bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anti-cancer drug-induced mitochondrial alteration becomes a limitation of metabolic viability-based MTT assay in analyzing growth inhibition
Authors: Kumar Abhishek , Rai Yogesh , Bhatt Anant Narayan 
Published: September 2023

Abstract
Background
High throughput metabolic viability-based colorimetric MTT assay is widely used for cytotoxicity screening of various chemical compounds, anti-neoplastic drugs, and other chemotherapeutic agents. The yellow MTT tetrazolium salt reduces to purple formazan crystals, predominantly by mitochondrial dehydrogenases. The assay assumes all cells have a similar number of mitochondria with equivalent enzymatic activity, resulting in a linear relationship between colorimetric absorbance and cell number.
Method
Our present study involved the Cisplatin, Etoposide, and Doxorubicin-induced cytotoxicity evaluation using MTT and cell number enumeration in two widely used cancer cell lines, namely human lung epithelial adenocarcinoma cells (A549) and cervix carcinoma (HeLa). Further, Mitochondrial mass was examined to comment on the treatment-induced change in metabolic viability-based MTT assay.
Results
Drug-induced cell death determined by enumeration of the cell number did not correlate with growth inhibition observed by the MTT assay. Increased protein levels of majorly MTT converting enzyme SDH in both the cell lines following drug treatment were observed. The mitochondrial protein content of the cells was also found to be elevated in response to drug-induced cytotoxic stress.
Conclusion
In line with our earlier observation about the limitation of MTT assay in estimating radiation-induced cytotoxicity, it was found that certain anti-neoplastic drugs also modulate mitochondrial biogenesis and SDH expression level and enzymatic activity. Therefore, caution should be taken in applying the MTT assay to analyze drug-induced growth inhibition.
General significance:
Our findings reveal the MTT assay's limitations, which should be considered when determining anti-cancer and chemotherapeutic drugs' pre-clinical cytotoxicity and IC-50.
Butyricimonas is a key gut microbiome component for predicting postoperative recurrence of esophageal cancer
Authors: Otsuka Koji , Isobe Junya , Asai Yoshiyuki , Nakano Tomohisa , Hattori Kouya , Ariyoshi Tomotake , Yamashita Takeshi , Motegi Kentaro , Saito Akira , Kohmoto Masahiro , Hosonuma Masahiro , Kuramasu Atsuo , Baba Yuta , Murayama Masakazu , Narikawa Yoichiro , Toyoda Hitoshi , Funayama Eiji , Tajima Kohei , Shida Midori , Hirasawa Yuya , Tsurui Toshimitsu , Ariizumi Hirotsugu , Ishiguro Tomoyuki , Suzuki Risako , Ohkuma Ryotaro , Kubota Yutaro , Sambe Takehiko , Tsuji Mayumi , Wada Satoshi , Kiuchi Yuji , Kobayashi Shinichi , Horiike Atsushi , Goto Satoru , Murakami Masahiko , Kim Yun-Gi , Tsunoda Takuya , Yoshimura Kiyoshi 
Published: September 2023

Abstract
Background: Recently, intestinal bacteria have attracted attention as factors affecting the prognosis of patients with cancer. However, the intestinal microbiome is composed of several hundred types of bacteria, necessitating the development of an analytical method that can allow the use of this information as a highly accurate biomarker. In this study, we investigated whether the preoperative intestinal bacterial profile in patients with esophageal cancer who underwent surgery after preoperative chemotherapy could be used as biomarkers of postoperative esophageal cancer recurrence.
Methods:We analyzed the gut microbiome of the patients by utilizing 16SrRNA metagenome analysis, followed by statistical analysis. Simultaneously, we conducted a machine learning analysis using a random forest model with hyperparameter tuning and compared the data obtained.
Results: Statistical analysis and machine learning analysis identified two common bacterial genera, Butyricimonas and Actinomyces, which were prevalent in cases with recurrent esophageal cancer. Butyricimonasprimarily produces butyrate, while Actinomycesare oral bacteria whose function in the gut is unknown.
Conclusion: Our results indicate that Butyricimonas spp. may be a biomarker of postoperative esophageal cancer recurrence. Although the extent of the involvement of these bacteria in immune regulation remains unknown, future research should also investigate their presence in other pathological conditions. Such research could potentially lead to a better understanding of their immunological impact on patients with cancer and their applications as biomarkers.
Comparison of logistic regression with regularized machine learning methods for the prediction of tuberculosis disease in people living with HIV: cross-sectional hospital- based study in Kisumu County, Kenya
Authors: orwa James , Oduor Patience , Okelloh Douglas , Gethi Dickson , Agaya Janet , Okumu Albert , Wandiga Steve 
Published: September 2023

Abstract

Background
Tuberculosis (TB) is a major public health concern, particularly among people living with the Human immunodeficiency Virus (PLWH). Accurate prediction of TB disease in this population is crucial for early diagnosis and effective treatment. Logistic regression and regularized machine learning methods have been used to predict TB, but their comparative performance in HIV patients remains unclear. The study aims to compare the predictive performance of logistic regression with that of regularized machine learning methods for TB disease in HIV patients.
Methods
Retrospective analysis of data from HIV patients diagnosed with TB in three hospitals in Kisumu County (JOOTRH, Kisumu sub-county hospital, Lumumba health center) between [dates]. Logistic regression, Lasso, Ridge, Elastic net regression were used to develop predictive models for TB disease. Model performance was evaluated using accuracy, and area under the receiver operating characteristic curve (AUC-ROC).
Results
Of the 927 PLWH included in the study, 107 (12.6%) were diagnosed with TB. Being in WHO disease stage III/IV (aOR: 7.13; 95%CI: 3.86–13.33) and having a cough in the last 4 weeks (aOR: 2.34;95%CI: 1.43–3.89) were significant associated with the TB. Logistic regression achieved accuracy of 0.868, and AUC-ROC of 0.744. Elastic net regression also showed good predictive performance with accuracy, and AUC-ROC values of 0.874 and 0.762, respectively.
Conclusions
Our results suggest that logistic regression, Lasso, Ridge regression, and Elastic net can all be effective methods for predicting TB disease in HIV patients. These findings may have important implications for the development of accurate and reliable models for TB prediction in HIV patients.
Reliability and Validity of a Graphical Computerized Adaptive Test Longshi Scale for Rapid Assessment of Activities of Daily Living in Stroke Survivors
Authors: Zhou Jing , Zha Fubing , Liu Fang , Wan Li , Zhou Mingchao , Long Jianjun , Chen Miaoling , Xue Kaiwen , Wang Yulong 
Published: September 2023

Abstract
Background
Stroke survivors frequently experience difficulties in daily activities, such as bathing, feeding, and mobility. This study aimed to evaluate the reliability and validity of a computer-adaptive test-Longshi scale (CAT-LS) for assessing activities of daily living (ADL) in stroke survivors.
Methods
This cross-sectional study collected data using an electronic application. The ADL function of stroke survivors in rehabilitation departments of hospitals was assessed using both the CAT-LS and BI. Correlations between the CAT-LS and Barthel Index (BI) and concurrent validity were evaluated using Pearson’s correlation test and multiple linear regression. Interrater reliability was evaluated using the intraclass correlation coefficient based on a two-way random effect. The internal consistency of the CAT-LS was assessed using Cronbach’s coefficient (α) and corrected item-total correlations.
Results
Overall, 103 medical institutions in China were used in this study. In total, 7,151 patients with stroke were included in this study. The CAT-LS classified patients into three ADL groups (bedridden, domestic, and community) with significantly different BI scores (P < 0.05). The CAT-LS results obtained using the decision-tree scoring model were consistent with the scores for each BI item. A strong correlation was observed between CAT-LS and BI (Pearson’s r: 0.6–0.894, P < 0.001). The CAT-LS demonstrated good internal consistency (Cronbach’s α, 0.803–0.894) and interrater reliability (ICC, 0.928–0.979). CAT-LS is time-efficient and requires < 1 min to administer.
Conclusion
The CAT-LS is a reliable and valid tool for assessing ADL function in stroke survivors and can provide rapid and accurate assessments that reduce the burden on healthcare professionals. Further validation of this tool in other populations and settings is necessary.
Study registration number
No.: ChiCTR2000034067
http://www.chictr.org.cn/showproj.aspx?proj=54770
Extreme rainfall and landslides as a response to human-induced climate change: a case study at Baixada Santista, Brazil, 2020
Authors: de Souza Danilo Couto , Crespo Natália Machado , Silva Douglas Vieira da , Harada Lila Mina , de Godoy Renan Muinos Parrode , Domingues Leonardo Moreno , Luiz Rafael , Bortolozo Cassiano Antonio , Metodiev Daniel , de Andrade Marcio Roberto Magalhães , Hartley Andrew J. , de Abreu Rafael Cesário , Li Sihan , Lott Fraser C. , Sparrow Sarah 
Published: September 2023

Abstract

In March 2020, an extreme rainfall in Baixada Santista, Brazil, led to a series of landslides affecting more than 2,800 people and resulting losses exceeding USD 43 million. This attribution study compared extreme rainfall in two distinct runs from the UK Met Office Hadley Centre HadGEM3-GA6 model: one with all forcings and the other with natural forcings only, considering antecedent conditions and soil moisture (extreme 60-day rainfall, Rx60day) and heavy rainfall (extreme 3-day rainfall, Rx3day) which may trigger landslides. The long-term set-up became 74% more likely, while the short-term trigger was 46% more likely. The anthropogenic contribution to changes in rainfall accounted for 20-42% of the total losses and damages. The greatest economic losses occurred in Guarujá (42%), followed by São Vicente (30%) and Santos (28%). Landslides were responsible for 47% of homes damaged, 85% of homes destroyed, all reported injuries, and 51% of deaths associated with heavy rainfall. Changes in land cover and increased urbanization showed a pronounced increase in urbanized area in Guarujá (107%), São Vicente (61.7%) and Santos (36.9%) and a reduction in farming area. Population growth estimates also indicate higher exposure to extreme rainfall events. The proportion of irregular and/or precarious housing indicates vulnerability, with Guarujá being the municipality with the highest number (34.8%) of dwellings of this type. Our estimates suggest that extreme precipitation events are having shorter return periods due to climate change and increased urbanization and population growth is exposing more people to these events. These findings are especially important for decision-makers in the context of disaster risk reduction and mitigation and adaptation to climate change.
The Relationship Between Physical Exercise Behavior and Psychological Resilience of Teenagers: An Analysis of Chain Mediating Effect
Authors: Li Na , Wang Dianguo , Zhao Xiang , Li Zhen 
Published: September 2023

Abstract
Objective This study aimed to understanding the mechanisms underlying the association between physical exercise behavior and psychological resilience among teenagers,and the mediating role of social sensitivity and need to belong.
Methods Using the method of cluster sampling, 1106 students (average age=15.7, SD=0.598) that complied with the requirements were surveyed from Shandong Province in China. Physical Exercise Behavior, Psychological Resilience, Social Sensitivity and Need to Belong were assessed using standard scales. For data analysis, Pearson’s correlation analysis and bias-corrected percentile Bootstrap method were carried out in turn.
Results（1）Common method deviation can be accepted in this study,and the correlation among physical exercise behavior, psychological resilience, social sensitivity and need to belong are all significant; (2)Based on the self-determination theory to explain the relationship between teenagers physical exercise behavior and psychological resilience, the following conclusions are drawn:physical exercise behavior can directly and positively predict need to belong and psychological resilience, negatively predict social sensitivity. Likewise, social sensitivity can negatively predict need to belong and psychological resilience, need to belong can directly and positively predict psychological resilience; (3)The indirect effect of the path with social sensitivity as the mediating variable is 0.009,the indirect effect of the path with need to belong as the mediating variable is 0.033, and the indirect effect of the path with social sensitivity and need to belong as the mediating variable is 0.014.(4)The total of all indirect effects is 0.056.
Conclusion（1）Physical exercise behavior can significantly positively predict psychological resilience. （2）Social sensitivity and need to belong play a significant mediating role between physical exercise behavior and psychological resilience.（3）There are three mediating paths, namely, the separate mediating effect of social sensitivity, the separate mediating effect of need to belong, and the chain mediating effect of social sensitivity and need to belong.
Effects of the Menstrual Cycle on the Prevalence of Musculoskeletal Injuries Amongst Female Athletes
Authors: Christina Christina Sefotha , Caitlin Caitlin Beckett , Simoné Simoné Ferreira , Lynn Lynn Smith 
Published: September 2023

Abstract
Background: During the menstrual cycle (MC), neuromuscular performance varies among female athletes, and MC has been identified as an intrinsic risk factor for the development of musculoskeletal injuries. However, limited studies that demonstrate the extent to which the MC influences injury risk. Previous literature regarding the topic has focused mostly on the impact of the MC on overall sports performance among female athletes, as opposed to its impact on injury risk specifically. Therefore, the aim of this study was to establish the effects of MC on injury prevalence and risk among female athletes competing at the university level.
Methods: An online questionnaire was distributed to seventy-six female athletes competing at various levels in different sporting codes at the University of Johannesburg over a period of 3 months. Data were analysed quantitatively using the Statistical Package of Social Sciences (SPSS, version 28)
Results: Ankle and wrist sprains (32%) and muscle strain (18%) injuries were found to be the most common types of musculoskeletal injuries. Participants with early and/or late menarche had a greater prevalence of ligament sprains and dislocations. Participants with MC lengths of 24 to 26 days and 27 to 29 days reported a greater occurrence of ligament sprains (41% & 47%) and muscle strains (14% & 24%), whereas ligament sprains (25%) and dislocations (19%) were common among participants with MC lengths of 30 to 35 days.
Conclusion: The findings showed that the most common injuries among female athletes included ligament sprains, dislocations and muscle strains. This highlights the importance of training modification throughout the MC. This study helps broaden the knowledge of female athletes and the sports industry on the effects of the MC on injury occurrence and functionality of the female body.
A Survey of Big Data Tools for Remote Healthcare Services
Authors: Ray Himadri Sekhar , Mainuddin Md , Singha Susmita , Mukherjee Nandini 
Published: September 2023

Abstract
Health Data storage and analytics are the two important parts of the health or drugs business and health research. Health Data storage and management are important for storing and retrieving Health Data efficiently. The scalable and flexible infrastructure capable of efficient storing and processing the millions of Health Data generated every day must be very much needed for the industry. Big Data tools and NoSQL databases are becoming the necessary tools to store millions of data and respond to given queries efficiently. In general relational databases are used for many applications, but they are not at all efficient for storing and processing Big Data. The drawbacks of relational databases motivate the developers to use NoSQL databases and Big Data tools while creating the Health application. A comparative study must be made to find out the performance of different Big Data platforms along with the NoSQL Databases to store Health Data for a Health-related application and to respond to queries efficiently. In this paper, we have tested the performance of Hadoop, HIVE, Cassandra, MongoDB, HBASE and NGMR to respond to different queries to store Health Data for a remote health framework. Such a study helps us to come up with new ideas that can help us to store and retrieve the Health Data of a particular application using a data model that is iteratively tested and modified. It provides us with an understanding of the Big Data solution or tool as well. The key aim of the study is to make a review on the capability of data storage and the read/write performance of the tools
A New Analytical Approach to First Kind Volterra Integral Equations
Authors: Hussein Mohammed , jassim hassan , Elzaki Tarig , Almusawa Musawa , Ahmad Hijaz 
Published: September 2023

Abstract
A significant group of mathematical issues known as Volterra integral equations appear in numerous scientific and engineering applications. These equations are inherently nonlinear and complicated, making analytical solution difficult. In order to solve Volterra integral equations of the first class, a novel analytical technique known as the Hussein Jassim Method (HJ-method) is presented in this research work. The Volterra integral equations are introduced mathematically in the first section of the study, which also emphasizes their importance in simulating real-world processes. The novel method’s algorithm is then described, followed by an analysis. We also research the novel method’s convergence characteristics and the circumstances under which it produces trustworthy results. We provide a number of Volterra integral equation examples to show the potency of this approach.
In the end, the new method has proven to be effective and efficient in solving first-kind Volterra integral equations. The method has produced satisfactory results, with the obtained solution closely approximating the exact solution. These findings indicate the capability of this method to address the mathematical and technical challenges associated with solving Volterra integral equations. This also makes it possible to use the new technique in other relevant practical contexts.
Passive frequency comb generation at radiofrequency for ranging applications
Authors: Cassella Cristian , Hussein Hussein , Kim Seunghwi , Rinaldi Matteo , Alu Andrea 
Published: September 2023

Abstract
Optical frequency combs, featuring evenly spaced spectral lines, have been extensively studied and applied to metrology, signal processing, and sensing. Recently, frequency comb generation has been also extended to MHz frequencies by harnessing nonlinearities in microelectromechanical membranes. However, the generation of frequency combs at radio frequencies (RF) has been less explored, together with their potential application in wireless technologies. In this work, we demonstrate an RF system able to wirelessly and passively generate frequency combs. This circuit, which we name quasi-harmonic tag (qHT), offers a battery-free solution for far-field ranging of unmanned vehicles (UVs) in GPS-denied settings, and it enables a strong immunity to multipath interference, providing better accuracy than other RF approaches to far-field ranging. Here, we discuss the principle of operation, design, implementation, and performance of qHTs used to remotely measure the azimuthal distance of a UV flying in an uncontrolled electromagnetic environment. We show that qHTs can wirelessly generate frequency combs with μWatt-level of incident power by leveraging the nonlinear interaction between an RF parametric oscillator and a high quality factor piezoelectric microacoustic resonator. Our technique for frequency comb generation opens new avenues for a wide range of RF applications beyond ranging, including timing, computing and sensing.
Beyond a deterministic representation of the temperature dependence of soil CO2 efflux
Authors: Vargas Rodrigo , Le Van Huong 
Published: September 2023

Abstract
Soil CO2 efflux involves complex biological and physical processes that contribute to the production and transport of CO2 from soils to the atmosphere. Temperature is widely used in deterministic empirical models, but these approaches cannot fully capture the complexity of the temperature-soil CO2 efflux relationship due to environmental drivers' confounding and interacting effects beyond temperature. We introduce the Bernstein copula-based cosimulation (BCC) as a data-driven probabilistic approach for modeling the temperature-soil CO2 efflux relationship. The BCC considers the joint probability distribution and temporal dependence of soil CO2 efflux, often ignored in deterministic models. Our results show that this probabilistic approach accurately reproduced the original probability distribution, temporal dependency, and temperature-soil CO2 efflux relationship. We propose that probabilistic approaches hold promise for accurately representing dependency relationships for modeling soil CO2 efflux across various environmental conditions and predicting the effects of climate change.
Experimental Infection Of Aquatic Bird Bornavirus 1 (ABBV-1) In Canada Geese (Branta canadensis)
Authors: Ampuero Fernanda , Leacy Alexander , Pham Phuc H. , Che Sunoh , Tuling Jaime , El-khoury Antonius , Nagy Eva , Jardine Claire , Delnatte Pauline , Lillie Brandon , Susta Leonardo 
Published: September 2023

Abstract
Aquatic bird bornavirus 1 (ABBV-1) has a high prevalence of infection in certain North American populations of Canada geese (Branta canadensis), suggesting a possible role of these birds as an ABBV-1 reservoir. The goal of this study was to evaluate the ability of Canada geese to become experimentally infected with ABBV-1, develop lesions, and transmit the virus to conspecifics. One-week-old Canada geese (n, 65) were inoculated with ABBV-1 through the intramuscular (IM) or cloacal (CL) routes, with the control group receiving carrier only. An additional 6 geese were added to each group to test horizontal transmission (sentinel birds). Geese were monitored daily, and selected birds were euthanized at 1, 8, and 15-weeks post infection (wpi) to assess virus replication in tissues and lesion development. At 15 wpi, over 70% of IM birds were infected, while the CL route yielded only 1 infected goose. Of the infected IM geese, 26% developed encephalitis and/or myelitis after 8 wpi. No clinical signs were observed, and no sentinel birds became infected in any group. Only 1 oropharyngeal swab (IM group) tested positive for ABBV-1 RNA, while the water from the enclosures was consistently negative for virus RNA. This study documents successful experimental infection of Canada geese with ABBV-1, with findings comparable to what is described in infection trials with other waterfowl species. However, minimal shedding and lack of environmental dispersal indicate that Canada geese have little potential to disseminate the virus among wild waterfowl, and that other species could be better suited to act as chronic ABBV-1 shedders in the wild.