bluuebunny/crossref_metadata_2025 huggingface dataset:
Associations between repetitive head impact exposure and midlife mental health wellbeing in former amateur athletes
Authors: Buddenbaum Claire V. , Recht Grace O. , Rodriguez Adriana K. , Newman Sharlene D. , Kawata Keisuke
Published: May 2024

Introduction

Repetitive head impacts (RHI) have been suggested to increase the risk of developing a neurodegenerative disease, and many of these individuals develop a preceding mental health diagnosis. Given the lack of studies among amateur athletes, this study aimed to examine mental health outcomes in middle-aged amateur athletes who have been exposed to RHI through contact sport participation.

Methods

This is a single site, cohort study involving former amateur athletes aged between 30 and 60 with at least 10 years of organized contact or non-contact sport participation. All participants completed demographic and mental health questionnaires. Mental health outcomes included symptoms related to depression, anxiety, post-traumatic stress disorder (PTSD), attention deficit hyperactive disorder (ADHD), and aggression. Self-reported data on mental health diagnoses and associated prescription were elicited and used to estimate odds ratios (OR).

Results

Data from 41 contact athletes and 22 age/sex-matched non-contact athletes were available for analysis. The contact group exhibited a 2.25-fold higher likelihood of being diagnosed with mental health disorders and 1.29-fold higher likelihood of using associated medications compared to the non-contact group. The contact group reported significantly higher PTSD-related symptoms [4.61 (0.03,9.2), p=0.05] compared to the non-contact control group. While not statistically significant, the contact group showed increased depressive [2.37 (0.05, 4.79), p=0.07] and ADHD symptoms [4.53 (0.51, 9.57), p=0.08] compared to controls. In a secondary analysis, a distinct trend emerged within the contact group, revealing pronounced elevations in mental health symptoms among individuals with lower socioeconomic status (<$50,000/year) compared to higher income subgroups, and these symptoms decreased as income levels rose [depression: -3.08 (-4.47, -1.7), p<0.001; anxiety: -1.95 (-3.15, -0.76), p=0.002; ADHD: -4.99 (-8.28, -1.69), p=0.004; PTSD: -4.42 (-7.28, -1.57), p=0.003; aggression: -6.19 (-11.02, -1.36), p=0.01]. This trend was absent in the non-contact control group.

Discussion

Our data suggest that even individuals at the amateur level of contact sports have an increased likelihood of being diagnosed with mental health disorders or experiencing mental health symptoms compared to non-contact athletes. Our findings indicate that socioeconomic status may have an interactive effect on individuals’ mental health, particularly among those with a long history of RHI exposure.
The impact of internet use on adolescents’ health: empirical evidence from China
Authors: Du Nianyu , Liu Lele , Zhang Lianpan , Yin Shijiu
Published: May 2024

Background

With the continuous improvement in economic levels in various countries and the rapid development of the Internet, adolescents’ Internet use has become increasingly frequent. Many studies have explored the relationship between Internet use and adolescent health, but the possible mechanisms involved are unclear, and few have focused on Chinese adolescents.

Methods

Based on the data from the China Family Panel Studies 2010, 2014, 2016, 2018, and 2020, this study used the ordered probit model and OLS model to explore the impact of Internet use on self-rated health and mental health of Chinese adolescents and analyzed the possible mechanisms and heterogeneity involved.

Results

The results revealed that adolescents’ Internet use negatively affected their physical and mental health. Parent-child conflict, academic performance, and self-efficacy were the important mechanisms of internet use affecting adolescents’ health. Moreover, the negative effects of Internet use on adolescents’ physical and mental health were heterogeneous in boarding, mother’s education level, and family per capita income.

Conclusion

Adolescents exhibit a pattern of using the internet that influences their health status. Our finding that internet use may decrease adolescents’ health provides important insights into understanding the relationship between internet use behavior and adolescents’ health and suggests that intervention should be taken on adolescents’ internet use.
Predictors of health-related quality of life in a large cohort of adult patients living with sickle cell disease in France: the DREPAtient study
Authors: Yaya Issifou , Pourageaud Adrien , Derbez Benjamin , Odièvre Marie-Hélène , Oudin Doglioni Damien , Podevin Marieke , Thomas Gaëlle , Yombo-Kokule Lisa , Godart Christian , Lepetit Maryannick , Cassubie-Mercier Tania , Galacteros Frederic , Chassany Olivier ,   DREPAtient study group
Published: May 2024

Background

Sickle cell disease (SCD) is an inherited autosomal recessive disorder exhibiting a range of symptoms and acute and/or chronic complications that affect the quality of life. This study aimed to assess health-related quality of life (HRQoL) and to identify the associated factors in adult patients with SCD in France.

Methods

DREPAtient is a cross-sectional, multicenter study conducted from June 2020 to April 2021 in France and in certain French overseas territories where SCD is highly prevalent. Sociodemographic and clinical data were collected online. HRQoL was assessed by the French version of the 36-Item Short Form Survey (SF-36) questionnaire. HRQoL determinants were identified using multivariable linear regression analysis.

Results

In total, 570 participants were included, mostly women (68.9%), with a mean age of 33.3 (±10.7) years. The highest mean score HRQoL was found in the Physical functioning domain (67.5 ± 21.8) and the lowest mean score in the General Health perception domain (37.7 ± 20.3). The mean score of the physical composite (PCS) and mental composite (MCS) of SF-36 summary scores was 40.6 ± 8.9 and 45.3 ± 9.8, respectively. Participants receiving oxygen therapy (β = −3.20 [95%CI: −5.56; −0.85]), those with a history of femoral osteonecrosis (−3.09 [−4.64; −1.53]), those hospitalized for vaso-occlusive crisis (VOC) or acute chest syndrome (ACS) (−2.58 [−3.93; −1.22]), those with chronic complications (−2.33 [−4.04; −0.62]), female participants (−2.17 [−3.65; −0.69]), those with psychological follow-up (−2.13 [−3.59; −0.67]), older participants (−1.69 [−3.28; −0.09]), and those receiving painkillers (−1.61 [−3.16; −0.06]) reported worse PCS score. By contrast, those who had completed secondary or high school (4.36 [2.41; 6.31]) and those with stable financial situation (2.85 [0.94, 4.76]) reported better PCS scores. Worse MCS scores were reported among participants with psychological follow-up (−2.54 [−4.28; −0.80]) and those hospitalized for VOC/ACS in the last 12 months (−2.38 [−3.99; −0.77]), while those who had relatives’ support (5.27 [1.92; 8.62]) and those with stable financial situation (4.95 [2.65; 7.26]) reported better MCS scores.

Conclusion

Adults with major SCD reported poor physical and mental HRQoL scores. Hospitalization for VOC/ACS, chronic complications, use of painkillers, perceived financial situation, and support from relatives are important predictors of HRQoL in SCD patients. Interventions to improve HRQoL outcomes SCD should be considered.
How the Science Behind Video Games Helps Kids Walk
Authors: Tulchin-Francis Kirsten , Lewis Jessica , Rowan Mallory , Parrett Matthew
Published: May 2024

Did you know that some of the same technology used to make video games and movie special effects can help scientists better understand human movement? During motion capture, also called mocap, small reflective balls, or markers as they are called, are placed on specific points of a person’s body. Mocap systems work using multiple cameras around the room that track the motion of the markers as a person walks, runs, jumps, or plays. The information gathered during mocap can be used to help doctors decide the best possible care to improve a child’s walking. It can also be used to determine when someone is ready to go back to sports after an injury, to help prevent people from getting injuries in the first place, or to improve their sports performance.
The effect of total factor productivity on the food security and livelihood vulnerability of farm households in Bangladesh
Authors: Sarma Paresh Kumar , Alam Mohammad Jahangir , Begum Ismat Ara , McKenzie Andrew M.
Published: May 2024

Food security and livelihood vulnerability are important issues for the economic sustainability of developing countries like Bangladesh. This study examines the influence of total factor productivity (TFP) on the livelihood vulnerability and food security of rice farming households in Bangladesh. Data from 1,841 rice farming households were extracted from the Bangladesh Integrated Household Survey (2015 and 2018) conducted by the International Food Policy Research Institute. Various statistical methods, such as the stochastic frontier model, principal component analysis, path analysis using structural equation modeling, and multivariate regression, were employed to analyze the data. The study utilizes a multivariate modeling approach that combines the stochastic frontier model to determine TFP and sophisticated methodologies to estimate the livelihood vulnerability index (LVI) and women’s empowerment in agriculture index (WEAI). The LVI, household dietary diversity Score (HDDS), TFP, and WEAI scores were 0.454, 10.72, 0.703, and 0.717, respectively. The results indicate a significant relationship between TFP and both LVI and HDDS. Higher TFP is associated with lower LVI and higher HDDS among rice farming households, suggesting that improving TFP can enhance food security and reduce vulnerability. The multivariate regression analysis reveals that TFP, household wealth index, women’s empowerment in agriculture index, per capita food expenditure, household level welfare, and household size have a positive significant impact on HDDS, while TFP is negatively associated with LVI, per capita food expenditure and household size. The findings underscore the importance of increasing TFP to improve food security, reduce livelihood vulnerability, and achieve sustainable development goals in countries like Bangladesh. Higher TFP yields positive outcomes regarding household dietary diversity and livelihood vulnerability, highlighting the need for agricultural policies that prioritize TFP enhancement. Policymakers and professionals can use these findings as a roadmap to implement advanced agricultural policies to achieve food security and reduce livelihood vulnerability. Improving household dietary diversity and reducing livelihood vulnerability can be achieved by focusing on increasing TFP, enhancing household wealth, women’s empowerment, per capita food expenditure, household welfare, and household size. Therefore, increasing TFP should be considered in the design of policies aiming to achieve SDGs Goal 2.
Effects of a diet supplemented with polysaccharides from Pogostemon cablin on growth performance, meat quality, and antioxidant capacity in Chongren Partridge chickens
Authors: Tang Yantian , Chen Si , Chen Lingli , Ouyang Kehui , Chen Hui , Wang Wenjun
Published: May 2024

In this study, the Pogostemon cablin polysaccharides (PCPs) were heteropolysaccharides with molecular weights of 63.17 kDa and 8.99 kDa, and their total carbohydrate content was 76.17 ± 0.23%, uronic acid content was 19.92 ± 0.42%, and protein content was 1.24 ± 0.07%. PCP is composed of arabinose, galactose, glucose, and glucuronic acid, with a molar ratio of 0.196:0.249:0.451:0.104. In addition, we further investigated the effects of the diet supplemented with different doses of PCP on growth performance, meat quality, and anti-oxidant capacity in Chongren Partridge chickens. A total of 200 chickens were randomly allocated into 4 treatments, and fed with a basal diet of 0 (CON), 200 (LPCP), 400 (MPCP), and 800 (HPCP) mg/kg PCP for a 14-day prefeeding period and a formal experimental period of 56 days. Results showed that dietary PCP significantly increased final body weight (BW), average daily gain (ADG), and decreased feed-to-gain ratio (F/G) from days 1 to 56. Meanwhile, dietary PCP reduced yellowness (b∗) values and increased redness (a∗) values at 24 h in breast muscles (p < 0.05). Furthermore, LPCP and MPCP significantly increased the level of guanylic acid (GMP) (p < 0.05). MPCP increased the content of free amino acids (isoleucine, leucine, lysine, methionine, threonine, valine, alanine, glutamic acid, serine, cysteine), total essential amino acid (EAA), total flavor amino acid (FAA), total AA, the content of fatty acids (c14:1, c16:1, and c22:2), and monounsaturated fatty acids (MUFAs) in the breast muscle when compared to CON (p < 0.05). In addition, MPCP significantly reduced the content of malondialdehyde (MDA) and increased the transcript abundances of fatty acid desaturase 2 (FADS2), fatty acid synthase (FAS), lipoprotein lipase (LPL), and sterol regulatory element binding protein-1 (SREBP-1) in the breast muscles of the chickens (p < 0.05). In light of the aforementioned results, PCP at 400 mg/kg could be used as an effective additive because it not only promotes the growth performance of Chongren Partridge chickens but also shows a conducive role in meat quality, especially in meat flavor.
Green Manuring with Oilseed Rape (Brassica napus L.) Mitigates Methane (CH4) and Nitrous Oxide (N2O) Emissions in a Rice-Ratooning System in Central China
Authors: Yao Lai , Zhu Jie , Yang Wei , Zhao Dongzhu , Zhou Yong , Li Shaoqiu , Nie Jiangwen , Yi Lixia , Liu Zhangyong , Zhu Bo
Published: May 2024

The use of oilseed rape (OS, Brassica napus L.) as a winter green manure is crucial for enhancing soil fertility and reducing chemical N application in paddy fields. However, the impacts of replacing varying amounts of chemical N with OS on CH4 and N2O emissions in paddy soils have not been well evaluated. In this study, GHG emissions, soil properties and OS decomposition in a rice-ratooning system with different OS-urea N replacement rates (0%, 25%, 50%, 75% and 100%) were investigated. Our results indicate that 84.7–90.7% of the initial C and 97.5–98.4% of the N were released during the 192-day decomposition process, and that the mineralization patterns of net C and net N in the OS residue were consistent with a single exponential decay model. The lowest CH4 emissions (9.97 g m−2) were observed at 0% OS, while the highest N2O emissions (0.40 g m−2) were observed at this level of substitution. Conversely, the highest CH4 emissions (20.71 g m−2) and lowest N2O emissions (0.07 g m−2) were observed at 100% OS. Compared to 0% substitution, 25% substitution significantly decreased GWP and GHGI without reducing rice grain yield. Environmental parameters such as soil redox, NH4+-N and residual N and C were shown to be significantly associated with CH4 emissions, whereas soil redox, NH4+-N and residual C were the main drivers of N2O emissions. In conclusion, 25% substitution of OS was the most cost-effective measure for balancing greenhouse gas emission and rice yield.
Oat Threshing Damage and Its Effect on Nutritional Components
Authors: Liu Yun , Xin Peichen , Sun Jinyan , Zheng Decong
Published: May 2024

Mechanical threshing can cause damage to oats, and the nutritional quality of the damaged kernels easily changes during storage. The current research on oats with regard to threshing damage and nutritional quality falls into two separate research areas, but they are inextricably linked. It is necessary to combine these two types of studies. In order to explore the damage mechanism of oat threshing and its effect on the nutritional components, a three-dimensional model of oat–nail-tooth impact was established, and a finite element analysis of the dynamic impact process was performed using LS-DYNA. The changes in the von Mises stress, contact force, energy, critical velocity, and damage characteristics during impact on different surfaces of the kernel were analyzed. A threshing test was carried out, and the kernels were classified according to their different damage types. The differences in the nutrient compositions and contents of oats with different damage types were analyzed by means of near-infrared spectroscopy and physicochemical testing. The results showed that the von Mises stress and contact force tended to first increase and then decrease during impact. When the impact velocity was 12 m/s, for the top, bottom, front, back, and left sides of the oat impacted by the nail tooth, the maximum von Mises stresses were 10.05, 10.46, 8.60, 9.28, and 8.49 MPa, respectively. The maximum contact forces were 25.09, 18.57, 34.29, 38.37, and 35.19 N, respectively. The critical velocities of impact damage were 13.38, 13.10, 13.40, 14.64, and 16.00 m/s, respectively. The threshing damage could be divided into four typical types: transverse fracture, bottom breakage, side fracture, and back crack. The chemical compositions of oat kernels with different damage types were basically the same, but their nutrient contents were different. These results provide a theoretical basis for optimizing oat threshing devices, reducing threshing damage, and improving oat quality.
ApIsoT: An IoT Function Aggregation Mechanism for Detecting Varroa Infestation in Apis mellifera Species
Authors: Camayo Ana Isabel Caicedo , Muñoz Martin Alexander Chaves , Corrales Juan Carlos
Published: May 2024

In recent years, the global reduction in populations of the Apis mellifera species has generated a worrying deterioration in the production of essential foods for human consumption. This phenomenon threatens food security, as it reduces the pollination of vital crops, negatively affecting the health and stability of ecosystems. The three main factors generating the loss of the bee population are industrial agriculture, climate changes, and infectious diseases, mainly those of parasitic origin, such as the Varroa destructor mite. This article proposes an IoT system that uses accessible, efficient, low-cost devices for beekeepers in developing countries to monitor hives based on temperature, humidity, CO2, and TVOC. The proposed solution incorporates nine-feature aggregation as a data preprocessing strategy to reduce redundancy and efficiently manage data storage on hardware with limited capabilities, which, combined with a machine learning model, improves mite detection. Finally, an evaluation of the energy consumption of the solution in each of its nodes, an analysis of the data traffic injected into the network, an assessment of the energy consumption of each implemented classification model, and, finally, a validation of the solution with experts is presented.
An Internet of Things-Based Cluster System for Monitoring Lactating Sows’ Feed and Water Intake
Authors: He Xinyuan , Zeng Zhixiong , Liu Yanhua , Lyu Enli , Xia Jingjing , Wang Feiren , Luo Yizhi
Published: May 2024

Acquiring real-time feeding information for monitoring lactating sows and their feeding requirements is a challenging task. Real-time data represent an important input for numerous tasks, such as disease monitoring, nutritional regulation, and feeding modeling. However, concurrently monitoring large numbers of sows and processing the real-time information for modeling is challenging using existing platforms. In this paper, we describe the design and development of a system that monitors and processes sows’ feed and water consumption in real time. The system was custom-developed using open-source networking technologies. The system consists of three components: an electronic sow feeder connected to a central controller via a CAN network, an MQTT service cluster, and a data processing program. The MQTT service cluster uses Netty to develop a single service node, and it uses Zookeeper and Redis to complete node registration, discovery, and scheduling. The data processing program is based on Spark and Flink. We conducted comparative testing of three common codecs (Java Serializer, Marshalling, and Protostuff) to further speed up data transmission. The results of the experiment show that, with three service nodes, the system can concurrently monitor up to 20,000 sows. Moreover, the system achieves optimal performance when monitoring 10,000 sows at the same time, with a TPS of 6399 pcs/s and an RT of 643 ms.
Diversification of Intensively Used Grassland: Resilience and Good Fodder Quality across Different Soil Types
Authors: Albers Regine , Albach Dirk Carl
Published: May 2024

In Central Europe, grasslands for dairy production are typically characterised by monocultures with high input rates of artificial fertilisers. However, it was suggested that biodiversity could reduce the need for anthropogenic inputs in functionally diversified grassland mixes while maintaining or enhancing yields and fodder quality. To investigate this hypothesis, we developed five consecutively diversified grassland mixes consisting of ryegrass, legumes, a non-leguminous forb, and additional grass species for intensive fodder production, and tested them under regular agricultural conditions in a three-year experiment on sandy soil, marshland, and bog soil at one-hectare per mix and site. All mixtures produced similar high-quality forage in terms of utilisable crude protein content and net energy lactation rate, even under challenging climatic conditions. However, a high abundance of Dactylis glomerata can decrease these values, although factors such as seasonality and rainfall affect them to a greater degree. The seasonal composition changes between the functional groups, such as strong spring growth of grasses and strong summer growth of legumes, show complementarity rather than competition between the groups, resulting in consistent biomass production during the growth period. The results were consistent over the three soil types and provide the basis for further adaptation of mixes and breeding.
Role of Medaka (Oryzias latipes) Foxo3 in Resistance to Nervous Necrosis Virus Infection
Authors: Li Wen , Wang Zhi , Liang Jingjie , Xia Bilin , Chen Ruoxue , Chen Tiansheng
Published: May 2024

Upon encountering a virus, fish initiate an innate immune response, guided by IFNs. Foxo3 plays a part in the body’s immune response; however, its specific role in the IFN-guided immune response in fish is yet to be clarified. In this study, we characterized foxo3 in Japanese medaka (Oryzias latipes) and examined its role in the IFN-dependent immune response upon infection with the RGNNV. The results show that the coding region of the medaka foxo3 gene is 2007 base pairs long, encoding 668 amino acids, and possesses a typical forkhead protein family structural domain. The product of this gene shares high homology with foxo3 in other fish species and is widely expressed, especially in the brain, eyes, testes, and heart. Upon RGNNV infection, foxo3−/− mutant larvae showed a lower mortality rate, and adults exhibited a significant reduction in virus replication. Moreover, the absence of foxo3 expression led to an increase in the expression of irf3, and a decrease in the expression of other IFN-related genes such as tbk1 and mapk9, implying that foxo3 may function as a negative regulator in the antiviral signaling pathway. These findings provide crucial insights for disease-resistant breeding in the aquaculture industry.
Potential of Circulating miRNA Biomarkers and Exosomes for Early Pregnancy Diagnoses in Cattle
Authors: Ninomiya Chiaki , Yoshino Hitomi , Ishiguro-Oonuma Toshina , Iga Kosuke , Kanazawa Tomomi , Takahashi Toru , Kizaki Keiichiro
Published: May 2024

Circulating microRNAs (miRNAs) were investigated as biomarkers for the diagnosis of early pregnancy in cattle. The levels of prospective miRNA biomarkers and the features of extracellular vesicles (EVs) in the blood were evaluated. In Study 1, plasma samples from cows 21 days after artificial insemination (AI) were examined using RT-qPCR to determine the levels of seven circulating miRNAs. Only the levels of miR-126-3p were significantly lower in the pregnant group than in the non-pregnant group. In Study 2, among individuals not pregnant at the first AI, the miRNA levels were compared between the individuals pregnant at the second AI and those who remained non-pregnant. The miR-25 levels were significantly higher in the pregnant group at the second AI than in the pregnant group at the first AI; miR-19b, miR-27b, and miR-29a levels were also high. In the non-pregnant group, changes were absent in the miRNA levels in the same individual between the first and second AIs. In Study 3, Western blotting and RT-qPCR showed the presence of miRNAs in EVs and their levels were lower than in plasma. Thus, circulating miR-126-3p may serve as a biomarker for the diagnosis of early pregnancy in cattle. In addition, the expression of some miRNAs tended to be higher during pregnancy than during non-pregnancy in the same individual, suggesting their potential as an index to determine pregnancy and non-pregnancy rates using a comparative method.
Genetic Characterization and Population Structure of Drug-Resistant Mycobacterium tuberculosis Isolated from Brazilian Patients Using Whole-Genome Sequencing
Authors: Esteves Leonardo Souza , Gomes Lia Lima , Brites Daniela , Fandinho Fátima Cristina Onofre , Bhering Marcela , Pereira Márcia Aparecida da Silva , Conceição Emilyn Costa , Salvato Richard , Costa Bianca Porphirio da , Medeiros Reginalda Ferreira de Melo , Caldas Paulo Cesar de Souza , Redner Paulo , Dalcolmo Margareth Pretti , Eldholm Vegard , Gagneux Sebastien , Rossetti Maria Lucia , Kritski Afrânio Lineu , Suffys Philip Noel
Published: May 2024

The present study aimed to determine the genetic diversity of isolates of Mycobacterium tuberculosis (Mtb) from presumed drug-resistant tuberculosis patients from several states of Brazil. The isolates had been submitted to conventional drug susceptibility testing for first- and second-line drugs. Multidrug-resistant (MDR-TB) (54.8%) was the most frequent phenotypic resistance profile, in addition to an important high frequency of pre-extensive resistance (p-XDR-TB) (9.2%). Using whole-genome sequencing (WGS), we characterized 298 Mtb isolates from Brazil. Besides the analysis of genotype distribution and possible correlations between molecular and clinical data, we determined the performance of an in-house WGS pipeline with other online pipelines for Mtb lineages and drug resistance profile definitions. Sub-lineage 4.3 (52%) was the most frequent genotype, and the genomic approach revealed a p-XDR-TB level of 22.5%. We detected twenty novel mutations in three resistance genes, and six of these were observed in eight phenotypically resistant isolates. A cluster analysis of 170 isolates showed that 43.5% of the TB patients belonged to 24 genomic clusters, suggesting considerable ongoing transmission of DR-TB, including two interstate transmissions. The in-house WGS pipeline showed the best overall performance in drug resistance prediction, presenting the best accuracy values for five of the nine drugs tested. Significant associations were observed between suffering from fatal disease and genotypic p-XDR-TB (p = 0.03) and either phenotypic (p = 0.006) or genotypic (p = 0.0007) ethambutol resistance. The use of WGS analysis improved our understanding of the population structure of MTBC in Brazil and the genetic and clinical data correlations and demonstrated its utility for surveillance efforts regarding the spread of DR-TB, hopefully helping to avoid the emergence of even more resistant strains and to reduce TB incidence and mortality rates.
Nanoemulsions Based on Soluble Chenopodin/Alginate Complex for Colonic Delivery of Quercetin
Authors: Intiquilla Arturo , Arazo Migdalia , Gamboa Alexander , Caro Nelson , Gotteland Martin , Palomino-Calderón Alan , Abugoch Lilian , Tapia Cristian
Published: May 2024

Inflammatory bowel disease (IBD) is an autoimmune disorder caused by uncontrolled immune activation and the subsequent destruction of the colon tissue. Quercetin (Qt) is a natural antioxidant and anti-inflammatory agent proposed as an alternative to mitigate IBD. However, its use is limited by its low oral bioavailability. This study aimed to develop nanoemulsions (NEs) based on a soluble chenopodin/alginate (QPA) complex and Tween 80 (T80), intended for the colonic release of Qt, activated by the pH (5.4) and bacteria present in the human colonic microbiota. NEs with different ratios of QPA/Tw80 (F1-F6) were prepared, where F4Qt (60/40) and F5Qt (70/30) showed sizes smaller than 260 nm, PDI < 0.27, and high encapsulation efficiency (>85%). The stability was evaluated under different conditions (time, temperature, pH, and NaCl). The DSC and FTIR analyses indicated hydrophobic and hydrogen bonding interactions between QPA and Qt. F4Qt and F5Qt showed the greater release of Qt in PBS1X and Krebs buffer at pH 5.4 (diseased condition), compared to the release at pH 7.4 (healthy condition) at 8 h of study. In the presence of E. coli and B. thetaiotaomicron, they triggered the more significant release of Qt (ƒ2 < 50) compared to the control (without bacteria). The NEs (without Qt) did not show cytotoxicity in HT-29 cells (cell viability > 80%) and increased the antioxidant capacity of encapsulated Qt. Therefore, these NEs are promising nanocarriers for the delivery of flavonoids to the colon to treat IBD.
Advance in Iron Metabolism, Oxidative Stress and Cellular Dysfunction in Experimental and Human Kidney Diseases
Authors: Xie Tiancheng , Yao Li , Li Xiaogang
Published: May 2024

Kidney diseases pose a significant global health issue, frequently resulting in the gradual decline of renal function and eventually leading to end-stage renal failure. Abnormal iron metabolism and oxidative stress-mediated cellular dysfunction facilitates the advancement of kidney diseases. Iron homeostasis is strictly regulated in the body, and disturbance in this regulatory system results in abnormal iron accumulation or deficiency, both of which are associated with the pathogenesis of kidney diseases. Iron overload promotes the production of reactive oxygen species (ROS) through the Fenton reaction, resulting in oxidative damage to cellular molecules and impaired cellular function. Increased oxidative stress can also influence iron metabolism through upregulation of iron regulatory proteins and altering the expression and activity of key iron transport and storage proteins. This creates a harmful cycle in which abnormal iron metabolism and oxidative stress perpetuate each other, ultimately contributing to the advancement of kidney diseases. The crosstalk of iron metabolism and oxidative stress involves multiple signaling pathways, such as hypoxia-inducible factor (HIF) and nuclear factor erythroid 2-related factor 2 (Nrf2) pathways. This review delves into the functions and mechanisms of iron metabolism and oxidative stress, along with the intricate relationship between these two factors in the context of kidney diseases. Understanding the underlying mechanisms should help to identify potential therapeutic targets and develop novel and effective therapeutic strategies to combat the burden of kidney diseases.
Lianweng Granules Alleviate Intestinal Barrier Damage via the IL-6/STAT3/PI3K/AKT Signaling Pathway with Dampness-Heat Syndrome Diarrhea
Authors: Lv Jianyu , Fu Yuchen , Ga Yu , Han Chao , Fan Yimeng , Wei Yuanyuan , Hao Sijia , Hao Zhihui
Published: May 2024

Dampness-heat syndrome diarrhea (DHSD) is a common clinical disease with a high prevalence but still has no satisfactory therapeutic medicine, so the search for a safe and effective drug candidate is ongoing. This study aims to explore the efficacy and mechanisms of Lianweng granules (LWG) in the treatment of DHSD and to identify the blood transport components of LWG. We assessed the efficacy of LWG in DHSD by various in vivo metrics such as body weight, disease activity index (DAI), histopathologic examination, intestinal barrier function, levels of inflammatory, apoptotic biomarkers, and oxidative stress. We identified the blood components of LWG using ultra-high performance liquid chromatography-mass spectrometry/mass spectrometry (UHPLC-MS/MS), and the resolved key components were used to explore the relevant targets. We next predicted the potential mechanisms of LWG in treating DHSD using network pharmacology and molecular docking based on the relevant targets. Finally, the mechanisms were validated in vivo using RT-qPCR, Western blotting, ELISA, and immunofluorescence and evaluated in vitro using Cell Counting Kit-8 (CCK-8), small interfering RNA, cellular enthusiasm transfer assay (CETSA), and drug affinity response target stability (DARTS). Ninety-one pharmacodynamic components of LWG enter the bloodstream and exert possible therapeutic effects. In vivo, LWG treatment improved body weight, reduced colonic injury and DAI scores, lowered inflammation, oxidative stress, and apoptosis markers, and partially restored intestinal barrier function in DHSD mice. Guided by network pharmacology and molecular docking, it is suggested that LWG may exert therapeutic effects by inhibiting IL-6/STAT3/PI3K/AKT signaling. LWG significantly decreased the expression of IL-6, p-STAT3, p-PI3K, p-AKT, and other proteins. These findings were supported by in vitro experiments, where CETSA, DARTS, and siRNA evidenced LWG’s targeting of STAT3. LWG targeted STAT3 to inhibit inflammation, oxidative stress, and apoptosis in the colon, thereby restoring the intestinal barrier function to some extent and exerting a therapeutic effect on DHSD.
Purification of Phenolic Compounds from Camellia polyodonta Flower: Composition Analysis, Antioxidant Property, and Hypolipidemic Activity In Vitro and In Vivo
Authors: Xiang Zhuoya , Liu Li , Xu Zhou , Kong Qingbo , Liang Heng , Feng Shiling , Chen Tao , Zhou Lijun , Yang Hongyu , Ding Chunbang
Published: May 2024

Camellia polyodonta flowers are rich sources of phenolics and less attention has been paid to their potential biological activity. This study aims to explore the crude extracts and resulting purified fractions (CPFP-I, II, III, and IV) through compositional analysis and antioxidant and hypolipidemic activities in vitro and in vivo. Among four fractions, CPFP-II contained the highest total phenolic content and flavonoid content, while CPFP-III exhibited the greatest total proanthocyanidin content. Among the 14 phenolic compounds, CPFP-II displayed the highest content of procyanidin B2, B4, and C1, whereas CPFP-III contained the highest amount of 1,2,3,6-tetragalloylglucose. The DPPH, ABTS, and FRAP assessments demonstrated a consistent trend: CPFP-II > CPFP-III > CPFP-I > CPFP-IV. In vivo experiments showed that that all four fractions significantly reduced lipid levels in hyperlipidemic C. elegans (p < 0.05), with CPFP-II exhibiting the most potent effect. Furthermore, CPFP-II effectively bound to bile acids and inhibited the enzymatic activity of pancreatic lipase in vitro. Consequently, CPFP-II should be prioritized as a promising fraction for further exploration and should provide substantial support for the feasibility of the C. polyodonta flower as a natural alternative.
Pedestrian Abnormal Behavior Detection System Using Edge–Server Architecture for Large–Scale CCTV Environments
Authors: Song Jinha , Nang Jongho
Published: May 2024

As the deployment of CCTV cameras for safety continues to increase, the monitoring workload has significantly exceeded the capacity of the current workforce. To overcome this problem, intelligent CCTV technologies and server-efficient deep learning analysis models are being developed. However, real-world applications exhibit performance degradation due to environmental changes and limited server processing capacity for multiple CCTVs. This study proposes a real-time pedestrian anomaly detection system with an edge–server structure that ensures efficiency and scalability. In the proposed system, the pedestrian abnormal behavior detection model analyzed by the edge uses a rule-based mechanism that can detect anomalies frequently, albeit less accurately, with high recall. The server uses a deep learning-based model with high precision because it analyzes only the sections detected by the edge. The proposed system was applied to an experimental environment using 20 video streams, 18 edge devices, and 3 servers equipped with 2 GPUs as a substitute for real CCTV. Pedestrian abnormal behavior was included in each video stream to conduct experiments in real-time processing and compare the abnormal behavior detection performance between the case with the edge and server alone and that with the edge and server in combination. Through these experiments, we verified that 20 video streams can be processed with 18 edges and 3 GPU servers, which confirms the scalability of the proposed system according to the number of events per hour and the event duration. We also demonstrate that the pedestrian anomaly detection model with the edge and server is more efficient and scalable than the models with these components alone. The linkage of the edge and server can reduce the false detection rate and provide a more accurate analysis. This research contributes to the development of control systems in urban safety and public security by proposing an efficient and scalable analysis system for large-scale CCTV environments.
Comparing Two Deep-Learning Models in Discrete Choice Analysis of Customers’ Mobile Plan Preferences
Authors: Oliobi Chidimma , Chinhamu Knowledge , Zewotir Temesgen
Published: May 2024

A discrete choice experiment (DCE) was used to investigate students’ preferences for mobile phone plans at a South African university. Upon obtaining the data, this study compares the predictive performance of two machine-learning models for discrete choice analysis and makes recommendations for model selection. Using concepts from blocked fractional factorial designs, a locally optimal DCE was created for the choice sets. This contrasts with alternative ways that, in practice, could be more difficult, especially when there is a large number of attributes. The call rate, data speed, customer service, premiums, and network coverage were the features considered. A total of 180 respondents were chosen from the student population using a two-stage sample approach, and data were gathered through face-to-face interviews. In this study, two deep-learning models are examined to analyze the data, which are the artificial neural network (ANN) and the extreme gradient boosting (XGBoost) models. Root mean square error (RMSE) and mean absolute error (MAE) are used to assess the model fitness, while accuracy, precision, recall and F1 score were used to compare the models’ performance. The results showed that XGBoost performs better compared to ANN in model fitness and prediction. Thus, the use of the XGBoost deep-learning model in choice preference modeling is therefore encouraged.
Markov-Embedded Affinity Learning with Connectivity Constraints for Subspace Clustering
Authors: Shao Wenjiang , Zhang Xiaowei
Published: May 2024

Subspace clustering algorithms have demonstrated remarkable success across diverse fields, including object segmentation, gene clustering, and recommendation systems. However, they often face challenges, such as omitting cluster information and the neglect of higher-order neighbor relationships within the data. To address these issues, a novel subspace clustering method named Markov-Embedded Affinity Learning with Connectivity Constraints for Subspace Clustering is proposed. This method seamlessly embeds Markov transition probability information into the self-expression, leveraging a fine-grained neighbor matrix to uncover latent data structures. This matrix preserves crucial high-order local information and complementary details, ensuring a comprehensive understanding of the data. To effectively handle complex nonlinear relationships, the method learns the underlying manifold structure from a cross-order local neighbor graph. Additionally, connectivity constraints are applied to the affinity matrix, enhancing the group structure and further improving the clustering performance. Extensive experiments demonstrate the superiority of this novel method over baseline approaches, validating its effectiveness and practical utility.
Analysis of Shield Tunneling Parameters and Research on Prediction Model of Tunneling Excavation Speed in Volcanic Ash Strata of Jakarta–Bandung High-Speed Railway Project
Authors: Fan Xiaomin , Tan Zhongsheng , Zhang Baojin , Zhao Jinpeng , Cao Yuxin , Jiang Yongtao
Published: May 2024

Insufficient investigations have been conducted on the analysis of shield tunneling parameters and the prediction of the tunneling excavation speed in formations composed of volcanic ash strata. To address this issue, we employ a comprehensive approach utilizing literature research, mathematical statistics, and other methodologies, centered on the analysis of the No. 1 Tunnel of the Jakarta–Bandung High-Speed Railway. Our focus is on examining the evolution patterns and inter-relationships of shield tunneling parameters within volcanic ash strata. Subsequently, we propose an optimized strategy for these tunneling parameters. By employing six machine-learning algorithms to construct prediction models, we compare and analyze their performance in predicting the tunneling excavation speed. The results indicate a positive correlation between slurry pressure and tunnel depth in volcanic ash strata, suggesting that the grouting pressure should exceed the slurry pressure by approximately 0.22 MPa. In the composite stratum of “volcanic ash debris + round gravel”, the cutter torque exhibits a strong negative correlation with the total thrust (−0.77). Due to tool wear and ground resistance, the excavation speed and cutter speed are weakly negatively correlated. Compared to other strata, shield tunneling in volcanic ash strata exhibits larger grouting pressure fluctuations, slower tunneling excavation speed, greater total thrust, higher cutter torque, and lower cutter speed. Regarding shield tunneling excavation speed prediction, the ranking of the algorithm performance is RF > DNN > ANN > BPNN > MNR > SVM, with RF achieving a decision coefficient of 0.829. The RF model is well-suited for predicting the shield structure tunneling excavation speed.
Enhanced Wear Resistance of Microstripe-Textured Water-Lubricated Materials Fabricated via Hot Embossing
Authors: Li Zeyun , Wu Weibin , Yang Xue , Wang Xin
Published: May 2024

Water-lubricated material is the fundamental ingredient of a water-lubricated bearing (WLB), of which the friction and wear properties directly affect the working performance and service life of a WLB. We designed a micron-scale stripe texture and fabricated a negative microtexture mold by femtosecond laser etching. The microtextures were fabricated onto the surface of Thordon and polyurethane water-lubricated materials by a precision thermoforming machine. Tribological tests showed that the microstripe texture on water-lubricated materials had lower friction and wear properties than that on pristine surface materials. The results demonstrated that the presence of the microstripe texture effectively improved the friction and anti-wear properties of the water-lubricated materials. This study provides a new idea for the design and preparation of water-lubricated materials with good water-lubricating and anti-wear properties.
Different Fracture Liquids under the Action of Enclosure of Dense Sandstone Reservoir Micro-Damage Characteristics Study
Authors: Yan Wei , Cheng Qiang , Huang Gun
Published: May 2024

The sandstone reservoir in the Lule River group of Mahai East District is strong, densely dense, and the expansion of clay material is very easy to block the pores. Therefore, the new pressure cracks and cationic cluster stabilizers with double-season ammonium salt clay stabilizers are used. Experimental analysis is performed under the circumstances of the perimeter. Use nuclear magnetic real-time testing different fracture liquids to drive the pore structure structure changes before and after the sandstone, combined with differential theory to calculate the fractal dimensions of sandstone. As a result, under the condition of water full, as the perimeter pressure increases, the rocks are increased, and the rocks are increased, and the rocks are increased. The matrix occurs under the common action of the fence and the fracture fluid to prevent the inflation of clay minerals under the combined action of the fence and the fracture fluid, which causes a significant reduction in large holes and increased micropores and medium holes. Exploring different fracture liquids to reservoirs is of great significance to the development of dense sandstone reservoirs.
The Optuna–LightGBM–XGBoost Model: A Novel Approach for Estimating Carbon Emissions Based on the Electricity–Carbon Nexus
Authors: Cai Yuanhang , Feng Jianxin , Wang Yanqing , Ding Yuanming , Hu Yue , Fang Hui
Published: May 2024

With the challenge posed by global warming, accurately estimating and managing carbon emissions becomes a key step for businesses, especially power generation companies, to reduce their environmental impact. Optuna–LightGBM–XGBoost, a novel power and carbon emission relationship model that aims to improve the efficiency of carbon emission monitoring and estimation for power generation companies, is proposed in this paper. Deeply exploring the intrinsic link between power production data and carbon emissions, this model paves a new path for “measuring carbon through electricity”, in contrast to the emission factor method commonly used in China. Unit data from power generation companies are processed into structured tabular data, and a parallel processing framework is constructed with LightGBM and XGBoost, and optimized with the Optuna algorithm. The multilayer perceptron (MLP) is used to fuse features to enhance prediction accuracy by capturing characters that the individual models cannot detect. Simulation results show that Optuna–LightGBM–XGBoost can achieve better performance compared to existing methods. The mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) of the model are 0.652, 0.939, 0.136, and 0.994, respectively. This not only helps governments and enterprises to develop more scientific and reasonable emission reduction strategies and policies, but also lays a solid foundation for achieving global carbon neutrality goals.
Multi-Scale Target Detection in Autonomous Driving Scenarios Based on YOLOv5-AFAM
Authors: Ma Hang , Zhao Wei , Liu Bosi , Chen Wenbai
Published: May 2024

Multi-scale object detection is critically important in complex driving environments within the field of autonomous driving. To enhance the detection accuracy of both small-scale and large-scale targets in complex autonomous driving environments, this paper proposes an improved YOLOv5-AFAM algorithm. Firstly, the Adaptive Fusion Attention Module (AFAM) and Down-sampling Module (DownC) are introduced to increase the detection precision of small targets. Secondly, the Efficient Multi-scale Attention Module (EMA) is incorporated, enabling the model to simultaneously recognize small-scale and large-scale targets. Finally, a Minimum Point Distance IoU-based Loss Function (MPDIou-LOSS) is introduced to improve the accuracy and efficiency of object detection. Experimental validation on the KITTI dataset shows that, compared to the baseline model, the improved algorithm increased precision by 2.4%, recall by 2.6%, mAP50 by 1.5%, and mAP50-90 by an impressive 4.8%.