature consisting of 5 sEV protein-associated genes (S100A6, ENO1, MIF, PRDX6 and MYL6) was capable of predicting the response to nCRT, yielding an AUC of 0.621(95% CI: 0.454–0.788). Besides, this 5-sEV protein-associated gene signature enabled stratification of patients into low- and high-risk group, with the low-risk group demonstrating a longer overall survival in the testing set (P = 0.048). Moreover, our investigation identified 11 significantly up-regulated DEPs and 31 significantly down-regulated DEPs when comparing pre- and post-nCRT proteomic profiles. GO analysis unveiled enrichment in the regulation of phospholipase A2 activity.
Conclusions
Differential expression of sEV proteins distinguishes between GR and PR patients and holds promise as predictive markers for nCRT response and prognosis in patients with LARC. Furthermore, our findings highlight substantial alterations in sEV protein composition following nCRT.
Soft Sensing Modeling of Penicillin Fermentation Process Based on Local Selection Ensemble Learning
Authors: Huang Feixiang , Li Longhao , Du Chuanxiang , Wang Shuang , Liu Xuefeng
Published: June 2024

In the process of penicillin fermentation, there is a strong nonlinear relationship between the input eigenvector and multiple output vectors, which makes the prediction accuracy of the existing model difficult to meet the requirements of chemical production. Therefore, a local selective integrated learning multi-objective soft sensing modeling strategy is proposed in this paper. Firstly, a localization method based on transfer entropy and K-means is proposed to reconstruct the sample set. Then, based on the reconstructed local samples, the local soft sensing model is established by the multi-objective support vector regression method, and the selective integration of sub-models and the adaptive calculation of prediction weights are realized. At the same time, to reduce the adverse effects caused by improper selection of model parameters, the sparrow search algorithm is used to realize the tuning of the mentioned model parameters. Finally, the proposed modeling strategy is simulated. The results show that, compared with other methods, the proposed local selective integrated learning multi-objective soft sensing modeling strategy has better prediction performance.
An easier life to come for mosquito researchers: field-testing across Italy supports VECTRACK system for automatic count, identification and capture rate estimation of Aedes albopicts and Culex pipiens adult females and males.
Authors: Micocci Martina , Manica Mattia , Bernardini Ilaria , Soresinetti Laura , Varone Marianna , Lillo Paola Di , Caputo Beniamino , Poletti Piero , Severini Francesco , Montarsi Fabrizio , Epis Sara , Salvemini Marco , Torre Alessandra della
Published: June 2024

Background. Monitoring of mosquito vectors of human and zoonotic diseases is an essential prerequisite to optimize control interventions and for evidence-based risk predictions. However, conventional entomological monitoring methods are labor- and time-consuming and do not allow high temporal/spatial resolution. In 2022, a novel system coupling an optical sensor with machine learning technologies (VECTRACK) was proven effective in counting and identifying Aedes albopictus and Culex pipiens adult females and males. Here, we carried out the first extensive field evaluation of the VECTRACK system to assess: i) whether the catching capacity of a commercial BG-Mosquitaire trap (BGM) for adult mosquito equipped with VECTRACK (BGM+VECT) was affected by the sensor; ii) the accuracy of the VECTRACK algorithm in correctly classifying the target mosquito species genus and sex; iii) Ae. albopictus capture rate of BGM with or without VECTRACK.
Methods. The same experimental design was implemented in four areas in Northern (Bergamo and Padua districts), Central (Rome) and Southern (Procida Island, Naples) Italy. In each area, three types of traps - a BGM, a BGM+VECT, and Sticky Trap (N=4) were rotated each 48h in three different sites. Each sampling scheme was replicated three times/area. Collected mosquitoes were counted and identified both by the VECTRACK algorithm and by operator-mediated morphological examination. The performance of the VECTRACK system was assessed by generalized linear mixed and linear regression models. Aedes albopictus capture rates of BGMs were calculated based on the known capture rate of ST.
Results. A total of 3,829 mosquitoes (90.2% Ae. albopictus) were captured in 18 collection-days/trap type/site. The performance of BGM+VECT in collecting target mosquitoes and the VECTRACK algorithm performance in identifying Ae. albopictus and Cx. pipiens females and males were overall satisfactory, although with some inaccuracies. Moreover, the results allowed to quantify the heterogeneous effectiveness associated with different trap types in collecting Ae. albopictus and to predict estimates of its absolute density.
Conclusions. Obtained results strongly support the VECTRACK system as a powerful tool for mosquito monitoring and research, and its applicability over a range of ecological conditions, accounting for its high potential for continuous monitoring with minimal human effort.
18S and 25S ribosomal RNA molecules resistant to a 5'-monophosphate dependent exonuclease are produced by a mechanism independent of TOR
Authors: Rocha Miguel , Gowda Bhavani , Fleischmann Jacob
Published: June 2024

It has been previously shown that Saccharomyces cerevisiae yeast cells produce 18S and 25S ribosomal RNA components that are resistant to exonucleases and require a single phosphate at the 5’- end of the RNA. These molecules are produced during the stationary growth phase when TOR activity decreases. We wanted to further define the relationship between TOR and these resistant RNA molecules. Active suppression of TOR activity by rapamycin results in the production of these molecules. Similarly, a TORC1-deleted mutant Saccharomyces cerevisiae produces resistant 18S and 25S in a steady fashion. Thiouracil labeling of these molecules showed that molecules previously produced during the logarithmic growth phase can be converted to this resistant state. Thiouracil uptake assays also revealed that fewer 18S and 25S genes are produced during the stationary phase. The decapping of these molecules converts them back to an exonuclease-sensitive state. These data indicate that the production of exonuclease resistance of 18S and 25S is independent of TOR activity and is perhaps suppressed when TOR is active. Decapping converts them back to an exonuclease-sensitive state, indicating that at the minimum, there is an additional phosphate at their 5’-end. These molecules likely allow the presence of some ribosomes in the nutritional decline phase to maintain protein production.
Mathematical Modeling of the Sentiment Analysis Results of Psychoanalytic Diaries of the COVID-19 Pandemic
Authors: Duran Volkan , Hazar Elman , Gençel Nurgün
Published: June 2024

This study models the sentiment analysis results of "Psychoanalytic Diaries of the COVID-19 Pandemic" by Goisis and Moroni (2022) using differential equations. By employing sentence-level sentiment analysis, the research delves into the dynamic emotions documented during the COVID-19 pandemic. The integration of black box mathematical modeling enables the prediction of sentiment dynamics, revealing the intricate interplay of neutral and positive sentiments amidst collective trauma. Sentiment indicators are quantitatively transformed into percentage-based densities to facilitate a nuanced examination of the evolving emotional landscape. Sensitivity and cluster analyses, followed by linear regression, are utilized to construct a robust mathematical model that includes only variables with substantial influence. Critical evaluation of statistical indicators such as R-squared values and the Durbin-Watson statistic ensures the model's validity. The findings underscore the significant predictive power of emotions in understanding social perceptions, highlighting the essential role of sentiments in shaping human cognition and behavior. This research enhances our comprehension of sentiment dynamics during the COVID-19 crisis, demonstrating the potential of differential equations in modeling emotional structures. By bridging the gap between quantitative and qualitative methodologies, the study offers a unique perspective at the intersection of psychology, sociology, and mathematical modeling. The approach not only deepens our understanding of the emotional responses elicited during the pandemic but also sets a precedent for future research in exploring complex emotional phenomena through an integrated lens.
Associations between self-stigma and health promotion behaviors in overweight/obese patients with type 2 diabetes: a cross-sectional study
Authors: Niu Shilian , Li Rao , Yuan Li , Huang Dan
Published: June 2024

The correlation between stigma and health-promoting behaviors in overweight/obese type 2 diabetes (T2DM) patients is unclear. Therefore, this study aimed to investigate the association between the two in this particular population. Data were collected from an offline cross-sectional survey of 200 overweight/obese patients with T2DM aged 18-84 who were admitted to the Department of a tertiary general hospital in Chengdu, Sichuan Province, China between July 2022 and July 2023. Respondents were assessed for Stigma and health promoting behaviors using the SSCI and T2DHPS scales. Additionally, to examine the factors that influenced stigma, we utilized multiple linear regression analysis. Results revealed that stigma was significantly associated with health-promoting behaviors, with negative correlations with stress management and enjoyment of life. Several factors were found to increase the chronic disease stigma, including low monthly income, hypoglycemia, inpatient, and GLP-1RA treatment.
The Impact of COVID-19 Restrictions on the Health and Well-being of Women Living in Informal Settlements in Uganda.
Authors: Tetui Moses , Lee Na-Mee , Alhafi Laseen , Johnston Lesley A. , Babirye Susan , Dodd Warren , Mayora Chrispus , Kawooya Shafiq , Nakasinde Zeridah , Kirkpatrick Sharon I. , Butt Zahid A. , Kasasa Simon , Achom Mary , Byamukama Daniel , Janes Craig R.
Published: June 2024

Background:
The COVID-19 pandemic significantly impacted Uganda, with the first case reported in March 2020, resulting in extensive public health restrictions, including a lockdown, curfew, and closure of schools and workplaces. Urban residents, particularly those living in poverty in informal settlements, faced heightened challenges due to inadequate access to basic services, financial hardships, and increased caregiving responsibilities, especially for women. Women faced heightened risks of gender-based violence and engaged in transactional sex as coping mechanisms. This study explored the strategies used by women in Kampala and Mbale cities to meet basic needs during the pandemic and their implications for HIV infection vulnerability.
Methods:
Researchers conducted in-depth discussions with 282 women from various age groups in Kampala and Mbale's largest informal settlements, gathering insights into their pandemic experiences. These discussions, held in local languages, explored women's social, family, and financial challenges, as well as their perceptions of HIV risks. Transcripts were translated by local language experts before analysis. The team analyzed the transcripts using NVivo version 14 software, identifying patterns and themes that revealed survival strategies employed by women.
Results:
The study identified three interconnected themes that capture the complex strategies and challenges faced by women in informal settlements in Kampala and Mbale during the COVID-19 pandemic. Women struggled to cope with financial hardships and increased caregiving responsibilities, often resorting to desperate measures like transactional sex to survive, despite their resilience. The pandemic exacerbated vulnerabilities, heightening risks of HIV transmission and mental health issues, particularly among women living in poverty. While support networks provided some relief, they often fell short of meeting the diverse needs of women in these communities.
Conclusions:
The study shows that women in Uganda's informal settlements demonstrated resilience by taking on new roles and engaging in trading, but their reliance on transactional sex revealed stark power imbalances, increasing their vulnerability to gender-based violence, unintended pregnancies, and HIV infection. This highlights the urgent need for targeted interventions that address the complex challenges women face in crisis situations, which could enhance their resilience and alleviate their multiple struggles, with valuable lessons for similar contexts in low- and middle-income countries.
MA-GeSAN: Motion-Appearance Stream-Based Generative Self-Annotation Network Guided Self-Supervised Abnormal Event Detection in Videos
Authors: Chouhan Santosh Prakash , Bhattacharya Mahua , Sharma Gopal Krishna
Published: June 2024

In the recent one-class classification (OCC) approach for detecting abnormal events in surveillance videos, deep generative models (DGM) are specifically trained to learn regular hidden patterns in normal videos. These models assume that unusual events result in significant errors in their generated outputs. However, shared features related to both normal and abnormal events are often captured by DGM, resulting in similar generative errors at the output. Nevertheless, these models do not consider learning crucial domain-specific and distinguishable features, which limits their performance in complex and varying situations. In this paper, we present our model of motion and appearance stream-based generative self-annotation network (MA-GeSAN) guided distinguishable learning based on the conjunction of a generative-discriminative learning network to address the above challenge. The proposed model is established to learn the discriminative boundary of self-annotated video samples generated by the self-annotation network. The MA-GeSAN comprises two parts: (i) generative self-annotation network (GeSAN) for generating the critical frame level annotation based on the joint appearance anomaly score (AAS) and motion anomaly score (MAS), and (ii) deep 3D convolutional network (D3D-CNN) which is trained discriminatively on annotated video snippets \(v{s}_{0}\) (normal) and \(v{s}_{1}\)(abnormal) for identifying normal or abnormal video sequences. The GeSAN consists of a pipeline of spatial adversarial autoencoder (S-AAE) for generating the AAS based on appearance information and a temporal information module (TIM) for generating MAS based on motion information. Finally, the trained D3D-CNN is employed to classify the input video sequence into normal and abnormal classes. Our model performance is evaluated on three publicly available standard datasets, achieving 97.7% on UCSD Ped2, 87.9% on CHUK Avenue, and 99.5% on the UMN dataset in terms of AUC scores. These experimental results verify that our model offers excellent performance compared with other state-of-the-art models.
Multimodal Query Enhancement for Image Retrieval using Transformer Networks - MQIRT
Authors: Hosseini Seyed Mohammad Bagher , Bakhshandeh Soodeh
Published: June 2024

In today's world, with the dramatic increase of digital data and the variety of information, image recovery plays a very vital role in people's lives. For example, imagine a person in an online store looking for a dress similar to a friend's dress, but with distinct criteria such as blue flowers and red flags. The main challenge in this field is the existence of a semantic gap between the user's intention and the machine's understanding. The goal of image retrieval using multivariate (image-text) queries is to reduce this gap. An effective retrieval searches for images matching specific variations specified in a text expression related to the image. Existing methods use Convolutional Neural Networks (CNNs) and recurrent neural networks (LSTM) to extract image and text features that do not express the semantic relationships between the image and text well. In this regard, in order to improve these profiles, a transformer-based architecture is presented. In this research, Vision Transformer (ViT) is used to extract image features and Bidirectional Encoder (BERT) is used to extract text features. After combining the image and text features and applying the attention mechanism on images and text to enhance visual and text understanding. The proposed model of this research is inspired by deep metric learning and seeks to reduce the distance between the image and the input text with the searched images and the user's intent. In addition, a symmetric constraint has been used to improve the model indices. The evaluation results show that the proposed approach from the base model provides better performance in multimodal query-based image retrieval. To reproduce the results of this research, our source code is available at: https://github.com/smb-h/mqirtn
The response of human PMN zeta potential to selected ligands of the cAMP signal pathway under low-dose β-radiation
Authors: Zhirnov Victor , Iakovenko Igor
Published: June 2024

The objective of this study was to examine the zeta potential (ZP) response of human neutrophils to selected ligands of the cAMP signalling pathway under low-dose β-radiation (LDBR). ZP was calculated from the electrophoretic mobility (EPM) of the cells. Cells were irradiated at a dose rate of 10 µGy/hour for one hour. Irradiation of cell suspensions was conducted by adding appropriate aliquots of 14C-leucine to the incubation medium. EPM measurements were carried out in a radiation field. It was demonstrated that the LDBR and agonists of the AC system are capable of increasing the negative surface charge of human neutrophils. Conversely, the antagonist propranolol has been shown to reduce it. Furthermore, it has been demonstrated that radiation affects the response of the membrane ZP to some ligands of the AC pathway and vice versa. Therefore, LDBR can significantly alter the sensitivity of cells to drugs acting on the targets of these ligands. These results do not permit the conclusion that the effect of LDBR on ZP is mediated through the targets with which the studied ligands interact, since any of its components may undergo structural rearrangement, thereby altering the structural organisation of neutrophil membranes in the LDBR field.
Epidemiological Association in Asthma Rhinitis Overlap: Unveiling Key Hematological Markers Using Machine Learning
Authors: Li Haiyang , Yang Jing , Liao Ronghua , Wang Fei
Published: June 2024

Allergic rhinitis (AR) has been rising globally in recent years, now affecting between 10-30% of the population. The condition frequently coexists with asthma, with up to 40% of AR patients experiencing asthma symptoms and 80% of asthmatics reporting symptomatic AR. The presence of co-occurring AR exacerbates asthma, leading to increased risks of asthma attacks, emergency visits, and hospitalizations. This study aims to identify key biomarkers for assessing AR comorbidities in asthmatic patients to improve treatment and management strategies. We categorized subjects into three groups: healthy controls (n=4,032), asthma patients (n=21,506), and asthma patients with rhinitis (n=3,881). We applied a naive Bayesian machine learning algorithm to evaluate routine blood examinations and specific indicators. The ROC curve analysis was conducted to distinguish between normal, asthma, and asthma with AR states, revealing BAS%, ALB, NEUT%, and HB as key biomarkers with high diagnostic accuracy (AUCs of 0.722, 0.712, 0.680, and 0.711, respectively). Our findings indicate significant correlations between these biomarkers and disease states. In asthma with AR patients, lower levels of NEUT% and EOS% were observed compared to healthy and asthma-only groups. Gender differences were also noted, with a higher prevalence of asthma combined with AR in males. The analysis underscores the utility of BAS%, ALB, NEUT%, and HB in predictive modeling, providing a more accurate and early diagnosis crucial for effective disease management. This study highlights the potential of integrating biochemical indicators into advanced predictive models to enhance diagnostic precision and treatment outcomes for asthma and AR. Future research should validate these findings in larger cohorts and explore the integration of these biomarkers into clinical practice for better disease management and patient care.
Versatile Microwave Photonic Filter based on 100-Channel Brillouin Raman Fiber Laser
Authors: Yau Zhi-Yong , Shee Yu-Gang , Lim Eng-Hock , Zhang Zuxing , Mahdi Mohd Adzir
Published: June 2024

Microwave photonic filters (MPF) are among the most crucial components required for meeting the demands of high-speed and high-frequency signal processing of modern telecommunication systems. For the first time, here, we propose an MPF based on a double wavelength spacing Brillouin-Raman fiber laser (BRFL) to realize a versatile bandpass filter. The proposed setup generated 100 optical taps output with ~ 20 GHz spacings as the light source of the MPF. A dispersive medium of 5 km single mode fiber and 3.46 km dispersion compensating fiber (DCF) were used to characterize the effect of the time delay on the central frequency of the MPF passband. A reconfigurable 3-dB bandwidth from 150 MHz to 1.12 GHz centered around 10.3 GHz is achievable by varying the BRFL optical channel numbers using 10 to 100 optical taps with 20 GHz spacing in a 3.46 km DCF. The 3-dB bandwidth and Q-factor of the proposed MPF were investigated experimentally and found to be in good agreement with simulation, demonstrating the potential of the BRFL as a laser source for the realization of flexible and versatile RF transversal filters with potentially reduced cost and complexity.
Fast Best Viewpoint Selection with Geometry-Enhanced Multiple Views and Cross-Modal Distillation
Authors: Cao Zidi , Han Jiayi , Yang Sipeng , Jin Xiaogang
Published: June 2024

Despite significant progress on the mesh-based Best Viewpoint Selection (BVS) problem using multi-views, the current state-of-the-art BVS method requires 20-30 rendering views and is limited to selecting from a predefined sequence of viewpoint samples, which may miss optimal viewpoints and precludes its use in situations where response time is critical. To address the limitations, we present a new dual-branch fast best viewpoint selection regression model that significantly reduces reliance on a large number of input views, enables continuous perspective prediction, and enhances interactive response speeds. Our approach incorporates a geometry-enhanced multi-view feature extractor paired with a learnable token and utilizes a cross-modal distillation method to enrich the model’s understanding of 3D structures. Specifically, by embedding view features into a dimensionally matched learnable token and processing it through three cascaded self-attention layers, the resulting token effectively encapsulates fused features that are better suited to the viewpoint selection task.In addition, to reduce the number of views required, we incorporate cross-modal distillation into the BVS solution by imposing alignment constraints between 3D geometry descriptors and fused multi-view expressions, effectively avoiding the computational requirements of dozens of rendering views. Our experimental results on public benchmarks show that our method is approximately 35 times faster than the SOTA method when only six views are adopted, while also achieving the best quantitative metrics.
Research on High-Speed Drag Torque Characteristics of Wet Clutches Based on Mechanism and Data-Driven Approach
Authors: Zhang LIN , Zhou Haoyu , Zhang Peng , Wei Chao , Ma Ning , Yan Yunbing
Published: June 2024

The traditional drag torque model can accurately predict the drag torque in the low rotation speed stage, but cannot predict the drag torque rebound change in the high rotation speed stage. Therefore, a hybrid model based on the traditional wet clutch drag torque model and Particle Swarm Optimization-Back Propagation (PS0-BP) neural network is proposed in this paper, and the accuracy of the model is improved by the test data. The results show that the error of this hybrid model is 14.45%, which is better than the traditional drag torque model, and the stability and reliability are significantly improved compared with the other neural network models. The effects of oil temperature, the clearance of the friction pair, and the flow rate of lubricant on the drag torque are investigated. It was found that, with the increase of oil temperature and clearance of the friction pair, the rotational speed corresponding to the rebound change of drag torque decreases, and drag torque decreases. With the increase of the flow rate of lubricant, the rotational speed corresponding to the rebound change of drag torque rises, and drag torque increases.
Impact of Thermal Reservoir on Entanglement and Squeezing Characteristics of a Three-Level Laser Driven by Coherent Light in an Open Cavity
Authors: Adem Aliyyi
Published: June 2024

This research aims to study the squeezingand entanglement features of light in three-level atomsunder an open cavity with coherent light excitation.Using an approximation scheme for large timescales,we obtained the steady-state solutions of the evolutionequations for the atomic operators’ expectation valuesand the quantum Langevin equation for the cavity modeoperators. We employed these steady-state solutions todepict the squeezing characteristics, magnification ofentanglement, and normalized second-order correlationof the cavity radiation.The results of our researchshow that the light produced by the three-level lasergets squeezed, mainly in the minus quadrature. Themaximum quadrature squeezing for the light in thetwo-mode cavity is obtained as 37.9% at hni th = 0,and 37.5% at hni th = 0.02, and 37.2% at hni th = 0.03below the vacuum-state level. We demonstrated thatthe average and the variance of the number of photonsdecrease under the influence of spontaneous emission.Moreover, we determined that both the average andthe variance of the photon number are amplified bythe thermal reservoir effect. Additionally, we foundthat quadrature squeezing is enhanced by spontaneousemission, and some entanglement is created. In two-mode light, squeezing and entanglement are directlyrelated, such that an increase in squeezing producesmore entanglement and vice versa.
Transcriptional activation domains interact with ATPase subunits of yeast chromatin remodelling complexes SWI/SNF, RSC and INO80
Authors: Wendegatz Eva-Carina , Engelhardt Maike , Schüller Hans-Joachim
Published: June 2024

Chromatin remodelling complexes (CRC) are ATP-dependent molecular machines important for the dynamic organization of nucleosomes along eukaryotic DNA. CRCs SWI/SNF, RSC and INO80 can move positioned nucleosomes in promoter DNA, leading to nucleosome-depleted regions which facilitate access of general transcription factors. This function is strongly supported by transcriptional activators being able to interact with subunits of various CRCs. In this work we show that SWI/SNF subunits Swi1, Swi2, Snf5 and Snf6 can bind to activation domains of Ino2 required for expression of phospholipid biosynthetic genes in yeast. We identify an activator binding domain (ABD) of ATPase Swi2 and show that this ABD is functionally dispensable, presumably because ABDs of other SWI/SNF subunits can compensate for the loss. In contrast, mutational characterization of the ABD of the Swi2-related ATPase Sth1 revealed that some conserved basic and hydrophobic amino acids within this domain are essential for the function of Sth1. While ABDs of Swi2 and Sth1 define separate functional protein domains, mapping of an ABD within ATPase Ino80 showed co-localization with its HSA domain also required for binding actin-related proteins. Comparative interaction studies finally demonstrated that several unrelated activators each exhibit a specific binding pattern with ABDs of Swi2, Sth1 and Ino80.
Highly Sensitive Silver/Tin Selenide/Graphene Multilayer SPR Sensor for Hemoglobin and Glucose Levels Monitoring in Biological Fluids
Authors: Alsaad Ahmad M. , Al-Hmoud M. , Marashdeh M. W. , Tolstik Elen , Houshmand Milad , Telfah Ahmad
Published: June 2024

This work presents the simulation of a novel surface plasmon resonance (SPR) biosensor composed of silver/tin-selenide/graphene. The designed sensor aims to detect biological constituents in various chemical and biological solutions. While simulation packages based on finite element methods (FEM) are typically utilized in engineering and physics for structural and fluid dynamics analyses, their application in medical diagnostics is less common. In this study, we employed a simple FEM simulation method for medical diagnostics. The functionality of the proposed FEM-based simulated biosensor is examined by testing it on hemoglobin and glucose samples of a diabetic person. In the blood samples analyzed, a 6.1025 g/l increase in hemoglobin (HB) level corresponded to a 0.001 refractive index unit (RIU) increment. The SPR sensor design presented in this work demonstrated a novel capability to detect such minute changes using a simple and cost-effective setup, achieving an angular sensitivity of 158 deg/RIU. Additionally, the SPR sensor was employed for detecting glucose concentrations in urine samples, offering a potential indicator for diabetes diagnosis. The novelty of this SPR sensor lies in its simple schematic design, enabling precise detection of both hemoglobin and glucose levels.
Quantifying suitable low-impact development practices in mitigating runoff floods for the Kinyerezi River catchment in Dar es Salaam, Tanzania
Authors: Swilla Livingstone , Katambara Zacharia , Lingwanda Mwajuma
Published: June 2024

As cities expand, changes in land use increase the runoff quantities. Impermeable catchment areas contribute to peak flows, causing floods in insufficiently capacity river reaches. The rate of urbanization witnessed in the Kinyerezi River catchment in Dar es Salaam has contributed to floods in the Msimbazi River. The low-impact development (LID) practices that include bioretention (BR) ponds, rain barrels (RBs), rain gardens (RGs), vegetative swales (VSs), constructed wetlands (CWs), etc., can be utilized to mitigate a portion of the surface runoff. This study aims to quantify the suitable LID practices for the Kinyerezi River catchment in mitigating a portion of runoff floods. The sub-catchment physical characteristics and soil infiltration rates (Ks) were matched with each LID sitting requirements and later by multi-criteria decision-making (MCDM). The results on matching sub-catchment characteristics and LID sitting requirements indicated that BRs, RBs, VSs, RGs, and CWs were the preferable LIDs while MCDM analysis indicated the BRs, RGs, and RBs more appropriate. The BRs, RGs, and RBs were quantified to be 101, 3,698, and 3,698, respectively, within the catchment. BRs are recommended for catchment use while RBs and RGs are recommended for residential buildings. The RBs have the advantage of promoting water-demanding economic activities.
Online Assessments in Medical Education: Identified Challenges and PotentialSolutions
Authors: Shrivastava Saurabh RamBihariLal , Bobhate Prateek Sudhakar , Mishra Vaishnavi
Published: June 2024

:

The scope of online assessment in the field of medical education is extensive and varied, encompassing a wide range of types of assessments and
purposes. For the assessment of the cognitive domain, online assessment can be carried out with the help of a number of assessment methods. As is
the case with any potential tool, even online assessments have their share of limitations, and we must be aware of this as it can help us to make a
systematic and evidence-based decision about when to use online assessments and when to combine them with traditional assessments. In order to
enhance the acceptability and use of online assessments in medical education, it is crucial to overcome the identified limitations. The primary
strategy is to clearly communicate the format, the instructions, and the expectations from both teachers and students to avoid all kinds of confusion.
In conclusion, online assessments have immense scope in the field of medical education. However, considering the fact that the successful
implementation of these assessments depends on multiple factors, it becomes essential that we take appropriate measures to overcome the potential
challenges and adopt a concerted and collaborative approach.
Decoding the Expressions, Immune Relevance, and Prognostic Values of Ferroptosis Gene TMEM189: A Pan-cancer Analysis
Authors: Qiu Guanzhong , Song Chaoli , Lou Meiqing , Lin Jing
Published: June 2024

Background:

TMEM189 is a recently discovered transmembrane protein involved in
ether glycerophospholipid synthesis and ferroptosis regulation. However, its role in tumors is not
well understood.

Objective:

This study aimed to elucidate the oncogenic effects and prognostic values of
TMEM189 in tumors.

Methods:

We performed a pan-cancer analysis of TMEM189 using various databases, bioinformatics
and statistical tools, and tissue microarray analysis.

Results:

TMEM189 was upregulated in tumors compared to normal tissues. High TMEM189 expression
was found to be linked to reduced promoter methylation. Moreover, TMEM189 exhibited
a negative correlation with immunogenic markers, immune cell infiltration, and expression of
Immune Checkpoint Genes (ICGs) in most cancers, implicating its immunosuppressive role in tumor
microenvironments (TME). The genes that interact and are similar to TMEM189 were involved
in hotspot signaling pathways in pan-cancer. TMEM189 overexpression was found to be
usually associated with poor prognosis, especially an independent prognostic risk factor for BLCA,
BRCA, LUAD, MESO, LIHC, and SKCM.

Conclusion:

TMEM189 is overexpressed and exerts immunosuppressive effects in many tumors
with a significant association with poor prognosis, suggesting its potential as a therapeutic target
in cancer treatment.Keywords: TMEM189, ferroptosis, pan-cancer analysis, prognosis, immune
microenvironment.
Physochlainae Radix: A Review of Ethnobotany, Phytochemistry, Pharmacology, Q-marker Prediction, and Future Directions
Authors: Zhang Xin-bo , Zhao Peiyuan , Wang Yunlan , Zhang Ying , Lei Xuan , Song Xiao
Published: June 2024

Background:

Upon the release of the selection results of “Qin Medicine,” numerous
Chinese herbal medicines and proprietary Chinese medicines have regained attention. Physochlainae Radix (Huashanshen), a herbal medicine named after Mount Hua, the prominent peak in the
Qinling Mountains, has garnered particular interest. Despite this, the impact of Physochlainae Radix and Qin medicines as a whole remains significantly overshadowed by the renown of Mount
Hua.

Methods:

Search on Using “Physochlainae Radix” as the keyword; searches were conducted
across China National Knowledge Infrastructure (CNKI), Wanfang Data, WIP Database, PubMed,
Web of Science, and the National Library of China databases

Results:

This study presents an overview of Physochlainae Radix by reviewing its history, chemical composition, preparation methods, planting and cultivation practices, concoctions, alkaloid detection, contraindications for use, resource recycling, and predicting quality markers.

Conclusion:

To facilitate the further application and development of Physochlainae Radix, this
study also addresses the challenges in the development of Qin medicines and proposes potential
solutions.
Natural Bioactive Compounds as Anti-aging Agents: Current and Future
Perspectives
Authors: Sahoo Purbasha , Vyas Manish , Sahu Sanjeev Kumar
Published: June 2024

Aging is a natural biological process that occurs due to various factors like unhealthy
diet, environmental factors, genetic factors, and lack of moisture. This process leads to the loss of
skin elasticity, also known as sagging. It happens due to the gradual decline of collagen type VII
(Col-7) and fibril, which slows down the connection between the dermis and epidermis layers,
causing the skin to look aged externally. There are several theories of aging, such as the free radical theory, membrane theory, DNA or genetic theory, neuroendocrine theory, telomerase theory,
mitochondrial decline theory, and Hayflick limit theory. According to WHO, by 2030, one in six
individuals worldwide will be 60 years or older. There are synthetic compounds available in the
market for anti-aging purposes, but they pose various side effects. Natural products play an essential role in managing aging, and anti-aging phytoconstituents are mostly found in plant parts like
fruits, stems, roots, and other plant sources that have no side effects. This review focuses on various anti-aging agents derived from plants and other natural sources.
The Low Tumorigenic Risk and Subtypes of Cardiomyocytes Derived from Human-induced Pluripotent Stem Cells
Authors: Lu Jizhen , Zhang Lu , Cao Hongxia , Ma Xiaoxue , Bai Zhihui , Zhu Hanyu , Qi Yiyao , Zhang Shoumei , Zhang Peng , He Zhiying , Yang Huangtian , Liu Zhongmin , Jia Wenwen
Published: June 2024

Background:

Clinical application of human induced pluripotent stem cell-derived cardiomyocytes
(hiPSC-CMs) is a promising approach for the treatment of heart diseases. However,
the tumorigenicity of hiPSC-CMs remains a concern for their clinical applications and the composition
of the hiPSC-CM subtypes need to be clearly identified.

Methods:

In the present study, hiPSC-CMs were induced from hiPSCs via modulation of Wnt signaling
followed by glucose deprivation purification. The structure, function, subpopulation composition,
and tumorigenic risk of hiPSC-CMs were evaluated by single-cell RNA sequencing (scRNAseq),
whole exome sequencing (WES), and integrated molecular biology, cell biology, electrophysiology,
and/or animal experiments.

Results:

The high purity of hiPSC-CMs, determined by flow cytometry analysis, was generated.
ScRNAseq analysis of differentiation day (D) 25 hiPSC-CMs did not identify the transcripts representative
of undifferentiated hiPSCs. WES analysis showed a few newly acquired confidently
identified mutations and no mutations in tumor susceptibility genes. Further, no tumor formation
was observed after transplanting hiPSC-CMs into NOD-SCID mice for 3 months. Moreover, D25
hiPSC-CMs were composed of subtypes of ventricular-like cells (23.19%) and atrial-like cells
(66.45%) in different cell cycle stages or mature levels, based on the scRNAseq analysis. Furthermore,
a subpopulation of more mature ventricular cells (3.21%) was identified, which displayed
significantly up-regulated signaling pathways related to myocardial contraction and action potentials.
Additionally, a subpopulation of cardiomyocytes in an early differentiation stage (3.44%) experiencing
nutrient stress-induced injury and heading toward apoptosis was observed.

Conclusions:

This study confirmed the biological safety of hiPSC-CMs and described the composition
and expression profile of cardiac subtypes in hiPSC-CMs which provide standards for quality
control and theoretical supports for the translational applications of hiPSC-CMs.
The Overweight Prediction Model in the Risk Factor-based Adolescents Using a Web-based Online Application
Authors: Yuniarti Elsyie , Masrul Masrul , Sulastri Delmi , Elfitri Ikhwana , Lipoeto Nur Indrawati , Machmud Rizanda , Afrizal Afrizal , Symond Denas
Published: June 2024

Background

The overweight prevalence rate in Indonesian adolescents has kept increasing. Basic Health Research in Indonesia recorded the overweight prevalence and obese nutritional status (BMI/Age) in adolescents at 18.1%. The overweight nutritional status (BMI/Age) in 2010-2013 among adolescents at the age of 16-18 was 1.4% in 2010 and increased to 7.3% in 2013.

Objective

This study aims to establish a prediction model for overweight adolescents based on their risk factors to prevent an early overweight.

Methods

The samples were 300 students from 5 high schools in Padang City, Indonesia. This study applied mixed methods and used a logistic regression test to comprehend the determinant variables in establishing the prediction model and conducting the application tests.

Results

The research shows the result that these adolescents had the risk factors, namely excessive consumption of carbohydrates and fats, the amount of vegetable consumption was <3 portions/day, physical activity time was <15 minutes/day, and a low level of health knowledge. It was predicted that the odds of being overweight were 82.31%, with accuracy at 95.0%, sensitivity at 93.33%, and specificity at 95.71%. The result showed application design validation by experts at 0.96 and validation of application construction and content by experts at 0.84. The teachers’ response practicality was 92.22%, adolescents’ response practicality was 85.45%, and adolescents’ response effectiveness was 85.05.

Conclusion

The most dominant risk factors are fat consumption, carbohydrate consumption, amount of vegetable consumption, duration of physical activities, and level of health knowledge that can be considered to prevent overweight in adolescents.
Extracts from Artemisia annua Alleviates Myocardial Remodeling through
TGF-β1/Smad2/3 Pathway and NLRP3 Inflammasome
Authors: Ma Zizhe , Bai Zhenzhou , Li Bohan , Zhang Yue , Liu Wei
Published: June 2024

Background and Objectives:

Artemisinin and its derivatives, the well-known anti-malarial drugs extracted from traditional Chinese medicine, have been implicated in treating
fibrotic diseases. However, whether artemisinin affects cardiac fibrosis in the pathogenesis of heart failure is still unknown. This study aimed to
evaluate the possible effects of artemisinin on cardiac function and myocardial fibrosis in the heart failure model and to explore the underlying
mechanisms.

Methods:

Isoproterenol was injected subcutaneously for induction of the cardiac fibrosis model. Proteomic analysis was performed after 4 four weeks of
artemisinin treatment. Echocardiography was used to evaluate cardiac function and structure. Hematoxylin and eosin (H&E) staining, as well as
Masson staining, were performed for histopathology. The α-SMA, collagen I, and III expression in the myocardium was detected by
Immunohistochemical staining. The ratio of heart weight (HW) to body weight (HW/BW, mg/kg) and the ratio of heart weight to tibia length
(HW/TL, mg/mm) were calculated as indicators for cardiac remodeling. Brain natriuretic peptide (BNP) levels were quantified in rat plasma using
enzyme-linked immunosorbent assay (ELISA). In contrast, the protein levels of TGF-β1, p-Smad2/3, and Smad2/3 were assessed in myocardium
and fibroblasts via western blot analysis. RT-qPCR analysis of Col-I, Col-III, α-SMA, NLRP3, Caspase-1, IL-1β, and IL-18 was performed in the
heart.

Results:

Proteomic analysis identified 227 differentially expressed proteins (DEPs), including 119 upregulated and 108 downregulated proteins. These
proteins were identified as the core proteins targeted by artemisinin for improving myocardial remodeling. GO annotation of the DEPs indicated
that the DEPs were mainly associated with biological processes such as TGF-β and NLRP3 inflammasome regulation. In the in vivo study of an
isoproterenol-induced SD rat cardiac remodeling model, we found that artemisinin administration significantly ameliorated cardiac dysfunction and
reduced collagen production by suppressing TGFβ-1/Smads signaling and inhibiting NLRP3 inflammasome activation. As manifested by
downregulating the expression of α-SMA, Col-I, and Col-III, NLRP3, IL-1β, IL-18, Caspase-1 mRNA, and TGF-β1, p-SMAD 2/3 protein in the
myocardium. Similar beneficial effects of artemisinin were consistently observed in TGF-β1 treated primary cardiac fibroblasts.

Conclusions:

Artemisinin relieves myocardial remodeling through TGF-β1/Smad2/3 pathway and NLRP3 inflammasome.