bluuebunny/crossref_metadata_2025 huggingface dataset:
Examining Dimensions of Career Intentions: Insights From Medical and Nursing Students at a Private Not-for Profit University in Vietnam
Authors: Ha Minh Thuy , Dao Huy Cu , Nguyen Hoa Huyen , Nguyen Hoang Long , Le Phuoc
Published: July 2024

In undergraduate health professions education, the primary goal is to prepare students with the skills and knowledge for employment and to foster a motivated future health workforce. Studies show that job satisfaction is linked to educational satisfaction, and well-designed transition programs and clinical exposure are crucial for smooth transitions from academia to the professional world. Through a mixed-methods approach incorporating both quantitative surveys and qualitative interviews, this study aims to provide further insights into students' career aspirations and the underlying determinants for health professions students in Vietnam. In phase one, 198 respondents were surveyed, equivalent to 77% of recipients, providing demographic data and quantitative insight into career preferences. Phase two consisted of in-depth individual interviews with 11 students to explore the nuanced factors influencing their career intentions. The results reveal a diverse range of career aspirations among students, with a predominant interest in clinical practice, focusing on surgery, internal medicine and pediatrics. Notably, 22.7% (n = 45) of students aspire to practice overseas, while nearly 31.4% (n=62) have yet to decide between local or overseas practice. The study also reveals a need to improve career counseling support, as a significant portion (70.7%, n=140) of participants feel they have not received adequate assistance in this area. Factors such as personal interest, family influence, financial considerations, societal appreciation, and mentorship emerged as significant influences on students' career decisions. The study provides insights for educational institutions and policymakers to enhance career guidance and support services, identify the needs of counselling and mentorship program, thereby facilitating the successful transition of students into their chosen healthcare professions.
Flubendazole presents anti-tumor effects by promoting cell cycle arrest and inhibiting the invadopodia in pancreatic cancer
Authors: Zhao Pengcheng , Wang Zihe , Huang Xing , Xue Kang , Liu Xiaofeng , Tian Bole
Published: July 2024

Pancreatic ductal adenocarcinoma (PDAC) is characterised by its high aggressive biological tumor behavior leading to a poor prognosis. The existing chemotherapy regimes have considerable limitations such as drug resistance and serious adverse effects. Flubendazole is an antihelmintic drug with highly safety that is recently reported to be a potential anti-tumor agent in various types of human cancer cells. We conducted a series of assays to explore its role in PDAC, like CCK8 assays, transwell-migration and invasion assays. In addition, we constructed the invadopodia model in vitro to investigate the effect of flubendazole on invadopodia. We found that flubendazole could inhibit the viability of PDAC cells dose-dependently and time-dependently. It also caused G2/M arrest by disrupting the microtubule and also induce apoptosis. The migration of PDAC cells was attenuated and could be partly explained by the disruption of EMT caused by flubendazole. Besides, the invasion was weakened by flubendazole and the number of cells with mature invadopodia was also decreased. Moreover, it interfered the formation and maturation of invadopodia by inhibiting PI3K/Akt pathway and Src-mediated Tks5 phosphorylation, and thus inhibit the metastasis of PDAC cells. Due to its high safety, it may provide a novel insight for the prevention and treatment of pancreatic cancer metastasis.
Evaluation of easterly wave disturbances over the tropical South Atlantic in CMIP6 models
Authors: Cavalcante Lucas , Gomes Helber , Hodges Kevin , Ray Pallav , Herdies Dirceu , Barbosa Henrique , Gonçalves Weber , Silva Maria Cristina , Brito José Ivaldo , Nobre João Pedro , Lyra Matheus , Baltaci Hakki
Published: July 2024

This study assesses the performance of the latest phase of Coupled Model Intercomparison Project (CMIP6) models in simulating easterly wave disturbances (EWD) over the tropical South Atlantic (TSA) impacting northeast Brazil (NEB). Initially, we evaluate simulated precipitation from 17 historical CMIP, 16 AMIP, 7 hist-1950, and 10 highresSST-present models against the Global Precipitation Climatology Project (GPCP) dataset to identify models that accurately reproduce the spatial and temporal precipitation patterns in the study region. The ensemble's spatial analysis demonstrates their capability in reproducing annual and seasonal precipitation climatology. However, models underestimate precipitation intensity along NEB's coast while overestimating it in TSA and NEB's north. Model uncertainties tend to be greater with higher latitudes. The models represented the annual cycle in all subareas within the study region, particularly from July to October, albeit with a greater spread in the first half of the year, especially over the Intertropical Convergence Zone (ITCZ). Based on it, three top-performing models from each ensemble were selected for EWD evaluation. The automatic tracking algorithm for EWDs showed the model's ability to represent mean values of EWD lifetime (~ 6 days) and phase speed (~ 7 m s-1) as found in ERA5 reanalysis. However, they failed to capture EWD's interannual variability or climatological mean frequency. Despite CMIP6 model weaknesses, they accurately identified two primary EWD genesis regions: one over the TSA and another near the West African coast. Overall, CMIP6 models, particularly atmospheric and high-resolution models (HighResMIP), effectively captured precipitation climatology and EWD characteristics over NEB and the adjacent TSA.
An Optimised Hybrid ELSVM-BRO Model for Predicting Software Reliability
Authors: Rath Suneel Kumar , Sahu Madhusmita , Das Shom Prasad , Tripathy Hrudaya Kumar , Shah Mohd Asif , Mallik Saurav
Published: July 2024

In recent years, there has been a rise in strict environmental and safety regulations, resulting in the implementation of extra protocols dictating the functioning and state of software to effectively adhere to safety standards. As a result, the importance of timely, effective, and accurate maintenance procedures has grown significantly. Proper utilization of data has the potential to boost efficiency, reinforce safety measures, lower operational expenses, protect assets, enhance workforce productivity and advance environmental preservation efforts within the software industry. This research aims to devise a novel methodology capable of synchronizing data gathered from multiple sources and constructing a scalable framework to identify early indications of software malfunction. The proposed approach, explored in this study, integrates various Hybrid Extreme Learning Machine (ELM) and Support Vector Machine (SVM) with Binary Rao optimization (JAYA algorithm) techniques (ELSVM-BRO), directly evaluating time series data from the dataset. Pre-processing stages encompass data smoothing, filtering, outlier mitigation, and segmentation, followed by feature extraction for classification purposes. In the given context, a unique model is proposed. This model is a combination of Hybrid Extreme Learning and Support Vector Model, and it’s based on Binary Rao (BR) i.e., also known as Jaya Optimization. The primary purpose of this model is to evaluate the condition of a software system, specifically determining whether it’s faulty or healthy. Comparison with K-Nearest Neighbours (KNN), SVM, and Naïve Bayes (NB) and Random Forest (RF) classifiers using 10 datasets reveals that the ELSVM-BRO model attains superior balanced accuracy levels. The study suggests that amalgamating these algorithms enhances predictive reliability, particularly when applied to datasets of varying sizes.
YOLOv8-Seg: A Deep Learning Approach for Accurate Classification of Osteoporotic Vertebral Fractures
Authors: Yang Feng , Qian Yuchen , Xiao Heting , Zhao Xuewen , Chen Yuwei , Zhang Tianyou , Sun Haifu , Shan Lei , Li Yonggang , Wang Lingjie , Qiao Yusen , Chen Tonglei
Published: July 2024

The abstract of the article presents a study focused on the application of deep learning for the classification of osteoporotic vertebral fractures (OVF), a growing health concern among the elderly. The research aimed to explore the potential of deep learning to assist in diagnosing OVF, evaluate the clinical viability of this method, and enhance recovery rates. A dataset comprising 643 CT images of OVF from patients admitted between March 2013 and May 2023 was collected and classified according to the European Vertebral Osteoporosis Study Group (EVOSG) spine classification system. Of these, 613 images were utilized for training and validating a deep learning model, while 30 images served as a test set to assess the model's performance against clinician diagnoses. The deep learning system achieved an impressive 85.9% accuracy rate in classifying fractures according to the EVOSG criteria. The study concludes that deep learning offers a high degree of accuracy in identifying OVF from CT images, which could streamline and improve the current manual diagnostic process that is often complex and challenging. The study also introduces the YOLOv8-Seg model, a novel classification method designed to enhance the diagnostic capabilities for OVF. The use of deep learning in this context is positioned as a significant advancement with the potential to support medical professionals in making early and precise diagnoses, thereby improving patient outcomes. Key terms highlighted in the abstract include deep learning, osteoporotic vertebral fracture, and YOLOv8, indicating the integration of advanced technology in medical diagnosis.
Ambient temperature affects the composition of the vaginal microbiome and temperature sensitive vaginal microbes influence assisted reproductive technology outcomes
Authors: Liu Zheng , Hao Yuwen , Sun Tianyong , Li Meihui , Li Xiao , Qin Lang , Liu Xin , Bian Yuehong , Zhao Shigang , Zhao Qi , Zhao Han , Feng Qiang
Published: July 2024

Objective
To investigate the influence of environmental factors on the composition and structure of the vaginal microbiome, and to explore the interaction among environmental factors, vaginal microbiome and outcomes of assisted reproductive technology (ART).
Methods
Adonis test was utilized to evaluate the impact of 33 host/environmental variables on vaginal microbiome. DLNM, Mfuzz analysis and linear mixed effect model were employed to establish the correlations between ambient temperature and vaginal microbes.
Results
Ambient temperature was one of the most important environmental factors associated with vaginal microbiome. As the temperature increased, succession of vaginal microbes showed four patterns of abundance variation. Furthermore, a group of vaginal microbes showed a preference for certain temperatures, and these microbes' varying interactions partly drove the shift of microbial networks at different temperatures. The community assembly process of vaginal microbiome deviated from neutral model and exposure to ambient temperature did not affect the role of stochastic processes in shaping vaginal microbial community. Notably, vaginal microbiome prior to embryo transfer was significantly associated with preterm birth. Preterm women exhibited higher abundance of Lactobacillus iners and lower abundance of Lactobacillus crispatus.
Conclusions
Ambient temperature change can affect the structure and composition of the vaginal microbiome, and correlate with the abundance of certain vaginal microbes. Temperature sensitive vaginal bacteria may affect the risk of future preterm births.
Hypopituitarism after gamma knife radiosurgery for pituitary adenomas: long-term results from a single-center experience
Authors: Yu Jinxiu , Fu Jiaming , Li Yanli , Hu Guangxin , Hu Guanye , Hu Wentao , Liu Detian , Fu Junyi
Published: July 2024

Purpose
The aim of this study was to investigate the incidence and risk factors of hypopituitarism after gamma knife radiosurgery (GKRS) for pituitary adenomas in a single center.
Methods
In this retrospective study, 241 pituitary adenoma patients who underwent GKRS from 1993 to 2016 were enrolled. These patients had complete endocrine, imaging, and clinical data before and after GKRS. The median follow-up time was 56.0 (range, 12.7–297.6) months.
Results
Fifty patients (20.7%) developed new-onset hypopituitarism after GKRS, including hypogonadism (n = 22), hypothyroidism (n = 29), hypocortisolism (n = 20), and growth hormone deficiency (n = 4). The median time to new-onset hypopituitarism was 44.1 (range, 13.5–141.4) months. The rates of new-onset hypopituitarism were 3%, 11%, 18%, 37%, and 45% at 1, 3, 5, 10, and 15 years, respectively. In univariate analysis, sex (p = 0.012), suprasellar extension (p = 0.024), tumor volume (≥ 5 cm3) (p = 0.002), tumor margin dose (> 16 Gy) (p = 0.028), pre-existing hypopituitarism (p = 0.008), and previous surgery (p = 0.007) were significantly associated with new-onset hypopituitarism. In multivariate analysis, only tumor volume (≥ 5 cm3) and previous surgery were independent risk factors associated with new-onset hypopituitarism (hazard ratio [HR] = 2.149, 95% confidence interval [CI] = 1.190–3.880, p = 0.011 and HR = 1.893, 95% CI = 1.066–3.361, p = 0.029, respectively).
Conclusion
New-onset hypopituitarism was not uncommon after GKRS for pituitary adenomas. In this study, large tumor volume (≥ 5 cm3) and previous surgery before GKRS were associated with new-onset hypopituitarism.
BASA-GAN:Self-Attention-Guided Semi-Supervised Balanced Augmented Image Recognition Model
Authors: Hu Jing , Zhang Rumin , Lian Bingquan , Wang Fang
Published: July 2024

Existing deep learning image recognition models heavily rely on large amounts of manually labeled data by professionals, which is difficult to acquire, costly in terms of human labeling, and prone to subjective influence. Additionally, datasets in practical scenarios often exhibit imbalance, with a significant skew towards majority classes over minority classes. Compared to the majority classes, the rare minority classes are often more meaningful. However, most existing models tend to bias towards the majority classes during fitting, resulting in insufficient recognition accuracy for minority classes, which significantly hinders the widespread application of deep learning in practical image recognition. This paper introduces a new semi-supervised generative adversarial network, BASA-GAN, which can realize fair training of each class in unbalanced data set and improve the attention and recognition rate of minority classes. Firstly, we introduce a balanced generator module (SAG) that utilizes an autoencoder to learn features from all classes in the original labeled dataset and generates a balanced dataset through reconstruction. The reconstructed dataset is then fed into the generator to achieve fair ing for each class during training. In SAG we design a completely new class-balanced loss that encourages the autoencoder to generate a more balanced hidden space representation for different classes of data. Then, by incorporating the self-attention mechanism into the SAG module and the discriminator, we enhance the quality of the synthesized images and the discriminative power of the discriminator. Additionally, we introduce the spectral normalization into the semi-supervised model of BASA-GAN to address the instability issues during GAN training. Experimental results demonstrate that the SAG module achieves highly competitive performance in semi-supervised imbalanced image recognition tasks, not only improving the recognition accuracy for minority classes but also achieving fair training for each category in the dataset.
Governance of biological sample sharing in health research: Material Transfer Agreements (MTAs) in Zambia and South Africa – necessary but sufficient?
Authors: Chalwe Victor , Rossouw Theresa , Brand Dirk , Moodley Keymanthri
Published: July 2024

Introduction:The transfer of biological materials is a pivotal aspect of health research, especially in clinical trials conducted in Africa. Globally, standard material transfer agreements (MTAs) have been developed in an effort to standardize the transfers of biological materials. Recent controversial conduct in research in sub-Saharan Africa highlightsthe need for robust regulation, especially concerning biological sample transfer. The question remains whether these new regulations in African countries are sufficient to ensure ethical conduct.
Methods:This study evaluated the sufficiency of Zambia's existing legislation concerning MTAs using South African laws and guidelines as comparators. A qualitative study approach was adopted utilizing a desk review. Thematic analysis was conducted after extracting information from relevant national legal documents thatare publicly accessible. Necessary permissions and approvals were obtained before conducting the research.
Results: Thisstudy determined that Zambia and South Africa (SA) have established regulations for transfer of biological materials in health research. Zambia's framework is based on the National Health Research Act No. 2 of 2013 and MTA regulations of 2018. This Act emphasizes the importance of consent when extracting tissue or blood, and mandates that samples and data remain the property of the Zambian government. In contrast, South Africa's guidelines stemmed from the National Health Act 61 of 2003 and regulations SAMTA 2018, detailing an ongoing informed consent process and protection of donor data privacy.
South Africa provides a more detailed account of benefit sharing, whereas Zambia adopts a more generic approach. The South African framework offers specific guidance on the secondary use of materials and custodianship.
Both nations emphasize intellectual property rights but to differing extents. However, ambiguities persist in both countries regarding the details of benefit sharing
Conclusion:
The study revealed that Zambia and South Africa have established detailed legal frameworks governing the transfer of biological materials in health research incorporating consent, national sovereignty and protection of privacy. However, the effectiveness of their enforcement and implementation remains a critical concern, particularly in addressing ambiguities related to benefit sharing, ownership, custodianship, and intellectual property rights.
Inhalational versus intravenous anesthetic for cerebrovascular accident outcomes after surgical revascularization for adult Moyamoya disease
Authors: Cheng Yifei , Zha Chaochao , Che Xuehua , Wang Yingwei
Published: July 2024

Purpose: To compare the effects of inhalational anesthetics and intravenous anesthetics on the neurological function of patients with moyamoya disease (MMD) after vascular bypass surgery.
Methods: The clinical anesthesia data of patients were retrospectively collected. Patients who underwent bypass grafts with general anesthesia from January 1st, 2019, to December 31st, 2020, in Huashan Hospital affiliated with Fudan University, were selected. The primary endpoint was stroke incidence within seven days after anesthesia, and the secondary endpoints included hyperperfusion syndrome (HPS) and incidence of postoperative seizure.
Results: We compared the data of MMD patients who received inhalational anesthetics (Sevoflurane anesthetics ,n = 199, group S) and intravenous anesthetics (Propofol anesthetics , n = 219，group P). The stroke incidence in the two groups (group S vs. group P) was 6.6% vs. 5.9% (OR = 0.835; 95% CI, 0.388-1.797; p = 0.841), and the group S vs. group P of HPS incidence was 32.5% vs. 31.1% (OR=0.942; 95% CI, 0.636-0.1.397, p = 0.753). At discharge, anesthetics didn't affect the neurological endpoint. There were statistical no differences in the NHISS score (p50:S group vs. P group = 2:1, p=0.082) at 7 days after surgery, but mRS score (p50:S group vs. P group = 2:1, p<0.001) at 7 days after surgery, as well as the mRS score at 6 months of follow-up (p50:S group vs. P group=0:0, p<0.001) have tatistical differences.
Conclusion: Our data indicated that both inhalational and intravenous anesthetics had protective effects on patients who underwent MMD bypass grafts. MMD patients who received inhalational anesthetics and intravenous anesthetics had similar odds of neurological deficits. When comparing long-term clinical data, most patients experience good neurological recovery after receiving inhalation or intravenous anesthesia, but when compared mRS score p75（S group vs. P group = 3:1）in 6 month intravenous anesthetics might be more suitable for patients undergoing MMD bypass grafts. Keywords: Moyamoya disease; Surgical therapy; Anesthesia; Sevoflurane; Propofol
Pleiotropic Activity of Hop Extract: Unveiling its Antimicrobial Efficacy in Oral Cavity
Authors: Guan Qunli , Wang Yaozhong , Mo Jianning , Tang Shang , Li Guotai , Deng Jing
Published: July 2024

The extract of Hops (Humulus lupulus L.), a herb medicine with a rich history spanning over 2000 years, has recently received extensive attention in food, health, and biomedicine. However, its reports in oral application are rare. To provide fundamental information for further clinical study in oral treatment, in this work, pleiotropic activity of hop extract including the stability, cytotoxicity, antioxidant activity, and antimicrobial activity of hop extract are investigated. The UV and thermal stability of hop extract were assessed using FT-IR analysis, while antioxidant activity was determined through experiments measuring DPPH, ABTS, and hydroxyl radical scavenging activities. Cytotoxicity was evaluated using the CCK-8 assay. Furthermore, we examined the antimicrobial activities of hop extract against four pathogenic microorganisms commonly associated with oral diseases—namely, E. faecalis, S. aureus, E. coli, and C. albicans—through inhibition zone and colony-forming unit assays. Experimental results show that hop extract has good UV and thermal stability, as well as good biological biocompatibility and antioxidant activity. Importantly, antimicrobial tests indicate that hop extract exhibits not only strong antibacterial activity against both Gram-positive and Gram-negative bacteria, but also effective antifungal ability. This study highlights the potential of hop extract as a promising antimicrobial agent for oral treatment. It serves as a crucial first step towards further applications and paves the way for the development of new treatments in oral therapies.
Whole genome sequencing for tuberculosis disease species identification, lineage determination, and drug resistance detection in Kashgar prefecture, China
Authors: Liu Dongxin , Badeerhan Gulina , Emam Mawlanjan , Jiang Mengnan , Hong Geng , Xie Mengjiao , Liu Yang , Wang Xijiang , Wei Qiang
Published: July 2024

Background
We aimed to use whole genome sequencing (WGS) to determine species and lineage composition and drug resistant profile in a high tuberculosis (TB)-burden region of China.
Methods
We conducted WGS to 1791 acid-fast staining positive isolates and culture-positive isolates collected from Kashgar prefecture in 2020. Bioinformatic analysis was applied to confirm species, lineage and drug resistant mutations. The drug susceptibility testing were performed on confirmed Mycobacterium tuberculosis complex(MTBC) isolates. We determined the accuracy of WGS by comparing with phenotypes.
Results
95.03% (1702/1791) were identified MTBC, 3.18% (57/1791) were nontuberculous mycobacteria (NTM), 0.61% (11/1791) and 0.89%(16/1791) were Nocardia and Gordonia respectively, 4 were identified as mixed infection. MTBC were composed of lineage 2 (45.83%, 780/1702), lineage 3 (462/1702, 27.14%), lineage 4 (455/1702, 26.73%), lineage 1(1/1702, 0.06%) and M.bovis (La1, 4/1702, 0.24%). Resistance to rifampicin, ethambutol, fluoroquinolones, aminoglycosides and ethionamide were accurately predicted with sensitivity of 96.43%, 83.33%,100%, 100% and 94.74% by WGS, and resistance to isoniazid with the sensitivity of 81.62% .
Conclusions
WGS can be an important approach in assessing TB control strategy and for determining therapeutic schemes in high TB-burden regions. The drug resistant TB of Kashgar prefecture is at low level and the application of WGS may prevent the increase of resistance rate.
Molecular confirmation of ToLCNDV resistance in cucumber (Cucumis sativus L.) genotypes through agroinoculation and field screening
Authors: Elango Naveena , Venkatachalam Rajasree , Kanti Behara Tusar , Gandhi Karthikeyan , Murugavel Kavitha , Durai Rameshkumar
Published: July 2024

Research was carried out to identify the source of resistance in four cucumber genotypes for ToLCNDV under natural field epiphytotic and greenhouse conditions. Over all the mean percent disease index and incidence ranged from 0 to 92.00% and 0 to 93.3% respectively. Under natural field conditions, the genotype DC 70 was found to be totally free from ToLCNDV infection followed by P-85 with 8.57 PDI and 28.57% disease incidence while DC 773 recorded 75.00 PDI and 87.50% disease incidence and DC 769 with 42.85 PDI and 71.42% disease incidence in rabi season under field epiphytotic condition. Similarly, during the kharif season the genotype DC 70 and P-85 were found to be totally free from ToLCNDV infection while DC 773 recorded 65.71 PDI and 85.00% disease incidence and DC 769 with 40.00 PDI and 75.00% disease incidence. Based on natural field evaluation the selected entries were subjected to artificial screening under greenhouse conditions. DC 70 was totally free from ToLCNDV infection upon artificial screening by agroinoculation. This was followed by P-85 with 22.91 PDI and 46.60% disease incidence and DC 773 recorded 92.00 PDI and 93.3%disease incidence. Symptomatic and asymptomatic leaves were confirmed for the presence of ToLCNDV by PCR assay. Susceptible genotypes expressed leaf curling, yellowing and severe mosaic on 28 days post-inoculation. Out of four genotypes screened, DC 70 showed highly resistant reaction and identified as reliable source of resistance for ToLCNDV in cucumber. The resistant source identified is a good candidate for resistant breeding for ToLCNDV in cucumber.
Survival Analysis and Its Determinants among Patients with End Stage Renal Disease in Eastern Ethiopia: A Retrospective Cohort Study
Authors: Fiseha Getahun , Amsalu Alemneh , Molla Alemayehu , Hailu Mickiale
Published: July 2024

Background
End-stage renal disease is the last stage of chronic kidney disease. It is estimated that by 2030 more than 70% of patients with end-stage renal disease would be living in low-income countries. The aim of this study was to analyze the survival time and its determinants among patients with end stage renal disease in Eastern, Ethiopia.
Method
A retrospective cohort study design was employed to analyze the survival time and its determinants among 754 end stage renal disease patients with hemodialysis follow up between September 1/2015 and August 30/2020 in Eastern Ethiopia. Data was collected from patients chart using listing questionnaire by 10 data collectors and analyzed using STATA version 14. Frequency tables and Kaplan-Meier graphs were used to describe the characteristic of the data, while the Weibull regression model was employed at 5% levels of significance to assess association between the covariates and the survival time of end stage renal disease patients.
Result
Among 754 hemodialysis patients, 176(23.3%) were died. The overall median survival time of patients in the five year follow up period was 40.6[95%CI: 38.54, 43.8] months, with a mortality rate of 5.84 [95%CI: 5.04, 6.77] per 1000 person-months. In the Weibull regression model, urban area [HR = 6.61, 95%CI: 2.67, 16.36], being widowed [HR = 13.11, 95%CI:10.79, 16.09], having family history of RD [HR = 1.42, 95%CI: 1.02, 2.97] and using central venous catheters vascular access [HR = 2.52, 95%CI: 1.34, 4.34] were significantly associated with increased risk of death, while having follow up in Sheik Hassen hospital [HR = 0.48, 95%CI: 0.26, 0.58], three times dialysis per week [HR = 0.21, 95%CI: 0.09, 0.49], 4 dialysis hours per session [HR = 0.26, 95%CI: 0.11, 0.63], and higher Kt/v level [HR = 0.30, 95%CI: [0.11, 0.80] were significantly associated with lower risk of death.
Conclusion
The median survival time of patients was lower than other studies. AV fistula should be also adapted as dialysis modality.
The Therapeutic Potential of Chi Shao and Fu Zi in Acute-on-Chronic Liver Failure: Insights from Network Pharmacology and Animal Studies
Authors: Tian Xiaoling , Zhang Yu , Fu Qin , Chen Bin
Published: July 2024

Background & Aims
Acute-on-chronic liver failure (ACLF) has a high incidence and mortality rate, which has become an urgent clinical problem to be solved.Traditional Chinese medicine (TCM) has been widely applied in the clinical and experimental researches of ACLF. But its specific mechanism is not yet fully understood. This study attempted to identify the effective active ingredients, key targets, and biological mechanisms of Chinese herbal medicines Chi Shao (Paeoniae radix Rubra) and Fu Zi (Aconitum carmichaelii Debx) (CSFZ) for treating ACLF based on network pharmacology and animal experiments.
Methods & Results
Network pharmacology was performed to predicte the major components of CSFZ and potential signal pathways. Molecular docking method was applied to determine the binding affinity between the main components and the key targets. A rat model of ACLF was constructed. The liver injury were measured by histopathological methods. Biochemical indexes were used to evaluate liver function. ELISA was used to detect the IL-6, TNF-α, Caspase-3, BCL-2, ALB, and TB level. Also, PI3K/Akt signaling molecules were detected through RT-qPCR and WB. Immunofluorescence staining was used for PCNA and Cyclin B1. In the results we found that forty-nine potential active ingredients and 104 drug targets were screened from CSFZ, and 2730 genes were identified as ACLF targets, of which 72 overlapped with CSFZ targets. we identified ten key active ingredients of CSFZ. Moreover, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that CSFZ modulated ACLF may through numerous biological pathways, including antibacterial and anti-inflammatory mechanisms, cell proliferation, and apoptosis. Molecular docking verification shows that key components and core targets have good binding affinity. Also, through the vivo studies we found that CSFZ enhanced hepatic regeneration, improved hepatic structural damage, reduced hepatocyte apoptosis, and promoted the expression of PI3K and AKT.
Conclusions
Network pharmacology and in vivo experiments indicated that CSFZ may ameliorate hepatic injury by regulating the PI3k/Akt signaling pathway.
Bias compensation based recursive least squares identification algorithm for multivariable Hammerstein nonlinear systems
Authors: Lyu Bensheng , Wang Qiang , Xu Yanling , Zhang Huajun , Cai Chunbo
Published: July 2024

The multivariable Hammerstein nonlinear system contains the sum of bilinear parameters, which is not a regression form. By using the special properties of binary signals, we can transform the sum of bilinear parameter matrices into two different models, achieving the parameter separation for parallel nonlinear subsystems and a linear subsystem. In order to improve the accuracy of parameter identification, this paper uses a biased correction technique to compensate a biased recursive least squares estimates. Then, a bias compensation based recursive least squares algorithm is proposed to separately identify the parameters of a linear subsystem and parallel nonlinear systems. The numerical simulation indicate that the proposed algorithm has a higher accuracy than recursive least squares and over-parametrization based identification algorithms. The multivariate Hammerstein nonlinear system is implemented on a case study from the process industry namely the continuous stirred tank reactor. The accuracy of the prediction is improved by a biased correction term.
Efficient Crowd Density Estimation: Fusion of Faster CNN and Vision Transformer
Authors: Kushwaha Hemant , Gupta Sanjai Kumar
Published: July 2024

Accurate crowd density estimation in densely populated areas is essential for applications such as urban planning, security, and event management. Traditional methods often fall short in terms of accuracy and efficiency, especially when handling large datasets and real-time demands. This study introduces an efficient approach to crowd density estimation by integrating a rapid Convolutional Neural Network (CNN) with a Vision Transformer (ViT) architecture.Our method capitalizes on the strengths of both models to achieve enhanced performance. The fast CNN effectively captures local features and spatial details, while the Vision Transformer excels at identifying long-range dependencies and global context. By fusing these models, we create a synergistic effect that significantly improves crowd density estimation accuracy.We validate our approach through experiments on several benchmark datasets, covering both indoor and outdoor scenes with varying crowd densities. The results indicate that our method surpasses existing techniques in terms of accuracy while also maintaining high computational efficiency. We further demonstrate the scalability of our approach by testing its performance on large-scale datasets, confirming its suitability for real-world applications. Additionally, we explore the interpretability of the fused model, showing how the combination of CNN and Vision Transformer features enhances crowd density estimation. In summary, our proposed fusion method offers a promising solution for efficient and accurate crowd density estimation, with broad implications for practical applications in crowd analysis and management.
Synthesis of novel 4-substituted isatin Schiff base derivatives as potential autophagy inducers and evaluation of their antitumour activity
Authors: Tan Huayuan , Zhang Guanglong , Xu Chenlu , Lei Xue , Chen Jiayi , Long Haitao , Qiu Xuemei , Wang Wenhang , Zhou Yue , Chen Danping , Li Chengpeng , Li Zhurui , Wang Zhenchao
Published: July 2024

Autophagy is a potential target in cancer therapy. In the present study, we designed and synthesized a series of isatin Schiff base derivatives containing thioether structures. After discovering the highly active target compound H13 (IC50 = 4.83 μM) based on in vitro antiproliferation, we also found it had a high safety against normal cells HEK293 with CC50 of 69.01 μM. In addition, to provide reference for subsequent studies, a model was successfully constructed by Sybyl software. Preliminary mechanistic studies suggested that H13-induced apoptosis may be closely related to ROS accumulation and mitochondrial dysfunction. Subsequent studies revealed that H13 inhibited cell proliferation by inducing cellular autophagy mainly through blocking signal of the PI3K/AKT/mTOR pathway. Altogether, these results suggested that H13 was potentially valuable as a lead compound.
A Contributing Factor and Characteristics of High 210Po Activity in Aerosols at Hanoi, Vietnam
Authors: Pham-Thi Thanh-Xuan , Trung Tien Chu , Hegedűs Miklós , Kovac Tibor , Ngo Thi Thuy Huong , Duong Van-Hao
Published: July 2024

Air pollution in crowded cities has become an urgent issue in recent years. The high toxic 210Po activity and trace heavy elements’ content in 24 aerosol samples in Hanoi, Vietnam were determined at roadside and residential areas. 210Po activity in the studied aerosol samples was observed with a wide range (from 92.2 to 3500 µBq.m− 3 and 1395 µBq.m− 3 on average) and relatively high activities in roadside samples in comparison with the worldwide reference value. The results showed the predominance of the earth's crustal and fuel-combusting elements relating to traffic activities, the lower elements concentration origin from other combusting sources, the large Ni excess, the strong relationship between 210Po and Ni, the high ratio of Ni/Pb and the far greater 210Po activities in the roadside in comparison with residential aerosol samples at the study area. A suggestion, the main primary sources and a factor contributing to high 210Po activity in Hanoi aerosol samples are human activity relating to fuel combustion, high traffic density, and local sources.
Odor prediction of whiskies based on their molecular composition
Authors: Singh* Satnam , Schicker* Doris , Haug Helen , Sauerwald Tilman , Grasskamp Andreas T.
Published: July 2024

Aroma compositions are usually complex mixtures of odor-active compounds exhibiting diverse molecular-structure. Due to the chemical interactions of the compounds in the olfactory system, assessing or even predicting the olfactory quality of such mixtures is a difficult problem, not only for statistical models, but even for trained assessors. Here, we combine fast automated analytical assessment tools with human sensory data of 11 trained panelists and machine learning algorithms. Using 16 previously analyzed whisky samples (American or Scotch origin), we use the linear classifier OWSum to distinguish the samples based on their detected molecules and to gain insights into the key molecular structure characteristics and odor descriptors for sample type. Moreover, we use OWSum and a Convolutional Neural Network (CNN) architecture to classify the five most relevant odor attributes of each sample and predict their sensory scores with promising accuracies (up to F1: 0.66, MCC: 0.65, ROCAUC: 0.76). The predictions outperform the panel and thus demonstrate previously impossible data-driven sensory assessment in mixtures.

*Satnam Singh and Doris Schicker contributed equally to the work and are shared first authors.
Gas-Fueled Non-Equilibrium Co-Assembly via C1 Catalytic Feedback for Gas-Encoded 4D Information Encryption
Authors: YAN Qiang , Zhang Yulian , Yang Cuiqin , Liang Xin , Xiang Jun
Published: July 2024

Dissipative self-assembly, which exploits energy inputs of chemical fuels to maintain the functional states far from equilibrium, is essential to the living systems. Among a variety of fuels, carbon dioxide (CO2) gas, as one of the most ubiquitous but original forms of fuel on which life depends, has yet been introduced in artificial dissipative materials. Here we describe a CO2-fueled non-equilibrium co-assembly system that couples with a C1 catalytic feedback path to drive fuel dissipation and function output. Using common frustrated Lewis pair (FLP) as precursors, CO2 can dynamically bridge between them to constitute metastable amphiphiles, which not only highly activate CO2 but also enable their co-assembly with substrates into a transient fibrillar gel. In turn, the feedback process is realized by cooperative C1 catalytic insertion owing to the proximity of substrate and activated CO2 species in the assembled state. This can boost the depletion of gas fuel and facilitate disassembly to sol. Moreover, tailoring the intrinsic substrate/FLP chemistries, as well as external cues, to shift the catalytic activity is accessible to regulate the period and lifetime of sol-gel-sol transition over a wide range. Based on the tunability in phase transition on a time scale, we develop time-dependent information encryption materials using the transient FLP array loaded gas-encoded substrates, and the correct information can be read only at a specified time window. This study provides inspiration on a new fuel paradigm for dissipative system and their intelligent material applications.
Management of Pneumonia
Authors: Rankoussi Dima , Naser Noor , Bardan Housam
Published: July 2024

Background: The primary treatment for pneumonia is timely administration of antibiotics, so it is important to highlight the treatments used in Damascus Hospital in order to improve survival, morbidity, duration of hospitalization, and bacterial resistance.
Methods and materials: A prospective, retrospective study in which 100 patients with a primary diagnosis of community or hospital-acquired pneumonia, aged over 18 years, were studied during the period 1/22/2023 to 1/22/2024. The data were analyzed using the SPSS-26 program.
Results: The average age of the patients was 56.75±19.175 years, the most common age group was 60-74 years, males were 56%, and females were 44%. We found that community-acquired pneumonia was more common than nosocomial pneumonia, and the most common comorbid condition was type 2 diabetes, 7%. The most common symptoms and signs observed are respiratory depression 87%, cough 84%, general symptoms 83%, phlegm 73%, fever 56%, the most common radiological manifestation is multi-lobular density 45%, diffuse bilateral infiltrates 40%, and unilateral density 37%. The most common therapeutic protocols for all patients (intravenous ceftriaxone plus and oral levofloxacin), 41%, followed by oral levofloxacin, oral clindamycin, and intravenous ceftriaxone, 17%, and oral levofloxacin and intravenous vancomycin, 16%. Additional treatments included mucolytics, antipyretics, anticoagulants, and steroids.
Conclusion: Regarding empiric antibiotic therapy for pneumonia, the use of ceftriaxone could be reduced, broad-spectrum antibiotics could be administered more carefully to prevent resistance, and potential indications for systemic corticosteroid administration in patients with pneumonia should be documented more carefully.
Agro-industrial by-products as a feeding strategy for producing functional milk
Authors: Abd El-Maksoud A. A. , Radwan M. A. , Rahmy H. A.F. , Elshaghabee F. M.F. , Hamed A. M.
Published: July 2024

Agro-industrial by-products contain valuable components such as polyphenols that can play a significant role in producing milk with specific properties through rumen fermentation. In Egypt, the buffalo milk chain has a potential market, which is larger than that for cow milk, especially in small villages. Therefore, this study aims to explore different feed ingredients from agro-waste for enhancing the functional properties of raw buffalo milk including polyphenols, flavonoids, vitamins A, C, α-tocopherol, and conjugated linoleic acid (CLA) contents. For this purpose, thirty dairy water buffalo (Bubalus bubalis) with a weight of about 520 kg were randomly divided into five groups of six animals each. The first group was fed a basal diet (silage) without agro-waste, while the other four groups were fed the basal diet after replacing 25% of the diet with different agro-wastes including barley (snack/bakery waste), sweet potato/carrot, biscuit/cake waste and tomato pomace. The feeding experimental period lasted 90 days, then milk samples (n = 150) were collected. Our results show that adding sweet potato/ carrot or tomato pomace to the basal diet enhanced the contents of vitamins A, C, and phenolic compounds reflecting on the enhancement of the antioxidant capacity of raw buffalo milk. Concerning the CLA content, the milk samples collected from buffalo fed the basal diet fortified with tomato pomace and biscuit/cake waste had the highest CLA and α-tocopherol content. Therefore, this study recommends using the tested agro-waste ingredients for producing functional buffalo milk, especially for small-medium milk producers.
Molecular peptide grafting as a tool for creating new generation of biopeptides: A mini-review
Authors: Chernukha I. M. , Tikhonov S. L. , Tikhonova N. V.
Published: July 2024

Molecular peptide grafting (MPG) is the isolation/synthesis of a bioactive fragment of a peptide/protein and its subsequent transfer to a target protein/peptide to create a new protein product with specified unique biological properties. This is one of the methods together with molecular stapling and peptide backbone circularization to strengthen the structural organization of short peptides. Nowadays research on MPT is mainly focused on demonstrating its usefulness and applicability, rather than on the development of next-generation biopeptides. The purpose of the mini-review is to demonstrate the applicability of MPT to create stable and bioavailable peptides of a new generation with enhanced biological properties. Choosing the right scaffold for subsequent inoculation of a biologically active peptide sequence into it is the most important task in creating targeted biopeptides. Peptides with the necessary framework, such as cyclotides, can be obtained by three-phase synthesis. Cyclotides have a common mechanism of action. Their biological activity is determined both by the ability to bind proteins with the formation of pores and destruction of biological target-membranes, and by the properties necessary to create new peptides in the scaffold. Various peptide inserts can be used to ensure the functionality of new biopeptides obtained by the MPT method. Different peptide drugs are an example of the effective practical use of MTP. Consequently, MPT makes it possible to effectively design a new generation of biopeptides characterized by high epitope thermodynamic and metabolic stability with new or enhanced biological functions. However, the effectiveness of the peptides obtained by the MPT must be proved in vitro and in vivo.
Iodine deficiency in Russia: Current state of the problem, global practice and new approaches to therapy
Authors: Barkovskaya I. A. , Kruchinin A. G. , Rozhkova I. V.
Published: July 2024

Iodine performs a number of important functions in the body, participating in the synthesis of thyroid hormones, which creates the need for constant replenishment of the element in adequate amounts. Continuous monitoring of micronutrient deficiency in the Russian Federation reveals low average daily iodine intake and an increase in the number of cases of thyroid diseases in the period from 2010 to 2020. This actualizes the need to develop new therapeutic and preventive approaches to replenish iodine deficiency. The aim of the review is to analyze the problem of iodine deficiency in Russia and existing practices of its leveling in order to develop a new approach to the prevention and treatment of iodine deficiency conditions. The sample includes publications in Russian and English in the period from 2002 to 2023, using the resources of scientific metric databases Elibrary, Google Scholar, CyberLeninka, PubMed and ScienceDirect. The research work showed that the common practice of eliminating iodine deficiency is to increase the level of consumption of the trace element in the diet, the consequence of which is the availability of a wide range of iodized food supplements and products on the market. However, the analysis of the current functional nutrition sector has revealed a number of drawbacks associated with low bioavailability of the element and its resistance to technological factors in the production of food products. The article presents the key factors influencing the effectiveness of nutritional supplements being developed for nutritional correction of iodine deficiency. They are based on the evaluation of existing means of prevention. The study proposes the development of the technology of whey hydrolysates enriched with iodine and zinc. Application in food production of a food additive based on protein components of milk whey opens new opportunities for processing of secondary dairy raw materials and for full utilization of all milk components. The rich amino acid composition of the additive helps to increase the concentration of essential trace elements in products, as amino acid residues are able to bind iodine and chelate zinc.